Tumor-Tissue Expression of the Hyaluronic Acid Receptor RHAMM Predicts Histological Transformation in Follicular Lymphoma Patients

Hyaluronan-Mediated Motility Receptor (HMMR) Overexpression Is Correlated with Poor Survival in Patients with B-ALL

Acute lymphoblastic leukemia (ALL) is a malignant neoplasm with the highest incidence in the pediatric population. Although the 5-year overall survival is greater than 85%, in emerging countries such as Mexico, the mortality rate is high. In Mexico, B-ALL is the most common type of childhood cancer; different characteristics suggest the presence of the disease; however, the prognosis is dependent on clinical and laboratory features, and no adverse prognostic molecular marker for B-ALL has yet been identified. The present research aimed to identify the prognostic value of HMMR expression in pediatric patients with B-ALL. The differential expression profile of B-ALL cells was determined via in silico analysis, and HMMR expression was subsequently measured via qRT-PCR and immunocytochemistry. The results were statistically analyzed via the ROUT test, Kolmogorov-Smirnov Z test, and Mann-Whitney U test. ROC curves and the Youden index were constructed, and Kaplan-Meier curves were plotted. We found that HMMR expression was increased in B-ALL patients (p < 0.0001). We observed that high expression was related to poor prognosis (p < 0.05). We observed that high expression was related to poor prognosis (p < 0.05). The increase in HMMR expression could be a potential early molecular prognostic marker and/or a new target in childhood B-ALL patients.

Differential tumor protein expression at follicular lymphoma diagnosis reveals dysregulation of key molecular pathways associated with histological transformation

Follicular lymphoma (FL) is the most common low-grade lymphoma. Despite its indolent nature, FL carries an inherent risk of histological transformation (HT) to a more aggressive lymphoma. Existing biomarkers are insufficient to predict HT, indicating the need for more robust biological predictors. Previously, we used mass spectrometry-based proteomics to identify differentially expressed proteins in diagnostic FLs with and without subsequent HT. This study sought to further investigate identified proteins in transformation of FL, generally acting in important cellular pathways such as (i) apoptosis (BID), (ii) cell cycle (CDC26, CDK6, SRSF1, SRSF2), (iii) GTPase signaling (IQGAP2, MEK1), (iv) cytoskeletal rearrangement and cellular migration (ACTB, CD11a, MMP9, SEPT6), and (v) immune processes (CD81, IgG, MPO, PIK3AP1). We analyzed pre-therapeutic samples from 48 FL patients, either non-transforming FL (nt-FL, n = 30) or subsequently-transforming FL (st-FL, n = 18), the latter with histologically-confirmed transformation after their initial FL diagnosis. Paired high-grade lymphomas (tFL, n = 18) from the time of transformation were also analyzed. We used immunohistochemistry and digital image analysis to quantify protein levels. In all five pathway classes, several proteins were differentially expressed between either the diagnostic nt-FL and st-FL samples, or between the paired st-FL and tFL samples (p < 0.05). Interestingly, we found correlation between expression levels of several proteins, indicating a complex involvement between several pathways. Differential expression of most proteins was also associated with shorter transformation-free survival (p < 0.05). These findings emphasize underlying differences in FL biology predictive of subsequent transformation, highlighting deregulation of important interconnected cellular pathways.

Impact of the Immune Landscape in Follicular Lymphoma: Insights into Histological Transformation in the Rituximab Era

Background: Follicular lymphoma (FL) presents significant clinical heterogeneity, with some patients experiencing transformation into an aggressive disease, a key contributor to FL-related mortality. Based on gene expression profiles, this study aimed to provide insights into immunological differences associated with transformation. Methods: Gene expression analysis using the NanoString nCounter Tumor Signaling 360 Panel was performed on diagnostic lymphoma samples from 70 FL patients diagnosed in the rituximab era, either non-transforming FL (nt-FL, n = 34) or subsequently transforming FL (st-FL, n = 36), with paired high-grade transformed FL (tFL, n = 36) samples available. In silico immunophenotyping was performed to infer immune cell infiltration using the CIBERSORTx algorithm. Results: The gene expression analysis revealed 164 significantly differentially expressed genes, distinguishing st-FL from nt-FL and generally presenting an upregulation of B cell-related genes (CD40, IRF4, RELB), immunosuppressive molecules (IL10, SOCS3), and immune checkpoint molecules (CD276, TIM3). Analysis of immune cell proportions indicated significant differences in infiltrates of M1-like macrophages (p = 0.007) and neutrophils (p = 0.012) in nt-FL versus st-FL samples. Transformation-free survival (TFS) was associated with high numbers of both these cellular subsets (p = 0.006 and 0 = 0.002, respectively). This was even more evident when combined with inferior TFS in lymphomas with high infiltrates of both cell types (p < 0.001). After transformation, tFL samples showed a reduction in T follicular helper cells (p = 0.008) and an increase in immunosuppressive M2-like macrophages and neutrophils (p < 0.001 and p = 0.028, respectively). Conclusion: By elucidating the distinct molecular and immune landscapes of FL at the time of diagnosis and transformation, this study underscores the importance of immune microenvironment in FL transformation and patient outcome.

Molecular Biomarkers in Prediction of High-Grade Transformation and Outcome in Patients with Follicular Lymphoma: A Comprehensive Systemic Review

Follicular lymphoma (FL) is the most prevalent indolent B-cell lymphoma entity, often characterized by the t(14;18) BCL2-IGH translocation. The malignancy represents a clinically and biologically highly heterogeneous disease. Most patients have favorable prognoses; however, despite therapeutic advancements, the disease remains incurable, with recurrent relapses or early disease progression. Moreover, transformation to an aggressive histology, most often diffuse large-B-cell lymphoma, remains a critical event in the disease course, which is associated with poor outcomes. Understanding the individual patient's risk of transformation remains challenging, which has motivated much research on novel biomarkers within the past four decades. This review systematically assessed the research on molecular biomarkers in FL transformation and outcome. Following the PRISMA guidelines for systemic reviews, the PubMed database was searched for English articles published from January 1984 through September 2024, yielding 6769 results. The identified publications were carefully screened and reviewed, of which 283 original papers met the inclusion criteria. The included studies focused on investigating molecular biomarkers as predictors of transformation or as prognostic markers of time-related endpoints (survival, progression, etc.). The effects of each biomarker were categorized based on their impact on prognosis or risk of transformation as none, favorable, or inferior. The biomarkers included genetic abnormalities, gene expression, microRNAs, markers of B cells/FL tumor cells, markers of the tumor microenvironment, and soluble biomarkers. This comprehensive review provides an overview of the research conducted in the past four decades, underscoring the persistent challenge in risk anticipation of FL patients.

Proteomic Profiling Identifies Predictive Signatures for Progression Risk in Patients with Advanced-Stage Follicular Lymphoma

Background: Follicular lymphoma (FL) is characterized by an indolent nature and generally favorable prognosis, yet poses a particular clinical challenge, since disease progression is observed in a notable subset of patients. Currently, it is not possible to anticipate which patients will be at risk of progression, highlighting the need for reliable predictive biomarkers that can be detected early in the disease. Methods: We applied tandem-mass-tag labelled nano-liquid chromatography tandem mass spectrometry (nLC-MS/MS) on 48 diagnostic formalin-fixed, paraffin-embedded tumor samples from patients with advanced-stage FL. Of these, 17 experienced subsequent progression (subsequently-progressing, sp-FL) while 31 did not (non-progressing, np-FL). Results: We identified 99 proteins that were significantly differentially expressed between sp-FL samples and np-FL samples (p < 0.05; log2-fold changes between 0.2 and -1.3). Based on this subset of proteins, we classified patients into high-risk and low-risk subgroups using unsupervised machine learning techniques. Pathway analyses of the identified proteins revealed aberrancies within the immune system and cellular energy metabolism. In addition, two proteins were selected for immunohistochemical evaluation, namely stimulator of interferon genes 1 (STING1) and isocitrate dehydrogenase 2 (IDH2). Notably, IDH2 retained significantly lower expression levels in sp-FL samples compared with np-FL samples (p = 0.034). Low IDH2 expression correlated with shorter progression-free survival (PFS, p = 0.020). Conclusions: This study provides evidence for some of the biological mechanisms likely to be involved in FL progression and, importantly, identifies potential predictive biomarkers for improvement of risk stratification up-front at time of FL diagnosis.

Proteomics identifies apoptotic markers as predictors of histological transformation in patients with follicular lymphoma

Follicular lymphoma (FL) is an indolent lymphoma with a generally favorable prognosis. However, histological transformation (HT) to a more aggressive disease leads to markedly inferior outcomes. This study aims to identify biological differences predictive of HT at the time of initial FL diagnosis. We show differential protein expression between diagnostic lymphoma samples from patients with subsequent HT (subsequently-transforming FL [st-FL]; n = 20) and patients without HT (nontransforming FL [nt-FL]; n = 34) by label-free quantification nano liquid chromatography-tandem mass spectrometry analysis. Protein profiles identified patients with high risk of HT. This was accompanied by disturbances in cellular pathways influencing apoptosis, the cytoskeleton, cell cycle, and immune processes. Comparisons between diagnostic st-FL samples and paired transformed FL (n = 20) samples demonstrated differential protein profiles and disrupted cellular pathways, indicating striking biological differences from the time of diagnosis up to HT. Immunohistochemical analysis of apoptotic proteins, CASP3, MCL1, BAX, BCL-xL, and BCL-rambo, confirmed higher expression levels in st-FL than in nt-FL samples (P < .001, P = .015, P = .003, P = .025, and P = .057, respectively). Moreover, all 5 markers were associated with shorter transformation-free survival (TFS; P < .001, P = .002, P < .001, P = .069, and P = .010, respectively). Notably, combining the expression of these proteins in a risk score revealed increasingly inferior TFS with an increasing number of positive markers. In conclusion, proteomics identified altered protein expression profiles (particularly apoptotic proteins) at the time of FL diagnosis, which predicted later transformation.

IDO1 Protein Is Expressed in Diagnostic Biopsies from Both Follicular and Transformed Follicular Patients

Follicular lymphoma (FL) is a lymphoid neoplasia characterized by an indolent clinical nature. Despite generally favorable prognoses, early progression and histological transformation (HT) to a more aggressive lymphoma histology remain the leading causes of death among FL patients. To provide a basis for possible novel treatment options, we set out to evaluate the expression levels of indoleamine 2,3-dioxygenase 1 (IDO1), an immunoinhibitory checkpoint molecule, in follicular and transformed follicular biopsies. The expression levels of IDO1 were assessed using immunohistochemical staining and digital image analysis in lymphoma biopsies from 33 FL patients without subsequent HT (non-transforming FL, nt-FL) and 20 patients with subsequent HT (subsequently transforming FL, st-FL) as well as in paired high-grade biopsies from the time of HT (transformed FL, tFL). Despite no statistical difference in IDO1 expression levels seen between the groups, all diagnostic and transformed lymphomas exhibited positive expression, indicating its possible role in novel treatment regimens. In addition, IDO1 expression revealed a positive correlation with another immune checkpoint inhibitor, namely programmed death 1 (PD-1). In summary, we report IDO1 expression in all cases of FL and tFL, which provides the grounds for future investigations of anti-IDO1 therapy as a possible treatment for FL patients.

The Matrix Reloaded-The Role of the Extracellular Matrix in Cancer

As the core component of all organs, the extracellular matrix (ECM) is an interlocking macromolecular meshwork of proteins, glycoproteins, and proteoglycans that provides mechanical support to cells and tissues. In cancer, the ECM can be remodelled in response to environmental cues, and it controls a plethora of cellular functions, including metabolism, cell polarity, migration, and proliferation, to sustain and support oncogenesis. The biophysical and biochemical properties of the ECM, such as its structural arrangement and being a reservoir for bioactive molecules, control several intra- and intercellular signalling pathways and induce cytoskeletal changes that alter cell shapes, behaviour, and viability. Desmoplasia is a major component of solid tumours. The abnormal deposition and composition of the tumour matrix lead to biochemical and biomechanical alterations that determine disease development and resistance to treatment. This review summarises the complex roles of ECM in cancer and highlights the possible therapeutic targets and how to potentially remodel the dysregulated ECM in the future. Furthering our understanding of the ECM in cancer is important as the modification of the ECM will probably become an important tool in the characterisation of individual tumours and personalised treatment options.