Biomarkers of potential prognostic significance in diffuse large B-cell lymphoma

Development and validation of a novel risk stratification model and a survival rate calculator for diffuse large B-cell lymphoma in the rituximab era: a multi-institutional cohort study

BACKGROUND

This study aimed to develop and validate a novel risk stratification model and a web-based survival rate calculator to improve discriminative and predictive accuracy for diffuse large B-cell lymphoma (DLBCL) in the rituximab era.

METHODS

We retrospectively collected pre-treatment data from 873 primary DLBCL patients who received R-CHOP-based immunochemotherapy regimens at the Cancer Hospital, Chinese Academy of Medical Sciences, from January 1, 2005, to December 31, 2018. An independent cohort of 175 DLBCL patients from Fujian Cancer Hospital was used for external validation.

FINDINGS

Age, ECOG PS, number of extranodal sites, Ann Arbor stage, bulky disease, and LDH levels were screened to develop the nomogram and web-based survival rate calculator. The C-index of the nomogram in the training, internal validation, and external validation cohorts was 0.761, 0.758, and 0.768, respectively. The risk stratification model generated based on the nomogram effectively stratified patients into three distinct risk groups. K-M survival curves demonstrated that the novel risk stratification model exhibited a superior level of predictive accuracy compared to IPI, R-IPI, and NCCN-IPI both in training and two validation cohorts. Additionally, the area under the curve (AUC) value of the novel model (0.763) for predicting 5-year overall survival rates was higher than those of IPI (0.749), R-IPI (0.725), and NCCN-IPI (0.727) in the training cohort. Similar results were observed in both internal and external validation cohort.

CONCLUSIONS

In conclusion, we have successfully developed and validated a novel risk stratification model and a web-based survival rate calculator that demonstrated superior discriminative and predictive accuracy compared to IPI, R-IPI, and NCCN-IPI in the rituximab era.

Development and Validation of a Novel Risk Stratification Model for Cancer-Specific Survival in Diffuse Large B-Cell Lymphoma

Diffuse large B-cell lymphoma (DLBCL) is a biologically and clinically heterogenous disease. Identifying more precise and individual survival prognostic models are still needed. This study aimed to develop a predictive nomogram and a web-based survival rate calculator that can dynamically predict the long-term cancer-specific survival (CSS) of DLBCL patients. A total of 3,573 eligible patients with DLBCL from 2004 to 2015 were extracted from the Surveillance, Epidemiology and End Results (SEER) database. The entire group was randomly divided into the training (n = 2,504) and validation (n = 1,069) cohorts. We identified six independent predictors for survival including age, sex, marital status, Ann Arbor stage, B symptom, and chemotherapy, which were used to construct the nomogram and the web-based survival rate calculator. The C-index of the nomogram was 0.709 (95% CI, 0.692–0.726) in the training cohort and 0.700 (95% CI, 0.671–0.729) in the validation cohort. The AUC values of the nomogram for predicting the 1-, 5-, and 10- year CSS rates ranged from 0.704 to 0.765 in both cohorts. All calibration curves revealed optimal consistency between predicted and actual survival. A risk stratification model generated based on the nomogram showed a favorable level of predictive accuracy compared with the IPI, R-IPI, and Ann Arbor stage in both cohorts according to the AUC values (training cohort: 0.715 vs 0.676, 0.652, and 0.648; validation cohort: 0.695 vs 0.692, 0.657, and 0.624) and K-M survival curves. In conclusion, we have established and validated a novel nomogram risk stratification model and a web-based survival rate calculator that can dynamically predict the long-term CSS in DLBCL, which revealed more discriminative and predictive accuracy than the IPI, R-IPI, and Ann Arbor stage in the rituximab era.

Low serum cholesterol levels predict inferior prognosis and improve NCCN-IPI scoring in diffuse large B cell lymphoma

Low circulating cholesterol concentration is associated with elevated cancer incidence and mortality. However, the association between cholesterol levels and diffuse large B cell lymphoma (DLBCL) remains unknown. The aim of our study was to evaluate the prognostic value of serum lipid profile in DLBCL. Five hundred and fifty enrolled subjects with detailed serum lipid levels at diagnosis of DLBCL were randomly divided into a training set (n = 367) and a validation set (n = 183) (ratio, 2:1). Multivariate Cox regression analyses screened the prognostic factors associated with progression-free survival (PFS) and overall survival (OS). Performances of models were compared using C-index and area under the curve in internal and external validation. The results showed that decreased levels of total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) were associated with unfavorable PFS and OS in the rituximab era, and concurrently low HDL-C together with low LDL-C was an independent prognostic indicator for both PFS and OS. Patients achieving complete remission or partial remission after 6-8 circles of chemotherapies had significantly increased cholesterol levels compared to the levels at DLBCL diagnosis, and HDL-C or LDL-C elevations were correlated with better survival. Furthermore, the predictive and discriminatory capacity of the National Comprehensive Cancer Network (NCCN)-International Prognostic Index (IPI) together with low cholesterol levels was superior to NCCN-IPI alone both in the training and validation set. In conclusion, serum cholesterol levels are simple and routinely tested parameters, which may be good candidates for predicting prognosis in the future clinical practice of DLBCL.

Pathophysiology and molecular aspects of diffuse large B-cell lymphoma

Diffuse large B-Cell lymphoma is the most common subtype of non-Hodgkin lymphoma in the West. In Brazil, it is the fifth cause of cancer, with more than 55,000 cases and 26,000 deaths per year. At Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo - HCFMUSP, diffuse large B-Cell lymphoma represents 49.7% of all non-Hodgkin lymphoma cases. Initially, the classification of non-Hodgkin lymphoma was based on morphology, but advances in immunology and molecular medicine allowed the introduction of a biological classification for these diseases. As for other cancers, non-Hodgkin lymphoma involves patterns of multifactorial pathogenesis with environmental factors, as well as genetic, occupational and dietary factors, contributing to its development. Multiple lesions involving molecular pathways of B-cell proliferation and differentiation may result in the activation of oncogenes such as the BCL2, BCL6, and MYC genes and the inactivation of tumor suppressor genes such as p53 and INK4, as well as other important transcription factors such as OCT-1 and OCT-2. A dramatic improvement in survival was seen after the recent introduction of the anti-CD20 monoclonal antibody. The association of this antibody to the cyclophosphamide, hydroxydaunorubicin, oncovin and prednisolone (CHOP) regimen has increased overall survival of diffuse large B-Cell lymphoma and follicular lymphoma patients by 20%. However, 50% of all diffuse large B-Cell lymphoma patients remain incurable, creating a demand for more research with new advances in treatment. Thus, it is important to know and understand the key factors and molecular pathways involved in the pathogenesis of diffuse large B-Cell lymphoma.

Potential role of proteomics in the diagnosis of lymphoma: a meta-analysis

Surface-enhanced laser desorption/ionisation time-of-flight mass spectrometry (SELDI-TOF-MS) has been approved for identifying biomarkers and diagnosing many diseases such as lymphomas. It is arguable whether the SELDI technique has its value of diagnostic accuracy for lymphomas. The purpose of our study is to determine the diagnostic accuracy of SELDI-TOF-MS for diagnosing lymphomas. The Cochrane Central Register of Controlled Trials, MEDLINE, Pub Med, EMBASE, the Chinese Biomedical Literature Database, the China Academic Journals Full-text Database, and the Chinese Scientific Journals Database were searched systematically for potential studies. Reference lists of included studies and review articles were also reviewed. All studies that reported data on patients with a confirmed diagnosis of lymphomas and that compared the measurement of SELDI-TOF-MS with pathology standard were considered for inclusion. Eleven studies were included in the systematic review. The ranges of the diagnostic value of SELDI-TOF-MS for lymphoma were as follows: sensitivity (SEN) was 0.69-0.96; specificity (SPE) was 0.70-1.00; positive likelihood ratio (PLR) was 2.99-96.09; negative likelihood ratio (NLR) was 0.04-0.35; and diagnostic odds ratio (DOR) was 18.13-1250.71, respectively. Further, we analysed serum samples as a subgroup, and the pooled endpoints were as follows: pooled SEN was 0.89 (0.85-0.91); pooled SPE was 0.91 (0.88-0.93); pooled PLR was 12.35 (5.36-28.44); pooled NLR was 0.13 (0.09-0.20); and pooled DOR was 101.04 (39.57-258.04), respectively. SELDI-TOF-MS showed high accuracy in identifying lymphoma and could be a useful screening tool for diagnosing lymphoma patients.

B cells with high side scatter parameter by flow cytometry correlate with inferior survival in diffuse large B-cell lymphoma

Despite advances in the understanding of diffuse large B-cell lymphoma (DLBCL) biology, only the clinically based International Prognostic Index (IPI) is used routinely for risk stratification at diagnosis. To find novel prognostic markers, we analyzed flow cytometric data from 229 diagnostic DLBCL samples using an automated multiparameter data analysis approach developed in our laboratory. By using the developed automated data analysis pipeline, we identified 71 of 229 cases as having more than 35% B cells with a high side scatter (SSC) profile, a parameter reflecting internal cellular complexity. This high SSC B-cell feature was associated with inferior overall and progression-free survival (P = .001 and P = .01, respectively) and remained a significant predictor of overall survival in multivariate Cox regression analysis (IPI, P = .001; high SSC, P = .004; rituximab, P = .53). This study suggests that high SSC among B cells may serve as a useful biomarker to identify patients with DLBCL at high risk for relapse. This is of particular interest because this biomarker is readily available in most clinical laboratories without significant alteration to existing routine diagnostic strategies or incurring additional costs.

Primary diffuse large B-cell lymphoma of the oral cavity: germinal center classification

Primary lymphomas of the oral cavity are rare and the most frequent type is diffuse large B-cell lymphoma (DLBCL). Recently, several reports have highlighted the value of classifying DLBCL into prognostically important subgroups, namely germinal center B-cell like (GCB) and non-germinal center B-cell like (non-GCB) lymphomas based on gene expression profiles and by immunohistochemical expression of CD10, BCL6 and MUM-1. GCB lymphomas tend to exhibit a better prognosis than non-GCB lymphomas. Studies validating this classification have been done for DLBCL of the breast, CNS, testes and GI tract. Therefore we undertook this study to examine if primary oral DLBCLs reflect this trend. We identified 13 cases (age range 38-91 years) from our archives dating from 2003-09. IHC was performed using antibodies against germinal center markers (CD10, BCL6), activated B-cell markers (MUM1, BCL2) and Ki-67 (proliferation marker). Cases were sub-classified as GCB subgroup if CD10 and/or BCL6 were positive and MUM-1, was negative and as non-GCB subgroup if CD10 was negative and MUM-1 was positive. Immunoreactivity was noted in 2/13 cases for CD10, in 12/13 for BCL6, in 8/13 for MUM-1, and in 6/13 for BCL2. Therefore, 8/13 (58%) were sub-classified as non-GCB DLBCLs and 5/13 (42%) as GCB subgroup. All tumors showed frequent labeling with Ki-67 (range 40-95%). Four of the 8 patients with non-GCB subgroup succumbed to their disease, with the mean survival rate of 16 months. Two patients in this group are alive, one with no evidence of disease and another with disease. No information was available for the other 3 patients in this group. Four of the 5 patients in the GCB subgroup were alive with no evidence of disease and one patient succumbed to complications of therapy and recurrent disease after 18 months. In conclusion, our analysis shows that primary oral DLBCL predominantly belongs to the non-GCB subgroup, which tends to exhibit a poorer prognosis. These findings could allow pathologists to provide a more accurate insight into the potential aggressive behavior and poorer prognosis of these lymphomas.

Prognostic evaluation of immunohistochemical profiles in diffuse large B-cell lymphoma: a Chinese study

Diffuse large B-cell lymphoma (DLBCL) has been classified into different prognostic subgroups using immunohistochemistry in Western populations. However, the applicability in Chinese patients of these subgroups was unclear. We collected 116 specimens and performed immunohistochemical staining for CD10, BCL-6, MUM1, CD138, and CD5, and the results were classified into subgroups according to 3 different algorithms. We then analyzed the subgroups' correlation to patient survival. Expression of CD10 and BCL-6 predicted favorable 5-year OS (70 and 62.5%, respectively) and PFS (64.3 and 61.5%, respectively) rates. In contrast, the expression of MUM1 predicted unfavorable 5-year OS (23.1%) and PFS (17.9%) rates and was also independent of other markers. All algorithms led to useful subclassifications. Using Hans' algorithm based on CD10, BCL-6, and MUM1, the non-germinal center (GC) subgroup (66.4%) had worse 5-year OS (29.8%) and PFS (26.7%) rates than did the GC subgroup. Likewise, using Muris' algorithm based on CD10 and MUM1, fewer non-GC cases (27%) showed poorer OS (20.3%) and PFS (16.2%) rates than did GC cases, an effect that was independent of both the International Prognostic Index, a clinical indicator, and treatment. It identified a subgroup with a high-risk of death and seemed to be applicable in our series. In conclusion, these algorithms can be used effectively in Chinese patients with DLBCL.

BCL2 gene aberration as an IPI-independent marker for poor outcome in non-germinal-centre diffuse large B cell lymphoma

Aim:

Diffuse large B cell lymphoma (DLBCL) is the most common lymphoid malignancy in the western hemisphere, and is characterised by a highly variable outcome that impedes individual risk assessment. Lacking reliable biomarkers, the international prognostic index (IPI) has been the most reliable factor to predict survival and stratify patients for therapy. The aim of this study was to investigate the frequency and potential prognostic role of BCL2 aberrations on the chromosomal level and the protein level in a large DLBCL collective.

Methods:

Fluorescence in situ hybridisation (FISH) with commercially available dual-colour break-apart probes and immunohistochemistry were used to assess BCL2 gene abnormalities and bcl2 protein expression on validated tissue microarrays containing 224 well-characterised cases of primary DLBCL.

Results:

FISH analysis of BCL2 revealed a break in 40/215 cases (19%) and a gain in 66/171 (39%) cases. Only BCL2 gains correlated with bcl2 protein expression (p = 0.001). Presence of any BCL2 gene abnormality, particularly gains, correlated independently of the IPI with a significantly worse prognosis in DLBCL of non-germinal centre (non-GC) phenotype as opposed to DLBCL of non-GC type without this genetic alteration (p = 0.003). DLBCL of germinal centre phenotype did not show this association.

Conclusions:

Cases of DLBCL of the non-GC type with BCL2 gene aberration are accompanied by a significantly worse prognosis as opposed to cases without such gene abnormalities. It may be helpful to asses BCL2 gene abnormalities by FISH in addition to assessing established parameters for individual risk estimation in DLBCL.

Serum diagnosis of diffuse large B-cell lymphomas and further identification of response to therapy using SELDI-TOF-MS and tree analysis patterning

BACKGROUND

Currently, there are no satisfactory biomarkers available to screen for diffuse large B cell lymphoma (DLBCL) or to identify patients who do not benefit from standard anti-cancer therapies. In this study, we used serum proteomic mass spectra to identify potential serum biomarkers and biomarker patterns for detecting DLBCL and patient responses to therapy.

METHODS

The proteomic spectra of crude sera from 132 patients with DLBCL and 75 controls were performed by SELDI-TOF-MS and analyzed by Biomarker Patterns Software.

RESULTS

Nine peaks were considered as potential DLBCL discriminatory biomarkers. Four peaks were considered as biomarkers for predicting the patient response to standard therapy. The proteomic patterns achieved a sensitivity of 94% and a specificity of 94% for detecting DLBCL samples in the test set of 85 samples, and achieved a sensitivity of 94% and a specificity of 92% for detecting poor prognosis patients in the test set of 66 samples.

CONCLUSION

These proteomic patterns and potential biomarkers are hoped to be useful in clinical applications for detecting DLBCL patients and predicting the response to therapy.

Expression of PLK1 and survivin in diffuse large B-cell lymphoma

Polo-like kinase 1 (PLK1) belongs to a conservative family of serine/threonine kinase and plays an important role in the process of cell cycle. Survivin is a member of inhibitor of apoptosis protein (IAP) family. We investigated the expression of PLK1 and survivin with immunohistochemical techniques in diffuse large B-cell lymphoma (DLBCL) and assessed their significance as a potent new tumor marker. The expression rate of PLK1 and survivin were 66.7% (26/39) and 82.1% (32/39), respectively. PLK1 expression correlated with systemic symptom, LDH level, IPI scores and therapeutic effect in DLBCL, while survivin did not. PLK1 expression correlated with shortened event-free survival (EFS) using the Log-rank test in DLBCL, but survivin did not. Cox regression analysis identified the independent prognostic significance for PLK1. The results suggest that there is a significant relationship between over expression of PLK1, the clinical features and survival time. Compared with survivin, PLK1 seems to be a better independent prognostic factor for DLBCL.

Treatment of non-Hodgkin's lymphoma: a look over the past decade

The past decade has seen enormous changes in our understanding of lymphomas with a better classification (World Heath Organization) and identification of better prognostic factors; however, important genetic prognostic factors have not been completely analyzed. The appearance of rituximab and other monoclonal antibodies has completely revolutionized the treatment of this disease. If monoclonal antibodies have activity when used alone, most patients experienced relapse after such a treatment, even after maintenance therapy. The combination of rituximab with chemotherapy has now been shown in several randomized studies to increase the response rate, decrease the relapse rate, and prolong progression-free survival and overall survival. Rituximab plus CHOP (cyclophosphamide/doxorubicin/prednisone/vincristine; R-CHOP) has become the standard for patients with diffuse large B-cell lymphoma. Rituximab chemotherapy, probably with the CHOP regimen, is slowly gaining importance as the standard for patients with follicular lymphoma. Although little is known for other indolent lymphomas and mantle cell lymphoma, progress has been made there, too. Several questions remain for future randomized studies to continue our search toward cure.

Predicting the outcome in non-Hodgkin lymphoma with molecular markers

The World Health Organization classification divides non-Hodgkin lymphomas into B-cell, T-cell and natural killer-cell lymphomas. They are heterogeneous in epidemiology, histopathology and outcome. Clinical prognostic indices rely only on patient factors and staging. Molecular prognostic markers reflect the intrinsic lymphoma biology, measure tumour load and may provide novel therapeutic targets. Lymphomagenesis involves mutations, deletions or dysregulations of genes critical in the control of cell cycle and apoptosis, which are in turn prognostically important. Genome-wide gene expression profiling, either by allowing lymphomas to be classified according to different stages of lymphoid maturation, or by defining specific gene expression signatures, is also of prognostic significance. In lymphomas where viral infections of the neoplastic cells occur, quantification of viral copies is a surrogate marker for tumour load and hence prognosis. Molecular markers together with patient and clinicopathological features will provide more accurate prognostic models for risk stratification, in order to improve treatment outcome.