Analysis of GNA13 Protein in Follicular Lymphoma and its Association With Poor Prognosis

Identification of potentially functional modules and diagnostic genes related to amyotrophic lateral sclerosis based on the WGCNA and LASSO algorithms

Amyotrophic lateral sclerosis (ALS) is a genetically and phenotypically heterogeneous disease results in the loss of motor neurons. Mounting information points to involvement of other systems including cognitive impairment. However, neither the valid biomarker for diagnosis nor effective therapeutic intervention is available for ALS. The present study is aimed at identifying potentially genetic biomarker that improves the diagnosis and treatment of ALS patients based on the data of the Gene Expression Omnibus. We retrieved datasets and conducted a weighted gene co-expression network analysis (WGCNA) to identify ALS-related co-expression genes. Functional enrichment analysis was performed to determine the features and pathways of the main modules. We then constructed an ALS-related model using the least absolute shrinkage and selection operator (LASSO) regression analysis and verified the model by the receiver operating characteristic (ROC) curve. Besides we screened the non-preserved gene modules in FTD and ALS-mimic disorders to distinct ALS-related genes from disorders with overlapping genes and features. Altogether, 4198 common genes between datasets with the most variation were analyzed and 16 distinct modules were identified through WGCNA. Blue module had the most correlation with ALS and functionally enriched in pathways of neurodegeneration-multiple diseases', 'amyotrophic lateral sclerosis', and 'endocytosis' KEGG terms. Further, some of other modules related to ALS were enriched in 'autophagy' and 'amyotrophic lateral sclerosis'. The 30 top of hub genes were recruited to a LASSO regression model and 5 genes (BCLAF1, GNA13, ARL6IP5, ARGLU1, and YPEL5) were identified as potentially diagnostic ALS biomarkers with validating of the ROC curve and AUC value.

CD37 expression in follicular lymphoma

CD37 is a tetraspanin protein expressed in various B-cell lymphomas that mediates tumor survival signaling. Follicular lymphoma (FL) is a representative B-cell neoplasm composed of germinal center B cells. In recent years, CD37 has been focused on as a therapeutic target for B-cell lymphoma. The purpose of this study was to characterize CD37 expression in FL patients to identify risk factors associated with various prognostic factors. We retrospectively reviewed 167 cases of FL and evaluated the immunohistochemical expression of CD37 and its statistical association with clinicopathological features. Immunohistochemically, CD37 was observed in the cytoplasm and/or membrane of neoplastic cells, mainly in neoplastic follicles to various extents. One hundred cases (100/167, 60.0%) were categorized as CD37-positive, and 67 cases were CD37-negative. In cases with high Follicular Lymphoma International Prognostic Index (FLIPI), CD37-negative cases had a poor overall survival compared with CD37-positive cases (P = 0.047), although no significant differences were observed in other clinicopathologic factors, including histological grade, BCL2-IGH translocation, and immunohistochemical phenotype. Therefore, CD37 protein may play a role in tumor progression and may serve as a therapeutic target. However, further studies are needed to explore its significance.

Clinicopathological analysis of immunohistochemical expression of immune checkpoint molecules in follicular lymphoma

Follicular lymphoma (FL) is characterized by an indolent clinical course and a high relapse rate, and often exhibits a diffuse pattern beyond the follicular area. Our group previously reported that immune checkpoint (ICP) pathways, such as programmed cell death (PD-1) and programmed death ligand 1 (PD-L1), are poor prognostic factors for diffuse large B-cell lymphoma and adult T-cell leukemia/lymphoma.In this study, the association between the expression of multiple ICP molecules according to immunohistochemistry and clinicopathological features in FL was determined via immunostaining of 173 biopsy samples. Membrane and/or cytoplasm expression of CD86 (nCD86) and PD-L1 (nPD-L1) was found in tumor cells, whereas PD-1 (miPD-1), Galectin-9 (miGalectin-9), OX40 (miOX40), CTLA-4 (miCTLA-4), Tim-3 (miTim-3), OX40L (miOX40L), and LAG-3 (miLAG-3) were expressed in non-neoplastic stromal cells. MiPD-1 expression was significantly higher in the follicular area than in the diffuse area (p=0.0450). Expression of miOX40 and miCTLA-4 was significantly higher in the diffuse area than in the follicular area (respectively, p=0.0053 and p=0.0092). MiTim-3 tended to be higher in the diffuse area than in the follicular area (p=0.0616). MiTim-3 was significantly higher in relapse cases than in new-onset cases (p=0.0440); miLAG-3 tended to be higher in relapse cases than in new-onset cases (p=0.0622, not significant). The miOX40L-high FL group had a significantly worse overall survival than the miOX40L-low group (p=0.0320).The expression of multiple ICP molecules on several cells reflects activated anti-tumor immunity and the unique FL microenvironment. Further studies on gene expression or genomic abnormalities will reveal the clinical and biological significance of ICP molecules in FL. This article is protected by copyright. All rights reserved.

GNA13 regulates BCL2 expression and the sensitivity of GCB-DLBCL cells to BCL2 inhibitors in a palmitoylation-dependent manner

GNA13, encoding one of the G protein alpha subunits of heterotrimeric G proteins that transduce signals of G protein-coupled receptors (GPCR), is frequently mutated in germinal center B-cell-like diffuse large B-cell lymphoma (GCB-DLBCL) with poor prognostic outcomes. Due to the "undruggable" nature of GNA13, targeted therapy for these patients is not available. In this study, we found that palmitoylation of GNA13 not only regulates its plasma membrane localization, but also regulates GNA13's stability. It is essential for the tumor suppressor function of GNA13 in GCB-DLBCL cells. Interestingly, GNA13 negatively regulates BCL2 expression in GCB-DLBCL cells in a palmitoylation-dependent manner. Consistently, BCL2 inhibitors were found to be effective in killing GNA13-deficient GCB-DLBCL cells in a cell-based chemical screen. Furthermore, we demonstrate that inactivating GNA13 by targeting its palmitoylation enhanced the sensitivity of GCB-DLBCL to the BCL2 inhibitor. These studies indicate that the loss-of-function mutation of GNA13 is a biomarker for BCL2 inhibitor therapy of GCB-DLBCL and that GNA13 palmitoylation is a potential target for combination therapy with BCL2 inhibitors to treat GCB-DLBCL with wild-type GNA13.

Deep learning shows the capability of high-level computer-aided diagnosis in malignant lymphoma

A pathological evaluation is one of the most important methods for the diagnosis of malignant lymphoma. A standardized diagnosis is occasionally difficult to achieve even by experienced hematopathologists. Therefore, established procedures including a computer-aided diagnosis are desired. This study aims to classify histopathological images of malignant lymphomas through deep learning, which is a computer algorithm and type of artificial intelligence (AI) technology. We prepared hematoxylin and eosin (H&E) slides of a lesion area from 388 sections, namely, 259 with diffuse large B-cell lymphoma, 89 with follicular lymphoma, and 40 with reactive lymphoid hyperplasia, and created whole slide images (WSIs) using a whole slide system. WSI was annotated in the lesion area by experienced hematopathologists. Image patches were cropped from the WSI to train and evaluate the classifiers. Image patches at magnifications of ×5, ×20, and ×40 were randomly divided into a test set and a training and evaluation set. The classifier was assessed using the test set through a cross-validation after training. The classifier achieved the highest levels of accuracy of 94.0%, 93.0%, and 92.0% for image patches with magnifications of ×5, ×20, and ×40, respectively, in comparison to diffuse large B-cell lymphoma, follicular lymphoma, and reactive lymphoid hyperplasia. Comparing the diagnostic accuracies between the proposed classifier and seven pathologists, including experienced hematopathologists, using the test set made up of image patches with magnifications of ×5, ×20, and ×40, the best accuracy demonstrated by the classifier was 97.0%, whereas the average accuracy achieved by the pathologists using WSIs was 76.0%, with the highest accuracy reaching 83.3%. In conclusion, the neural classifier can outperform pathologists in a morphological evaluation. These results suggest that the AI system can potentially support the diagnosis of malignant lymphoma.

Good prognosis for follicular lymphoma with estrogen receptor α-positive follicular dendritic cells

Follicular lymphoma (FL) has a meshwork of follicular dendritic cells (FDCs). We previously demonstrated the presence of estrogen receptor alpha (ERα)⁺CD23⁺ FDCs in grades 1‐2 FL. The significance of FDCs as a prognostic factor in FL remains unknown. The current study aimed to compare clinicopathological features, including prognosis, between FL with and without ERα⁺ FDCs. This study evaluated the clinicopathological significance of ERα expression in 70 FL patients by immunostaining. The presence of ERα mRNA on FDCs from 5 FL patients was confirmed by CD21/ERα double staining (immunohistochemistry and in situ hybridization). We defined patients with frequent ERα expression as the ERα^high group and those with infrequent ERα expression as the ERα^low group. Thirty‐two patients were assigned to the ERα^high group (45.7%), and 38 patients were assigned to the ERα^low group (54.3%). Both overall survival (OS) and progression‐free survival (PFS) were significantly better in the ERα^high group than in the ERα^low group (OS, log‐rank, P = .0465; PFS, log‐rank, P = .0336). Moreover, high ERα expression on FDCs was an independent prognostic factor for OS in both the univariate ([hazard ratio] HR, 0.163; P = .0260) and multivariate (HR, 0.050; P = .0188) analyses and for PFS in both the univariate (HR, 0.232; P = .0213) and multivariate (HR, 0.084; P = .0243) analyses. ERα mRNA expression was detected in CD21⁺ FDCs within the neoplastic follicles of FL patients. In conclusion, a neoplastic follicular microenvironment with ERα‐positive FDCs might affect the grade and presence of the follicular pattern of FL and improve patient prognosis.

Hepatitis C virus infection is an independent prognostic factor in follicular lymphoma

Hepatitis C virus (HCV) is a single-stranded RNA virus that not only affects hepatocytes, by B cells as well. It is thought that HCV is involved in the onset of B-cell lymphoma. The clinicopathological characteristics of HCV-positive diffuse large B-cell lymphoma (DLBCL) and HCV-positive splenic marginal zone lymphoma (SMZL) are known, but there has been no report on HCV-positive follicular lymphoma (FL). In this study, the clinicopathological characteristics of HCV-positive FL were examined in 263 patients with FL who were classified into a HCV-positive group with HCV antibody and negative groups without one. The number of patients with HCV-positive FL and HCV-negative FL was 10 (3.8%) and 253 (96.2%), respectively. The patients with HCV-positive FL commonly had more than one region of lymphadenopathy, Ann Arbor stage III/IV, hemoglobin <120 g/l, elevated lactate dehydrogenase level, and high-risk categorization of Follicular Lymphoma International Prognostic Index (FLIPI) than in patients with HCV-negative FL. Overall survival and progression-free survival were poorer in patients with HCV-positive FL than in those with HCV-negative FL (p < 0.0001 and 0.006, respectively). Also, multivariate analysis revealed that positive HCV antibody was a poor prognostic factor of OS. In conclusion, HCV-positive FL has unique clinical features and may have a great impact on the overall survival of affected patients.