Immunohistochemical expression of RELA, REL, and p(Ser 727)-STAT3.
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Article Type: Research Paper
Date of acceptance: March 2022
Date of publication: March 2022
copyright: ©2022 The Author(s), Licensee IntechOpen, License: CC BY 4.0
Peripheral T-cell lymphomas not otherwise specified (PTCL/NOS) is the commonest subtype of PTCL. NF–kB related molecules have been found to be variably expressed in PTCL/NOS, suggesting a potential involvement of the NF–kB system in their pathogenesis. However, the actual contribution of NF–kB molecular programs to the PTCL/NOS landscape has not been investigated yet. In this study, we assessed in a large series of PTCL/NOS, the activation status of NF–kB programs and investigated the prognostic impact of such NF–kB expression. Moreover, we explored the possible role of NF–kB inhibitors. We studied the gene expression profiles of 180 PTCL cases and tested two different drugs, the IKK inhibitor BMS-345541 and the proteasome inhibitor Bortezomib, in four PTCL cell lines. We found that most cases (84%) presented with some degree of NF–kB activation, based on the expression of REL and RELA. Functionally, the latter was strictly related with TCR signaling activation, while REL was at least partially TCR independent. We also identified genes related with NF–kB activation in this setting that were mainly involved in cell proliferation and apoptosis inhibition. Further, by reverse engineering we defined the transcriptional network of both REL and RELA in PTCLs that only partially overlapped. On the clinical ground, we found that RELA expression was related to a significantly poorer overall survival, with similar trends for REL. However, most remarkably, when all the three genes were considered together, cases with at least one gene over-expressed, showed a dramatically inferior overall survival (28.67 vs. 56.018 months; p = 0.004). Finally, we showed that NF–kB pharmacological inhibition was associated with cell cycle arrest and cell death in NF–kB positive PTCL cells. In conclusion, we extensively explored NF–kB activation in PTCL/NOS, documenting its negative prognostic role. Further, we showed that NF–kB inhibition might represent a rational therapeutic approach in selected cases.
peripheral T-cell lymphoma
NF kappa B
Peripheral T-cell lymphomas not otherwise specified (PTCL/NOS) is the commonest subtype of PTCL [1, 2]. This is a complex entity, characterized by significant morphologic, immunophenotypic and clinical variability, whose molecular pathology is still largely unknown [3, 4].
Recently, gene expression profiling (GEP) allowed the identification of PTCL/NOS-associated signatures, leading to the better understanding of its histogenesis, pathogenesis and prognostication [5–12]. Interestingly, GEP studies suggested that PTCL/NOS may present with up- or down-regulation of nuclear factor kappa B (NF–kB) molecules [5–7], with possible prognostic relevance [7, 13]. However, these studies investigated a limited number of PTCLs/NOS cases [7, 13] and mostly included cases with prominent non-neoplastic components . In addition, only one NF–kB effector, RelA, has been studied at protein level. By contrast, the NF–kB pathway is a complex system including five main characters (namely, RELA/p65, RELB, REL, p50 and p52 encoded by
Importantly, NF–kB molecules are basically retained in the cytoplasm in an inactive form by specific inhibitors (IKB family members), while exerting their transcription factor activity when located in nuclei upon specific stimulation. To be functional, NF–kB effectors need to constitute specific dimers which activate the so called canonical (RELA/p50, RELA/RELA, p50/REL and RELA/REL) and alternative (RELB/p52) pathways. The transcription activation domain (TAD) necessary for the positive regulation of gene expression is present only in RELA/p65, REL and RELB . By contrast, as they lack TADs, p50 or p52 may repress transcription unless associated with TAD-containing NF–kB family member .
In T-lymphocytes, NF–kB activation is mainly induced by the T-cell receptor (TCR) signaling, that is commonly abrogated in some PTCL such as anaplastic large cell lymphoma  and, possibly, in a fraction of PTCL/NOS  and angioimmunoblastic lymphomas (AITL) .
As NF–kB is a suitable therapeutic target in cancer, bortezomib, a selective inhibitor of the proteasome 26S, involved in the NF–kB cell signaling regulation, has been evaluated for treatment of patients with PTCL. A Phase I study of bortezomib used in association with CHOP chemotherapy was conducted in 13 patients with advanced PTCL or NK/T-cell lymphoma . The reported CR rate was 62%, with no data published on PFS or OS. A phase II study of bortezomib as a single agent for patients with relapsed PTCL (
In this study, we assessed in a large series of PTCL/NOS, the activation status of Nf-kB programs by focusing for the first time on all the main components, representing both the canonical and alternative pathways, and investigated the relation with TCR signaling as well as the prognostic impact of such NF–kB expression. Moreover, we explored the possible role of NF–kB inhibitors in this setting.
We studied 180 PTCLs from which GEP were previously generated using fresh/frozen tissues [9–11, 21] (GEO data sets: GSE6338 and GSE19069). All of the cases were reviewed by at least two expert hematopathologists and diagnosed according to the WHO Classification ; furthermore, the diagnosis was refined by applying a molecular classifier recently developed by our group . The detailed clinicopathological characteristics of these cases were previously reported .
Specifically, to characterize the activation of NF–kB pathway, we studied the expression of RELA (201783_s_at and 209878_s_at), RELB (205205_at), and REL (206035_at, and 206036_s_at), as well as the one of a series of well-known NF–kB targets, previously used for analogue purposes  and validated biochemically (http://www.bu.edu/nf-kb/gene-resources/target-genes/; http://bioinfo.lifl.fr/NF-KB/) . Further, we studied genes encoding for proteins involved in TCR signaling .
Raw data were normalized in GeneSpring GX 12.5 (Agilent, CA); details on sample normalization and analysis have been previously reported [9–11, 21, 26, 27]. Reverse engineering was carried on by ARACNe algorithm in GeWorkbench 2.6.0 as previously described [27, 28]. Possible relationships among genes were further investigated by Cognoscente (http://vanburenlab.tamhsc.edu/cognoscente).
Gene expression studies were conducted according to MIAME guidelines. Raw gene expression are available at http://www.ncbi.nlm.nih.gov/projects/geo/.
Four human PTCL cell lines (Fe–Pd, Mac1, Karpass-299, and Jurkat) served as in vitro PTCLs models for treatment with BMS-345541 (SigmaAldrich) and Bortezomib (kindly provided by Dr. Guarguaglini). BMS-345541 (4(2
All the four cell lines and PBMC were cultured in RPMI medium 1640 containing 10% FBS and 2 mM L-glutamine (Lonza).
Cell viability was measured by CellTiter-Glo Luminescent Cell Viability Assay (Promega,Corporation Italy). Aliquots of 5 × 104 cells per well were distributed in 96-well opaque microplates in 100 μl of medium and incubated at 37 °C in a 5% CO2 humidified incubator for 48 h. BMS-345541 and Bortezomib were added at progressively increasing concentrations ranging from 0.1 μM up to 9 μM and from 2 nM up to 15 nM, respectively, to determine growth inhibition curves for all cell lines. Following incubation, 100 μl of CellTiter-Glo Reagent was added to the volume of cell culture medium present in each well, according to the manufacturer’s instructions. The relative cell viability was determined at 490 nm using a Victor2 (PerkinElmer) 96-well plate reader instrument. Each experiment was performed in triplicate.
To evaluate apoptosis and cell cycle, the four cell lines were incubated for 48 h with and without BMS-345541 (3.5, 4, 5 and 6 μM) and Bortezomib (5 and 8 nM).
In order to detect and quantify apoptosis we used Annexin-V-Fluos staining kit (Roche, Italy). Cells were harvested, washed twice and re-suspended in 100 μl of Annexin-V-Fluos labeling solution for 15 min, according to the manufacturer’s instructions. Then, we added 500 μl of incubation Buffer and analyzed with NAVIOS cytometer (Beckman Coulter). Data were elaborated by Kaluza dedicated software. Annexin V + PI-cells represented the early apoptotic populations. Annexin V + PI + cells represented either late apoptotic or secondary necrotic populations.
We followed the progression of S-phase through the cell cycle by labeling cells with the thymidine analog 5-bromo-2
To assess the effective inhibition of Nf-kB pathway via IKK inhibitor, we used immunohistochemistry by staining the Fe–Pd cell line after 6 h of treatment with 5 μM of BMS-345541. Briefly, cells were collected, washed once with cold phosphate-buffered saline (PBS), and centrifuged at 1500 r.p.m. for 5 min. The cell pellets were fixed in PBS-buffered formalin at room temperature at least 2 h. The cells were centrifuged for 10 min, then the cell pellets were washed with physiological saline and centrifuged. Subsequently, we added to the cell pellets human plasma and Simplastin (Tromborel) in ratio of 1:2 to allow formation of the clot. Finally, the clots were then routinely embedded in paraffin wax, as described previously , and processed for the detection of RELA and P50 by IHC. Briefly, FFPE clots were investigated by antibodies raised against fixation resistant epitopes: RELA (mouse monoclonal; Santa Cruz Inc.) and p50 (rabbit polyclonal; Thermo Scientific). The antigen retrieval protocols, dilutions and revelation system are detailed in table 1. Immunohistochemical preparations were visualized and images were captured using Olympus Dot-slide microscope digital system equipped with the VS110 image analysis software.
|REL||Santa Cruz Inc.||1:20||PtLink, high pH 92 °C × 20 min||K8012*|
|RELA||Santa Cruz Inc.||1:20||PtLink, high pH 92 °C × 20 min||K8012*|
|p(Ser 727)-STAT3||Cell signaling technology||1:25||PtLink, high pH 92 °C × 20 min||K8012*|
NF–kB pathway activation status was also evaluated on formalin-fixed paraffin-embedded (FFPE) samples corresponding to 48 PTCL/NOS. All the cases were retrieved from the archives of the Haematopathology Unit, Department of Experimental, Diagnostic and Specialty Medicine—DIMES, University of Bologna. The study was conducted according to the principles of the Helsinki declaration after approval of the Internal review Board. Two different tissue-microarrays (TMAs) were constructed from these paraffin-embedded blocks as previously reported . TMAs sections were investigated by antibodies raised against fixation resistant epitopes; REL (rabbit polyclonal; Santa Cruz Inc.), RELA (mouse monoclonal; Santa Cruz Inc.), and p(Ser 727)-STAT3 (1:25) (Cell Signaling Technology, Beverly, MA). The antigen retrieval protocols, dilutions and revelation system are detailed in table 1. Notably, each TMA was also tested with anti-CD20 and CD3 antibodies to define the number of reactive B-cells comprised within the neoplastic T-cell population. Each section was independently evaluated by at least two experienced hematopathologists. NF–kB pathway in each case was scored as activated if more than 30% of the examined neoplastic cells showed nuclear positivity for one or more among transcription factors REL, RELA (canonical pathway) Immunohistochemical preparations were visualized, and images were captured using Olympus Dot-slide microscope digital system equipped with the VS110 image analysis software.
Each section was independently evaluated by at least two experienced hematopathologists. Cases were considered positive if 30% or more of the tumor cells were stained with antibody. The number of positive cells was estimated by each observer. The intensity of staining was also evaluated, but not used to determine positivity, as it can vary with the degree of tissue fixation. All the 48 cases included in the TMA had also been studied by GEP.
Statistical analyses were carried on with the IBM SPSS Statistics 20.0 (IBM, USA). Anova, and unpaired T-Test were adopted for GEP data analyses. Survival data were analyzed by using the Kaplan-Meier method . Specifically, overall survival (OS) was calculated from the time of diagnosis to death or last follow up; progression free survival (PFS) was calculated from the end of induction treatment until progression, death, or last contact. Clinical information and complete follow up were available for 43/48 cases.
The limit of significance for all analyses was defined as
All cases were collected at diagnosis, before any treatment administration. The study was approved by the Local Ethical Committee and conduced according to the Helsinki Declaration principles.
First, we studied the expression of
To further test whether such division could be reliable, we performed a supervised analysis between the two groups (NF–kB positive vs. NF–kB negative) and identified 781 probe sets, corresponding to 668 unique genes, that were differentially expressed in the two groups (figure 2A; supplementary table 1). Based on the expression of these genes, cases were then clustered and roughly separated according to NF–kB activation (figure 2B). Of interest, when we sought for pathways and cellular programs enriched in these genes, we found, among others, the TCR signaling (the main upstream of NF–kB in T-cells), the NF–kB pathway cascade itself, and the NF–kB transcriptional targets (figure 3; supplementary tables 2–4).
Noteworthy, IHC did confirm GEP data, with nuclear RELA/REL expression in activated cases (figure 4). Specifically, 17/17 NF–kB positive cases showed nuclear staining for either RELA or RELB or REL. Conversely, none of the 24 negative cases presented nuclear staining of a REL family component (table 2).
|Case #||RELA result||RELA localization||RELB result||RELB localization||REL result||REL localization||NF–kB at GEP|
|PTCL NOS 1||Positive||C||Positive||C||Positive||C||Negative|
|PTCL NOS 2||Positive||C||Positive||C||Positive||C||Negative|
|PTCL NOS 3||Positive||C||Positive||C||Positive||C||Negative|
|PTCL NOS 4||Positive||C||Positive||C||Positive||C||Negative|
|PTCL NOS 5||Positive||C||Positive||C||Positive||C||Negative|
|PTCL NOS 6||Positive||C||Positive||C||Positive||C||Negative|
|PTCL NOS 7||Positive||C||Positive||C||Positive||C||Negative|
|PTCL NOS 8||Positive||C||Positive||C||Positive||C||Negative|
|PTCL NOS 9||Positive||C||Positive||C||Positive||C||Negative|
|PTCL NOS 10||Positive||C||Positive||C||Positive||C||Negative|
|PTCL NOS 11||Positive||C||Positive||C||Positive||C||Negative|
|PTCL NOS 12||Positive||C||Positive||C||Positive||C||Negative|
|PTCL NOS 13||Positive||C||Positive||C||Positive||C||Negative|
|PTCL NOS 14||Positive||C||Positive||C||Positive||C||Negative|
|PTCL NOS 15||Positive||C||Positive||C||Positive||C||Negative|
|PTCL NOS 16||Positive||C||Positive||C||Positive||C||Negative|
|PTCL NOS 17||Positive||C||Positive||C||Positive||C||Negative|
|PTCL NOS 18||Positive||C||Positive||C||Positive||C||Negative|
|PTCL NOS 19||Positive||C||Positive||C||Positive||C||Negative|
|PTCL NOS 20||Positive||C||Positive||C||Positive||C||Negative|
|PTCL NOS 21||Positive||C||Positive||C||Positive||C||Negative|
|PTCL NOS 22||Positive||C||Positive||C||Positive||C||Negative|
|PTCL NOS 23||Positive||C||Negative||NA||Positive||C||Negative|
|PTCL NOS 24||Positive||C||Negative||NA||Positive||C||Negative|
|PTCL NOS 25||Positive||NC||Positive||C||Positive||C||Positive|
|PTCL NOS 26||Positive||NC||Positive||C||Positive||C||Positive|
|PTCL NOS 27||Positive||NC||Positive||C||Positive||C||Positive|
|PTCL NOS 28||Positive||C||Positive||C||Positive||NC||Positive|
|PTCL NOS 29||Positive||C||Positive||C||Positive||NC||Positive|
|PTCL NOS 30||Positive||C||Positive||C||Positive||NC||Positive|
|PTCL NOS 31||Positive||C||Positive||C||Positive||NC||Positive|
|PTCL NOS 32||Positive||C||Positive||C||Positive||NC||Positive|
|PTCL NOS 33||Positive||C||Positive||C||Positive||NC||Positive|
|PTCL NOS 34||Positive||C||Positive||C||Positive||NC||Positive|
|PTCL NOS 35||Positive||C||Positive||C||Positive||NC||Positive|
|PTCL NOS 36||Positive||NC||Positive||C||Positive||NC||Positive|
|PTCL NOS 37||Positive||NC||Positive||C||Positive||NC||Positive|
|PTCL NOS 38||Positive||NC||Positive||C||Positive||NC||Positive|
|PTCL NOS 39||Positive||C||Positive||NC||Positive||C||Positive|
|PTCL NOS 40||Positive||C||Positive||NC||Positive||C||Positive|
|PTCL NOS 41||Positive||C||Negative||NA||Positive||NC||Positive|
Together, these data indicated that PTCL/NOS category includes two discrete subgroups apparently characterized by activated and non-activated NF–kB pathway. As RELA and REL but not RELB were involved, it appeared that the canonical rather than the alternative pathway was activated in PTCL/NOS.
As NF–kB pathway is a downstream of TCR signaling in T-lymphocytes, we then focused on the expression of genes representative of TCR signaling (Unigene) . We found several genes differentially expressed between cases with or without NF–kB activation, including
We then investigated whether
When the costimulatory molecules were considered,
Together, these data indicate that NF–kB activation is mediated by TCR signaling and RELA in a fraction of PTCL/NOS cases, being at least partially TCR independent and REL associated in other instances.
As RELA and REL appeared to be activated at least in part by different mechanisms (i.e. TCR dependent or independent), we used reverse engineering to characterize their functional networks aiming to identify possible similarities and differences. To do this, we applied ARACNe, an algorithm previously found to be very effective in recognizing transcription factors targets as well as other molecules functionally related to them. We identified 281 genes significantly related to REL and 849 genes significantly related to RELA. Within the two networks, 133 and 723 genes were univocally related to
The value of the identified networks was then further validated demonstrating by GSEA their significant enrichment in genes already found to be
Together, these data documented that RELA and REL are involved in partially different functional networks in PTCLs, but do also share a significant number of first neighbor
As PTCL/NOS appeared to be composed by two populations according to NF-KB molecular pathway, we sought to investigate the possible prognostic significance of such distinction.
When we studied the overall survival of patients divided in the 4 quartiles, we observed that patients with lower levels of
|Means and medians for survival time||Log rank (Mantel-Cox)|
|95% Confidence interval||95% Confidence interval|
|Estimate||Std. error||Lower bound||Upper bound||Estimate||Std. error||Lower bound||Upper bound|
We established whether NF–kB pathway was active in the four available cell lines. Based on GEP, Fe–Pd, Mac1, Karpass-299, and Jurkat cells were considered RELA-positive, REL-positive, and RELB-negative. Consistently, RELA (p65), REL and p50, representative of the canonical pathway, showed a nucleus-cytoplasmic localization at immunofluorescence, while RELB and p52 typical of the alternative pathway, appeared to be confined to the cytoplasm, indicating an active and inactive status for the canonical and alternative pathways, respectively (supplementary figure 5).
We then sought to assess whether NF–kB pathway shut off could affect the cellular vitality of PTCL cells. We used BMS-345541, a specific IKK inhibitor (upstream NF–kB activator) as well as Bortezomib, a proteasome inhibitor. The latter, though less specific, is already available in the clinical practice and determines NF–kB blockage via proteasome inhibition .
To verify whether BMS-345541 and Bortezomib could inhibit PTCL cell growth we used increasing concentrations of the two drugs from 0.1 μM to 9 μM and 2 nM to 15 nM for 48 h, respectively. The cell growth of PTCL cells was inhibited in a dose-dependent manner. Specifically, the IC50 values for BMS-345541 (figure 8A) and Bortezomib (figure 8B) at 48 h for the four cells lines were as follows: Fe–Pd 5 μM and 8 nM; MAC1 6.5 μM and 10 nM; Karpas 6.97 μM and 9.63 nM; Jurkat >12 μM and >15 nM (table 4). Jurkat cells were resistant to BMS-345541 and Bortezomib treatment, as expected.
|Cell line||PTCL subtype||BMS-345541 (μM)||BORTEZOMIB (nM)|
|Fe–Pd||PTCL/NOS CD30+||4,141 (3,8–4,7)||8,35 (8,1–8,6)|
|MAC1||CTCL||6,59 (6,1–7,1)||10,01 (9,6–10,4)|
|KARPAS||ALK+_ALCL||6,97 (6,7–7,2)||9,63 (9,0–10,2)|
We then investigated whether NF–kB inactivation could be responsible for PTCL cell cycle progression arrest and induction of cell death. To evaluate the effect of NF–kB inhibition over cell cycle progression we considered 5 μM and 8 nM for BMS-345541 and Bortezomib, respectively, corresponding to their Ic50. After measurement of the fraction of BrdU-labeled cells by flow-cytometry, we observed an arrest of cell cycle in G0/G1 phase in Fe–Pd (68% for BMS-345541 and 73.6% for Bortezomib), Mac1 (33% for BMS-345541 and 47% for Bortezomib), Karpas (50% for BMS-345541 and 48% for Bortezomib). On the contrary, Jurkat cells were insensitive to both the treatments (16% for BMS-345541 and 19% for Bortezomib) (figure 8).
We subsequently evaluated the apoptosis rate by Annexin V assay in PTCL cells lines treated or not with BMS-345541 and Bortezomib as single agents at different concentrations (3.5–6 μM for BMS-345541; 5–8 nM for Bortezomib). After 48 h, we observed an increase in the apoptotic events up to 76% in Fe–Pd, 36% in MAC1, 47% in Karpas and 9% in Jurkat cells line upon BMS-345541 treatment (figure 8). Similar results we observed when we treated PTCLs cells lines with Bortezomib. Particularly, we documented 58% of apoptotic events in Fe–Pd, 22% in MAC1, 10% in Karpas, and 8% in Jurkat cells lines upon administration of Bortezomib 8 nM. To further assess the specificity of the effects exerted by NF–kB inhibitors on PTCL cells and evaluate the potential toxicity of such treatment, we investigated the induction of apoptosis in PBMCs from healthy donors. Healthy donor PBMCs were exposed to BMS-345541 at 5 μM and Bortezomib at 8 nM (IC50) for 48 h. Importantly, we did not record any significant cytotoxicity or apoptosis induction in non-neoplastic T-cells (supplementary figure 6).
Finally, to prove that the observed pharmacologic effects were associated with NF–kB inhibition, we performed immunocytochemical analysis of RELA and p50 expression in Fe–Pd cell line before and after 6 h of treatment with 5 μM BMS-345541. While untreated Fe–Pd cells showed a marked nucleo-cytoplasmic positivity for both RELA and p50 proteins, after incubation with BMS-345541 a dramatic reduction of the nuclear staining with RELA and p50 was observed, the two molecules expression being substantially confined to the cytoplasm (supplementary figure 7).
Taken together, these data indicate that NF–kB inhibition is effective against NF–kB positive PTCL cells
In this paper we thoroughly explored NF–kB effectors expression in a large series of PTCLs/NOS by gene expression analysis. We documented for the first time a relatively high prevalence of NF–kB activation in PTCL/NOS in comparison with previous reports [6, 7, 13]. However, it should be noted that previous works mainly focused on RELA expression, while our investigation included REL and RELB as well. If we limited the analysis to RELA, our data would perfectly parallel previous observations. Indeed, the present results are also in line with previous evidences of TCR signaling integrity in PTCL/NOS , as NF–kB is one of the main downstream TCR targets. Particularly, our data are in line with evidences supporting the activity of SYK tyrosine kinase in most PTCL/NOS . Interestingly, our data indicated for the first time that different mechanisms might be responsible for NF–kB triggering in PTCL. In fact,
The evidence of TCR/NF–kB activity in these tumors raises the question whether such activation is constitutive rather than mediated by microenvironmental stimuli, as physiologically happens in T-lymphocytes. So far, a few studies investigated the mutational landscape of PTCL/NOS [39, 40] but failed to identify consistent genetic abnormalities potentially responsible for NF–kB constitutive activation. On the other hand, in a SNPs array study, it was shown that REL locus is quite rarely affected by amplifications leading to
The robustness of our classification system into NF–kB positive and NF–kB negative cases was validated biologically. We showed that the two groups presented with differential expression of genes known to be transcriptional target of NF–kB, differential enrichment in NF–kB pathway cascade, and TCR-signaling related genes. This translated in the differential expression of genes related to lymphocyte activation, blockage of programmed cell death/apoptosis, and cell proliferation. In this regard, we showed that the molecular profile of PTCL/NOS is closer to that of activated rather than resting T-lymphocytes ; which is in line with NF–kB pathway playing a central role in physiological T-cell development and activation. In fact, it has been demonstrated that NF–kB activation by TCR is necessary and sufficient for T-cell activation and survival
The distinction of PTCLs according to NF–kB status was also validated clinically. In fact, cases classified as NF–kB negative showed a significantly better OS. This finding is in line with previous evidences that tumors provided with higher proliferation rate (documented by either immunohistochemistry or gene expression profiling) have a more aggressive course [13, 33]. By contrast, a couple of studies showed a better outcome for NF–kB cases [7, 13]; however, both these studies were limited to RELA, significantly underestimating the NF–kB positive group. As REL family members mRNA quantization is relatively easy and cheap, if their prognostic role will be confirmed in independent, possibly prospective, studies, it may become a novel biomarker for patients’ prognostication in clinic. Conversely, our data are consistent with more recent evidence that expression of NIK, an upstream controller of NF–kB pathways, is associated with a poor outcome in PTCLs .
Based on the evidence that the pathway is active in a fraction of cases, this being also related to an adverse outcome with conventional chemotherapy, we tested whether NF–kB inhibition might be a rational therapeutic strategy. A similar approach had been previously adopted for diffuse large B-cell lymphomas (DLBCL); in this setting, in fact, NF–kB activation is related to a worse outcome and can be efficiently targeted in vivo [48–54]. We found that the unique available PTCL/NOS cell line was characterized by NF–kB activation and its inhibition by both a IKKB specific inhibitor or a proteasome inhibitor led to cell cycle blockage and finally cell death. Recent clinical data suggested only a modest activity of bortezomib in PTCL patients . However, no case selection was operated and a possible relation between efficacy and NF–kB inhibition was assessed by using immunohistochemistry, the interpretation of which in PTCL cases with usually abundant reactive components is subjective and more often indeed problematic. By contrast, in CTCL, that are usually NF–kB positive, bortezomib was quite successful .
In conclusion, we performed for the first time, a thorough investigation of NF–kB expression and activation in PTCL/NOS, documenting its negative prognostic role. Further, we provided a biological rationale for adopting NF–kB inhibition strategies in a subset of PTCL/NOS cases. Future studies should confirm the prognostic relevance of NF–kB status in prospective independent series, identify the key events underlying NF–kB activation/shut off in PTCL clones, and explore the clinical efficacy of NF–kB inhibition in PTCL/NOS patients.
The Authors are grateful to Dr. Maria Antonella Laginestra, Dr. Simona Righi, Dr. Maura Rossi, and Dr. Maria Teresa Sista for the skilled technical assistance, and to Dr. Guarguaglini for medicine support.
Gene expression raw data are available at GEO website (https://www.ncbi.nlm.nih.gov/geo/) (see specific datasets in the Material and Methods section).
The Authors have no conflict of interest to disclose.
This work was supported by BolognAIL, Prof. Piccaluga, RFO (Prof. Piccaluga), and FIRB Futura 2011 RBFR12D1CB (Prof. Piccaluga). The authors have no conflicting financial interests to declare.
PPP coordinated the research and performed molecular analyses. MN, CA and PPP wrote the manuscript. CA, and PW, were responsible for case collection, immunohistochemistry and data analysis. FR, PLT, DG, were involved in case collection, flow cytometry and molecular analyses. The authors reported no potential conflicts of interest.
Supplementary materials are available at https://cdn.intechopen.com/journals/docs/Supplementary˙Data.zip.
Article Type: Research Paper
Date of acceptance: March 2022
Date of publication: March 2022
Copyright: The Author(s), Licensee IntechOpen, License: CC BY 4.0
© 2022 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution 4.0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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