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Objective: Follicular lymphoma (FL) is an indolent B-cell lymphoproliferative disorder, characterized by a lymphoid follicular pattern of growth. PFI-1 or CPI-203 has been known to effectively promote the inhibition of primary effusion lymphoma progression. This study aimed at investigating the anti-tumor properties of PFI-1 and CPI-203 on FL cells and uncover the underlying mechanism of action. Methods: FL cells were treated with PFI-1 and CPI-203, and the treated cells were evaluated for their cell viability, cell cycle and apoptosis using CCK8, flow cytometry, and Western blot assays. A xenograft mouse model was used for assessing the in vivo effects of CPI-203 on tumorigenesis. Results: PFI-1 or CPI-203 showed potential inhibitory effects on the cell viability of DOHH2 and RL cells in a dose-response-dependent manner. Furthermore, PFI-1 and CPI-203 inhibited cell growth, induced apoptosis of FL cells in vitro, and facilitated the translocation of ß-catenin into cytoplasm both in vitro and in vivo. After engrafted with FL cells, CPI-203-treated mice got a longer duration of survival and a smaller tumor size than control mice. Mechanistically, PFI-1 and CPI-203 impede the activity of ß-catenin and its downstream molecules by regulating the DVL2/GSK3ß axis. Conclusion: In conclusion, PFI-1 and CPI-203 may serve as potential anti-tumor inhibitors for the therapy of FL.
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Background: Progression of disease within 24 months (POD24) is a risk factor for poor survival in follicular lymphoma (FL), and there is currently no optimal prognostic model to accurately predict patients with early disease progression. How to combine traditional prognostic models with new indicators to establish a new prediction system, to predict the early progression of FL patients more accurately is a future research direction. Methods: This study retrospectively analyzed patients with newly diagnosed FL patients in Shanxi Provincial Cancer Hospital from January 2015 to December 2020. Data from patients undergoing immunohistochemical detection (IHC) were analyzed using χ2 test and multivariate Logistic regression. Also, we built a nomogram model based on the results of LASSO regression analysis of POD24, which was validated in both the training set and validation set, and additional external validation was performed using a dataset (n = 74) from another center, Tianjin Cancer Hospital. Results: The multivariate Logistic regression results suggest that high-risk PRIMA-PI group, Ki-67 high expression represent risk factors for POD24 (P<0.05). Next, PRIMA-PI and Ki67 were combined to build a new model, namely, PRIMA-PIC to reclassify high and low-risk groups. The result showed that the new clinical prediction model constructed by PRIMA-PI with ki67 has a high sensitivity to the prediction of POD24. Compared to PRIMA-PI, PRIMA-PIC also has better discrimination in predicting patient's progression-free survival (PFS) and overall survival (OS). In addition, we built nomogram models based on the results of LASSO regression (histological grading, NK cell percentage, PRIMA-PIC risk group) in the training set, which were validated using internal validation set and external validation set, we found that C-index and calibration curve showed good performance. Conclusion: As such, the new predictive model-based nomogram established by PRIMA-PI and Ki67 could well predict the risk of POD24 in FL patients, which boasts clinical practical value.
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OBJECTIVE: To study the relationship between myc gene rearrangement and myc protein expression in diffuse large B cell lymphoma (DLBCL), and their correlation with prognosis. METHODS: One hundred and six cases of DLBCLs with follow-up data were analyzed using interphase fluorescence in situ hybridization (FISH) technique. Immunophenotyping analysis for CD20, CD3, myc, Mum-1, CD10, bcl-6 was also performed using EnVision immunohistochemistry. RESULTS: The percentages of tumor cells expressing myc, Mum-1, CD10 and bcl-6 were 70.8%, 56.6%, 21.7% and 26.4%, respectively. Twenty six cases (24.5%) were of GCB type and the rest (75.5%) were of non-GCB (non germinal center) type. The myc rearrangement was identified in 13 (12.3%) of 106 cases. 13 cases showed to be of non-GCB type. There was no correlation between myc rearrangement and myc protein expression. DLBCLs (n = 13) with myc rearrangement showed significantly poorer overall survival (OS) and progression free survival (PFS), with a median OS and PFS time of 4.7 and 3.2 months, respectively (for OS and PFS, P < 0.001). Multivariate analysis using Cox proportional hazard model confirmed that myc rearrangement, ECOG performance status of 2-4, immunophenotyping subgroup and myc protein were independent factors affecting the prognosis and significantly associated with the survival. However, myc rearrangement was the strongest prognostic factor. CONCLUSIONS: DLBCL with myc gene rearrangement is a subgroup of non-GCB DLBCL with poor outcome. It is an independent and useful factor for prognosis in DLBCL. Expression of myc is influenced by many factors and myc rearrangement may be one of these factors.