Qiuyun Luo^*†1, Wentao Pan^*†‡1, Suna Zhou^*†1, Guangfeng Wang^‡, Hanjie Yi^*§, Lin Zhang^*¶, Xianglei Yan^*†, Luping Yuan^*†, Zhenyi Liu^#, Jing Wang^**, Haibo Chen^#, MiaoZhen Qiu^*††, DaJun Yang^*†‡, Jian Sun^*‡‡

Oncology Research, Vol.28, No.4, pp. 331-344, 2020, DOI:10.3727/096504020X15825405463920

Abstract Despite therapeutic advances, the effective treatment for relapsed or refractory diffuse large B-cell lymphoma (DLBCL) remains a major clinical challenge. Evasion of apoptosis through upregulating antiapoptotic B-cell lymphoma-2 (BCL-2) family members and p53 inactivation, and abnormal activation of B-cell receptor signaling pathway are two important pathogenic factors for DLBCL. In this study, our aim is to explore a rational combination of BCL-2 inhibitor plus Bruton’s tyrosine kinase (BTK) blockade or p53 activation for treating DLBCL with the above characteristics. We demonstrated that a novel BCL-2 selective inhibitor APG-2575 effectively suppressed DLBCL with BCL-2 high expression via activating the mitochondrial apoptosis… More >

Kazuo Umezawa^*, Andrzej Breborowicz^†, Shamil Gantsev^‡

Oncology Research, Vol.28, No.5, pp. 541-550, 2020, DOI:10.3727/096504020X15929100013698

Abstract There have been great advances in the therapy of cancer and leukemia. However, there are still many neoplastic diseases that are difficult to treat. For example, it is often difficult to find effective therapies for aggressive cancer and leukemia. An NF- B inhibitor named dehydroxymethylepoxyquinomicin (DHMEQ) was discovered in 2000. This compound was designed based on the structure of epoxyquinomicin isolated from a microorganism. It was shown to be a specific inhibitor that directly binds to and inactivates NF- B components. Until now, DHMEQ has been used by many scientists in the world to suppress animal models of cancer and… More >

Jean-Claude Ferrandez^1,*, Pierre-Henri Ganchou², Serge Theys³, Maria Torres-Lacomba⁴, Daniel Serin¹

Oncologie, Vol.24, No.1, pp. 25-33, 2022, DOI:10.32604/oncologie.2022.018110

Abstract Upper limb lympedema is a frequent consequence of breast cancer treatment. The International Society of Lymphology recommends physical therapy for lymphedema management. This treatment includes a combination of manual lymphatic drainage and high-compression bandaging. Actually, the effectiveness of manual lymphatic drainage remains an area of controversy, especially because of the many different techniques called “manual lymphatic drainage” since 1930. The purpose of this review was to emphasise the efficacy of these different techniques according to physiological data and evidence-based practice. To improve the manual lymphatic drainage efficiency, the pressure, sometimes important, should be tailored to each edema and the techniques… More >

Elsa Maitre, Xavier Troussard^*

Oncologie, Vol.24, No.1, pp. 3-24, 2022, DOI:10.32604/oncologie.2022.021490

Abstract Hairy cell leukemia (LT) accounts for 2% of all leukemias. The diagnosis is based on the presence in the blood and/ or the marrow of hairy cells expressing CD103, CD123, CD11c and CD25. The BRAF^V600E mutation, a molecular marker of the disease, is present in more than 80% of cases. LT should be distinguished from other chronic B-cell lymphoproliferative disorders, including the variant form of hairy cell leukemia (HCL-V) and diffuse splenic red pulp lymphoma (DSRPL). Progress has recently been made in the management of patients. The purine analogues (PNAs) in monotherapy, deoxycoformycin (DCF) or 2-chloro-deoxyadenosine (CDA), remain the first-line… More >

R. Kavitha^1,*, N. Viswanathan²

Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 1305-1320, 2022, DOI:10.32604/iasc.2022.022816

Abstract Bone marrow cancer is considered to be the most complex and dangerous disease which results due to an uncontrolled growth of white blood cells called leukocytes. Acute Lymphoblastic Leukemia (ALL) and Multiple Myeloma (MM) are considered to be important categories of bone cancers, which induces a larger number of cancer cells in the bone marrow, results in preventing the production of healthy blood cells. The advent of Artificial Intelligence, especially machine and deep learning, has expanded humanity’s capacity to analyze and detect these increasingly complex diseases. But, accurate detection of cancer cells and reducing the probability of false alarm rates… More >

G. Sriram¹, T. R. Ganesh Babu², R. Praveena^2,*, J. V. Anand³

Molecular & Cellular Biomechanics, Vol.19, No.1, pp. 29-40, 2022, DOI:10.32604/mcb.2022.016966

Abstract Leukemoid reaction like leukemia indicates noticeable increased count of WBCs (White Blood Cells) but the cause of it is due to severe inflammation or infections in other body regions. In automatic diagnosis in classifying leukemia and leukemoid reactions, ALL IDB2 (Acute Lymphoblastic Leukemia-Image Data Base) dataset has been used which comprises 110 training images of blast cells and healthy cells. This paper aimed at an automatic process to distinguish leukemia and leukemoid reactions from blood smear images using Machine Learning. Initially, automatic detection and counting of WBC is done to identify leukocytosis and then an automatic detection of WBC blasts… More >

Xiaodan He, Jingshi Wang, Zhao Wang^*

Oncologie, Vol.23, No.4, pp. 559-567, 2021, DOI:10.32604/oncologie.2021.018647

Abstract Despite extensive work-ups, some patients have been diagnosed with hemophagocytic lymphohistiocytosis (HLH) of unknown etiology. For HLH of unknown etiology, to investigate the clinical features and the factors that may affect the prognosis, we retrospectively reviewed the medical records of 94 patients hospitalized from January 2014 to December 2019. Survival times were evaluated until April 2020. For the 94 patients, the underlying causes of their diseases remained unclear at the end of the follow-up period, and the 1-, 3-, and 6-month survival rates, and the overall survival (OS) rates were 86.2%, 78.7%, 73.4%, and 70.2%, respectively. The multivariate analysis showed… More >

Sunil Kr. Jha^1,*, Zulfiqar Ahmad²

CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.2, pp. 567-594, 2021, DOI:10.32604/cmes.2021.016817

Abstract Health care data mining is noteworthy in disease diagnosis and recognition procedures. There exist several potentials to further improve the performance of machine learning based-classification methods in healthcare data analysis. The selection of a substantial subset of features is one of the feasible approaches to achieve improved recognition results of classification methods in disease diagnosis prediction. In the present study, a novel combined approach of feature generation using latent semantic analysis (LSA) and selection using ranker search (RAS) has been proposed to improve the performance of classification methods in lymph disease diagnosis prediction. The performance of the proposed combined approach… More >

Jiangyong Liu^1,#,*, Mingming Gu^2,#, Yang Xue¹, Qiong Wang³, Yong Ren³, Wencai Huang^1,*

Oncologie, Vol.23, No.3, pp. 439-452, 2021, DOI:10.32604/oncologie.2021.017220

Abstract Cavitary lung cancer is a rare type of lung cancer. Generally, the relationship between cavitary lung adenocarcinoma (LUAD) and specific immune checkpoints remains unknown. In this study, we aimed to detect the expression of programmed cell death ligand-1(PD-L1) and the density of CD8-positive (CD8⁺) tumor-infiltrating lymphocytes (TILs) to evaluate their clinicopathological significance in the case of patients with cavitary LUAD. This study included 65 patients with cavitary LUAD. Patient specimens were obtained from surgery. The expression of PD-L1 protein and CD8⁺ TIL status was detected by traditional immunohistochemistry and multiplex quantitative immunofluorescence technology. The correlation of PD-L1 expression and CD8⁺… More >

Schahrazad Soltane^*, Sameer Alsharif , Salwa M.Serag Eldin

Computer Systems Science and Engineering, Vol.40, No.2, pp. 629-644, 2022, DOI:10.32604/csse.2022.019333

Abstract 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… More >