Prognostic value of expression of nuclear factor kappa-B/p65 in non-GCB DLBCL patients

Reduced CXCR4 expression in associated with extramedullary and predicts poor survival in newly diagnosed multiple myeloma

BACKGROUND

Multiple myeloma (MM), a bone marrow-resident hematological malignancy of plasma cells, has remained largely incurable despite the recent advancement in novel therapies. The heterogeneity of myeloma cells makes risk stratification of MM important for therapeutic regimen planning.

RESEARCH DESIGN AND METHODS

No immunohistochemical (IHC) predictive and prognostic marker of MM has been constructed yet. Herein, the prognostic value of chemokine (C-X-C motif) receptor 4 (CXCR4) expression in 48 newly diagnosed MM patients was explored using IHC. Correlations between CXCR4 expression and clinical features of MM were analyzed.

RESULTS

CXCR4-positive patients significantly outperformed CXCR4-negative patients in both 3-year estimated overall survival (93.8% vs 45.8%, P = 0.0392) and progression-free survival (57.1% vs 40.9%, P = 0.0436).

CONCLUSIONS

The incidence of extramedullary lesions in CXCR4-negative patients increased significantly compared with CXCR4-positive patients. Plasma cells that reduce CXCR4 expression have poor prognosis and increase the incidence of extramedullary lesions.

Exploration of the core protein network under endometriosis symptomatology using a computational approach

BACKGROUND

Endometriosis is defined by implantation and invasive growth of endometrial tissue in extra-uterine locations causing heterogeneous symptoms, and a unique clinical picture for each patient. Understanding the complex biological mechanisms underlying these symptoms and the protein networks involved may be useful for early diagnosis and identification of pharmacological targets.

METHODS

In the present study, we combined three approaches (i) a text-mining analysis to perform a systematic search of proteins over existing literature, (ii) a functional enrichment analysis to identify the biological pathways in which proteins are most involved, and (iii) a protein-protein interaction (PPI) network to identify which proteins modulate the most strongly the symptomatology of endometriosis.

RESULTS

Two hundred seventy-eight proteins associated with endometriosis symptomatology in the scientific literature were extracted. Thirty-five proteins were selected according to degree and betweenness scores criteria. The most enriched biological pathways associated with these symptoms were (i) Interleukin-4 and Interleukin-13 signaling (p = 1.11 x 10^-16), (ii) Signaling by Interleukins (p = 1.11 x 10^-16), (iii) Cytokine signaling in Immune system (p = 1.11 x 10^-16), and (iv) Interleukin-10 signaling (p = 5.66 x 10^-15).

CONCLUSION

Our study identified some key proteins with the ability to modulate endometriosis symptomatology. Our findings indicate that both pro- and anti-inflammatory biological pathways may play important roles in the symptomatology of endometriosis. This approach represents a genuine systemic method that may complement traditional experimental studies. The current data can be used to identify promising biomarkers for early diagnosis and potential therapeutic targets.

Diffuse large B cell lymphoma originating from the maxillary sinus with skin metastases: A case report and review of literature

BACKGROUND

Diffuse large B-cell lymphoma (DLBCL) is the most common type of malignant lymphoma (ML), accounting for 30%-40% of cases of non-Hodgkin’s lymphoma (NHL) in adults. Primary paranasal sinus lymphoma is a rare presentation of extranodal NHL that accounts for only 0.17% of all lymphomas. ML from the maxillary sinus (MS) is a particularly rare presentation, and is thus often difficult to diagnose. We have reported the first known case of DLBCL originating from the MS with rapidly occurrent multiple skin metastasis.

CASE SUMMARY

An 81-year-old Japanese man visited our hospital due to continuous pain for 12 d in the left maxillary nerve area. His medical history included splenectomy due to a traffic injury, an old right cerebral infarction from when he was 74-years-old, hypertension, and type 2 diabetes mellitus. A plain head computed tomography (CT) scan revealed a 3 cm × 3.1 cm × 3 cm sized left MS. On day 25, left diplopia and ptosis occurred, and a follow-up CT on day 31 revealed the growth of the left MS mass. Based on an MS biopsy on day 50, we established a definitive diagnosis of DLBCL, non-germinal center B-cell-like originating from the left MS. The patient was admitted on day 62 due to rapid deterioration of his condition, and a plain CT scan revealed the further growth of the left MS mass, as well as multiple systemic metastasis, including of the skin. A skin biopsy on day 70 was found to be the same as that of the left MS mass. We notified the patient and his family of the disease, and they opted for palliative care, considering on his condition and age. The patient died on day 80.

CONCLUSION

This case suggests the need for careful, detailed examination, and for careful follow-up, when encountering patients presenting with a mass.

Classifying 2-year recurrence in patients with dlbcl using clinical variables with imbalanced data and machine learning methods

BACKGROUND

Treatments are limited for patients with relapsed/refractory Diffuse large B-cell lymphoma (DLBCL), and their survival rate is low. Prediction of the recurrence hazard for each patient could provide a reference regarding chemotherapy regimens for clinicians to extend patients' period of long-term remission. As current strategies cannot satisfy such need, we have established predictive models to classify patients with DLBCL with complete remission who had recurrences in 2 years from ones who did not.

METHODS

We assessed 518 patients with DLBCL and measured 52 variables of each patient. They were treated between January 2011 and July 2016. 17 variables were first selected by variable selection methods (including Lasso, Adaptive Lasso, and Elastic net). Then, we set classifiers and probability models for imbalanced data by combining the SMOTE sampling, cost-sensitive, and ensemble learning (consisting of AdaBoost, voting strategy, and Stacking) methods with the machine learning methods (Support Vector Machine, BackPropagation Artificial Neural Network, Random Forest), respectively. Last, assessed their performance.

RESULTS

The disease stage and other 5 variables are significant indicators for recurrence. The SVM with AdaBoost ensemble learning method modeling by SMOTE data performs the best (Sensitivity=97.3%, AUC=96%, RMSE=19.6%, G-mean=96%) in all classifiers. The SVM with AdaBoost method(AUC=98.7%, RMSE=17.7%, MXE=12.7%, Cal mean=3.2%, BS0=2.5%, BS1=4%, BSALL=3.1%) and random forest (AUC=99.5%, RMSE=19.8%, MXE=16.2%, Cal mean=9.1%, BS0=4.8%, BS1=2.9%, BSALL=3.9%) both modeling by SMOTE sampling data perform well in probability models.

CONCLUSIONS

This predictive model has high accuracy for almost all DLBCL patients and the six indicators can be recurrence signals.

Tumor Microenvironment in Diffuse Large B-Cell Lymphoma: Role and Prognosis

Diffuse large B-cell lymphoma (DLBCL) represents 30-40% of all non-Hodgkin lymphomas (NHL) and is a disease with an aggressive behavior. Because about one-third of DLBCL patients will be refractory or resistant to standard therapy, several studies focused on identification of new individual prognostic and risk stratification biomarkers and new potential therapeutic targets. In contrast to other types of cancers like carcinomas, where tumor microenvironment was widely investigated, its role in DLBCL pathogenesis and patient survival is still poorly understood, although few studies had promising results. The composition of TME and its interaction with neoplastic cells may explain the role of several genes (beta2-microglobulin gene, CD58 gene), receptor-like programmed cell death-1 (PD-1) and its ligand (PD-L1), or other cell components (Treg) in tumor evasion of immune surveillance, resulting in tumor progression. Also, it was found that “gene expression profile” of the microenvironmental cells, the phenotype of tumor-associated macrophages (TAM), the expression of matricellular proteins like SPARC and fibronectin, the overexpression of several types of matrix metalloproteinases (MMPs) like MMP-2 and MMP-9, or the tissue inhibitors of matrix metalloproteinases (TIMPs) may lead to a favorable or adverse outcome. With this review, we try to highlight the influence of microenvironment components over lymphoid clone progression and their prognostic impact in DLBCL patients.

β-TrCP1 promotes cell proliferation via TNF-dependent NF-κB activation in diffuse large B cell lymphoma

Diffuse large B cell lymphoma (DLBCL), a heterogeneous group of invasive disease, is the most common type of B-cell non-Hodgkin's lymphomas. The mechanism of its development is closely related to the constitutive activation of NF-κB. In this study, we investigated the function and the mechanism of β-TRCP1 in DLBCL. CCK8 and EdU assays showed that β-TRCP1 could promote the growth of DLBCL cells under the stimulation of TNFα. Furthermore, overexpression of β-TRCP1 enhanced NF-κB activation in the presence of TNFα. Moreover, ectopic expression of β-TRCP1 decreased IκB-α expression but increased phospho-p65 expression. In addition, β-TRCP1 promoted cell cycle progression by accelerating G1-S phase transition. We also found that silencing of β-TrCP1 increased mitoxantrone-induced cell growth arrest and apoptosis. Based on these, we proposed that the expression of β-TRCP1 promoted cell proliferation via TNF-dependent NF-κB activation in DLBCL cells.

A Phase II Trial of Bortezomib and Vorinostat in Mantle Cell Lymphoma and Diffuse Large B-cell Lymphoma

BACKGROUND

The proteasome inhibitor bortezomib has demonstrated marked preclinical activity when combined with the histone deacetylase inhibitor vorinostat in leukemia, multiple myeloma, and mantle cell lymphoma (MCL) cells. The present study evaluated the efficacy and safety of the combination in patients with relapsed or refractory MCL and diffuse large B-cell lymphoma (DLBCL).

PATIENTS AND METHODS

The present multicenter, nonrandomized phase II trial used a Simon 2-stage design with 3 cohorts: cohort A, MCL with no previous bortezomib (including untreated MCL); cohort B, MCL with previous bortezomib; and cohort C, relapsed or refractory DLBCL with no previous bortezomib. Vorinostat (400 mg) was administered orally on days 1 to 5 and 8 to 12 before bortezomib (1.3 mg/m2), which was administered intravenously on days 1, 4, 8, and 11 of each 21-day cycle.

RESULTS

For the 65 treated patients (22 in cohort A, 4 in cohort B, and 39 in cohort C), the overall response rate was 31.8%, 0%, and 7.7%, respectively. The median progression-free survival was 7.6 months for cohort A and 1.8 months for cohort C. In cohort A, 7 patients had a partial response (PRs), 5 had stable disease (SD), 7 had progressive disease (PD), 1 was not assessed, and 2 were not evaluable. In cohort B, 2 had SD and 2 had PD. In cohort C, 3 had a PR, 8 had SD, 23 had PD, and 5 were not assessed. Baseline NF-κB activation, measured as nuclear RelA by immunohistochemistry, did not correlate with clinical response.

CONCLUSION

The combination of bortezomib and vorinostat is safe and has modest activity in MCL and limited activity in DLBCL.