Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Lineage tracing of acute myeloid leukemia reveals the impact of hypomethylating agents on chemoresistance selection

ABSTRACT: Chemotherapy-resistant cancer recurrence is a major cause of mortality. In acute myeloid leukemia (AML), chemorefractory relapses result from the complex interplay between altered genetic, epigenetic and transcriptional states in leukemic cells. We developed an experimental model system using in vitro lineage tracing coupled with exome, transcriptome and in vivo functional readouts to assess the AML population dynamics and associated molecular determinants underpinning chemoresistance development. We found that combining standard chemotherapeutic regimens with low doses of DNA methyltransferase inhibitors (DNMTi, hypomethylating drugs) prevents chemoresistant relapses. Mechanistically, DNMTi suppressed the outgrowth of a pre-determined set of chemoresistant AML clones with stemness properties, instead favoring the expansion of rarer and unfit chemosensitive clones. Importantly, we confirmed the capacity of DNMTi combination to suppress stemness-dependent chemoresistance development in both xenotransplantation models and primary AML patient samples. Together, these results support the potential of DNMTi combination treatment to circumvent the development of chemorefractory AML relapses.

ORGANISM(S): Homo sapiens

PROVIDER: GSE134506 | GEO | 2019/07/19

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Similar Datasets

Small RNA-sequencing of bone marrow samples from acute myeloid leukemia patients chemoresistant (n=27) versus chemosensitive (n=20).

Project description:The aim of our research project is to identify microRNAs involved in chemoresistance in acute myeloid leukemia patients. We performed small RNA-sequencing on baseline bone marrow samples and compared chemoresistant versus chemosensitive patient samples.

2021-02-11 | E-MTAB-8775 | biostudies-arrayexpress

Blast cells surviving acute myeloid leukemia induction therapy are in cycle with a signature of FOXM1 activity

Project description:Disease relapse remains common following treatment of acute myeloid leukemia (AML) and is due to chemoresistance of leukemia cells with disease repopulating potential. To date, attempts to define the characteristics of in vivo resistant blasts have focused on comparisons between leukemic cells at presentation and relapse. However, further treatment responses are often seen following relapse, suggesting that most blasts remain chemosensitive. Here we characterize in vivo chemoresistant blasts by studying the transcriptional and genetic features of blasts from before and after induction chemotherapy using paired samples from 6 patients with primary refractory AML.

2021-10-04 | GSE162542 | GEO

A multi-omics approach to decipher the complexity of drug resistance in diffuse large B-cell lymphoma

Project description:17 samples (7 chemorefractory and 10 chemosensitive) of DLBLC patients were analyzed by Ampliseq whole transcriptome assay (Thermofisher).

2018-03-29 | E-MTAB-6597 | biostudies-arrayexpress

Chemoresistance in acute myeloid leukemia: a single-cell RNA sequencing approach

Project description:Introduction Our previous study demonstrated that myc, mitochondrial oxidative phosphorylation, mTOR, and stemness were independently responsible for chemoresistance in AML. The current study aimed to further identify the potential mechanisms of chemoresistance of the “7+3” induction in AML using a single-cell RNA sequencing (scRNA-seq) approach. Methods Thirteen untreated de novo AML patients were enrolled and stratified into the complete remission (CR) (n = 8) and the non-CR (n = 5) groups. We used scRNA-seq to analyze the genetic profiles of 28950 AML cells from these 13 patients. A previously published bulk RNA-seq dataset validated our results. Results Chemoresistant AML cells had more premature accumulation in early hematopoiesis. The hematopoietic stem cell-like cells from the non-CR group expressed more leukemic stem cell markers (CD9, CD82, IL3RA and, IL1RAP) than those from the CR group. Besides, chemoresistant progenitor cells had impaired myeloid differentiation due to early hematopoiesis arrest. Importantly, the AML cells analyzed by the scRNA-seq and bulk RNA-seq honored comparable myeloid lineage cell fraction, which internally validated our results. Using the TCGA database, our analysis demonstrated that AML patients with a higher expression of chemoresistant genetic markers (IL3RA and IL1RAP had a worse overall survival (p < 0.01 for IL3RA; p < 0.05 for IL1RAP).

2023-03-01 | GSE198681 | GEO

Gene expression patterns of chemoresistant and chemosensitive serous epithelial ovarian tumors with possible predictive value in response to initial chemotherapy

Project description:Chemotherapy (CT) resistance in ovarian cancer is broad and encompasses diverse, unrelated drugs, suggesting more than one mechanism of resistance. We aimed to analyze the gene expression patterns in primary serous epithelial ovarian cancer (EOC) samples displaying different responses to first-line CT in an attempt to identify specific molecular signatures associated with response to CT. Initially, the expression profiles of 15 chemoresistant serous EOC tumors [time to recurrence (TTR) ≤6 months] and 10 chemosensitive serous EOC tumors (TTR ≥30 months) were independently analyzed which allowed the identification of specific sets of differentially expressed genes that might be functionally implicated in the evolution of the chemoresistant or the chemosensitive phenotype. Our data suggest that the intrinsic chemoresistance in serous EOC cells may be attributed to the combined action of different molecular mechanisms and factors linked with drug influx and efflux and cell proliferation, as possible implications of other molecular events including altered metabolism, apoptosis and inflammation cannot be excluded. Next, gene expression comparison using hierarchical clustering clearly distinguished chemosensitive and chemo- resistant tumors from the 25 serous EOC samples (training set), and consecutive class prediction analysis was used to develop a 43-gene classifier that was further validated in an independent cohort of 15 serous EOC patients and 2 patients with other ovarian cancer histotypes (test set). The 43-gene predictor set properly classified serous EOC patients at high risk for early (≤22 months) versus late (>22 months) relapse after initial CT. Thus, gene expression array technology can effectively classify serous EOC tumors according to CT response. The proposed 43-gene model needs further validation. 2 condition experiment: chemoresistant clinical samples versus chemosensitive samples

2011-07-23 | E-GEOD-28739 | biostudies-arrayexpress

Acquired semi-squamalization during chemotherapy suggests a differentiation therapy for bladder cancer

Project description:Cisplatin-based chemotherapy is the most common treatment for unresectable bladder cancers and also increasingly used as neoadjuvant treatments before or after surgery and radiotherapy. Unfortunately, though many patients respond to the treatment, most of them develop resistance quickly with unclear mechanisms and few further treatment options. Here, we report that semi-squamazation is acquired during chemo treatment in both mice and human. Multi-omics analyses show that cathepsin H (CTSH), a direct target of p63, is associated with chemoresistance and semi-squamation. Treatment with the cathepsin inhibitor E64 specifically restrains chemoresistant but not chemosensitive cancer. Mechanistically, cathepsin inhibition induces fully squamous differentiation of bladder cancer cells, which requires TNF receptor 1alpha and is associated with pyroptosis. Our study suggests that semi-squamazation would be a diagnosistic marker for chemoresistance and differentiation therapy by targeting CTSH might be a potential treatment for chemoresistant bladder cancer.

2022-07-09 | GSE192575 | GEO

Homo sapiens

Project description:Transcriptomic comparison of chemosensitive and chemoresistant cells

| PRJNA131103 | ENA

Genome-wide profiling of long noncoding RNA expression patterns in chemoresistant breast cancer cells

Project description:Long non-coding RNAs (lncRNAs) are involved in cancer progression. In this study, the lncRNA profiling were analyzed in chemoresistant and sensitive breast cancer cells. We found a group of dysregulated lncRNAs in chemoresistant cells. Expression of dysregulated lncRNAs are correlated with dysregulated mRNAs, and enriched in GO and KEGG pathways related with cancer progression and chemoresistance development. Within those lncRNA-mRNA interactions, some lncRNAs may cis-regulate neighboring protein coding genes and involved in chemoresistance. The lncRNA NONHSAT028712 was then validated to regulate nearby CDK2 and interfere with cell cycle and chemoresistance. Furthermore, we identified another group of lncRNAs trans-regulated gene expression via interacting with different transcription factors (TF). Whereby NONHSAT057282 and NONHSAG023333 was found to modulate chemoresistance and most likely interacted with ELF1 and E2F1 respectively. In conclusion, this study reported for the first time the lncRNA expression patterns in chemoresistant breast cancer cells, and provided a group of novel lncRNA targets in mediating chemoresistance development in both cis- and trans- action mode. MCF-7/ADM replication 3 times, MCF-7/WT replication 3 times

2016-05-28 | E-GEOD-81971 | biostudies-arrayexpress

miR-197-3p promotes osteosarcoma stemness and chemo-resistance by inhibiting SPOPL

Project description:First-line treatment for osteosarcoma includes chemotherapy and surgery. However, the five-year survival rate of refractory osteosarcoma remains unsatisfactory. Osteosarcoma cancer stem cells, possessing stemness and chemoresistance, are one of the critical causes for poor response to chemotherapy. Elucidating regulatory signaling pathways of osteosarcoma cancer stem cells may provide a rationale for improving regimens against chemoresistant osteosarcoma. Methotrexate (MTX)-resistant osteosarcoma cells were established. microRNA expression profiles were used for detecting differentially expressed microRNA in resistant clones and the parental cells. microRNA target databases were employed to predict potential microRNA and mRNA interaction. Flow cytometry was performed to measure stem cell marker Prominin-1 (CD133) positive cells. Im-munofluorescence staining was applied to detect CD133 expression. miR-197-3p mimic or an-ti-miR-197-3p stably transfected cells were used to generate xenograft models. In the study, we found miR-197-3p was increased in MTX-resistant cell lines. Overexpression of miR-197-3p en-hanced the expression of cancer stem cell markers CD133, Octamer-binding protein 4 (OCT4), Transcription factor SOX-2 (SOX2), and Homeobox protein NANOG (NANOG), as well as chemoresistance-associated genes ATP-dependent translocase ABCB1 (ABCB1) and Broad substrate specificity ATP-binding cassette transporter ABCG2 (ABCG2), whereas miR-197-3p knockdown inhibited stemness and recovered sensitivity to MTX. We also classified the tumor suppressor Speckle-type POZ protein-like (SPOPL) as a target of miR-197-3p. The miR-197-3p mutation that cannot combine SPOPL promoter regions was unable to sustain stemness or chemoresistance. Collectively, we discovered miR-197-3p conferred osteosarcoma stemness and chemotherapy resistance by targeting SPOPL, prompting promising therapeutic candidates for refractory oste-osarcoma treatment. miRNA qPCR assay

2023-01-31 | GSE223857 | GEO

Gene expression patterns of chemoresistant and chemosensitive serous epithelial ovarian tumors with possible predictive value in response to initial chemotherapy

2011-07-24 | GSE28739 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data