Artificial intelligence to detect MYC translocation in slides of diffuse large B-cell lymphoma.
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ABSTRACT:
SUBMITTER: Swiderska-Chadaj Z
PROVIDER: S-EPMC8448690 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous and prevalent subtype of aggressive non-Hodgkin lymphoma that poses diagnostic and prognostic challenges, particularly in predicting drug responsiveness. In this study, we used digital pathology and deep learning to predict responses to immunochemotherapy in patients with DLBCL. We retrospectively collected 251 slide images from 216 DLBCL patients treated with rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP), with their immunochemotherapy response labels. The digital pathology images were processed using contrastive learning for feature extraction. A multi-modal prediction model was developed by integrating clinical data and pathology image features. Knowledge distillation was employed to mitigate overfitting on gigapixel histopathology images to create a model that predicts responses based solely on pathology images. Based on the importance derived from the attention mechanism of the model, we extracted histological features that were considered key textures associated with drug responsiveness. The multi-modal prediction model achieved an impressive area under the ROC curve of 0.856, demonstrating significant associations with clinical variables such as Ann Arbor stage, International Prognostic Index, and bulky disease. Survival analyses indicated their effectiveness in predicting relapse-free survival. External validation using TCGA datasets supported the model's ability to predict survival differences. Additionally, pathology-based predictions show promise as independent prognostic indicators. Histopathological analysis identified centroblastic and immunoblastic features to be associated with treatment response, aligning with previous morphological classifications and highlighting the objectivity and reproducibility of artificial intelligence-based diagnosis. This study introduces a novel approach that combines digital pathology and clinical data to predict the response to immunochemotherapy in patients with DLBCL. This model shows great promise as a diagnostic and prognostic tool for clinical management of DLBCL. Further research and genomic data integration hold the potential to enhance its impact on clinical practice, ultimately improving patient outcomes.
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Project description:A proportion of MYC translocation positive diffuse large B-cell lymphomas (DLBCL) harbour a BCL2 and/or BCL6 translocation, known as double-hit DLBCL, and are clinically aggressive. It is unknown whether there are other genetic abnormalities that cooperate with MYC translocation and form double-hit DLBCL, and whether there is a difference in clinical outcome between the double-hit DLBCL and those with an isolated MYC translocation. We investigated TP53 gene mutations along with BCL2 and BCL6 translocations in a total of 234 cases of DLBCL, including 81 with MYC translocation. TP53 mutations were investigated by PCR and sequencing, while BCL2 and BCL6 translocation was studied by interphase fluorescence in situ hybridization. The majority of MYC translocation positive DLBCLs (60/81 = 74%) had at least one additional genetic hit. In MYC translocation positive DLBCL treated by R-CHOP (n = 67), TP53 mutation and BCL2, but not BCL6 translocation had an adverse effect on patient overall survival. In comparison with DLBCL with an isolated MYC translocation, cases with MYC/TP53 double-hits had the worst overall survival, followed by those with MYC/BCL2 double-hits. In MYC translocation negative DLBCL treated by R-CHOP (n = 101), TP53 mutation, BCL2 and BCL6 translocation had no impact on patient survival. The prognosis of MYC translocation positive DLBCL critically depends on the second hit, with TP53 mutations and BCL2 translocation contributing to an adverse prognosis. It is pivotal to investigate both TP53 mutations and BCL2 translocations in MYC translocation positive DLBCL, and to distinguish double-hit DLBCLs from those with an isolated MYC translocation.
| S-EPMC4915334 | biostudies-literature
Project description:Convolutional neural networks (CNNs) may improve response prediction in diffuse large B-cell lymphoma (DLBCL). The aim of this study was to investigate the feasibility of a CNN using maximum intensity projection (MIP) images from 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) baseline scans to predict the probability of time-to-progression (TTP) within 2 years and compare it with the International Prognostic Index (IPI), i.e. a clinically used score. 296 DLBCL 18F-FDG PET/CT baseline scans collected from a prospective clinical trial (HOVON-84) were analysed. Cross-validation was performed using coronal and sagittal MIPs. An external dataset (340 DLBCL patients) was used to validate the model. Association between the probabilities, metabolic tumour volume and Dmaxbulk was assessed. Probabilities for PET scans with synthetically removed tumors were also assessed. The CNN provided a 2-year TTP prediction with an area under the curve (AUC) of 0.74, outperforming the IPI-based model (AUC = 0.68). Furthermore, high probabilities (> 0.6) of the original MIPs were considerably decreased after removing the tumours (< 0.4, generally). These findings suggest that MIP-based CNNs are able to predict treatment outcome in DLBCL.
| S-EPMC10423266 | biostudies-literature
Project description:Genomic alterations and protein expression levels have been established as prognostic factors for survival in patients with diffuse large B-cell lymphoma (DLBCL). In particular, double-hit DLBCL (DHL), which exhibits translocations in MYC and BCL2 and/or BCL6, is known to be associated with a poor prognosis. However, the clinical significance of gene alterations and protein expression levels for MYC, B-cell lymphoma (BCL)2, and BCL6 are unclear. In this study, we analyzed 61 adult patients diagnosed with DLBCL without DHL, who were treated with rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisolone, or similar regimens. There were no differences in the distribution of MYC expression rates among the different MYC gene statuses. In log-rank tests, MYC translocation was a prognostic factor for overall survival (OS; P = 0.011), whereas BCL2 and BCL6 translocation were not prognostic indicators (P = 0.999 and P = 0.925, respectively). Although the expression levels of MYC and BCL6 were not significantly associated with OS, the expression of BCL2 was a prognostic factor for OS (P = 0.027). Furthermore, copy number gains in the MYC, BCL2, and BCL6 genes did not affect OS. MYC translocation (hazard ratio, 4.769; range, 1.518-14.98; P = 0.007) and BCL2 protein expression (hazard ratio, 3.072; range, 1.002-9.413; P = 0.049) were independent prognostic factors for survival in multivariate analyses. In conclusion, MYC translocation and BCL2 expression may need to be investigated at the initial diagnosis to predict prognosis in patients with DLBCL.
| S-EPMC4968597 | biostudies-literature
Project description:BackgroundMYC is a heterogeneously expressed transcription factor that plays a multifunctional role in many biological processes such as cell proliferation and differentiation. It is also associated with many types of cancer including the malignant lymphomas. There are two types of aggressive B-cell lymphoma, namely Burkitt lymphoma (BL) and a subgroup of diffuse large cell lymphoma (DLBCL), which both carry MYC translocations and overexpress MYC but both differ significantly in their clinical outcome. In DLBCL, MYC translocations are associated with an aggressive behavior and poor outcome, whereas MYC-positive BL show a superior outcome.MethodsTo shed light on this phenomenon, we investigated the different modes of actions of MYC in aggressive B-cell lymphoma cell lines subdivided into three groups: (i) MYC-positive BL, (ii) DLBCL with MYC translocation (DLBCLpos) and (iii) DLBCL without MYC translocation (DLBCLneg) for control. In order to identify genome-wide MYC-DNA binding sites a chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-Seq) was performed. In addition, ChIP-Seq for H3K4me3 was used for determination of genomic regions accessible for transcriptional activity. These data were supplemented with gene expression data derived from RNA-Seq.ResultsBioinformatics integration of all data sets revealed different MYC-binding patterns and transcriptional profiles in MYC-positive BL and DLBCL cell lines indicating different functional roles of MYC for gene regulation in aggressive B-cell lymphomas. Based on this multi-omics analysis we identified ADGRE5 (alias CD97) - a member of the EGF-TM7 subfamily of adhesion G protein-coupled receptors - as a MYC target gene, which is specifically expressed in BL but not in DLBCL regardless of MYC translocation.ConclusionOur study describes a diverse genome-wide MYC-DNA binding pattern in BL and DLBCL cell lines with and without MYC translocations. Furthermore, we identified ADREG5 as a MYC target gene able to discriminate between BL and DLBCL irrespectively of the presence of MYC breaks in DLBCL. Since ADGRE5 plays an important role in tumor cell formation, metastasis and invasion, it might also be instrumental to better understand the different pathobiology of BL and DLBCL and help to explain discrepant clinical characteristics of BL and DLBCL.
| S-EPMC6451309 | biostudies-literature
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| S-EPMC8377611 | biostudies-literature
Project description:Primary diffuse large B-cell lymphoma of the central nervous system (CNS DLBCL) is a rare, aggressive subtype of DLBCL, the biology of which is poorly understood. Recent studies have suggested a prognostic role of MYC protein expression in systemic DLBCL, but little is known about the frequency and significance of MYC protein expression in CNS DLBCL. Hence, we investigated MYC protein expression profiles of CNS DLBCL and assessed the relationship between MYC expression and a variety of histopathologic, immunophenotypic, genetic, and clinical features. Fifty-nine CNS DLBCL diagnosed at our institution over the past 13 years were evaluated. The majority of cases (80%) showed centroblastic morphology, and 12 (20%) displayed a perivascular pattern of infiltration. According to the Hans criteria, 41 (69%) cases had a non-germinal center B-cell and 18 (31%) had a germinal center B-cell cell-of-origin (COO) phenotype. Mean MYC protein expression was 50% (median: 50%, range: 10-80%). Forty-three cases (73%) showed MYC overexpression (? 40%), and 35 (60%) showed MYC/BCL2 coexpression. MYC overexpression was seen in the single case harboring MYC translocation and in the cases showing increased copies of MYC (27%); however, no significant difference in mean MYC expression was seen between groups harboring or lacking MYC aberrations. In our series, age was associated with a significantly increased risk of death, and the perivascular pattern of infiltration was associated with a significantly increased risk of disease progression. Neither MYC expression (with or without BCL2 coexpression) nor other variables, including COO subtype were predictive of clinical outcome. Our findings indicate that the proportion of CNS DLBCL overexpressing MYC is higher compared to systemic DLBCL, and MYC overexpression appears to be independent of genetic MYC abnormalities. Thus, MYC expression and other immunophenotypic markers used for prognostication of systemic DLBCL might not apply to CNS DLBCL due to differences in disease biology.
| S-EPMC4257680 | biostudies-literature
Project description:We previously described involvement of the MYC/miR-150/MYB/ZDHHC11 network in the growth of Burkitt lymphoma (BL) cells. Here we studied the relevance of this network in the two other B-cell lymphomas: Hodgkin lymphoma (HL) and diffuse large B-cell lymphoma (DLBCL). Expression levels of the network components were assessed at the RNA and protein level. The effect of modulating levels of the network components on cell growth was determined through GFP competition assay. AGO2-RNA immunoprecipitation was performed to validate targeting by miR-150. Expression levels of MYC, MYB and ZDHHC11 were increased, while miR-150 levels were decreased similar to the pattern observed in BL. The knockdown of MYC, MYB and ZDHHC11 decreased the growth of HL and DLBCL cells. In contrast, overexpression of miR-150 did not induce clear phenotypes in HL, and limited the effects in DLBCL. This could not be explained by the differences in overexpression levels. Furthermore, we showed that in HL, ZDHHC11 and MYB are efficiently targeted by miR-150. To conclude, MYC, MYB and ZDHHC11 are critical for the growth of HL and DLBCL cells consistent with the role observed in BL cells, while low endogenous miR-150 levels appeared to be less critical for the growth of HL and DLBCL cells despite the effective targeting of ZDHHC11 and MYB.
| S-EPMC8871936 | biostudies-literature
Project description:PurposeMYC is a critical driver oncogene in many cancers, and its deregulation in the forms of translocation and overexpression has been implicated in lymphomagenesis and progression of diffuse large B-cell lymphoma (DLBCL). The MYC mutational profile and its roles in DLBCL are unknown. This study aims to determine the spectrum of MYC mutations in a large group of patients with DLBCL, and to evaluate the clinical significance of MYC mutations in patients with DLBCL treated with rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) immunochemotherapy.Experimental designWe identified MYC mutations in 750 patients with DLBCL using Sanger sequencing and evaluated the prognostic significance in 602 R-CHOP-treated patients.ResultsThe frequency of MYC mutations was 33.3% at the DNA level (mutations in either the coding sequence or the untranslated regions) and 16.1% at the protein level (nonsynonymous mutations). Most of the nonsynonymous mutations correlated with better survival outcomes; in contrast, T58 and F138 mutations (which were associated with MYC rearrangements), as well as several mutations occurred at the 3' untranslated region, correlated with significantly worse survival outcomes. However, these mutations occurred infrequently (only in approximately 2% of DLBCL). A germline SNP encoding the Myc-N11S variant (observed in 6.5% of the study cohort) was associated with significantly better patient survival, and resulted in reduced tumorigenecity in mouse xenografts.ConclusionsVarious types of MYC gene mutations are present in DLBCL and show different impact on Myc function and clinical outcomes. Unlike MYC gene translocations and overexpression, most MYC gene mutations may not have a role in driving lymphomagenesis. Clin Cancer Res; 22(14); 3593-605. ©2016 AACR.
| S-EPMC4947447 | biostudies-literature