Integrating genomic alterations in diffuse large B-cell lymphoma identifies new relevant pathways and potential therapeutic targets

Abstract

Genome studies of diffuse large B-cell lymphoma (DLBCL) have revealed a large number of somatic mutations and structural alterations. However, the clinical significance of these alterations is still not well defined. In this study, we have integrated the analysis of targeted next-generation sequencing of 106 genes and genomic copy number alterations (CNA) in 150 DLBCL. The clinically significant findings were validated in an independent cohort of 111 patients. Germinal center B-cell and activated B-cell DLBCL had a differential profile of mutations, altered pathogenic pathways and CNA. Mutations in genes of the NOTCH pathway and tumor suppressor genes (TP53/CDKN2A), but not individual genes, conferred an unfavorable prognosis, confirmed in the independent validation cohort. A gene expression profiling analysis showed that tumors with NOTCH pathway mutations had a significant modulation of downstream target genes, emphasizing the relevance of this pathway in DLBCL. An in silico drug discovery analysis recognized 69 (46%) cases carrying at least one genomic alteration considered a potential target of drug response according to early clinical trials or preclinical assays in DLBCL or other lymphomas. In conclusion, this study identifies relevant pathways and mutated genes in DLBCL and recognizes potential targets for new intervention strategies.

Figure 1

Recurrent mutated genes and pathways in 150 DLBCLs patients. (a) Bar-graphs show mutated genes in more than 5% of DLBCL patients and frequently mutated pathways. Each color bar indicates biological subtypes; GCB: germinal center B-cell type, ABC: activated B-cell type, UC: unclassified, ND/NE: not done or not evaluable. An asterisk represents mutated genes/pathways significantly enriched in one of the subtypes of COO and asterisk color denotes the enriched group. Tumor suppressor genes include mutations and deletions in TP53 and CDKN2A, respectively. (#) (b) Heat maps show the distribution of MYD88 and TP53 mutated patients in both DLBCL subtypes. TP53 mutations are divided into truncating and missense mutations located on the DNA binding domains (DBD) and ‘others’. Columns depict individual cases and rows mutated genes/mutation type. (c, d) Heat maps representing relationships among mutated genes in B-cell receptor (BCR)/Toll-like receptor signaling, Epigenome/Chromatin Modifier and NOTCH pathways. Graph-bars above show the total number of mutated cases for each gene. One black asterisk represents significant mutated gene concurrence and two asterisks significant exclusion. Significant P-values corrected by false discovery rate (FDR) are showed. (e) Gene-set enrichment analysis (GSEA) of NOTCH pathway mutated cases vs cases with no mutations in genes of this pathway. (f) Box plots show HES1 mRNA expression levels in NOTCH pathway mutated cases and cases with no mutations in this pathway.

Figure 2

Copy number alterations (CNA) in 119 DLBCLs patients and integration with other genetic alterations. (a) Frequency of CNA of 119 DLBCL patients analyzed by Cytoscan HD assay. Each probe is aligned from chromosome 1 to 22 and p to q. Chromosomes X and Y were excluded from the analysis because sex-matched reference DNA samples were not used. The vertical axis indicates frequency of the genomic aberration among the analyzed cases. Gains are depicted in dark blue and losses are depicted in red. Genes affected by copy number alterations and not previously described in DLBCL are indicated. (b) Significant patterns of CNAs between DLBCL subtypes are depicted: ABC (light blue boxes) and GCB (orange boxes). The X-axis shows P-value among these two groups and significant threshold is marked with a green line. (c) Bar-graph represents frequency of mutations and CNAs for each gene in 119 DLBCL cases, determined by targeted NGS (CDKN2A by Sanger sequencing) and copy number analysis. Gene alterations are divided into four groups: Mutations (single-nucleotide mutations and/or small indels), homozygous deletion, loss (loss of one allele) and bialleic inactivation (Loss+mutation or CNN-LOH+mutation).

Figure 3

Forest plots of OS and PFS of gene alterations and pathways in the initial series. Gene alterations herein shown correspond to those with significant impact on overall (OS) or progression-free survival (PFS) in the statistical analysis before correction for multiple comparisons, as well as those drivers included in any of the three significant pathways. The P-values shown were corrected for multiple comparisons (Benjamini–Hochberg method). *indicates gene and pathway mutations that had prognostic value independent of the IPI and COO of the tumor in the multivariate analysis.

Figure 4

PFS and OS according to alterations in NOTCH and JAK-STAT pathways and TP53/CDKN2A (4A and 4B are for the initial and the validation series, respectively).

Figure 5

Genomic-guided therapeutic opportunities of the DLBCL cohort. Therapeutic opportunities have been classified according to the level of evidence supporting the effect of the genomic biomarker into (i) clinical guidelines (for example, FDA-approved or NCNN recommendations), (ii) late (phases III–IV) or (iii) early (phases I–II) clinical trials, (iv) case reports or (v) preclinical data. In addition to the alterations described as biomarkers of drug response in DLBCL (biomarker and tumor match), we included driver mutations in genes described as biomarkers of drug response in DLBCL upon a different amino acid change (biomarker match of different gene mutation), as well as genomic alterations described as biomarkers of drug response in other tumor types (biomarker match and tumor repurposing). (a) This panel depicts the therapeutic opportunities per patient (each patient has been counted only once according to their best therapeutic option following the above classification). (b) This panel depicts the therapeutic opportunities per gene; the numbers on top of the bars correspond to the number of patients exhibiting a biomarker of drug response in that gene (each patient has been counted only once according to their best therapeutic option given the gene alteration). Biomarkers that have been described for DLBCL and other non-Hodgkin lymphomas were also considered in the tumor match category. (c) Finally, this panel depicts the contribution of each alteration type to the overall number of in silico prescriptions per patient and altered gene.