Project description:The survival of patients with diffuse large-B-cell lymphoma after chemotherapy is influenced by molecular features of the tumors. We used the gene-expression profiles of these lymphomas to develop a molecular predictor of survival. METHODS: Biopsy samples of diffuse large-B-cell lymphoma from 240 patients were examined for gene expression with the use of DNA microarrays and analyzed for genomic abnormalities. Subgroups with distinctive gene-expression profiles were defined on the basis of hierarchical clustering. A molecular predictor of risk was constructed with the use of genes with expression patterns that were associated with survival in a preliminary group of 160 patients and was then tested in a validation group of 80 patients. The accuracy of this predictor was compared with that of the international prognostic index. RESULTS: Three gene-expression subgroups--germinal-center B-cell-like, activated B-cell-like, and type 3 diffuse large-B-cell lymphoma--were identified. Two common oncogenic events in diffuse large-B-cell lymphoma, bcl-2 translocation and c-rel amplification, were detected only in the germinal-center B-cell-like subgroup. Patients in this subgroup had the highest five-year survival rate. To identify other molecular determinants of outcome, we searched for individual genes with expression patterns that correlated with survival in the preliminary group of patients. Most of these genes fell within four gene-expression signatures characteristic of germinal-center B cells, proliferating cells, reactive stromal and immune cells in the lymph node, or major-histocompatibility-complex class II complex. We used 17 genes to construct a predictor of overall survival after chemotherapy. This gene-based predictor and the international prognostic index were independent prognostic indicators.
Project description:Trabectedin is a DNA-damaging agent with a peculiar mechanism of action; it traps the DNA repair machinery leading to DNA single- and double-strand breaks, particularly in BRCA1/2-deficient tumors. We hypothesized that trabectedin-induced DNA damage might activate PARP1 (a DNA-repair machinery key player), and consequently, PARP1 inhibition would perpetuate trabectedin-induced DNA damage. In several tumor histotypes, we demonstrated a different degree of synergism between trabectedin and PARP1 inhibitors (PARP1-Is). Independent of BRCA1/2 status, PARP1 expression dictated the degree of synergism. Namely, silenced PARP1 reduced trabectedin-PARP1-Is synergism, whereas overexpressed PARP1 increased combination efficacy. High-PARP1 expression and specific gene signatures associated with DNA damage response and repair (DDR-R) were predictive of trabectedin+PARP1-I synergy. These findings pave the way for the clinical development of this novel combination therapy, as well as evaluation of PARP1 expression and DDR-R signatures in tumor samples as predictive biomarkers of response
Project description:Trabectedin is a DNA-damaging agent with a peculiar mechanism of action; it traps the DNA repair machinery leading to DNA single- and double-strand breaks, particularly in BRCA1/2-deficient tumors. We hypothesized that trabectedin-induced DNA damage might activate PARP1 (a DNA-repair machinery key player), and consequently, PARP1 inhibition would perpetuate trabectedin-induced DNA damage. In several tumor histotypes, we demonstrated a different degree of synergism between trabectedin and PARP1 inhibitors (PARP1-Is). Independent of BRCA1/2 status, PARP1 expression dictated the degree of synergism. Namely, silenced PARP1 reduced trabectedin-PARP1-Is synergism, whereas overexpressed PARP1 increased combination efficacy. High-PARP1 expression and specific gene signatures associated with DNA damage response and repair (DDR-R) were predictive of trabectedin+PARP1-I synergy. These findings pave the way for the clinical development of this novel combination therapy, as well as evaluation of PARP1 expression and DDR-R signatures in tumor samples as predictive biomarkers of response.
Project description:Diffuse large B-cell lymphoma (DLBCL), the most common lymphoid malignancy in adults, is curable in less than 50% of patients. Prognostic models based on pre-treatment characteristics, such as the International Prognostic Index (IPI), are currently used to predict outcome in DLBCL. However, clinical outcome models identify neither the molecular basis of clinical heterogeneity, nor specific therapeutic targets. We analyzed the expression of 6,817 genes in diagnostic tumor specimens from DLBCL patients who received cyclophosphamide, adriamycin, vincristine and prednisone (CHOP)-based chemotherapy, and applied a supervised learning prediction method to identify cured versus fatal or refractory disease. The algorithm classified two categories of patients with very different five-year overall survival rates (70% versus 12%). The model also effectively delineated patients within specific IPI risk categories who were likely to be cured or to die of their disease. Genes implicated in DLBCL outcome included some that regulate responses to B-cell-receptor signaling, critical serine/threonine phosphorylation pathways and apoptosis. Our data indicate that supervised learning classification techniques can predict outcome in DLBCL and identify rational targets for intervention. golub-00095 Assay Type: Gene Expression Provider: Affymetrix Array Designs: Hu6800 Organism: Homo sapiens (ncbitax) Tissue Sites: Lymphoid tissue Material Types: synthetic_DNA, synthetic_RNA, organism_part Cell Types: B-Lymphocyte Disease States: Diffuse large B-cell Lymphoma, Follicular Lymphoma
Project description:Most genotoxic anticancer agents fail in tumors with intact DNA repair. Therefore, trabectedin, a unique agent more toxic to cells with active DNA repair, specifically transcription-coupled nucleotide excision repair (TC-NER), provides new therapeutic opportunities. To unlock the potential of trabectedin and inform its application in precision oncology, a full mechanistic understanding of the drug’s TC-NER-dependent toxicity is needed. Here, we determined that abortive TC-NER of trabectedin-DNA adducts forms persistent single-strand breaks (SSBs) by blocking the second of the two sequential NER incisions by XPG. We mapped the 3’-hydroxyl groups of SSBs originating from the first NER incision at trabectedin lesions, recording TC-NER on a genome-wide scale. We showed that trabectedin-induced SSBs primarily occur in transcribed strands of active genes and peak near transcription start sites. Frequent SSBs were also found outside gene bodies, revealing TC-NER connection to divergent transcription from promoters. This work advances trabectedin as a tool compound for precision oncology and for studying TC-NER and transcription.
Project description:Desmoplastic small round cell tumor (DSRCT) is a rare and incurable malignancy characterized by the oncogenic EWSR1-WT1 transcription factor. This study exploited a novel DSRCT patient-derived xenograft (PDX), which reproduces histomorphological and molecular characteristics of the paired clinical tumor, to comparatively assess the activity of cytotoxic and targeted anticancer agents. Anti-tumor effect was moderate for single-agent doxorubicin, pazopanib and larotrectenib [maximum tumor volume inhibition (max TVI): 55-66%] while trabectedin had a higher effect (max TVI: 82%). Single-agent vinorelbine, irinotecan and eribulin achieved a nearly complete tumor growth inhibition (max TVI: 96-98%), although tumors started to re-growth after the end of treatment. Combination of irinotecan with either eribulin or trabectedin resulted in complete responses which were maintained until the end of the experiment for irinotecan plus trabectedin. Irinotecan-based combinations almost completely abrogated the expression of proteins involved in the G2/M checkpoint preventing cell entrance in mitosis and induced apoptotic and necroptotic cell death. This study emphasizes the importance of patient-derived pre-clinical models to explore new treatments in DSRCT and fosters clinical investigation in the activity of irinotecan plus trabectedin.
Project description:Desmoplastic small round cell tumor (DSRCT) is a rare and incurable malignancy characterized by the oncogenic EWSR1-WT1 transcription factor. This study exploited a novel DSRCT patient-derived xenograft (PDX), which reproduces histomorphological and molecular characteristics of the paired clinical tumor, to comparatively assess the activity of cytotoxic and targeted anticancer agents. Anti-tumor effect was moderate for single-agent doxorubicin, pazopanib and larotrectenib [maximum tumor volume inhibition (max TVI): 55-66%] while trabectedin had a higher effect (max TVI: 82%). Single-agent vinorelbine, irinotecan and eribulin achieved a nearly complete tumor growth inhibition (max TVI: 96-98%), although tumors started to re-growth after the end of treatment. Combination of irinotecan with either eribulin or trabectedin resulted in complete responses which were maintained until the end of the experiment for irinotecan plus trabectedin. Irinotecan-based combinations almost completely abrogated the expression of proteins involved in the G2/M checkpoint preventing cell entrance in mitosis and induced apoptotic and necroptotic cell death. This study emphasizes the importance of patient-derived pre-clinical models to explore new treatments in DSRCT and fosters clinical investigation in the activity of irinotecan plus trabectedin.
Project description:Gene expression profiling of DLBCL patient samples was performed to investigate, whether molecular gene expression signatures retain their prognostic significance in patients treated with chemotherapy plus Rituximab. The lymphnode, germinal center signature and a new angiogenesis signature were combined to a final multivariate model which defined quartile groups among Rituximab-CHOP-treated patients with distinct 3-year overall survival rates. Keywords: clinical history design
Project description:Diffuse large B-cell lymphoma (DLBCL), the most common lymphoid malignancy in adults, is curable in less than 50% of patients. Prognostic models based on pre-treatment characteristics, such as the International Prognostic Index (IPI), are currently used to predict outcome in DLBCL. However, clinical outcome models identify neither the molecular basis of clinical heterogeneity, nor specific therapeutic targets. We analyzed the expression of 6,817 genes in diagnostic tumor specimens from DLBCL patients who received cyclophosphamide, adriamycin, vincristine and prednisone (CHOP)-based chemotherapy, and applied a supervised learning prediction method to identify cured versus fatal or refractory disease. The algorithm classified two categories of patients with very different five-year overall survival rates (70% versus 12%). The model also effectively delineated patients within specific IPI risk categories who were likely to be cured or to die of their disease. Genes implicated in DLBCL outcome included some that regulate responses to B-cell-receptor signaling, critical serine/threonine phosphorylation pathways and apoptosis. Our data indicate that supervised learning classification techniques can predict outcome in DLBCL and identify rational targets for intervention.