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Expression levels of long non-coding RNAs are prognostic for AML outcome

Mer, Arvind Singh (author)
Karolinska Inst, Dept Med Epidemiol & Biostat, Nobels Vag 12A, SE-17177 Stockholm, Sweden.
Lindberg, Johan (author)
Karolinska Institutet,Karolinska Inst, Dept Med Epidemiol & Biostat, Sci Life Lab, Nobels Vag 12A, SE-17177 Stockholm, Sweden.
Nilsson, Christer (author)
Karolinska Institutet,Karolinska Univ Hosp, Hematol Ctr, Stockholm, Sweden.;Karolinska Inst, Stockholm, Sweden.
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Klevebring, Daniel (author)
Karolinska Inst, Dept Med Epidemiol & Biostat, Nobels Vag 12A, SE-17177 Stockholm, Sweden.
Wang, Mei (author)
Karolinska Inst, Dept Med Epidemiol & Biostat, Nobels Vag 12A, SE-17177 Stockholm, Sweden.
Gronberg, Henrik (author)
Karolinska Institutet,Karolinska Inst, Dept Med Epidemiol & Biostat, Nobels Vag 12A, SE-17177 Stockholm, Sweden.
Lehmann, Sören (author)
Karolinska Institutet,Uppsala universitet,Hematologi,Karolinska Univ Hosp, Hematol Ctr, Stockholm, Sweden.;Karolinska Inst, Stockholm, Sweden.
Rantalainen, Mattias (author)
Karolinska Institutet,Karolinska Inst, Dept Med Epidemiol & Biostat, Nobels Vag 12A, SE-17177 Stockholm, Sweden.
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Karolinska Institutet Karolinska Inst, Dept Med Epidemiol & Biostat, Nobels Vag 12A, SE-17177 Stockholm, Sweden (creator_code:org_t)
2018-04-07
2018
English.
In: Journal of Hematology & Oncology. - : BIOMED CENTRAL LTD. - 1756-8722. ; 11
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • Background: Long non-coding RNA (lncRNA) expression has been implicated in a range of molecular mechanisms that are central in cancer. However, lncRNA expression has not yet been comprehensively characterized in acute myeloid leukemia (AML). Here, we assess to what extent lncRNA expression is prognostic of AML patient overall survival (OS) and determine if there are indications of lncRNA-based molecular subtypes of AML. Methods: We performed RNA sequencing of 274 intensively treated AML patients in a Swedish cohort and quantified lncRNA expression. Univariate and multivariate time-to-event analysis was applied to determine association between individual lncRNAs with OS. Unsupervised statistical learning was applied to ascertain if lncRNA-based molecular subtypes exist and are prognostic. Results: Thirty-three individual lncRNAs were found to be associated with OS (adjusted p value < 0.05). We established four distinct molecular subtypes based on lncRNA expression using a consensus clustering approach. LncRNA-based subtypes were found to stratify patients into groups with prognostic information (p value < 0.05). Subsequently, lncRNA expression-based subtypes were validated in an independent patient cohort (TCGA-AML). LncRNA subtypes could not be directly explained by any of the recurrent cytogenetic or mutational aberrations, although associations with some of the established genetic and clinical factors were found, including mutations in NPM1, TP53, and FLT3. Conclusion: LncRNA expression-based four subtypes, discovered in this study, are reproducible and can effectively stratify AML patients. LncRNA expression profiling can provide valuable information for improved risk stratification of AML patients.

Subject headings

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Cancer och onkologi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Cancer and Oncology (hsv//eng)
MEDICIN OCH HÄLSOVETENSKAP  -- Medicinska och farmaceutiska grundvetenskaper -- Medicinsk genetik (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Basic Medicine -- Medical Genetics (hsv//eng)
MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Hematologi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Hematology (hsv//eng)

Keyword

lncRNA
Acute myeloid leukemia
Prognosis
Molecular subtype

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