Identification of XPO1 interactors and modulation by selinexor in diffuse large B cell lymphoma
Bibliographic record
Abstract
Abstract Background Diffuse large B cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphoma (NHL). Relapsed/refractory (R/R) patients commonly have poor outcomes, highlighting the need for novel treatment regimens. Selinexor, an orally-available inhibitor of nuclear export via Exportin-1 (XPO1) is active in R/R DLBCL, but knowledge gaps in understanding how XPO1 drives DLBCL are limiting our ability to properly select patients that may benefit from selinexor and design effective combinations. Specifically, large-scale proteomics studies identifying XPO1 cargo molecules in DLBCL are lacking. Additionally, selinexor's mechanism of action in DLBCL is not fully understood. As such, we aimed to identify XPO1 interactors in DLBCL, to better characterize the repertoire of XPO1 cargo molecules in this lymphoma subtype. In addition, to determine how selinexor mediates downstream activity following XPO1 inhibition, we conducted a mass spectrometry based analysis to delineate selinexor-mediated changes to the mitochondrial proteome. Methods XPO1 interactors were identified using a proximity-dependent biotinylation (BioID) (Sears et al., 2019) assay in DLBCL cell lines. Cells were treated with 0.5mM selinexor or DMSO for 24 hours, followed by the addition of 50mM biotin. Biotinylated proteins were isolated using streptavidin conjugated beads and identified using mass spectrometry. To determine selinexor mediated changes to the mitochondrial proteome, cells underwent the treatment conditions described above and were then subjected to mitochondrial enrichment prior to proteomic analysis via mass spectrometry. To identify putative XPO1 cargo molecules, protein sequences were analyzed using the LocNES nuclear export sequence (NES) algorithm to locate canonical XPO1 binding sequences (Xu et al., 2014). Results The BioID experiment identified 2766 unique peptides, which, once adjusted for control interactions, found 45 proteins as significant (BFDR<0.1) XPO1 interactors. Interacting proteins included Ran binding protein 2 (RanBP2), as well as 13 proteins of the nuclear pore complex (NPC), the conduit that allows XPO1 to shuttle between the nucleus and cytoplasm. Of interest was NUP88, which promotes NFkB activity and is overexpressed in several cancers (Singh et al., 2023), as well as NUP98, which assists with nuclear export of mRNA via interactions with its export factor Rae1 (Lin et al., 2018) and is dysregulated in several hematological malignancies (Michmerhuizen et al., 2020). We found that, in the presence of selinexor, increased biotinylation of NPC subunits was observed, indicating that XPO1's relative interactions with the NPC may increase with selinexor. This may be interpreted as the ability of the XPO1 cycle to continue with selinexor bound to the NES binding pocket, and may be independent of cargo protein binding. Similarly, selinexor treatment resulted in a decreased abundance of 61 mitochondrial proteins. Proteins relevant to DLBCL metabolism were identified and discussed previously (Trkulja et al., 2024). Of these proteins, we found a decrease in the mitochondrial levels of ORC1, which is involved in initiating the DNA replication and whose nuclear export is required for elongation to proceed. DNA replication proteins such DNA helicase RECQL4 have been found to shuttle to the mitochondria to aid in mtDNA maintenance (Lionaki et al., 2016), highlighting a novel role for such targets. ORC1 was significantly decreased in the mitochondria of selinexor-treated cells, suggesting its nuclear export is inhibited which may impact DNA elongation and cell division. The peptide sequence of ORC1 was found to contain a potential NES, indicating that it may be a novel XPO1 cargo protein modulated by selinexor in DLBCL. We confirmed that selinexor modulates the cell cycle and show that cell cycle arrest occurs at 24hrs following treatment with the drug even in p53 null DLBCL cell lines. Conclusion XPO1 interacts with several proteins in the NPC, even in the presence of selinexor, suggesting that that the XPO1 cycle still occurs when interactions with cargo proteins are blocked. Furthermore, selinexor reduced the extra-nuclear abundance ORC1, whose export is required for DNA elongation and cell cycle progression. This describes a potential p53-independent mechanism of cell cycle arrest mediated by selinexor, providing an additional mechanism of action by which XPO1 modulates the cell cycle.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".