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HLA-DPB1*03:01:29 differs from HLA-DPB1*03:01:01:01 by one nucleotide in exon 2.
Subject(s)
HLA-DP beta-Chains , Nucleotides , Humans , Alleles , Sequence Analysis, DNA , ChinaABSTRACT
Aim: Daratumumab, a CD38 monoclonal antibody, has been widely used in patients with multiple myeloma. Although a variety of adverse events have been reported, consciousness impairment has not been reported yet. We report a case of encephalopathy associated with daratumumab. Case presentation: A 57-year-old male, diagnosed with relapsed multiple myeloma, was treated with daratumumab. He developed a loss of consciousness after the first administration. Cerebral spinal fluid and magnetic resonance imaging of the brain suggested encephalopathy. Conclusion: It is recommended to be aware of rare but life threatening side effects of daratumumab. We present a case of rare encephalopathy characterized by consciousness disorder associated with daratumumab, which was successfully resolved on prompt institution of steroids, although the mechanism was unknown.
Daratumumab is a drug. It is used to treat multiple myeloma. Many patients use this drug. It has many side effects. But consciousness disorder is rare. A 57-year-old male was diagnosed with multiple myeloma. He was treated with daratumumab. He became unconscious after this treatment. Steroids helped his recovery.
Subject(s)
Brain Diseases , Multiple Myeloma , Humans , Male , Middle Aged , Antibodies, Monoclonal/adverse effects , Antineoplastic Combined Chemotherapy Protocols/adverse effects , Brain Diseases/etiology , Brain Diseases/chemically induced , Multiple Myeloma/diagnosis , Multiple Myeloma/drug therapyABSTRACT
PURPOSE: To compare the efficacy of radiomics models via five machine learning algorithms in predicting the histological grade of hepatocellular carcinoma (HCC) before surgery and to develop the most stable model to classify high-risk HCC patients. METHODS: Contrast-enhanced computed tomography (CECT) images of 175 HCC patients before surgery were analysed, and radiomics features were extracted from CECT images (including arterial and portal phases). Five machine learning models, including Bayes, random forest (RF), k-nearest neighbors (KNN), logistic regression (LR), and support vector machine (SVM), were applied to establish the model. The stability of the five models was weighed by the relative standard deviation (RSD), and the lowest RSD value was chosen as the most stable model to predict the histological grade of HCC. The area under the curve (AUC) and Delong tests were devoted to assessing the predictive efficacy of the models. RESULTS: High-grade HCC accounted for 28.57% (50/175) of the 175 patients. The RSD value of AUC via the RF machine learning model was the lowest (2.3%), followed by Bayes (3.2%), KNN (6.4%), SVM (8.7%) and LR (31.3%). In addition, the RF model (AUC = 0.995) was better than the other four models in the training set (p < 0.05), as well as obtained good predictive performance in the test set (AUC = 0.837). CONCLUSION: Among the five machine learning models, the RF-based radiomics model was the most stable and performed excellently in identifying high histological grade of HCC.
Subject(s)
Carcinoma, Hepatocellular , Liver Neoplasms , Humans , Bayes Theorem , Carcinoma, Hepatocellular/diagnostic imaging , Carcinoma, Hepatocellular/surgery , Liver Neoplasms/diagnostic imaging , Liver Neoplasms/surgery , Algorithms , Machine Learning , Retrospective StudiesABSTRACT
OBJECTIVE: This study aimed to extract radiomics features (RFs) from pre-treatment CT scans in patients with acute ischemic stroke (AIS), and to establish a radiomics model to predict hemorrhagic transformation (HT) after endovascular therapy (EVT). METHODS: A total of 105 patients who were diagnosed with AIS [with occlusion of the M1 segment of the middle cerebral artery (MCA) and/or internal carotid artery] and received EVT were enrolled. They were randomly divided into the development cohort (n = 73) and the validation cohort (n = 32). The clinicoradiological data of all patients, including pre-treatment cranial CT without contrast enhancement, CT perfusion, and CT angiography, were obtained. The MCA territory on pre-treatment CT images was segmented to extract RFs associated with HT after EVT. Then, a CT radiomics model based on the selected RFs was constructed to predict HT after EVT. RESULTS: The sensitivity, speciï¬city, and area under the curve of the CT radiomics model for predicting HT after EVT based on pre-treatment CT RFs was 0.806, 0.649, and 0.781 (95% confidence interval (CI): 0.675-0.886), respectively, in the development cohort. The sensitivity, specificity, and area under the curve in the validation cohort was 0.625, 0.875, and 0.797 (95% CI: 0.642-0.951), respectively. CONCLUSION: CT radiomics analysis is a valuable tool for predicting HT in AIS patients receiving EVT. It may guide the selection of patients in practice and improve procedural safety and effectiveness. ADVANCES IN KNOWLEDGE: Identification of the importance of pre-treatment CT radiomics in the prediction of HT in AIS patients after EVT.
Subject(s)
Brain Ischemia , Endovascular Procedures , Ischemic Stroke , Stroke , Humans , Stroke/diagnostic imaging , Stroke/therapy , Stroke/etiology , Ischemic Stroke/diagnostic imaging , Ischemic Stroke/therapy , Tomography, X-Ray Computed/methods , Computed Tomography Angiography/methods , Endovascular Procedures/methods , Retrospective Studies , Brain Ischemia/diagnostic imaging , Brain Ischemia/therapy , Brain Ischemia/etiologyABSTRACT
PURPOSE: Radiomics analysis is a promising image analysis technique. This study aims to extract a radiomics signature from baseline computed tomography (CT) to predict malignant cerebral edema (MCE) in patients with acute anterior circulation infarction after endovascular treatment (EVT). METHODS: In this retrospective study, 111 patients underwent EVT for acute ischemic stroke caused by middle cerebral artery (MCA) and/or internal carotid artery occlusion. The participants were randomly divided into two datasets: the training set (n = 77) and the test set (n = 34). The clinico-radiological profiles of all patients were collected, including cranial non-contrast-enhanced CT, CT angiography, and CT perfusion. The MCA territory on non-contrast-enhanced CT images was segmented, and the radiomics features associated with MCE were analyzed. The clinico-radiological parameters related to MCE were also identified. In addition, a routine visual radiological model based on radiological factors and a combined model comprising radiomics features and clinico-radiological factors were constructed to predict MCE. RESULTS: The areas under the curve (AUCs) of the radiomics signature for predicting MCE were 0.870 (P < 0.001) and 0.837 (P = 0.002) in the training and test sets, respectively. The AUCs of the routine visual radiological model were 0.808 (P < 0.001) and 0.813 (P = 0.005) in the training and test sets, respectively. The AUCs of the model combining the radiomics signature and clinico-radiological factors were 0.924 (P < 0.001) and 0.879 (P = 0.001) in the training and test sets, respectively. CONCLUSION: A CT image-based radiomics signature is a promising tool for predicting MCE in patients with acute anterior circulation infarction after EVT. For clinicians, it may assist in diagnostic decision-making.
Subject(s)
Brain Edema , Ischemic Stroke , Radiology , Humans , Ischemic Stroke/diagnostic imaging , Ischemic Stroke/surgery , Brain Edema/diagnostic imaging , Brain Edema/etiology , Retrospective Studies , InfarctionABSTRACT
PURPOSE: To develop and validate the nomogram by combining MRI-derived radiomics and clinical features for preoperatively predicting massive intraoperative blood loss (IBL) in high-risk placenta accreta spectrum (PAS) patients. METHODS: A total of 152 high-risk PAS patients from Hospital A were enrolled and constituted the training cohort, and 64 patients from Hospital B constituted the validation cohort. Clinical features were analyzed retrospectively. Placental regions of interest were manually positioned on sagittal T2-weighted HASTE images for each patient to extract quantitative radiomics features. Clinical model, radiomics model, and nomogram were built to predict the risk of massive IBL. The diagnostic performance was assessed using the area under the receiver operating characteristic curve (AUC) and the DeLong test. Decision curve analysis (DCA) was performed to determine the performance of the best predictive model. RESULTS: The nomogram (AUC = 0.866 and 0.876, respectively) and radiomics model (AUC = 0.821 and 0.855, respectively) outperformed the clinical model (AUC = 0.685 and 0.619, respectively) both in the training and validation cohorts (Delong test, P < 0.05). Furthermore, the nomogram performed best with an accuracy of 0.844, sensitivity of 0.882, and specificity of 0.830 for differentiating massive IBL in the validation cohort. DCA confirmed the clinical utility of the nomogram. CONCLUSION: The nomogram can be used to noninvasively predict massive IBL patients and guide obstetricians to make reasonable preoperative treatment plans.
Subject(s)
Blood Loss, Surgical , Placenta Accreta , Pregnancy , Humans , Female , Nomograms , Retrospective Studies , Placenta , Prenatal Diagnosis , Magnetic Resonance ImagingABSTRACT
PURPOSE We aimed to systematically explore the value of iodine values calculated from dual-energy computed tomography (DECT) as potential prognostic factors for locally advanced gastric cancer (LAGC) patients undergoing neoadjuvant chemotherapy (NAC). METHODS Eighty-five LAGC patients were examined using DECT before and after NAC and were divided into responders and non-responders based on the tumor regression grade (TRG). The iodine values, including portal- and delayed-phase iodine uptake (IU-p and IU-d, mg/ml) and total iodine uptake (TIU-p and TIU-d, mg) were acquired. Correlations between the reduction ratios of iodine values and TRG were analyzed. The diagnostic performance of parameters for differentiating responders from non-responders was calculated. Kaplan-Meier method was used for survival analysis. RESULTS The reduction ratios of total iodine uptake (%â³TIU-p and %â³TIU-d) were significantly correlated with TRG (p < 0.001). The ypN stage, %â³TIU-p and %â³TIU-d were significant factors influencing PFS (p < 0.050). A value of %â³TIU-d≤62.19% was associated with negative prognosis [relative risk (RR):2.103; P = 0.021], as was ypN stage (RR:4.250; p = 0.003). CONCLUSION Iodine values (especially the TIU) are noninvasive quantitative parameters that are potentially helpful for evaluating the treatment response and survival prognosis of LAGC after NAC. %â³TIU-d represents a strong independent prognostic factor, increasing preoperative risk assessment performance.
Subject(s)
Iodine , Stomach Neoplasms , Humans , Iodine/therapeutic use , Neoadjuvant Therapy , Prognosis , Retrospective Studies , Stomach Neoplasms/diagnostic imaging , Stomach Neoplasms/drug therapy , Stomach Neoplasms/pathology , Survival AnalysisABSTRACT
Purpose: This study aims to uncover and validate an MRI-based radiomics nomogram for detecting lymph node metastasis (LNM) in pancreatic ductal adenocarcinoma (PDAC) patients prior to surgery. Materials and Methods: We retrospectively collected 141 patients with pathologically confirmed PDAC who underwent preoperative T2-weighted imaging (T2WI) and portal venous phase (PVP) contrast-enhanced T1-weighted imaging (T1WI) scans between January 2017 and December 2021. The patients were randomly divided into training (n = 98) and validation (n = 43) cohorts at a ratio of 7:3. For each sequence, 1037 radiomics features were extracted and analyzed. After applying the gradient-boosting decision tree (GBDT), the key MRI radiomics features were selected. Three radiomics scores (rad-score 1 for PVP, rad-score 2 for T2WI, and rad-score 3 for T2WI combined with PVP) were calculated. Rad-score 3 and clinical independent risk factors were combined to construct a nomogram for the prediction of LNM of PDAC by multivariable logistic regression analysis. The predictive performances of the rad-scores and the nomogram were assessed by the area under the operating characteristic curve (AUC), and the clinical utility of the radiomics nomogram was assessed by decision curve analysis (DCA). Results: Six radiomics features of T2WI, eight radiomics features of PVP and ten radiomics features of T2WI combined with PVP were found to be associated with LNM. Multivariate logistic regression analysis showed that rad-score 3 and MRI-reported LN status were independent predictors. In the training and validation cohorts, the AUCs of rad-score 1, rad-score 2 and rad-score 3 were 0.769 and 0.751, 0.807 and 0.784, and 0.834 and 0.807, respectively. The predictive value of rad-score 3 was similar to that of rad-score 1 and rad-score 2 in both the training and validation cohorts (P > 0.05). The radiomics nomogram constructed by rad-score 3 and MRI-reported LN status showed encouraging clinical benefit, with an AUC of 0.845 for the training cohort and 0.816 for the validation cohort. Conclusions: The radiomics nomogram derived from the rad-score based on MRI features and MRI-reported lymph status showed outstanding performance for the preoperative prediction of LNM of PDAC.
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Objectives: The study developed and validated a radiomics nomogram based on a combination of computed tomography (CT) radiomics signature and clinical factors and explored the ability of radiomics for individualized prediction of Ki-67 expression in hepatocellular carcinoma (HCC). Methods: First-order, second-order, and high-order radiomics features were extracted from preoperative enhanced CT images of 172 HCC patients, and the radiomics features with predictive value for high Ki-67 expression were extracted to construct the radiomic signature prediction model. Based on the training group, the radiomics nomogram was constructed based on a combination of radiomic signature and clinical factors that showed an independent association with Ki-67 expression. The area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA) were used to verify the performance of the nomogram. Results: Sixteen higher-order radiomic features that were associated with Ki-67 expression were used to construct the radiomics signature (AUC: training group, 0.854; validation group, 0.744). In multivariate logistic regression, alfa-fetoprotein (AFP) and Edmondson grades were identified as independent predictors of Ki-67 expression. Thus, the radiomics signature was combined with AFP and Edmondson grades to construct the radiomics nomogram (AUC: training group, 0.884; validation group, 0.819). The calibration curve and DCA showed good clinical application of the nomogram. Conclusion: The radiomics nomogram developed in this study based on the high-order features of CT images can accurately predict high Ki-67 expression and provide individualized guidance for the treatment and clinical monitoring of HCC patients.
Subject(s)
Uterine Diseases , Uterine Neoplasms , Female , Humans , Hysterosalpingography , Uterus/diagnostic imagingABSTRACT
We describe a case of reactive nodular fibrous pseudotumor (RNFP) misdiagnosed as lymph node metastasis after gastric cancer surgery. Additionally, we summarize the clinical and imaging characteristics of RNFP, combined with the literature, to improve the understanding of preoperative diagnosis. Radiological features of RNFP are a homogenous, isodense, solid mass with gradually mild enhancement on multiphasic abdominal computed tomography (CT), and slight 18F-FDG uptake by positron emission tomography/computed tomography (PET/CT). To the best of our knowledge, this is the first report in the English literature of a case of reactive nodular fibrous pseudotumor associated with gastric cancer and its appearance on PET/CT images.
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Ischemic stroke remains the leading cause of death and disability, while the main mechanisms of dominant neurological damage in stroke contain excitotoxicity, oxidative stress, and inflammation. The clinical application of many neuroprotective agents is limited mainly due to their inability to cross the blood-brain barrier (BBB), short half-life and low bioavailability. These disadvantages can be better eliminated/reduced by nanoparticle as the carrier of these drugs. This review expounded the currently hot researched nanomedicines from the perspective of the mechanism of ischemic stroke. In addition, this review describes the bionic nanomedicine delivery strategies containing cells, cell membrane vesicles and exosomes that can effectively avoid the risk of clearance by the reticuloendothelial system. The potential challenges and application prospect for clinical translation of these delivery platforms were also discussed.
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The vascular endothelial glycocalyx is a dense, bush-like structure that is synthesized and secreted by endothelial cells and evenly distributed on the surface of vascular endothelial cells. The blood-brain barrier (BBB) is mainly composed of pericytes endothelial cells, glycocalyx, basement membranes, and astrocytes. The glycocalyx in the BBB plays an indispensable role in many important physiological functions, including vascular permeability, inflammation, blood coagulation, and the synthesis of nitric oxide. Damage to the fragile glycocalyx can lead to increased permeability of the BBB, tissue edema, glial cell activation, up-regulation of inflammatory chemokines expression, and ultimately brain tissue damage, leading to increased mortality. This article reviews the important role that glycocalyx plays in the physiological function of the BBB. The review may provide some basis for the research direction of neurological diseases and a theoretical basis for the diagnosis and treatment of neurological diseases.
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BACKGROUND: Both omacetaxine (HHT) and curcumin were shown to exhibit anti-proliferative effect on lymphoma cells. However, the role of combination of HHT with curcumin (HHT/curcumin combination) on lymphoma cells remains unclear. Thus, this study aimed to investigate the effect of HHT/curcumin combination on the proliferation, migration, and angiogenesis of lymphoma cells. METHODS: Cell counting kit-8 (CCK-8), Ki67 immunofluorescence and transwell assays were used to assess the viability, proliferation and migration of U937 and Raji cells respectively. In addition, tube formation assay was used to determine the effects of HHT/curcumin combination on angiogenesis in human umbilical vein endothelial cells (HUVECs). RESULTS: In this study, we found that HHT/curcumin combination significantly inhibited the proliferation, migration and invasion in U937 and Raji cells (all P < 0.01). In addition, combination treatment markedly inhibited the secreted levels of vascular endothelial growth factor (VEGF)-(A-D) (all P < 0.01) in Raji cells. Moreover, combination treatment exhibited anti-tumor effects in Raji cells, as shown by the decreased signals of phosphorylated VEGF receptor 2 (p-VEGFR2) and phosphorylated protein kinase B (p-Akt) (all P < 0.01). Meanwhile, combination treatment inhibited VEGFA levels (P < 0.01) in exosomes derived from Raji cells. Application of exosomes with downregulated VEGF to HUVECs notably inhibited proliferation, migration and tube formation of HUVECs, evidenced by the decreased signals of p-Akt, angiogenin-1, matrix metallopeptidase 2 (MMP2) and matrix metallopeptidase 9 (MMP9) (all P < 0.01). CONCLUSION: Our findings indicated that combination of HHT and curcumin could inhibit lymphoma cell growth and angiogenesis via inhibition of VEGF/Akt signaling pathway. These results suggested that HHT combined with curcumin might be regarded as a promising therapeutic approach for the treatment of lymphoma.
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Both homoharringtonine (HHT) and curcumin exhibit anti-proliferative effects on lymphoma cells, but the effects of combined HHT and curcumin treatment remain unclear. Here, we investigated the effects of HHT/curcumin combination on the proliferation, apoptosis, and invasion in lymphoma cells. CCK-8, flow cytometry, and transwell assays were used to assess proliferation, apoptosis, and invasion of U937 and Raji cells. p-Smad3, E-cadherin, and N-cadherin expression were also measured in Raji cells using Western blot assays. Combination of HHT and curcumin synergistically inhibited U937 and Raji cell proliferation and invasion. In addition, the combination treatment markedly increased apoptosis of Raji cells as evidenced by increased Bax, cleaved caspase 3, and cleaved caspase 9 expression. Meanwhile, the combination treatment promoted anti-tumor mechanisms in Raji cells as indicated by decreases in p-Smad3 and N-cadherin and increases in E-cadherin. In vivo experiments showed that the combination treatment suppressed tumor growth in a mouse Raji xenograft model. Our findings indicate that combination of HHT and curcumin inhibited lymphoma cell growth by downregulating the TGF-ß/Smad3 pathway. These results suggest that HHT combined with curcumin might be a promising therapeutic approach for the treatment of lymphoma.
Subject(s)
Antineoplastic Agents/pharmacology , Curcumin/pharmacology , Homoharringtonine/pharmacology , Lymphoma/drug therapy , Plant Extracts/pharmacology , Smad3 Protein/metabolism , Transforming Growth Factor beta/metabolism , Animals , Antineoplastic Agents/therapeutic use , Apoptosis , Cadherins/metabolism , Caspase 3/metabolism , Caspase 9/metabolism , Cell Line, Tumor , Cell Proliferation , Cephalotaxus/chemistry , Curcuma/chemistry , Curcumin/therapeutic use , Drug Therapy, Combination , Homoharringtonine/therapeutic use , Mice, Inbred BALB C , Mice, Nude , Neoplasm Invasiveness , Phytotherapy , Plant Extracts/therapeutic use , Signal Transduction , Xenograft Model Antitumor Assays , bcl-2-Associated X Protein/metabolismABSTRACT
BACKGROUND: C-Myc aberrations confer a more aggressive clinic behavior in diffuse large B-cell lymphoma (DLBCL). Matrine is an alkaloid extracted from Sophora flavescens Ait. It possesses anti-cancer property through inhibiting the cell proliferation and inducing the apoptosis. The present study aimed to explore the underlying mechanisms of matrine in suppressing the cell growth of DLBCL. METHODS: The influence of matrine on the viability of cultured DLBCL cell lines SU-DHL-16 and OCI-LY3 cells were determined by CCK-8. Apoptosis and cell cycle were measured by flow cytometry after matrine exposure. Western blot was taken to investigate the expression of activated Caspase-3, cleaved PARP, c-Myc, phospho-c-Myc (Ser62), CaMKIIγ, phospho-CaMKIIγ (Thr287), CDK4 and CDK6 after matrine treatment. Cycloheximide chase analysis was used to determine the c-Myc protein half-lives before and after matrine treatment. Growth salvage analysis was taken by ectopic expression of c-Myc. RESULTS: In cultured DLBCL cells, matrine suppressed cell viability in a concentration and time dependent fashion. Matrine treated SU-DHL-16 and OCI-LY3 cells for 48 h with IC50 value of 1.76 mM and 4.1 mM, respectively. Matrine induced apoptosis through a caspase-independent pathway and caused G0/G1 cell cycle arrest in a concentration dependent manner in DLBCL cells. The protein expression of c-Myc was inhibited while the transcription of c-Myc was not reduced by matrine. c-Myc protein half-lives were decreased from 30.4, 69.4 min to 16.6, 15.9 min after matrine treatment in SU-DHL-16 and OCI-LY3, respectively. As a critical protein kinase of c-Myc, CaMKIIγ phosphorylation at Thr287 was found to be down-regulated and c-Myc phosphorylation at Ser62 was reduced together after matrine treatment in DLBCL. The growth suppression of SU-DHL-16 cells induced by matrine was rescued by over-expression of c-Myc achieved by recombinant adenovirus infection. The decreased expression of CDK6, not CDK4, induced by matrine was rescued by ectopic expression of c-Myc protein. CONCLUSIONS: This study has shown for the first time that matrine suppresses cell growth of DLBCL via inhibiting CaMKIIγ/c-Myc/CDK6 signaling pathway.
Subject(s)
Alkaloids/pharmacology , Antineoplastic Agents/pharmacology , Cell Proliferation/drug effects , Lymphoma, Large B-Cell, Diffuse/metabolism , Quinolizines/pharmacology , Signal Transduction/drug effects , Calcium-Calmodulin-Dependent Protein Kinase Type 2/metabolism , Cell Line, Tumor , Cell Survival/drug effects , Cyclin-Dependent Kinase 6/metabolism , Humans , Proto-Oncogene Proteins c-myc/metabolism , MatrinesABSTRACT
OBJECTIVES: To systematically evaluate and compare the predictive capability for microvascular invasion (MVI) in hepatocellular carcinoma (HCC) patients based on radiomics from multi-parametric MRI (mp-MRI) including six sequences when used individually or combined, and to establish and validate the optimal combined model. METHODS: A total of 195 patients confirmed HCC were divided into training (n = 136) and validation (n = 59) datasets. All volumes of interest of tumors were respectively segmented on T2-weighted imaging, diffusion-weighted imaging, apparent diffusion coefficient, artery phase, portal venous phase, and delay phase sequences, from which quantitative radiomics features were extracted and analyzed individually or combined. Multivariate logistic regression analyses were undertaken to construct clinical model, respective single-sequence radiomics models, fusion radiomics models based on different sequences and combined model. The accuracy, sensitivity, specificity and area under the receiver operating characteristic curve (AUC) were calculated to evaluate the performance of different models. RESULTS: Among nine radiomics models, the model from all sequences performed best with AUCs 0.889 and 0.822 in the training and validation datasets, respectively. The combined model incorporating radiomics from all sequences and effective clinical features achieved satisfactory preoperative prediction of MVI with AUCs 0.901 and 0.840, respectively, and could identify the higher risk population of MVI (P < 0.001). The Delong test manifested significant differences with P < 0.001 in the training dataset and P = 0.005 in the validation dataset between the combined model and clinical model. CONCLUSIONS: The combined model can preoperatively and noninvasively predict MVI in HCC patients and may act as a usefully clinical tool to guide subsequent individualized treatment.
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BACKGROUND: Diffuse large B-cell lymphoma (DLBCL) is a common type of the Non-Hodgkin lymphomas (NHLs) formed by the neoplastic transformation of mature B cells. As the first-line therapeutics, CHOP (cyclophosphamide/doxorubicin/vincristine/prednisone) chemotherapy and R-CHOP (Rituximab + CHOP), either using alone or in combination with GM-CSF, have achieved great efficacy in DLBCL patients. However, the underlying mechanisms are still largely unknown. METHODS: In the present study, the combination use of CHOP and R-CHOP with GM-CSF was used to evaluate their effects on the tumor immune microenvironment of DLBCL. CHOP and R-CHOP administration was found to inhibit the growth and metastasis of DLBCL, with a higher efficacy in R-CHOP-challenged DLBCL mice. The anti-tumor effect of CHOP and R-CHOP was further amplified by GM-CSF. RESULTS: CHOP and R-CHOP therapeutics potentiated the anti-tumor properties of macrophages, as evidenced by the increased M1 macrophage and the decreased M2 macrophage accumulation in DLBCL-bearing mice. In a co-culture system, macrophages primed with CHOP and R-CHOP therapeutics inhibited multiple malignant behaviors of DLCBL cells. Mechanistically, CHOP/R-CHOP suppressed the activation of AKT signaling. These anti-tumor effects of CHOP/R-CHOP were all augmented by GM-CSF. CONCLUSIONS: Our work provided new insights into the immune-regulatory roles of CHOP and R-CHOP in the treatment of DLBCL, as well as the synergistic effects of GM-CSF in CHOP and R-CHOP therapeutics. Although our results suggest the synergistic effect of GM-CSF on DLBCL already sensitive to CHOP and R-CHOP, however, future studies are warranted to explore the role of GM-CSF on R-CHOP-resistant DLBCL. Trial registration Not applicable.