Project description:In AML, most patients are initiated on standard chemotherapy and afterwards assigned to a post-remission strategy based on genetically-defined risk categories. However, outcomes remain heterogeneous, indicating the need for novel biomarker tests that can rapidly and accurately identify high-risk patients, allowing better stratification of both induction and post-remission therapy. As patient outcomes are linked to leukemia stem cell (LSC) properties that confer therapy resistance and drive relapse, LSC-based biomarkers may be highly informative. We tested 227 CD34/CD38 cell fractions from 78 AML patients for LSC activity in xenotransplantation assays. Comparison of microarray-based gene expression (GE) profiles between 138 LSC+ and 89 LSC? fractions identified 104 differentially-expressed LSC-specific genes. To obtain prognostic signatures, we performed statistical regression analysis of LSC GE against patient outcome using a training cohort of 495 AML patients treated with curative intent. A score calculated as the weighted sum of expression of 17 LSC signature genes (LSC17) was strongly associated with survival in 4 independent datasets (716 AML cases) spanning all risk categories in multi-variate analysis; an optimized 3-gene sub-score (LSC3) was prognostic in favorable risk subsets. These scores were robust across GE technology platforms, including the clinically serviceable NanoString system (LSC17: HR=2.73, P<0.0001; LSC3: HR=6.3, P<0.02). The LSC17 and LSC3 scores provide rapid and accurate identification of high-risk patients for whom conventional chemotherapy is non-curative. These scores will enable evaluation in clinical trials of whether such patients may benefit from novel and/or more intensified therapies during induction or in the post-remission setting.
Project description:In AML, most patients are initiated on standard chemotherapy and afterwards assigned to a post-remission strategy based on genetically-defined risk categories. However, outcomes remain heterogeneous, indicating the need for novel biomarker tests that can rapidly and accurately identify high-risk patients, allowing better stratification of both induction and post-remission therapy. As patient outcomes are linked to leukemia stem cell (LSC) properties that confer therapy resistance and drive relapse, LSC-based biomarkers may be highly informative. We tested 227 CD34/CD38 cell fractions from 78 AML patients for LSC activity in xenotransplantation assays. Comparison of microarray-based gene expression (GE) profiles between 138 LSC+ and 89 LSC? fractions identified 104 differentially-expressed LSC-specific genes. To obtain prognostic signatures, we performed statistical regression analysis of LSC GE against patient outcome using a training cohort of 495 AML patients treated with curative intent. A score calculated as the weighted sum of expression of 17 LSC signature genes (LSC17) was strongly associated with survival in 4 independent datasets (716 AML cases) spanning all risk categories in multi-variate analysis; an optimized 3-gene sub-score (LSC3) was prognostic in favorable risk subsets. These scores were robust across GE technology platforms, including the clinically serviceable NanoString system (LSC17: HR=2.73, P<0.0001; LSC3: HR=6.3, P<0.02). The LSC17 and LSC3 scores provide rapid and accurate identification of high-risk patients for whom conventional chemotherapy is non-curative. These scores will enable evaluation in clinical trials of whether such patients may benefit from novel and/or more intensified therapies during induction or in the post-remission setting.
Project description:The leukemic stem cell score 17 (LSC-17) based on stemness gene expression signature is recognized as indicator of poor disease outcome in acute myeloid leukemia (AML). However, our understanding of the relationships between LSC and pre-leukemic cells is still incomplete. In particular, it is not known whether “niche-anchoring” of pre-leukemic cell affects disease evolution. To address this issue, we conditionally inactivated the adhesion molecule Jam-C expressed by haematopoietic stem cells (HSC) and LSC in an inducible iMLL-AF9-driven AML mouse model. Deletion of Jam-C in HSC before activation of the leukemia-initiating iMLL-AF9 fusion resulted in a shift from long term (LT-HSC) to short term-HSC (ST-HSC) expansion, suggesting that transcriptional programs of leukemic HSC were altered. RNA sequencing performed on leukemic HSC and GMP isolated from diseased mice revealed that genes upregulated in Jam-C-deficient animals belonged to Activation Protein-1 (AP-1) and TNF-/NFB signalling pathways. Using three publicly available datasets of AML gene expression, we further showed that human orthologs of dysregulated genes belonged to a gene regulon distinct from the LSC-17 signature. A prognosis 14-genes score from the AP-1/TNF-/NFB gene expression signature was established and called ATIC for “AP-1/TNF- initiating cell”. ATIC was independent of the LSC-17 score and improved the stratification of AML patients obtained with the LSC-17 score suggesting that the ATIC score reflected the presence of ST-HSC-initiating AML cells at diagnosis. Collectively we provide a novel tool for understanding AML disease heterogeneity through the identification of specific transcriptional programs for leukemic stem and progenitor cells.
Project description:This study explored resistance functions and their interactions in de novo AML treated with the "7 + 3" induction regimen. We analyzed RNA-sequencing profiles of whole bone marrow samples from 52 de novo AML patients who completed the "7 + 3" regimen and stratified patients into CR (n = 35) and non-CR (n = 17) groups. A systematic gene set analysis revealed significant associations between chemoresistance and mTOR (P < .001), myc (P < .001), mitochondrial oxidative phosphorylation (P < .001), and stemness (P = .002). These functions were independent with regard to gene contents and activity scores. An integration of these four functions showed a prediction of chemoresistance (area under the receiver operating characteristic curve = 0.815) superior to that of each function alone. Moreover, our proposed seven-gene scoring system significantly correlated with the four-function model (r = .97; P < .001) to predict chemoresistance to the "7 + 3" regimen. On multivariate analysis, a seven-gene score of ≥-0.027 (hazard ratio: 11.18; 95% confidence interval: 2.06-60.65; P = .005) was an independent risk factor for induction failure. In summary, Myc, OXPHOS, mTOR, and stemness were responsive for chemoresistance in AML. Treatments other than the "7 + 3" regimen need to be considered for de novo AML patients predicted to be refractory to the "7 + 3" regimen.
Project description:Acute myeloid leukemia (AML) is a hematopoietic malignancy with poor prognosis and limited treatment options. Here we provide a comprehensive census of the bone marrow immune microenvironment in adult and pediatric AML patients. We characterize unique inflammation signatures in a subset of AML patients, associated with inferior outcomes. We identify atypical B cells, a dysfunctional B cell subtype enriched in high-inflammation AML patients, as well as an increase in CD8+ GZMK+ and regulatory T cells, accompanied by a reduction in T cell clonal expansion. We derive an inflammation-associated gene score (iScore) that associates with poor survival outcomes in AML patients. Addition of the iScore refines current risk stratifications for AML patients and may enable identification of patients in need of more aggressive treatment. This work provides a framework for classifying AML patients based on their immune microenvironment and a rationale for consideration of the inflammatory state in clinical settings.
Project description:Acute myeloid leukemia (AML) is a hematopoietic malignancy with poor prognosis and limited treatment options. We characterize unique inflammation signatures in a subset of AML patients, and derive an inflammation-associated gene score (iScore) that associates with poor survival outcomes in AML patients. The addition of the iScore refines current risk stratifications for AML patients and may enable the identification of patients in need of more aggressive treatment. This work provides a framework for classifying AML patients based on their immune microenvironment and a rationale for consideration of the inflammatory state in clinical settings. This submission represents the adult RNA-Seq component of study.
Project description:We have previously shown that expression levels of 48 long non-coding RNAs (lncRNAs) can generate a prognostic lncRNA score that independently associates with outcome of older patients (aged ≥ 60 years) with cytogenetically normal acute myeloid leukemia (CN-AML). However, the techniques that were used to identify and measure prognostic lncRNAs are not tailored for real-life clinical testing. Herein we report on an assay (based on the nCounter platform), which is designed to produce targeted measurements of prognostic lncRNAs in a clinically friendly manner. We analyzed an independent cohort of 76 older CN-AML patients and found that the nCounter assay yielded reproducible measurements and that the lncRNA score retained its prognostic value; patients with favorable lncRNA scores were more likely to achieve a complete remission (CR, P=0.009) and have longer diseased-free (DFS, P=0.05), overall (OS, P=0.02) and event-free survival (EFS, P=0.002) than patients with unfavorable lncRNA scores. In multivariable analyses, lncRNA score status independently associated with CR rates (P=0.02), as well as OS (P=0.02) and EFS (P=0.02) duration. To gain biological insights, we examined a dataset of older CN-AML patients, previously analyzed with RNA sequencing. We found genes involved in immune response and B cell receptor signaling (for which targeted inhibitors are currently available) to be enriched in patients with unfavorable lncRNA scores. We conclude that clinically applicable lncRNA profiling is feasible and potentially useful for risk stratification of older CN-AML patients. In addition we identify potentially targetable molecular pathways that are active in the high-risk patients with unfavorable lncRNA scores.
Project description:Background: The relationships between cancer stem cells (CSCs), epithelial-to-mesenchymal transition (EMT), and the tumor microenvironment (TME) in bladder urothelial carcinoma (BLCA) remain unclear. Methods: We first constructed tumor stemness (TS) score using principal component analysis to quantify tumor stemness in BLCA. Then, we evaluated the clinical value of the TS score for predicting the response to tumor immunotherapy using immunotherapy cohorts. Finally, we built an EMT cell model by treating T24 cells with TGF-β and validated the relationship between the TS score and the EMT process in tumors by real-time quantitative PCR, cell invasion assays, and RNA-seq. Results: A TS scoring system was established with 61 TS-related genes to quantify the TS. The prognostic value of the TS score was then confirmed in multiple independent cohorts. A high TS score was associated with high EMT activity, CSC characteristics, high stromal cell content, high TP53 mutation rate, poor prognosis, and high tumor immunotherapy tolerance. Conclusion: The TS score provides an index for EMT and CSC research and helps clinicians develop treatment plans and predict outcomes for patients.