Research ArticleExperimental Studies
Open Access

Exploring TBL1XR1 and NCOR1 Expression in B-cell Lymphoma Subtypes: Interaction With DNA Damage Repair Genes

ADNAN MANSOOR, ARIZ AKHTER, MAHBOOBSADAT HAMIDI, TARIQ MAHMOOD ROSHAN, MEER-TAHER SHABANI-RAD and DOUGLAS STEWART
Anticancer Research November 2023, 43 (11) 4801-4807; DOI: https://doi.org/10.21873/anticanres.16677

Abstract

Background/Aim: B-cell lymphomas are characterized by diverse genetic anomalies affecting B-cell differentiation. To expand targeted therapies, an in-depth grasp of the molecular dynamics in the germinal center (GC) is vital. Transducin β-like 1 X-linked receptor 1 (TBL1XR1) and nuclear receptor corepressor 1 (NCOR1) are instrumental within the GC, modulating myriad oncogenic pathways. Their prognostic roles in various cancers are established, yet their precise impact on B-cell lymphoma is elusive. Materials and Methods: Digital RNA quantification (Nanostring) of previously curated 188 B-cell lymphoma specimens across four subtypes, follicular lymphoma (FL), diffuse large B-cell lymphoma, not otherwise specified (DLBCL-NOS), primary testicular lymphoma (PTL), and plasmablastic lymphoma (PBL), was reanalyzed with focus on TBL1XR1 and NCOR1 expression, juxtaposing them with 730 ontogenically linked genes. Results: Notably, TBL1XR1 expression was significantly elevated in the PTL- ABC-subtype versus DLBCL-NOS- ABC-subtype (p<0.001), with no marked disparity in GCB-subtypes between them. The median TBL1XR1 expression was remarkably diminished in FL, yet, intriguingly, GCB-subtypes of DLBCL-NOS exhibited significantly enhanced expression compared to FL (p=0.001). In contrast, NCOR1’s expression trajectory was consistent across DLBCL-NOS, PTL, and PBL. A strong inverse correlation between TBL1XR1 and NCOR1 was observed in PBL (p=0.001). Importantly, TBL1XR1’s pronounced association with several DNA Damage repair (DDR) genes was noted suggesting influence on DNA repair. TBL1XR1-DDR gene signature was further validated employing a public data set of DLBCL-NOS. Conclusion: Our exploratory findings unravel the expression patterns of TBL1XR1/NCOR1 in B-cell lymphoma variants. The TBL1XR1-DDR genes connection offers insights into potential DNA repair roles, paving avenues for innovative therapies in B-cell lymphomas.

Key Words:

B-cell lymphomas arise from mutations affecting B-cell differentiation, particularly within germinal centers (GCs) where B-cells interact with T follicular helper cells (1). Upon antigen exposure, B-cells in the GC undergo somatic hypermutation, promoting the evolution of high-affinity antigen receptors and differentiating into memory B-cells or plasma cells (2). The complexities in B-cell lymphoma, including the common diffuse large B-cell lymphoma (DLBCL) subtype, originate from accumulated genetic anomalies during this differentiation process (3).

The protein transducin β-like 1 X-linked receptor 1 (TBL1XR1) regulates gene expression as part of the nuclear receptor corepressor (NCoR)/silencing mediator for retinoid and thyroid receptors (SMRT) corepressor complex (4). It is known to be a central component in the formation of GCs by binding and recruiting the majority of TBL1XR1/SMRT/NCOR1 complexes, a process mediated by B-cell lymphoma 6 (BCL6) gene expression (5). TBL1XR1 over-expression has been linked to poor prognosis in several solid organ cancers, impacting various oncogenic signaling pathways (6). It has an essential role in B-cell development, influencing the transition of memory B-cells to plasma cells, while mutations in the TBL1XR1 gene have been observed to inhibit this progression and promote lymphomagenesis (7, 8). B-cell receptor diversification, essential for adaptive immunity, depends on processes like V(D)J recombination and somatic hypermutation (1). Ensuring repair of DNA lesions in these processes is vital for genomic stability and preventing oncogenic translocations. DNA damage response (DDR) plays a key role in maintaining this integrity (7, 8).

Our study examined the TBL1XR1/NCOR1 RNA expression across B-cell lymphoma subtypes and its relationship with DDR pathway gene expression patterns, offering a foundation for future investigations into these intricate mechanisms and potential therapeutic avenues for B-cell lymphoma.

Materials and Methods

Patients and samples. Gene expression data were pooled from a previously curated heterogenous group of 188 lymphoma patients (102 FL, 27 DLBCL-NOS, 26 PTL, 33 PBL) from our institution (2008-2016), using diagnostic biopsies and excluding double-hit genetic abnormalities. Histological diagnoses followed the 2016 WHO Classification (9), and two hematopathologists reviewed all samples. For validation, we incorporated a public dataset from The Cancer Genome Atlas (TCGA) comprising 47 DLBCL and 337 normal tissues. The study conformed to the Declaration of Helsinki and secured approval from the Health Research Ethics Board of Alberta (HREBA) (HREBA study #.CC-16-0218; REN 7 dated December 15, 2022).

Gene expression analysis and determination of the Cell-of-Origin (Lymph2CX) using NanoString nCounter platform. For RNA isolation, we extracted RNA from triplicate 1 mm cores of diagnostic FFPE blocks using the Ambion Kit (ThermoFisher Scientific, Waltham, MA USA) and assessed concentrations with a Nanodrop spectrophotometer and Bio-analyzer 2100 (Nanodrop Technologies, Wilmington, DE, USA). mRNA expression was analyzed with the PanCancer pathway code set on NanoString (NanoString, Seattle, WA, USA), targeting 730 cancer genes. After a 20-h probe hybridization at 65°C, the nCounterTM Digital Analyzer quantified expression, with normalization through nSolver Analysis Software v4.0 (NanoString). For DLBCL’s cell-of-origin determination, we utilized the Lymph2Cx 20-gene expression-based assay on the NanoString platform with 250 ng of total RNA as described previously (10).

Statistical assessment: We determined the necessary sample size for each B-cell lymphoma group using a dedicated online tool (https://bioinformatics.mdanderson.org/MicroarraySampleSize/), setting our criteria at p<0.001, a false positive rate below 0.05, and a fold change >2.0. For our statistical evaluations, we utilized SPSS software v28.0 (IBM, Armonk, NY, USA) and normalized raw counts using nSolver software v4.0. Qlucore Omics Explorer v3.8 (Qlucore, Lund, Sweden) supported in-depth statistical analyses, setting benchmarks at a log fold change >2.0, p<0.01, and an FDR/q value <0.05. Furthermore, we enriched our findings using the Gene Expression Profiling Interactive Analysis (GEPIA) v2 tool, which integrates data from both The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases, facilitating comparisons between cancerous and normal tissue samples (11).

Results

Clinicopathological overview. We pooled data from previously curated 188 B-cell lymphoma samples, with a distribution of 54% follicular lymphoma (FL), 14% DLBCL, 14% primary testicular lymphoma (PTL), and 18% plasmablastic lymphoma (PBL). Notably, this sample distribution deviates from the typical clinical prevalence of B-cell lymphoma subtypes, a reflection of the inherent selection bias in our cohort. Nonetheless, our sample size achieved robust statistical power, ensuring the validity of findings even in instances where no differences were discerned. Examining the age distribution, DLBCL and FL cohorts showcased no significant age discrepancy, with 74% and 59% of the patients being above 60, respectively (p=0.07). A striking observation was made in the PBL cohort, where patients under 60 constituted a significant majority (61%), notably higher than both DLBCL and FL counterparts (23% and 41%, respectively; p=0.002). In terms of disease progression, patients diagnosed at advanced stages showed consistent distribution across DLBCL-NOS, FL, and PBL groups (p=0.845). Contrarily, PTL predominantly encompassed patients diagnosed at earlier stages (85%), a proportion significantly greater than that of DLBCL-NOS at 42% (p<0.01). Using the Lymph2Cx tool, we discerned that the ABC subtype was comparably prevalent in both DLBCL NOS (75%) and PTL (81%) cohorts, with no significant difference (p=0.175).

Expression of TBL1XR1 and NCOR1 genes across B-cell lymphoma sub-types. Through digital RNA expression analysis, we identified significant variations in TBL1XR1 and NCOR1 expression across different B-cell lymphoma subtypes (Figure 1). PTL-ABC subtype exhibited the highest median expression for TBL1XR1 (6,401), compared to ABC subtype in DLBCL-NOS (3,339), PBL (2,141), and FL (1,726) (Table I). Statistical analysis confirmed a significant correlation between TBL1XR1 expression and lymphoma subtype (p<0.001). We noted no marked disparity in GCB-subtypes between PTL and DLBCL-NOS. However, the median TBL1XR1 expression was significantly higher in DLBCL-GCB subtype compared to FL (2,719 vs. 1,733, p=0.001). The highest median expression of NCOR1 was noted in FL (2,426), followed closely by DLBCL-NOS ABC subtype (2,281) and PTL-ABC subtype (2,098), with the lowest levels noted in PBL (1,555) (Table I and Figure 1A). However, NCOR1 expression was not significantly linked to lymphoma subtype (p=0.302).

Figure 1.
Figure 1.

Comprehensive representation of RNA expression variations across B-cell lymphoma subtypes. (A) Box plot delineating the fold change (y-axis) differential expression profile of transducin β-like 1 X-linked receptor 1 (TBL1XR1). (B) Corresponding to the fold change (y-axis) expression landscape of nuclear receptor corepressor 1 (NCOR1). (C) A heatmap detailing the differential expression signatures of 730 pertinent genes within the context of B-cell lymphoma subtypes.

View this table:
Table I.

Comparison of median expression levels and significance analysis for TBL1XR1 and NCOR1 in B-cell lymphoma subtypes.

TBL1XR1 expression in FL grades and NCOR1 expression disparity. We evaluated TBL1XR1 expression in low- and high-grade FLs, finding comparable mean and median levels between the two grades (p=0.809). Additionally, upon analyzing TBL1XR1 and NCOR1 expression in relation to FL stages, there were no discernible differences between early and advanced stages (p=0.862). A correlation study between TBL1XR1 and NCOR1 expression across both lymphoma grades revealed no significant association (Pearson r=0.15; 95%CI=0.53 to −0.21; p=0.489).

TBL1XR1 and NCOR1 expression in PBL. PBL showcased notably lower median TBL1XR1 expression levels (2,141) than both DLBCL-NOS (3,086) and PTL (5,562) (p=0.001). However, NCOR1 expression was consistent across PBL, DLBCL-NOS, and PTL. Within PBL samples, TBL1XR1 and NCOR1 demonstrated a significant negative correlation (Pearson r=−0.600; 95%CI=−0.778 to 0.315; p=0.001), hinting at divergent roles for these genes in PBL pathology.

Investigation of TBL1XR1 function and its association with DNA damage response (DDR) in B-cell lymphoma. We investigated the elevated expression of TBL1XR1 in B-cell lymphoma to discern its potential roles. Utilizing stringent criteria, we identified genes showing significant correlation with TBL1XR1. Remarkably, we found a pronounced association with key DNA damage response (DDR) genes, including RAD50, RAD51, FN1, RFC4, FANCA, MCM4, HELLS, STAG2, and RAC1. Bivariate analysis reinforced a significant tie between TBL1XR1 and these DDR genes (Pearson correlation r=0.496-0.770; p≤0.01) (Table II). A network plot (Figure 2A) visually represents these intricate relationships, emphasizing TBL1XR1’s potential interaction with critical DNA repair mechanisms in B-cell lymphoma.

View this table:
Table II.

Pearson’s correlation between TBL1XR1 gene expression and genes associated with the DNA damage repair (DDR) pathway.

Figure 2.
Figure 2.

Detailed visualization of TBL1XR1’s interplay with DNA repair genes and its expression landscape across diverse cancers. (A) Network plot illustrating the intricate associations between transducin β-like 1 X-linked receptor 1 (TBL1XR1) expression and key DNA repair genes in the context of B-cell lymphoma. (B) Box plot contrasting the TBL1XR1-DNA damage response (DDR) gene signature’s expression profiles in normal versus tumor tissues, spotlighting diffuse large B-cell lymphoma (DLBCL), breast carcinoma (BRCA), and stomach cancer (STAD) using data sourced from the TCGA public dataset.

Validation of the distinct expression of TBL1XR1-DDR pathway genes signature in a second cohort. In a second set of analysis, we probed the expression levels of TBL1XR1-DDR gene signature, namely TBL1XR1, FANCA, FN1, HDAC2, RFC4, RAC1, RAD50, and RAD51, across three cancer types namely, DLBCL, breast carcinoma, and gastric cancer. Leveraging data from the publicly available TCGA and GTEx databases, we juxtaposed these findings against their respective normal tissue controls. Remarkably, only DLBCL samples exhibited a statistically significant expression of TBL1XR1-DDR signature genes. In contrast, the solid tumors from breast and gastric origins showed no discernible association between TBL1XR1 and DDR gene expression (Figure 2B).

Discussion

TBL1XR1 and NCOR1, components of the nuclear receptor corepressor complex, are vital for cell differentiation and metabolism, modulating gene expression through chromatin modifications. In various cancers, aberrant expression, especially elevated TBL1XR1, is linked to poor prognosis, tumor growth, and therapy resistance. Their role, dependent on context, either inhibits tumor suppressor genes or activates oncogenic genes. Genomic aberrations disrupt this balance, enabling cancerous growth. While understood in solid tumors, knowledge about their dynamics in B-cell lymphoma remains scant. Disruptions in these proteins can impede B-cell differentiation, fostering lymphoid malignancies. Deciphering their roles can shed light on B-cell transformation mechanisms. TBL1XR1 and NCOR1 are key components of the nuclear receptor corepressor complex, pivotal in embryogenesis, cell differentiation, and metabolism by regulating transcription and modifying chromatin structure (12). In various cancers, including colorectal and breast, dysregulated expression, especially increased TBL1XR1, is linked to worse outcomes and increased resistance to treatment (13). The intricate interplay of TBL1XR1 and NCOR1 in cancer can either suppress tumor suppressor genes or amplify oncogenic ones (14). Genomic changes, like mutations, can disrupt this balance, enabling cancer cells to bypass growth control (15). However, knowledge about their roles in B-cell lymphoma remains rudimentary.

TBL1XR1 and NCOR1, integral to the corepressor complex, are pivotal in lymphohematopoietic processes. Their absence in hematopoietic stem cells (HSC) hampers lymphoid differentiation, as they shape gene expression and chromatin structure during cellular maturation (16). However, aberrations in these proteins can disturb lymphohematopoietic equilibrium, particularly in mature B-cell differentiation, potentially leading to lymphoid malignancies (8). TBL1XR1 has been associated with abnormal memory B cell formation and plasma cell differentiation hindrance, linking it to lymphoma development. Notably, TBL1XR1 mutations have been found in lymphomas including DLBCL and among MYD88 wild-type Waldenstrom’s macroglobulinemia, imparting aggressive behavior (3, 17), emphasizing the critical need to unravel their roles for understanding B-cell malignancies’ underpinnings.

In this study, we delve into the distinct expression profiles of TBL1XR1 and NCOR1 genes across B-cell lymphoma subtypes, aiming to uncover their associations with disease pathology and DNA repair mechanisms. We identified a specific expression pattern of TBL1XR1 in Activated B-cell-like (ABC) subsets of PTL compared to ABC- subtype of DLBCL-NOS, a distinction that holds promise for individualized therapeutic approaches and improved patient outcomes. Previous work by Youssef et al. found TBL1X (a homolog of TBL1XR1) to influence DLBCL prognosis, suggesting TBL1XR1’s potential as a biomarker or therapeutic pivot in ABC-DLBCL in preclinical model (18). While TBL1XR1’s oncogene-rich genomic region is implicated in driving aggressive malignancies, NCOR1 remains consistently expressed across DLBCL subsets. The observed inverse relationship between TBL1XR1 and NCOR1 in ABC-DLBCL underscores the necessity for further investigation, paving the way for enhanced understanding and innovative treatments.

TBL1XR1, known to stabilize G-protein pathway suppressor 2 (GPS2) via SUMOylation, is implicated in diverse physiological activities, ranging from DNA repair and cell proliferation to apoptosis and brain development (19). While the explicit role of TBL1XR1 in DDR within cancers such as B-cell lymphoma is still being deciphered, its encoding of an F-box-like/WD repeat-containing protein aligns it with the WD40 repeat protein family, previously associated with DNA damage pathways and cellular reactions to genotoxic stress (20). In our detailed analysis of B-cell lymphoma, we identified a compelling association between TBL1XR1 and a cluster of DDR genes (including RAD50, RAD51, and others). This elevated TBL1XR1-DDR gene signature in DLBCL was cross-verified using public databases (TCGA and GTEx). The intricate interactions of TBL1XR1 with pivotal DNA repair pathway components like XPA and BRCA1 accentuate its potential significance in DNA repair, illuminating its possible contributions to DDR and the ensuing ramifications for B-cell lymphoma pathogenesis.

In conclusion, our investigation revealed differential expression patterns of TBL1XR1 and NCOR1 across various B-cell lymphoma subtypes, particularly within the ABC-DLBCL subset of PTL and DLBCL-NOS. We observed a notably elevated expression of TBL1XR1, suggesting potential therapeutic avenues for customized treatments. Furthermore, we established a strong association between high TBL1XR1 expression and the DDR gene signature, a finding further substantiated in a separate validation cohort. While TBL1XR1 may have a pro-proliferative role, NCOR1 exhibited no significant differential expression between germinal centre and post-germinal centre derived B-cell lymphomas. Intriguingly, an inverse relationship between TBL1XR1 and NCOR1 expressions was evident in ABC-subtypes of PTL and DLBCL-NOS. These insights underscore the potential of TBL1XR1 as a therapeutic target in DLBCL and set the stage for subsequent investigations.

Acknowledgements

The Authors would like to acknowledge the support provided by the Alberta Precision Laboratories (APL) research department in retrieving diagnostic tissue archival material for the patients in this cohort.

Footnotes

  • Authors’ Contributions

    DS and AM, conceived and designed the study, devised all the protocols, and edited the final manuscript. MH performed data collection and analysis. AA performed experimental work and QA. TMR, MTSR contributed samples/clinical data and reviewed pathology.

  • Conflicts of Interest

    The Authors declare no competing financial interests concerning this work.

  • Funding

    This work was supported by a research grant from Alberta Cancer Foundation (grant #25999).

  • Received September 7, 2023.
  • Revision received September 21, 2023.
  • Accepted September 25, 2023.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC-ND) 4.0 international license (https://creativecommons.org/licenses/by-nc-nd/4.0).

References

  1. ↵
    1. Victora GD,
    2. Nussenzweig MC
    : Germinal centers. Annu Rev Immunol 40(1): 413-442, 2022. DOI: 10.1146/annurev-immunol-120419-022408
    OpenUrlCrossRef
  2. ↵
    1. Chen H,
    2. Zhang Y,
    3. Ye AY,
    4. Du Z,
    5. Xu M,
    6. Lee CS,
    7. Hwang JK,
    8. Kyritsis N,
    9. Ba Z,
    10. Neuberg D,
    11. Littman DR,
    12. Alt FW
    : BCR selection and affinity maturation in Peyer’s patch germinal centres. Nature 582(7812): 421-425, 2020. DOI: 10.1038/s41586-020-2262-4
    OpenUrlCrossRefPubMed
  3. ↵
    1. Shen R,
    2. Xu PP,
    3. Wang N,
    4. Yi HM,
    5. Dong L,
    6. Fu D,
    7. Huang JY,
    8. Huang HY,
    9. Janin A,
    10. Cheng S,
    11. Wang L,
    12. Zhao WL
    : Influence of oncogenic mutations and tumor microenvironment alterations on extranodal invasion in diffuse large B-cell lymphoma. Clin Transl Med 10(7): e221, 2020. DOI: 10.1002/ctm2.221
    OpenUrlCrossRef
  4. ↵
    1. Yoon HG,
    2. Chan DW,
    3. Huang ZQ,
    4. Li J,
    5. Fondell JD,
    6. Qin J,
    7. Wong J
    : Purification and functional characterization of the human N-CoR complex: the roles of HDAC3, TBL1 and TBLR1. EMBO J 22(6): 1336-1346, 2003. DOI: 10.1093/emboj/cdg120
    OpenUrlAbstract/FREE Full Text
  5. ↵
    1. Hatzi K,
    2. Jiang Y,
    3. Huang C,
    4. Garrett-Bakelman F,
    5. Gearhart MD,
    6. Giannopoulou EG,
    7. Zumbo P,
    8. Kirouac K,
    9. Bhaskara S,
    10. Polo JM,
    11. Kormaksson M,
    12. MacKerell AD Jr.,
    13. Xue F,
    14. Mason CE,
    15. Hiebert SW,
    16. Prive GG,
    17. Cerchietti L,
    18. Bardwell VJ,
    19. Elemento O,
    20. Melnick A
    : A hybrid mechanism of action for BCL6 in B cells defined by formation of functionally distinct complexes at enhancers and promoters. Cell Rep 4(3): 578-588, 2013. DOI: 10.1016/j.celrep.2013.06.016
    OpenUrlCrossRefPubMed
  6. ↵
    1. Pray BA,
    2. Youssef Y,
    3. Alinari L
    : TBL1X: At the crossroads of transcriptional and posttranscriptional regulation. Exp Hematol 116: 18-25, 2022. DOI: 10.1016/j.exphem.2022.09.006
    OpenUrlCrossRefPubMed
  7. ↵
    1. Hatzi K,
    2. Melnick A
    : Breaking bad in the germinal center: how deregulation of BCL6 contributes to lymphomagenesis. Trends Mol Med 20(6): 343-352, 2014. DOI: 10.1016/j.molmed.2014.03.001
    OpenUrlCrossRefPubMed
  8. ↵
    1. Venturutti L,
    2. Teater M,
    3. Zhai A,
    4. Chadburn A,
    5. Babiker L,
    6. Kim D,
    7. Béguelin W,
    8. Lee TC,
    9. Kim Y,
    10. Chin CR,
    11. Yewdell WT,
    12. Raught B,
    13. Phillip JM,
    14. Jiang Y,
    15. Staudt LM,
    16. Green MR,
    17. Chaudhuri J,
    18. Elemento O,
    19. Farinha P,
    20. Weng AP,
    21. Nissen MD,
    22. Steidl C,
    23. Morin RD,
    24. Scott DW,
    25. Privé GG,
    26. Melnick AM
    : TBL1XR1 mutations drive extranodal lymphoma by inducing a pro-tumorigenic memory fate. Cell 182(2): 297-316.e27, 2020. DOI: 10.1016/j.cell.2020.05.049
    OpenUrlCrossRefPubMed
  9. ↵
    1. Swerdlow SH,
    2. Campo E,
    3. Pileri SA,
    4. Harris NL,
    5. Stein H,
    6. Siebert R,
    7. Advani R,
    8. Ghielmini M,
    9. Salles GA,
    10. Zelenetz AD,
    11. Jaffe ES
    : The 2016 revision of the World Health Organization classification of lymphoid neoplasms. Blood 127(20): 2375-2390, 2016. DOI: 10.1182/blood-2016-01-643569
    OpenUrlAbstract/FREE Full Text
  10. ↵
    1. Scott DW,
    2. Wright GW,
    3. Williams PM,
    4. Lih CJ,
    5. Walsh W,
    6. Jaffe ES,
    7. Rosenwald A,
    8. Campo E,
    9. Chan WC,
    10. Connors JM,
    11. Smeland EB,
    12. Mottok A,
    13. Braziel RM,
    14. Ott G,
    15. Delabie J,
    16. Tubbs RR,
    17. Cook JR,
    18. Weisenburger DD,
    19. Greiner TC,
    20. Glinsmann-Gibson BJ,
    21. Fu K,
    22. Staudt LM,
    23. Gascoyne RD,
    24. Rimsza LM
    : Determining cell-of-origin subtypes of diffuse large B-cell lymphoma using gene expression in formalin-fixed paraffin-embedded tissue. Blood 123(8): 1214-1217, 2014. DOI: 10.1182/blood-2013-11-536433
    OpenUrlAbstract/FREE Full Text
  11. ↵
    1. Tang Z,
    2. Kang B,
    3. Li C,
    4. Chen T,
    5. Zhang Z
    : GEPIA2: an enhanced web server for large-scale expression profiling and interactive analysis. Nucleic Acids Res 47(W1): W556-W560, 2019. DOI: 10.1093/nar/gkz430
    OpenUrlCrossRefPubMed
  12. ↵
    1. Li JY,
    2. Daniels G,
    3. Wang J,
    4. Zhang X
    : Tbl1xr1 in physiological and pathological states. Am J Clin Exp Urol 3(1): 13-23, 2015.
    OpenUrlPubMed
  13. ↵
    1. Pereira B,
    2. Chin SF,
    3. Rueda OM,
    4. Vollan HK,
    5. Provenzano E,
    6. Bardwell HA,
    7. Pugh M,
    8. Jones L,
    9. Russell R,
    10. Sammut SJ,
    11. Tsui DW,
    12. Liu B,
    13. Dawson SJ,
    14. Abraham J,
    15. Northen H,
    16. Peden JF,
    17. Mukherjee A,
    18. Turashvili G,
    19. Green AR,
    20. McKinney S,
    21. Oloumi A,
    22. Shah S,
    23. Rosenfeld N,
    24. Murphy L,
    25. Bentley DR,
    26. Ellis IO,
    27. Purushotham A,
    28. Pinder SE,
    29. Børresen-Dale AL,
    30. Earl HM,
    31. Pharoah PD,
    32. Ross MT,
    33. Aparicio S,
    34. Caldas C
    : The somatic mutation profiles of 2,433 breast cancers refines their genomic and transcriptomic landscapes. Nat Commun 7: 11479, 2016. DOI: 10.1038/ncomms11479
    OpenUrlCrossRefPubMed
  14. ↵
    1. Mottis A,
    2. Mouchiroud L,
    3. Auwerx J
    : Emerging roles of the corepressors NCoR1 and SMRT in homeostasis. Genes Dev 27(8): 819-835, 2013. DOI: 10.1101/gad.214023.113
    OpenUrlAbstract/FREE Full Text
  15. ↵
    1. Battaglia S,
    2. Maguire O,
    3. Campbell MJ
    : Transcription factor co-repressors in cancer biology: roles and targeting. Int J Cancer 126(11): 2511-2519, 2010. DOI: 10.1002/ijc.25181
    OpenUrlCrossRefPubMed
  16. ↵
    1. Wan X,
    2. Liu L,
    3. Zhou P,
    4. Hui X,
    5. He Q,
    6. Yu F,
    7. Zhang W,
    8. Ding X,
    9. Yuan X,
    10. Zhang N,
    11. Zhao Y,
    12. Zhu R,
    13. Liu Y,
    14. Hao P,
    15. Auwerx J,
    16. Song X,
    17. Leng Q,
    18. Zhang Y
    : The nuclear receptor corepressor NCoR1 regulates hematopoiesis and leukemogenesis in vivo. Blood Adv 3(4): 644-657, 2019. DOI: 10.1182/bloodadvances.2018022756
    OpenUrlAbstract/FREE Full Text
  17. ↵
    1. Hunter ZR,
    2. Xu L,
    3. Tsakmaklis N,
    4. Demos MG,
    5. Kofides A,
    6. Jimenez C,
    7. Chan GG,
    8. Chen J,
    9. Liu X,
    10. Munshi M,
    11. Gustine J,
    12. Meid K,
    13. Patterson CJ,
    14. Yang G,
    15. Dubeau T,
    16. Samur MK,
    17. Castillo JJ,
    18. Anderson KC,
    19. Munshi NC,
    20. Treon SP
    : Insights into the genomic landscape of MYD88 wild-type Waldenström macroglobulinemia. Blood Adv 2(21): 2937-2946, 2018. DOI: 10.1182/bloodadvances.2018022962
    OpenUrlAbstract/FREE Full Text
  18. ↵
    1. Youssef Y,
    2. Karkhanis V,
    3. Chan WK,
    4. Jeney F,
    5. Canella A,
    6. Zhang X,
    7. Sloan S,
    8. Prouty A,
    9. Helmig-Mason J,
    10. Tsyba L,
    11. Hanel W,
    12. Zheng X,
    13. Zhang P,
    14. Chung JH,
    15. Lucas DM,
    16. Kauffman Z,
    17. Larkin K,
    18. Strohecker AM,
    19. Ozer HG,
    20. Lapalombella R,
    21. Zhou H,
    22. Xu-Monette ZY,
    23. Young KH,
    24. Han R,
    25. Nurmemmedov E,
    26. Nuovo G,
    27. Maddocks K,
    28. Byrd JC,
    29. Baiocchi RA,
    30. Alinari L
    : Transducin β-like protein 1 controls multiple oncogenic networks in diffuse large B-cell lymphoma. Haematologica 106(11): 2927-2939, 2021. DOI: 10.3324/haematol.2020.268235
    OpenUrlCrossRefPubMed
  19. ↵
    1. Bi H,
    2. Li S,
    3. Wang M,
    4. Jia Z,
    5. Chang AK,
    6. Pang P,
    7. Wu H
    : SUMOylation of GPS2 protein regulates its transcription-suppressing function. Mol Biol Cell 25(16): 2499-2508, 2014. DOI: 10.1091/mbc.E13-12-0733
    OpenUrlAbstract/FREE Full Text
  20. ↵
    1. Pines A,
    2. Vrouwe MG,
    3. Marteijn JA,
    4. Typas D,
    5. Luijsterburg MS,
    6. Cansoy M,
    7. Hensbergen P,
    8. Deelder A,
    9. de Groot A,
    10. Matsumoto S,
    11. Sugasawa K,
    12. Thoma N,
    13. Vermeulen W,
    14. Vrieling H,
    15. Mullenders L
    : PARP1 promotes nucleotide excision repair through DDB2 stabilization and recruitment of ALC1. J Cell Biol 199(2): 235-249, 2012. DOI: 10.1083/jcb.201112132
    OpenUrlAbstract/FREE Full Text
Back to top

In this issue

Print
Download PDF
Article Alerts
Email Article
Citation Tools
Reprints and Permissions
Exploring TBL1XR1 and NCOR1 Expression in B-cell Lymphoma Subtypes: Interaction With DNA Damage Repair Genes
ADNAN MANSOOR, ARIZ AKHTER, MAHBOOBSADAT HAMIDI, TARIQ MAHMOOD ROSHAN, MEER-TAHER SHABANI-RAD, DOUGLAS STEWART
Anticancer Research Nov 2023, 43 (11) 4801-4807; DOI: 10.21873/anticanres.16677
Twitter logo Facebook logo Mendeley logo

Jump to section

Keywords