The role of NPM1 alternative splicing in patients with chronic lymphocytic leukemia

Szelest, Monika; Masternak, Marta; Zając, M; Chojnacki, Michał; Zaleska, Joanna; Karczmarczyk, Agnieszka; Stasiak, Grażyna; Wawrzyniak, Ewa; Kotkowska, Aleksandra; Siemieniuk-Ryś, Monika; Purkot, Joanna; Subocz, Edyta; Cichocka, Edyta; Tomczak, Waldemar; Zawirska, Daria; Skórka, Katarzyna

doi:10.1371/journal.pone.0276674

Cited by 3 publications

(3 citation statements)

References 31 publications

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“…Alterations of gene expression and splicing play a key role in cancer [19], particularly in hematologic malignancy pathogenesis [20][21][22][23][24][25][26][27][28][29][30]. For instance, many hematologic malignancies are characterized by altered expression resulting from gene rearrangements that lead to the overexpression of specific transcription factors or cell cycle regulators.…”

Section: Introductionmentioning

confidence: 99%

Analysis of 3760 hematologic malignancies reveals rare transcriptomic aberrations of driver genes

Cao,

Huber,

Ahari

et al. 2024

Genome Med

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Background Rare oncogenic driver events, particularly affecting the expression or splicing of driver genes, are suspected to substantially contribute to the large heterogeneity of hematologic malignancies. However, their identification remains challenging. Methods To address this issue, we generated the largest dataset to date of matched whole genome sequencing and total RNA sequencing of hematologic malignancies from 3760 patients spanning 24 disease entities. Taking advantage of our dataset size, we focused on discovering rare regulatory aberrations. Therefore, we called expression and splicing outliers using an extension of the workflow DROP (Detection of RNA Outliers Pipeline) and AbSplice, a variant effect predictor that identifies genetic variants causing aberrant splicing. We next trained a machine learning model integrating these results to prioritize new candidate disease-specific driver genes. Results We found a median of seven expression outlier genes, two splicing outlier genes, and two rare splice-affecting variants per sample. Each category showed significant enrichment for already well-characterized driver genes, with odds ratios exceeding three among genes called in more than five samples. On held-out data, our integrative modeling significantly outperformed modeling based solely on genomic data and revealed promising novel candidate driver genes. Remarkably, we found a truncated form of the low density lipoprotein receptor LRP1B transcript to be aberrantly overexpressed in about half of hairy cell leukemia variant (HCL-V) samples and, to a lesser extent, in closely related B-cell neoplasms. This observation, which was confirmed in an independent cohort, suggests LRP1B as a novel marker for a HCL-V subclass and a yet unreported functional role of LRP1B within these rare entities. Conclusions Altogether, our census of expression and splicing outliers for 24 hematologic malignancy entities and the companion computational workflow constitute unique resources to deepen our understanding of rare oncogenic events in hematologic cancers.

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Section: Introductionmentioning

confidence: 99%

Analysis of 3760 hematologic malignancies reveals rare transcriptomic aberrations of driver genes

Cao,

Huber,

Ahari

et al. 2024

Genome Med

View full text Add to dashboard Cite

show abstract

“…Alterations of gene expression and splicing play a key role in cancer (8), particularly in hematologic malignancy pathogenesis (9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19). For instance, many hematologic malignancies are characterized by altered expression resulting from gene rearrangements that lead to the overexpression of specific transcription factors or cell cycle regulators.…”

Section: Introductionmentioning

confidence: 99%

“…Abnormal gene expression and splicing play a key role in cancer 8 and particularly in hematologic malignancy pathogenesis [9][10][11][12][13][14][15][16][17][18][19] . Abnormal gene expression, which could result in deregulated pathways, is suggested to be involved in development of hematologic malignancies.…”

Section: Introductionmentioning

confidence: 99%

Analysis of 3,760 hematologic malignancies reveals rare transcriptomic aberrations of driver genes

Cao,

Huber,

Ahari

et al. 2023

Preprint

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Rare driver mutations are suspected to substantially contribute to the large heterogeneity of hematologic malignancies, but their identification remains challenging. To address this issue, we generated the largest dataset to date of matched whole genome sequencing and total RNA sequencing of hematologic malignancies from over 3,760 patients spanning 24 disease entities. To discover rare and large regulatory aberrations, we analyzed aberrant expression and splicing events using an extension of DROP (Detection of RNA Outliers Pipeline) and AbSplice, an algorithm that identifies genetic variants causing aberrant splicing. We found a median of seven aberrantly expressed genes, two aberrantly spliced genes, and two rare splice-affecting variants per sample. Each category showed significant enrichment for well-characterized driver genes, with odds ratios exceeding three among genes called in more than one sample. We next trained disease-specific driver gene prediction models integrating these data with recurrent mutation analyses. On held-out data, integrative modeling significantly outperformed modeling based solely on genomic data and revealed promising novel candidate driver genes. Moreover, we found a truncated form of the low density lipoprotein receptor LRP1B to be aberrantly overexpressed in about half of hairy cell leukemia variant (HCL-V) samples and, to a lesser extent, in closely related B-cell neoplasms. This observation, which was confirmed in an independent cohort, suggests LRP1B be a novel biomarker and a yet unreported functional role of LRP1B within these rare entities. Altogether, this dataset and the companion computational workflow constitute unique resources to deepen our understanding of rare oncogenic events in hematologic cancers.

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Integrative Analysis of Multi-Omics Data to Identify Deregulated Molecular Pathways and Druggable Targets in Chronic Lymphocytic Leukemia

Mavridou,

Psatha,

Aivaliotis

2024

JPM

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Chronic Lymphocytic Leukemia (CLL) is the most common B-cell malignancy in the Western world, characterized by frequent relapses despite temporary remissions. Our study integrated publicly available proteomic, transcriptomic, and patient survival datasets to identify key differences between healthy and CLL samples. We exposed approximately 1000 proteins that differentiate healthy from cancerous cells, with 608 upregulated and 415 downregulated in CLL cases. Notable upregulated proteins include YEATS2 (an epigenetic regulator), PIGR (Polymeric immunoglobulin receptor), and SNRPA (a splicing factor), which may serve as prognostic biomarkers for this disease. Key pathways implicated in CLL progression involve RNA processing, stress resistance, and immune response deficits. Furthermore, we identified three existing drugs—Bosutinib, Vorinostat, and Panobinostat—for potential further investigation in drug repurposing in CLL. We also found limited correlation between transcriptomic and proteomic data, emphasizing the importance of proteomics in understanding gene expression regulation mechanisms. This generally known disparity highlights once again that mRNA levels do not accurately predict protein abundance due to many regulatory factors, such as protein degradation, post-transcriptional modifications, and differing rates of translation. These results demonstrate the value of integrating omics data to uncover deregulated proteins and pathways in cancer and suggest new therapeutic avenues for CLL.

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The role of NPM1 alternative splicing in patients with chronic lymphocytic leukemia

Cited by 3 publications

References 31 publications

Analysis of 3760 hematologic malignancies reveals rare transcriptomic aberrations of driver genes

Analysis of 3760 hematologic malignancies reveals rare transcriptomic aberrations of driver genes

Analysis of 3,760 hematologic malignancies reveals rare transcriptomic aberrations of driver genes

Integrative Analysis of Multi-Omics Data to Identify Deregulated Molecular Pathways and Druggable Targets in Chronic Lymphocytic Leukemia

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