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Comprehensive miRNA sequence analysis reveals survival differences in diffuse large B-cell lymphoma patients.

Lim EL, Trinh DL, Scott DW, Chu A, Krzywinski M, Zhao Y, Robertson AG, Mungall AJ, Schein J, Boyle M, Mottok A, Ennishi D, Johnson NA, Steidl C, Connors JM, Morin RD, Gascoyne RD, Marra MA - Genome Biol. (2015)

Bottom Line: Of these 25 miRNAs, six miRNAs are significantly associated with survival in our validation cohort.Abundant expression of miR-28-5p, miR-214-5p, miR-339-3p, and miR-5586-5p is associated with superior outcome, while abundant expression of miR-324-5p and NOVELM00203M is associated with inferior outcome.Our comprehensive sequence analysis of the DLBCL miRNome identifies candidate novel miRNAs and miRNAs associated with survival, reinforces results from previous mutational analyses, and reveals regulatory networks of significance for lymphomagenesis.

View Article: PubMed Central - PubMed

ABSTRACT

Background: Diffuse large B-cell lymphoma (DLBCL) is an aggressive disease, with 30% to 40% of patients failing to be cured with available primary therapy. microRNAs (miRNAs) are RNA molecules that attenuate expression of their mRNA targets. To characterize the DLBCL miRNome, we sequenced miRNAs from 92 DLBCL and 15 benign centroblast fresh frozen samples and from 140 DLBCL formalin-fixed, paraffin-embedded tissue samples for validation.

Results: We identify known and candidate novel miRNAs, 25 of which are associated with survival independently of cell-of-origin and International Prognostic Index scores, which are established indicators of outcome. Of these 25 miRNAs, six miRNAs are significantly associated with survival in our validation cohort. Abundant expression of miR-28-5p, miR-214-5p, miR-339-3p, and miR-5586-5p is associated with superior outcome, while abundant expression of miR-324-5p and NOVELM00203M is associated with inferior outcome. Comparison of DLBCL miRNA-seq expression profiles with those from other cancer types identifies miRNAs that were more abundant in B-cell contexts. Unsupervised clustering of miRNAs identifies two clusters of patients that have distinct differences in their outcomes. Our integrative miRNA and mRNA expression analyses reveal that miRNAs increased in abundance in DLBCL appear to regulate the expression of genes involved in metabolism, cell cycle, and protein modification. Additionally, these miRNAs, including one candidate novel miRNA, miR-10393-3p, appear to target chromatin modification genes that are frequent targets of somatic mutation in non-Hodgkin lymphomas.

Conclusions: Our comprehensive sequence analysis of the DLBCL miRNome identifies candidate novel miRNAs and miRNAs associated with survival, reinforces results from previous mutational analyses, and reveals regulatory networks of significance for lymphomagenesis.

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Differential expression analysis reveals novel and known miRNAs. Differential expression for each miRNA was calculated using the Wilcoxon ranked-sum test, and P values were multiple-test corrected using the BH algorithm. (a) MA (Log ratio (M) versus mean average (A) expression) plot showing differentially expressed miRNAs comparing DLBCL to centroblasts. (b) MA plot showing miRNA that are differentially expressed between the B-cell data sets (DLBCL and centroblasts) and all other TCGA cancer data sets. In both MA plots, significantly differentially expressed known miRNAs are represented by red dots, while significantly differentially expressed candidate novel miRNAs are represented by green dots. (c) Heatmap of differentially expressed miRNAs between the ABC and GCB DLBCL subtypes. Column labels represent the type of sample: Dark Blue: ABC-DLBCL; Light Blue: GCB-DLBCL; Gray: Unclassified-DLBCL. Row labels indicate if the miRNA is more abundant in a particular category of samples.
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Fig2: Differential expression analysis reveals novel and known miRNAs. Differential expression for each miRNA was calculated using the Wilcoxon ranked-sum test, and P values were multiple-test corrected using the BH algorithm. (a) MA (Log ratio (M) versus mean average (A) expression) plot showing differentially expressed miRNAs comparing DLBCL to centroblasts. (b) MA plot showing miRNA that are differentially expressed between the B-cell data sets (DLBCL and centroblasts) and all other TCGA cancer data sets. In both MA plots, significantly differentially expressed known miRNAs are represented by red dots, while significantly differentially expressed candidate novel miRNAs are represented by green dots. (c) Heatmap of differentially expressed miRNAs between the ABC and GCB DLBCL subtypes. Column labels represent the type of sample: Dark Blue: ABC-DLBCL; Light Blue: GCB-DLBCL; Gray: Unclassified-DLBCL. Row labels indicate if the miRNA is more abundant in a particular category of samples.

Mentions: To obtain a comprehensive list of candidate novel and known miRNAs that are characteristic of DLBCL, we compared the expression of each miRNA in DLBCL samples with those of benign centroblasts obtained from our miRNA-seq data. We noted that 63 miRNAs exhibited increased abundance in DLBCL, while 39 miRNAs exhibited decreased abundance in DLBCL (Wilcoxon test BH q-value <0.05; log2 fold change > 2; Figure 2a). Of the miRNAs with increased abundance in DLBCL, only miR-125b-5p [17] and miR-34-5p [18] have previously been implicated in lymphomagenesis in mouse models.Figure 2


Comprehensive miRNA sequence analysis reveals survival differences in diffuse large B-cell lymphoma patients.

Lim EL, Trinh DL, Scott DW, Chu A, Krzywinski M, Zhao Y, Robertson AG, Mungall AJ, Schein J, Boyle M, Mottok A, Ennishi D, Johnson NA, Steidl C, Connors JM, Morin RD, Gascoyne RD, Marra MA - Genome Biol. (2015)

Differential expression analysis reveals novel and known miRNAs. Differential expression for each miRNA was calculated using the Wilcoxon ranked-sum test, and P values were multiple-test corrected using the BH algorithm. (a) MA (Log ratio (M) versus mean average (A) expression) plot showing differentially expressed miRNAs comparing DLBCL to centroblasts. (b) MA plot showing miRNA that are differentially expressed between the B-cell data sets (DLBCL and centroblasts) and all other TCGA cancer data sets. In both MA plots, significantly differentially expressed known miRNAs are represented by red dots, while significantly differentially expressed candidate novel miRNAs are represented by green dots. (c) Heatmap of differentially expressed miRNAs between the ABC and GCB DLBCL subtypes. Column labels represent the type of sample: Dark Blue: ABC-DLBCL; Light Blue: GCB-DLBCL; Gray: Unclassified-DLBCL. Row labels indicate if the miRNA is more abundant in a particular category of samples.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4308918&req=5

Fig2: Differential expression analysis reveals novel and known miRNAs. Differential expression for each miRNA was calculated using the Wilcoxon ranked-sum test, and P values were multiple-test corrected using the BH algorithm. (a) MA (Log ratio (M) versus mean average (A) expression) plot showing differentially expressed miRNAs comparing DLBCL to centroblasts. (b) MA plot showing miRNA that are differentially expressed between the B-cell data sets (DLBCL and centroblasts) and all other TCGA cancer data sets. In both MA plots, significantly differentially expressed known miRNAs are represented by red dots, while significantly differentially expressed candidate novel miRNAs are represented by green dots. (c) Heatmap of differentially expressed miRNAs between the ABC and GCB DLBCL subtypes. Column labels represent the type of sample: Dark Blue: ABC-DLBCL; Light Blue: GCB-DLBCL; Gray: Unclassified-DLBCL. Row labels indicate if the miRNA is more abundant in a particular category of samples.
Mentions: To obtain a comprehensive list of candidate novel and known miRNAs that are characteristic of DLBCL, we compared the expression of each miRNA in DLBCL samples with those of benign centroblasts obtained from our miRNA-seq data. We noted that 63 miRNAs exhibited increased abundance in DLBCL, while 39 miRNAs exhibited decreased abundance in DLBCL (Wilcoxon test BH q-value <0.05; log2 fold change > 2; Figure 2a). Of the miRNAs with increased abundance in DLBCL, only miR-125b-5p [17] and miR-34-5p [18] have previously been implicated in lymphomagenesis in mouse models.Figure 2

Bottom Line: Of these 25 miRNAs, six miRNAs are significantly associated with survival in our validation cohort.Abundant expression of miR-28-5p, miR-214-5p, miR-339-3p, and miR-5586-5p is associated with superior outcome, while abundant expression of miR-324-5p and NOVELM00203M is associated with inferior outcome.Our comprehensive sequence analysis of the DLBCL miRNome identifies candidate novel miRNAs and miRNAs associated with survival, reinforces results from previous mutational analyses, and reveals regulatory networks of significance for lymphomagenesis.

View Article: PubMed Central - PubMed

ABSTRACT

Background: Diffuse large B-cell lymphoma (DLBCL) is an aggressive disease, with 30% to 40% of patients failing to be cured with available primary therapy. microRNAs (miRNAs) are RNA molecules that attenuate expression of their mRNA targets. To characterize the DLBCL miRNome, we sequenced miRNAs from 92 DLBCL and 15 benign centroblast fresh frozen samples and from 140 DLBCL formalin-fixed, paraffin-embedded tissue samples for validation.

Results: We identify known and candidate novel miRNAs, 25 of which are associated with survival independently of cell-of-origin and International Prognostic Index scores, which are established indicators of outcome. Of these 25 miRNAs, six miRNAs are significantly associated with survival in our validation cohort. Abundant expression of miR-28-5p, miR-214-5p, miR-339-3p, and miR-5586-5p is associated with superior outcome, while abundant expression of miR-324-5p and NOVELM00203M is associated with inferior outcome. Comparison of DLBCL miRNA-seq expression profiles with those from other cancer types identifies miRNAs that were more abundant in B-cell contexts. Unsupervised clustering of miRNAs identifies two clusters of patients that have distinct differences in their outcomes. Our integrative miRNA and mRNA expression analyses reveal that miRNAs increased in abundance in DLBCL appear to regulate the expression of genes involved in metabolism, cell cycle, and protein modification. Additionally, these miRNAs, including one candidate novel miRNA, miR-10393-3p, appear to target chromatin modification genes that are frequent targets of somatic mutation in non-Hodgkin lymphomas.

Conclusions: Our comprehensive sequence analysis of the DLBCL miRNome identifies candidate novel miRNAs and miRNAs associated with survival, reinforces results from previous mutational analyses, and reveals regulatory networks of significance for lymphomagenesis.

Show MeSH
Related in: MedlinePlus