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- Sevov, Marie, et al.
(författare)
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Longitudinal study of RNA-based prognostic markers in chronic lymphocytic leukemia reveals LPL as the most stable
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Several genes display differential expression in prognostic subsets in chronic lymphocytic leukemia (CLL), including LPL, TCL1, ZAP70 and MCL1. CLL patients commonly have an indolent course with low stage disease and long survival, and in this study we aimed to investigate the stability of RNA-based prognostic markers in such an indolent cohort over time. mRNA expression of LPL, TCL1, ZAP70 and MCL1 was measured in sequential unsorted samples obtained from 96 CLL patients at both diagnosis and a median follow-up of seven years. LPL was the only RNA-based marker that did not demonstrate any significant changes in expression in diagnostic vs. follow-up samples. Furthermore, an 82% concordance between both time-points was observed when grouping cases based on high or low expression. LPL expression was not affected by treatment and in addition, LPL expression in follow-up samples could predict overall survival. In contrast, TCL1 expression was found to increase at follow-up, especially in cases displaying low expression at diagnosis. As TCL1 promotes cell survival this increase could possibly be of importance for progression of the disease. Both ZAP70 and MCL1 mRNA expression were found to vary significantly during the disease course. In summary, using unsorted CLL samples, we have demonstrated that LPL is superior to other RNA-based markers based on stability over time. These findings fully endorse the use of LPL analysis at any time point of the disease.
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- Cozzi, Elisabetta, et al.
(författare)
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Identification of long non-coding RNAs involved in leukemogenesis and venetoclax response in acute myeloid leukemia through functional CRISPR-dCas9 interference screens
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Acute myeloid leukemia (AML) is a malignant hematologic disease with poor prognosis. Increased understanding of disease biology is therefore needed to improve outcome for patients. While the protein-coding genome is well characterized in AML, knowledge about the involvement of non-coding genes is very limited in AML. Here, it was sought to investigate how long non-coding RNAs (lncRNAs) could contribute to disease biology and treatment resistance in AML. Three high-throughput lncRNA-CRISPR-interference screens were performed in MOLM-13 cells, knocking down about 8000 lncRNA expressed in hematopoietic cells. Effects on cell proliferation, cell differentiation and response to the anti-leukemic Bcl-2-inhibitor venetoclax were investigated upon lncRNA repression. LncRNAs most likely to positively or negatively regulate these processes were identified and top lncRNA candidates investigated with respect to expression in AML and healthy CD34+ cells and clinical AML correlations. Four lncRNAs involved in AML cell proliferation were identified (lncRNAs MIR17HG, CATG00000056335, CATG00000095269, CATG00000002239), two lncRNAs involved in differentiation (lncRNAs RP11-444A22.1, CATG00000058672) and seven lncRNAs implicated in venetoclax response. Among those, enhanced expression of proliferation-promoting lncRNA MIR17HG significantly correlated with poor outcome in AML patients (p= 0.03; p= 0.016). Further, lncRNA RP11-444A2 was identified as a predicted negative regulator of cell differentiation and was found to correlate with poor outcome (p=0.014). Further, lncRNA AC009299.3, predicted in venetoclax sensitivity, was found to be associated with poor outcome (p<0.0001), adverse risk (p=0.0014) and increased age (p=0.0045) in AML patients. Together, this study identified 14 lncRNAs proposed to be implicated in key leukemogenic events, highlighting their potential for elucidating AML biology, prognosis or treatment-response prediction and/or therapeutic use.
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- Miliara, Sophia, et al.
(författare)
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The biological and prognostic role of long non-coding RNA NEAT1 in acute myeloid leukemia
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Nuclear paraspeckle assembly transcript 1 (NEAT1) is a long non-coding RNA localized in the cell nucleus that has been associated to promote several malignant solid tumors. Its role in acute myeloid leukemia (AML) remains largely elusive. Therefore, the aim of this study was to define the role of NEAT1 in AML compared to normal hematopoiesis. During normal hematopoiesis, it was identified that NEAT1 expression was low in early progenitors but increased in more differentiated cells, especially in monocytes. NEAT1 expression was increased in AML as a whole compared to normal bone marrow (NBM). It was specifically high in AML with inv(16) and t(8;21), while it was lower in patients with t(15;17). Further, NEAT1 expression correlated positively with ASXL1, KRAS and NRAS mutations and negatively with TP53 mutant AML. Higher NEAT expression was associated to better overall survival in AML, independent of other known risk factors. Antisense oligo-mediated knockdown of NEAT1 in AML cells significantly increased expression of the monocytic marker CD14 while granulocytic markers did not change. Genes affected by NEAT1-knockdown using CAGE-sequencing were significantly enriched for genes involved in glucose metabolism. By investigating genome-wide RNA and DNA interactions using RADICL-sequencing, it was revealed that NEAT1 binds to the loci of key hematopoietic regulator RUNX2 as well as the chromatin regulators KMT2A, KMT5B and CHD7. The results suggest that lncRNA NEAT1 has a potential role in hematopoietic and AML cell differentiation and could be a potential new biomarker in AML.
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- Neddermeyer, Anne, et al.
(författare)
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A new mutant NPM1/IDH2R140- and PML-RARA-associated lncRNA MALNC plays a role in AML biology, prognosis and drug response
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Acute myeloid leukemia (AML) is a hematopoietic malignancy characterized by poor prognosis that requires better understanding of its disease biology and new tools for suitable risk stratification and effective treatments. Long non-coding RNAs (lncRNAs) are involved in numerous molecular mechanisms, are implicated in tumor biology and can serve as clinical biomarkers, yet their role remains mostly unclear in AML. In this study, the aim was to discover and characterize lncRNAs implicated in AML and to describe their role in AML biology. Further aims were to explore their use as prognostic or predictive biomarkers. Using whole-transcriptome analysis, a novel lncRNA, here named MALNC, was identified. MALNC had elevated expression in two large AML cohorts compared to normal CD34+ cells. Clinical correlation analyses indicated that MALNC was almost uniquely expressed in patients with PML-RARA fusion gene and with co-mutated isocitrate dehydrogenase-2 R140 and nucleophosmin-1 (IDH2R140/NPM1). MALNC expression was specifically high at the promyelocytic stage and decreased with maturation in leukemic and normal cells. High MALNC expression associated independently with better overall survival. CRISPR-Cas9-knockout in promyelocytic cell lines impaired proliferation, colony formation and all-trans retinoic acid (ATRA)-induced differentiation. Also, MALNC-knockout dramatically sensitized cells to arsenic trioxide (ATO), ATO-ATRA combinatorial and Bcl-2-inhibitor venetoclax treatment as well as associated with cyclin-dependent kinase (Cdk)-inhibitor resistance. In conclusion, MALNC is overexpressed in certain subgroups of AML and could play a role during normal and leukemic hematopoietic maturation. Furthermore, it correlates with response to anti-leukemic drugs, which suggests a role as a predictive marker to drug response and survival in AML.
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- Hernestål-Boman, Jenny, 1980-, et al.
(författare)
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Individual PAI-1 increase over nine years relates differently in men and women to changes in anthropometric, glycaemic, inflammatory and lipid markers.
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Background: Levels of plasminogen activator inhibitor-1 (PAI-1) is known to correlate to factors related to the metabolic syndrome. We have previously shown that PAI-1 antigen increased by 75% in men and 95% in women over nine years.Objective: The aim of this study was to explore relationships between intra-individual changes in PAI-1 and changes in anthropometric measurements, blood pressure, glycaemic, lipid and inflammatory markers, separately for men and women.Method: In northern Sweden, 125 men and 116 women were examined first in 1990 and re-examined in 1999 during the morning hours. Changes over time (Δ) were calculated as the value at 1999 minus the value at 1990.Results: In men, ΔPAI-1 was significantly correlated to ΔBMI (r =0.33), ΔCRP (r =0.25), Δtriglycerides (r =0.39), Δfasting plasma glucose (r =0.41) and Δ2-hour plasma glucose (r =0.29). In women, ΔPAI-1 was significantly correlated to ΔBMI (r =0.36), Δwaist circumference (r =0.38), Δhip circumference (r =0.27), ΔCRP (r =0.27) and Δtotal cholesterol (r =0.19). The multivariate linear regression analysis showed that ΔPAI-1 was significantly related to Δfasting plasma glucose and ΔCRP in men (R2 for the complete model was 0.31). In women, ΔPAI-1 was significantly related to Δwaist circumference (R2 for the complete model was 0.17).Conclusion: We expected that changes in anthropometric, glycaemic, inflammatory and lipid markers would explain a large part of the observed PAI-1 increase. However, the multivariate analysis explained only 20% of the variation in ΔPAI-1 in women and 30% in men. Interestingly, the patterns of components correlating with the changes in PAI-1 differed between sexes.
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- Scott, Aaron M., et al.
(författare)
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Population scale proteomics enables adaptive digital twin modelling in sepsis
- 2024
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Sepsis is one of the leading causes of mortality in the world. Currently, the heterogeneity of sepsis makes it challenging to determine the molecular mechanisms that define the syndrome. Here, we leverage population scale proteomics to analyze a well-defined cohort of 1364 blood samples taken at time-of-admission to the emergency department from patients suspected of sepsis. We identified panels of proteins using explainable artificial intelligence that predict clinical outcomes and applied these panels to reduce high-dimensional proteomics data to a low-dimensional interpretable latent space (ILS). Using the ILS, we constructed an adaptive digital twin model that accurately predicted organ dysfunction, mortality, and early-mortality-risk patients using only data available at time-of-admission. In addition to being highly effective for investigating sepsis, this approach supports the flexible incorporation of new data and can generalize to other diseases to aid in translational research and the development of precision medicine.Competing Interest StatementThe authors have declared no competing interest.Funding StatementL.M. is funded by the Swedish Research Council (grant number VR-2020-02419), the Wallenberg foundation (grant number 2016.0023) and Alfred Österlunds Foundation. J.M. is a Wallenberg academy fellow (KAW 2017.0271) and is also funded by the Swedish Research Council (Vetenskapsrådet, VR) (2019-01646 and 2018-05795), the Wallenberg foundation (KAW2016.0023, KAW2019.0353 and KAW2020.0299), and Alfred Österlunds Foundation. E.M. is funded by Wenner-Gren Foundation (FT2020-0003), the Crafoord Foundation, and the Swedish Society of Medicine (SLS-985287). F.K. is funded by Region Skåne ALF project and the Crafoord Foundation. A.L. is funded by the Swedish Research Council VR 2023-02707 and Region Skåne ALF project 2022-0146.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:Ethical approval for the study was obtained from the Swedish National Ethics Committee (file numbers 2022-01454-01, 2014/741 and 2016/271).I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.YesData produced in the present study are available upon reasonable request to the authors
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