603 research outputs found
Circulating tumor DNA in early-stage breast cancer : personalized biomarkers for occult metastatic disease and risk of relapse?
No full textThe availability of blood-based markers topredict response of a solid tumor to treatment, estimate patient prognosis and diagnose relapse well before clinical symptoms arise, is a long-standing hope in clinical oncology. Ideally, assays designed to provide such information should be inexpensive (at least in the foreseeable future), simple, and, of course, predictive of the clinical evolution of the disease. While early research focused on circulating glycosylated tumor-derived protein biomarkers, the focus is now rapidly shifting to new opportunities, such as circulating tumor cells, extracellular vesicles, micro-RNAs and cancer-derived cell-free DNA a.k.a. circulating tumor-derived DNA (ctDNA).Non peer reviewe
Drug sensitivity and resistance testing identifies PLK1 inhibitors and gemcitabine as potent drugs for malignant peripheral nerve sheath tumors
No full textPatients with malignant peripheral nerve sheath tumor (MPNST), a rare soft tissue cancer associated with loss of the tumor suppressor neurofibromin (NF1), have poor prognosis and typically respond poorly to adjuvant therapy. We evaluated the effect of 299 clinical and investigational compounds on seven MPNST cell lines, two primary cultures of human Schwann cells, and five normal bone marrow aspirates, to identify potent drugs for MPNST treatment with few side effects. Top hits included Polo-like kinase 1 (PLK1) inhibitors (volasertib and BI2536) and the fluoronucleoside gemcitabine, which were validated in orthogonal assays measuring viability, cytotoxicity, and apoptosis. DNA copy number, gene expression, and protein expression were determined for the cell lines to assess pharmacogenomic relationships. MPNST cells were more sensitive to BI2536 and gemcitabine compared to a reference set of 94 cancer cell lines. PLK1, RRM1, and RRM2 mRNA levels were increased in MPNST compared to benign neurofibroma tissue, and the protein level of PLK1 was increased in the MPNST cell lines compared to normal Schwann cells, indicating an increased dependence on these drug targets in malignant cells. Furthermore, we observed an association between increased mRNA expression of PLK1, RRM1, and RRM2 in patient samples and worse disease outcome, suggesting a selective benefit from inhibition of these genes in the most aggressive tumors.Peer reviewe
The impact of RNA sequence library construction protocols on transcriptomic profiling of leukemia
No full textAbstract
Background
RNA sequencing (RNA-seq) has become an indispensable tool to identify disease associated transcriptional profiles and determine the molecular underpinnings of diseases. However, the broad adaptation of the methodology into the clinic is still hampered by inconsistent results from different RNA-seq protocols and involves further evaluation of its analytical reliability using patient samples. Here, we applied two commonly used RNA-seq library preparation protocols to samples from acute leukemia patients to understand how poly-A-tailed mRNA selection (PA) and ribo-depletion (RD) based RNA-seq library preparation protocols affect gene fusion detection, variant calling, and gene expression profiling.
Results
Overall, the protocols produced similar results with consistent outcomes. Nevertheless, the PA protocol was more efficient in quantifying expression of leukemia marker genes and showed better performance in the expression-based classification of leukemia. Independent qRT-PCR experiments verified that the PA protocol better represented total RNA compared to the RD protocol. In contrast, the RD protocol detected a higher number of non-coding RNA features and had better alignment efficiency. The RD protocol also recovered more known fusion-gene events, although variability was seen in fusion gene predictions.
Conclusion
The overall findings provide a framework for the use of RNA-seq in a precision medicine setting with limited number of samples and suggest that selection of the library preparation protocol should be based on the objectives of the analysis
Impact of normalization methods on high-throughput screening data with high hit rates and drug testing with dose-response data
No full textPeer reviewe
Systematic drug screening reveals specific vulnerabilities and co-resistance patterns in endocrine-resistant breast cancer
No full textAbstract
Background
The estrogen receptor (ER) inhibitor tamoxifen reduces breast cancer mortality by 31 % and has served as the standard treatment for ER-positive breast cancers for decades. However, 50 % of advanced ER-positive cancers display de novo resistance to tamoxifen, and acquired resistance evolves in 40 % of patients who initially respond. Mechanisms underlying resistance development remain poorly understood and new therapeutic opportunities are urgently needed. Here, we report the generation and characterization of seven tamoxifen-resistant breast cancer cell lines from four parental strains.
Methods
Using high throughput drug sensitivity and resistance testing (DSRT) with 279 approved and investigational oncology drugs, exome-sequencing and network analysis, we for the first time, systematically determine the drug response profiles specific to tamoxifen resistance.
Results
We discovered emerging vulnerabilities towards specific drugs, such as ERK1/2-, proteasome- and BCL-family inhibitors as the cells became tamoxifen-resistant. Co-resistance to other drugs such as the survivin inhibitor YM155 and the chemotherapeutic agent paclitaxel also occurred.
Conclusion
This study indicates that multiple molecular mechanisms dictate endocrine resistance, resulting in unexpected vulnerabilities to initially ineffective drugs, as well as in emerging co-resistances. Thus, combatting drug-resistant tumors will require patient-tailored strategies in order to identify new drug vulnerabilities, and to understand the associated co-resistance patterns
Prediction model for drug response of acute myeloid leukemia patients
No full textAbstract Despite some encouraging successes, predicting the therapy response of acute myeloid leukemia (AML) patients remains highly challenging due to tumor heterogeneity. Here we aim to develop and validate MDREAM, a robust ensemble-based prediction model for drug response in AML based on an integration of omics data, including mutations and gene expression, and large-scale drug testing. Briefly, MDREAM is first trained in the BeatAML cohort (n = 278), and then validated in the BeatAML (n = 183) and two external cohorts, including a Swedish AML cohort (n = 45) and a relapsed/refractory acute leukemia cohort (n = 12). The final prediction is based on 122 ensemble models, each corresponding to a drug. A confidence score metric is used to convey the uncertainty of predictions; among predictions with a confidence score >0.75, the validated proportion of good responders is 77%. The Spearman correlations between the predicted and the observed drug response are 0.68 (95% CI: [0.64, 0.68]) in the BeatAML validation set, –0.49 (95% CI: [–0.53, –0.44]) in the Swedish cohort and 0.59 (95% CI: [0.51, 0.67]) in the relapsed/refractory cohort. A web-based implementation of MDREAM is publicly available at https://www.meb.ki.se/shiny/truvu/MDREAM/
A method for finding putative causes of gene expression variation
No full textThe majority of microarray studies evaluate gene ex- pression differences between various specimens or con- ditions. However, the causes of this variability often re- main unknown. Our aim is to identify underlying causes of these patterns, a process that would eventually enable a mechanistic understanding of the deregulation of gene expression in cancer. The procedure consists of three phases: pre-processing, data integration and statistical analysis. We have applied the strategy to identify genes that are overexpressed due to amplification in breast cancer. The data were obtained from 14 breast cancer cell lines, which were subjected to cDNA microarray based copy number and expression experiments. The re- sult of the analysis was a list that consisted of 92 genes. This set includes several genes that are known to be both overexpressed and amplified in breast cancer. The com- plete study was published in Journal of the Franklin In- stitute 2004, and in this paper we focus on the main issues of the study
The E-cadherin/AmotL2 complex organizes actin filaments required for epithelial hexagonal packing and blastocyst hatching
No full textEpithelial cells connect via cell-cell junctions to form sheets of cells with separate cellular compartments. These cellular connections are essential for the generation of cellular forms and shapes consistent with organ function. Tissue modulation is dependent on the fine-tuning of mechanical forces that are transmitted in part through the actin connection to E-cadherin as well as other components in the adherens junctions. In this report we show that p100 amotL2 forms a complex with E-cadherin that associates with radial actin filaments connecting cells over multiple layers. Genetic inactivation or depletion of amotL2 in epithelial cells in vitro or zebrafish and mouse in vivo, resulted in the loss of contractile actin filaments and perturbed epithelial packing geometry. We further showed that AMOTL2 mRNA and protein was expressed in the trophectoderm of human and mouse blastocysts. Genetic inactivation of amotL2 did not affect cellular differentiation but blocked hatching of the blastocysts from the zona pellucida. These results were mimicked by treatment with the myosin II inhibitor blebbistatin. We propose that the tension generated by the E-cadherin/AmotL2/actin filaments plays a crucial role in developmental processes such as epithelial geometrical packing as well as generation of forces required for blastocyst hatching.Peer reviewe
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