scholarly journals BRAF Inhibitors Induce Feedback Activation of RAS Pathway in Thyroid Cancer Cells

2021 ◽  
Vol 22 (11) ◽  
pp. 5744
Author(s):  
Elisa Bonaldi ◽  
Chiara Gargiuli ◽  
Loris De Cecco ◽  
Arianna Micali ◽  
Maria Grazia Rizzetti ◽  
...  

BRAFV600E is the most frequent oncogenic mutation identified in papillary thyroid cancer (PTC). In PTC patients who do not respond to standard treatment, BRAF inhibitors are currently tested as alternative strategies. However, as observed for other targeted therapies, patients eventually develop drug resistance. The mechanisms of BRAF inhibitors response are still poorly understood in a thyroid cancer (TC) context. In this study, we investigated in BRAFV600E mutated TC cell lines the effects of Vemurafenib and Dabrafenib, two BRAF inhibitors currently used in a clinical setting. We assessed cell proliferation, and the expression and activity of the thyroid function related transporter NIS following the treatment with BRAF inhibitors. In addition, we investigated the global gene expression by microarray, the relevant modulated biological processes by gene set enrichment analysis (GSEA), and TC specific gene signatures related to MAPK pathway activation, thyroid differentiation, and transcriptional profile associated with BRAFV600E or RAS mutation. We found that both inhibitors induce antiproliferative and redifferentiative effects on TC cells, as well as a rewiring of the MAPK pathway related to RAS signaling. Our results suggest a possible mechanism of drug response to the BRAF inhibitors Vemurafenib or Dabrafenib, supporting very recent findings in TC patients treated with targeted therapies.

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 355-355 ◽  
Author(s):  
Kristine Misund ◽  
Niamh Keane ◽  
Yan W Asmann ◽  
Scott Van Wier ◽  
Daniel Riggs ◽  
...  

Abstract MYC expression is frequently dysregulated in multiple myeloma (MM). In one comprehensive study, MYC structural variations (SV) were found in nearly half of MM cases (Affer et al. Leukemia 2014). The prevalence was higher in hyperdiploid (HRD) tumors (65%) compared to non-hyperdiploid (NHRD) tumors (36%). The large amount of tumor DNA required for all of the genomic studies performed may have biased the samples analyzed (e.g., to those with higher tumor burdens). To validate the findings of recurrent MYC SV in another dataset, we analyzed the CoMMpass data. We analyzed long-insert whole genome sequencing (WGS) data from diagnostic samples in 420 patients from the IA7 release (dbGAP phs000748) for SV. The results of clinical data, processed WES (SNV), RNASeq (gene expression) and WGS (copy number) data from IA8 (http://research.themmrf.org) were used to calculate survival, RAS and NFKB pathway mutation (WES), TC class (RNA), NFKB index (RNA) and hyperdiploid index (WGS). MYC SVs were identified in 38% of tumors. They were present in 53% HRD and 28% NHRD, and by TC in 55% D1, 43% D2, 36% MMSET, 26% MAF, 13% CCND. Juxtaposition of an Ig enhancer (IgH, IgK, IgL) close to MYC was the most common MYC SV, representing ~40% of the MYC SV. Other enhancers identified have mostly been reported previously, with the most frequent being NSMCE2 (12% of SV) and TXNDC5 (5% of SV). Intrachromosomal SV (deletions, inversions, duplications) not associated with any known enhancer were also frequent (18% of SV). As expected, MYC expression was higher in tumors with MYC SV compared to those without (~2.4 fold, p-value<0.0001). We used Gene Set Enrichment Analysis (GSEA) to identify activated pathways that might substitute for MYC in HRD patients without MYC SV and observed significant activation of the NFkB pathway. Interestingly, examining patients with RAS/MAPK pathway (NRAS, KRAS, BRAF, FGFR3 - abbreviated RAS) mutations (identified in 50% of all patients) the same pattern was observed: in the absence of RAS mutation, there was a significantly higher NFkB index. In general, the HRD tumors seem to have either activation of RAS and/or MYC, or activation of NFkB (Figure). There was no difference in overall survival in patients with versus those without MYC SV. We developed a clinically applicable sequencing platform to identify MYC SV, which cannot be reliably identified by FISH. We sought to validate this targeted capture approach, where in addition to the coding exons of 81 interesting genes described previously (M3P), we also pulled down the region surrounding MYC (2 Mb), IgH (0.5 Mb), IgK (50 kb) and IgL (100 kb) allowing us to additionally identify SV in MYC and Ig loci. Using this approach we identified IgH translocations in 29/30 samples with translocations previously identified by FISH (97%). Moreover, we identified MYC SV in 19/22 patients with SV previously identified by mate-pair WGS (86%). Importantly, sequencing identified the precise translocation breakpoint, and identity of the enhancer dysregulating MYC, which may be important variables. In one informative patient two different MYC SV were present at diagnosis, only one of which was still present following a partial response to four cycles of lenalidomide and dexamethasone. This suggests that the two MYC SV are in different subclones, one of which was much more sensitive to the treatment. Interestingly, the enhancer dysregulating MYC in the sensitive subclone harbors 5 strong Ikaros binding sites identified by ChIPseq, suggesting one intriguing mechanism for sensitivity to lenalidomide. To summarize, we verified in a large dataset that MYC expression is frequently dysregulated by SV in MM (38%), and the RAS/MAPK (50%) and NFKB (23%) pathways are frequently activated by mutations. Surprisingly, given their generally good prognosis, nearly half of HRD tumors seem to be MYC driven, while this is true for only a quarter of NHRD tumors. HRD tumors not driven by MYC or RAS appear to be driven by NFKB. Remarkably, the pathways most commonly activated by mutation in MM: CCND, MYC, RAS, NFKB are common to many cancers and have been studied extensively individually. To understand their clinical impact in MM we have developed a comprehensive custom capture sequencing panel that identified 97% of IgH translocations, 86% of MYC SV, and as well as SNV and CNV of 81 recurrently mutated genes. It will be important to include such a comprehensive genetic analysis to complement clinical trials in the future. Figure. Figure. Disclosures Stewart: Bristol Myers Squibb: Consultancy; Celgene: Consultancy; Takeda Oncology: Consultancy; Janssen Pharmaceuticals: Consultancy.


2017 ◽  
Author(s):  
Abhijeet R. Sonawane ◽  
John Platig ◽  
Maud Fagny ◽  
Cho-Yi Chen ◽  
Joseph N. Paulson ◽  
...  

Although all human tissues carry out common processes, tissues are distinguished by gene expres-sion patterns, implying that distinct regulatory programs control tissue-specificity. In this study, we investigate gene expression and regulation across 38 tissues profiled in the Genotype-Tissue Expression project. We find that network edges (transcription factor to target gene connections) have higher tissue-specificity than network nodes (genes) and that regulating nodes (transcription factors) are less likely to be expressed in a tissue-specific manner as compared to their targets (genes). Gene set enrichment analysis of network targeting also indicates that regulation of tissue-specific function is largely independent of transcription factor expression. In addition, tissue-specific genes are not highly targeted in their corresponding tissue-network. However, they do assume bottleneck positions due to variability in transcription factor targeting and the influence of non-canonical regulatory interactions. These results suggest that tissue-specificity is driven by context-dependent regulatory paths, providing transcriptional control of tissue-specific processes.


Cancers ◽  
2021 ◽  
Vol 13 (24) ◽  
pp. 6194
Author(s):  
Prachi Mishra ◽  
Dipranjan Laha ◽  
Robert Grant ◽  
Naris Nilubol

Thyroid cancer is the most common type of endocrine malignancy comprising 2–3% of all cancers, with a constant rise in the incidence rate. The standard first-line treatments for thyroid cancer include surgery and radioactive iodine ablation, and a majority of patients show a good response to these therapies. Despite a better response and outcome, approximately twenty percent of patients develop disease recurrence and distant metastasis. With improved knowledge of molecular dysregulation and biological characteristics of thyroid cancer, the development of new treatment strategies comprising novel targets has accelerated. Biomarker-driven targeted therapies have now emerged as a trend for personalized treatments in patients with advanced cancers, and several multiple receptor kinase inhibitors have entered clinical trials (phase I/II/III) to evaluate their safety and efficacy. Most extensively investigated and clinically approved targeted therapies in thyroid cancer include the tyrosine receptor kinase inhibitors that target antiangiogenic markers, BRAF mutation, PI3K/AKT, and MAPK pathway components. In this review, we focus on the current advances in targeted mono- and combination therapies for various types of thyroid cancer.


Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 3766-3766
Author(s):  
Mark Wunderlich ◽  
Jing Chen ◽  
Eric O'Brien ◽  
Nicole Manning ◽  
Christina Sexton ◽  
...  

Therapies for pediatric acute myeloid leukemia (AML) remain unsatisfactory and generally do not incorporate molecularly-targeted agents aside from FLT3 inhibitors outside of the relapse setting. Patient-derived xenograft (PDX) models of AML are increasingly accessible for the preclinical evaluation of targeted therapies, though the degree to which these systems recapitulate the disease state as found in patients has not been well defined for AML. Gene expression profiling of patient blasts has been successfully used to discriminate distinct subtypes of AML, to uncover sub-type specific vulnerabilities, and to predict response to therapy and outcomes. We sought to systematically examine PDX models of pediatric AML for their ability to replicate global gene expression patterns and preserve mutational signatures found in patients. In addition, we conducted in-depth bioinformatic analyses of samples with cryptic CBA2T3-GLIS2 fusion generated by the inv(16)(p13.3q24.3) for identification of potential novel targeted therapies. We performed detailed analyses of RNA sequencing data from a diverse series of 24 pediatric AML PDX models established from samples obtained from patients with relapse and refractory disease. Initially we compared our PDX data against 49 selected relapse and refractory patient sample data files found in the NCI TARGET dataset of pediatric AML. When applying unsupervised hierarchical clustering to the PDX samples, we found that clustering was associated with MLL status. Clustering of the combined sets of samples by MLL status showed integration of samples according to mutation profile, regardless of data source (PDX or patient). The expression levels of all detectable transcripts were highly conserved between PDX and patient MLL-r samples. Separate analysis of each dataset yielded MLL specific gene lists that included a subset of overlapping genes which may point to a unique relapse and refractory pediatric MLL-r signature. This list contains several interesting new targets for further study. A subset of 12 PDX models were compared directly to the matched patient sample from which they were established. This analysis revealed strong similarity, with each PDX most closely related to its matched patient sample, suggesting retention of sample-specific gene expression in immune deficient mice. We set up our PDX models in NSG mice with transgenic expression of human myelo-supportive cytokines SCF, GM-CSF, and IL-3 in order to promote the most efficient and robust engraftment of precious patient material. In order to detect any skewing effects due to the host mouse strain, we compared NSGS PDX RNA sequencing data to 10 matched NSG PDX models. This comparison revealed consistent differences in only 9 transcripts, which were almost entirely related to increased JAK/STAT signaling and macrophage activation pathways in NSGS mice relative to NSG mice. Interestingly, during this analysis we observed a distinct PCA-driven clustering of a pair of PDX samples with previously clinically unidentified driver mutations. Reanalysis of the RNA sequencing data revealed evidence of a cryptic GLIS2 rearrangement (found in ~1% of pediatric AML cases) as the driver mutation, which was subsequently confirmed by RT-PCR in both samples. The unique CBFA2T3/GLIS2 RNA signature was mined to guide the composition of a focused 75-molecule in vitro drug screen against ex vivo PDX samples with an emphasis on the SHH, WNT, and BCL2 pathways. This screen identified the Wnt-C59 PORCN inhibitor as having specific activity against CBFA2T3/GLIS2+ AMLs. Further testing of C-59 in combinatorial studies revealed enhanced effects with the addition of the BCL2 inhibitor, venetoclax. In vivo experiments are currently underway to determine the pre-clinical efficacy of this novel combination. In summary, we found highly significant fidelity of gene expression in PDX models of relapse and refractory pediatric AML. Analysis of this dataset has led to several insights, including potential targeted therapies, highlighting how this system could be a valuable tool for discovery of novel targeted therapies, especially for very rare, distinct subtypes of disease. Disclosures Perentesis: Kurome Therapeutics: Consultancy.


2020 ◽  
Vol 117 (22) ◽  
pp. 12315-12323 ◽  
Author(s):  
Joshi J. Alumkal ◽  
Duanchen Sun ◽  
Eric Lu ◽  
Tomasz M. Beer ◽  
George V. Thomas ◽  
...  

The androgen receptor (AR) antagonist enzalutamide is one of the principal treatments for men with castration-resistant prostate cancer (CRPC). However, not all patients respond, and resistance mechanisms are largely unknown. We hypothesized that genomic and transcriptional features from metastatic CRPC biopsies prior to treatment would be predictive of de novo treatment resistance. To this end, we conducted a phase II trial of enzalutamide treatment (160 mg/d) in 36 men with metastatic CRPC. Thirty-four patients were evaluable for the primary end point of a prostate-specific antigen (PSA)50 response (PSA decline ≥50% at 12 wk vs. baseline). Nine patients were classified as nonresponders (PSA decline <50%), and 25 patients were classified as responders (PSA decline ≥50%). Failure to achieve a PSA50 was associated with shorter progression-free survival, time on treatment, and overall survival, demonstrating PSA50’s utility. Targeted DNA-sequencing was performed on 26 of 36 biopsies, and RNA-sequencing was performed on 25 of 36 biopsies that contained sufficient material. Using computational methods, we measured AR transcriptional function and performed gene set enrichment analysis (GSEA) to identify pathways whose activity state correlated with de novo resistance.TP53gene alterations were more common in nonresponders, although this did not reach statistical significance (P= 0.055).ARgene alterations and AR expression were similar between groups. Importantly, however, transcriptional measurements demonstrated that specific gene sets—including those linked to low AR transcriptional activity and a stemness program—were activated in nonresponders. Our results suggest that patients whose tumors harbor this program should be considered for clinical trials testing rational agents to overcome de novo enzalutamide resistance.


Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 383-383
Author(s):  
Beatriz Sanchez-Espiridion ◽  
Abel Sanchez-Aguilera ◽  
Carlos Montalban ◽  
Monica Garcia-Cosio ◽  
Carmen Bellas ◽  
...  

Abstract Despite the major advances in the treatment of classical Hodgkin Lymphoma (cHL) patients, around 30% to 40% of cases in advanced stages may relapse or die as result of the disease, and current markers to predict prognosis are rather unreliable. The identification of molecular events and biological processes associated with treatment failure are essential to develop new predictive tools. We used gene expression data from 29 samples of advanced cHL patients and HL-derived cell lines in order to identify transcriptional patterns from both tumoral cells and cell microenvironment. Student t-test was used to detect genes differentially overexpressed in cell lines and in tumor samples, thus creating two databases that report for genes expressed by the tumor HRS cells and genes expressed by the microenvironment. Using Gene Set Enrichment analysis (GSEA) we identified specific gene sets enriched in both databases in patients with favorable and unfavorable outcome, respectively. To validate these pathways we designed a novel Taqman low-density array (LDA) to examine the expression of the most relevant genes in 60 formalin-fixed, paraffin embedded (FFPE) tissue samples, and correlated the results with treatment outcome. Functional pathways related to unfavorable outcome significantly enriched in the HRS cells included the regulation of the G2/M checkpoint of the cell cycle, S phase and G1/S transition, chaperons, histone modification and other signaling pathways with an important representation of the MAPK pathway. On the other hand, genes reporting for specific T-cell populations (T-cytotoxic and T-regulatory cells) and macrophage activation were found to be overexpressed in the microenvironment. The final model presents a balanced representation of these genes, including also genes encoding factors implicated in drug resistance (RRM2, TYMS and TOP2A). RNA extracted from FFPE sections yielded analyzable data for 80% of samples. LDA analysis of the genes included in the model confirmed the feasibility of this approach, and the capacity for identifying cases with increased risk of failure.LDA provides an effective technique for analyzing gene expression in FFPE tissues, and it can be used for clinical prediction in diagnostic samples, using a selection of genes identified after GSEA analysis of the initial molecular signatures. This novel Taqman LDA will be used to develop a new molecular predictor of the outcome of patients with advanced cHL.


Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 4899-4899
Author(s):  
Christophe Desterke ◽  
Djamel Aggoune ◽  
Marie Laure Bonnet ◽  
Nais Prade ◽  
Jean-Claude Chomel ◽  
...  

Abstract Chronic myeloid leukemia (CML) is the paradigm of malignancy treated by targeted therapies by the use of tyrosine kinase inhibitors (TKI), essentially Imatinib, Dasatinib and Nilotinib. Despite their major efficiency, especially as first line therapies, resistance to these drugs develop partly due to genetic instability inherent to CML. BCR-ABL-kinase mutations remain the first cause of resistance, which appears to be due to clonal selection of cells bearing a given mutation under TKI therapies. Amongst these mutations, the “gatekeeper” T315I mutant is a major concern as it confers resistance to all three TKI clinically used and patients with this mutation have a poor prognosis. The inaccessibility of the TKI to the ABL kinase pocket might not be the only “mechanistic” cause of resistance and it has been suggested that T315I-mutated BCR-ABL (Skaggs BJ et al, 2006) could induce a specific phosphoproteome signature. To evaluate this possibility, we decided to determine if a specific gene expression profiling can be associated with T315I-mutated BCR-ABL, as compared to native BCR-ABL. The human hematopoietic cell line UT7 was transfected with retroviral vectors encoding for native BCR-ABL (UT7.11) or BCR-ABL with the T315I mutation (UT7.T315I). The cell lines were characterized by their cell growth, Western blotting and sequencing. UT7.11 cells were sensitive to Imatinib, Dasatinib and Nilotinib as well as to Ponatinib whereas UT7-T315I cells were resistant to all three TKI except for Ponatinib. Affymetrix microarrays were performed in triplicate on each of three groups (UT7, UT7.11, UT7.T315I). The datas were normalized using the dchip software. Bioinformatics analyzes were performed with R software (packages FactoMineR, limma, PAMR) Mev in TM4 software, enrichment analysis with the GSEA software (Broad institute). The principal component analysis (PCA) showed that the overall RNA expression of UT7.T315I was different from that of UT7.11 (native BCR-ABL) and parental UT7. On factorial map, UT7.11 was found more distant from parental UT7 than UT7.T315I. The contrast analysis of the linear model by the algorithm limma between the 3 groups, showed a strong differential signature of UT7.11 as compared to parental UT7 and UT7.T315I (respectively 4792 and 4813 genes). Only 800 genes were found to be differentially expressed between UT7.T315I and parental UT7. In hierarchical clustering, the total signature obtained in limma confirmed a closed profile between parental UT7 and UT7.T315I. Among the results of the limma model, we identified a 286 specific genes signature for UT7.T315I (both different from parental UT7 and UT7.11 and also not regulated between UT7.11 and UT7). This specific list of UT7.T315I was validated with the T315I group sample segregation by different multivariate methods: PCA, hierarchical clustering and non-negative matrix factorization. Among this T315I-specific gene list limma, 34 ZNF family genes were found (11.88%). Predicting class algorithm based on shunkren centroid (PAMR) separated the three group samples with low classification error and a global list of 368 genes: only 75 genes predicted UT7.T315I group and from this list 13 were in the ZNF gene family (13.33%). By the method of gene set enrichment analysis (GSEA), we explored the top 100 ranked genes as upregulated in UT7.T315I by comparing the two other sample groups. This gene set showed a high representation of ZNF family genes (25%). The design of a gene set with ZNF family genes selected showed a positive enrichment of ZNF (NES = +1.35, p-value <0.001) in the UT7.T315I by comparing the two other groups. The majority of these genes is localized in 19q13.41 (ZNF cluster 282). They exhibit C2H2 and Kruppel-associated box (KRAB) domains in their sequence. Interestingly the overexpression of KRAB-ZNF transcription factors has been recently reported in patients with gastrointestinal stromal tumors (GIST) as conferring resistance to Imatinib Mesylate (Rink L., PLOS One 2013). In conclusion, our work revealed for the first time a specific signature of the T315I mutation which includes a strong representation of the ZNF family. The identification of this signature could be interest for future drug screening strategies in advanced phase CML patients progressing under Ponatinib. Current experiments are underway to validate these results by analyzing the expression of ZNF family of genes in primary CML cells with T315I mutation. Disclosures: Turhan: Bristol Myers Squibb, Novartis: Consultancy, Honoraria.


2019 ◽  
Vol 20 (S18) ◽  
Author(s):  
Jiajie Peng ◽  
Guilin Lu ◽  
Hansheng Xue ◽  
Tao Wang ◽  
Xuequn Shang

Abstract Background The Gene Ontology (GO) knowledgebase is the world’s largest source of information on the functions of genes. Since the beginning of GO project, various tools have been developed to perform GO enrichment analysis experiments. GO enrichment analysis has become a commonly used method of gene function analysis. Existing GO enrichment analysis tools do not consider tissue-specific information, although this information is very important to current research. Results In this paper, we built an easy-to-use web tool called TS−GOEA that allows users to easily perform experiments based on tissue-specific GO enrichment analysis. TS−GOEA uses strict threshold statistical method for GO enrichment analysis, and provides statistical tests to improve the reliability of the analysis results. Meanwhile, TS−GOEA provides tools to compare different experimental results, which is convenient for users to compare the experimental results. To evaluate its performance, we tested the genes associated with platelet disease with TS−GOEA. Conclusions TS−GOEA is an effective GO analysis tool with unique features. The experimental results show that our method has better performance and provides a useful supplement for the existing GO enrichment analysis tools. TS−GOEA is available at http://120.77.47.2:5678.


2010 ◽  
Vol 9 ◽  
pp. CIN.S2892 ◽  
Author(s):  
Yarong Yang ◽  
Eric J. Kort ◽  
Nader Ebrahimi ◽  
Zhongfa Zhang ◽  
Bin T. Teh

Background Gene set enrichment analysis (GSEA) is an analytic approach which simultaneously reduces the dimensionality of microarray data and enables ready inference of the biological meaning of observed gene expression patterns. Here we invert the GSEA process to identify class-specific gene signatures. Because our approach uses the Kolmogorov-Smirnov approach both to define class specific signatures and to classify samples using those signatures, we have termed this methodology “Dual-KS” (DKS). Results The optimum gene signature identified by the DKS algorithm was smaller than other methods to which it was compared in 5 out of 10 datasets. The estimated error rate of DKS using the optimum gene signature was smaller than the estimated error rate of the random forest method in 4 out of the 10 datasets, and was equivalent in two additional datasets. DKS performance relative to other benchmarked algorithms was similar to its performance relative to random forests. Conclusions DKS is an efficient analytic methodology that can identify highly parsimonious gene signatures useful for classification in the context of microarray studies. The algorithm is available as the dualKS package for R as part of the bioconductor project.


Author(s):  
Sarbojoy Saha ◽  
Shampa Barmon

Genetic disorders are quite a major topic of discussion and debate in the recent world of biological sciences. Turner&rsquo;s syndrome is one such disorder caused by a chromosome aneuploidy and it has characteristic symptoms in the patient or the affected individual.&nbsp; The amniotic fluid is a complex biological material found in the amniotic sac of pregnant women and they can provide valuable knowledge and understanding of the pathogenesis of this particular chromosomal abnormality. In this study, global gene expression analysis of cell-free RNA in amniotic fluid supernatant was used to detect genes/organ systems which may be significant in the pathophysiology of Turner&rsquo;s syndrome. The cell-free RNA from the amniotic fluid of five mid-trimester Turner&rsquo;s syndrome fetuses and five euploid female fetuses matched for age of gestation were extracted, amplified and hybridized onto Affymetrix U33 Plus 2.0. array. The paired t-test was used to identify the significantly differentially regulated genes. Biological interpretation was conducted using ingenuity pathway analysis and BioGPS gene expression atlas. Of the genes, XIST was especially downregulated and SHOX was not expressed differentially. One of the most highly represented organ systems was the hematologic/immune system, differentiating the transcriptome of Turner&rsquo;s syndrome from other chromosomal aneuploidies that are discussed in this area of science. The differences in the transcriptome of the Turner&rsquo;s syndrome are due to genome-wide dysregulation. The hematologic/immune system differences are significant in early-onset autoimmune dysfunction. There are other genes which have been identified that are associated with the cardiovascular and the skeletal system, as these are often seen to be affected in the female patients with turner&rsquo;s syndrome. Hopefully, such knowledge gained from this study will help us to understand the deeper mechanisms of this disorder and the possible treatments of this disease.


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