Mining potentially actionable kinase gene fusions in cancer cell lines with the KuNG FU database.

Inhibition of kinase gene fusions (KGFs) has proven successful in cancer treatment and continues to represent an attractive research area, due to kinase druggability and clinical validation. Indeed, literature and public databases report a remarkable number of KGFs as potential drug targets, often identified by in vitro characterization of tumor cell line models and confirmed also in clinical samples. However, KGF molecular and experimental information can sometimes be sparse and partially overlapping, suggesting the need for a specific annotation database of KGFs, conveniently condensing all the molecular details that can support targeted drug development pipelines and diagnostic approaches. Here, we describe KuNG FU (KiNase Gene FUsion), a manually curated database collecting detailed annotations on KGFs that were identified and experimentally validated in human cancer cell lines from multiple sources, exclusively focusing on in-frame KGF events retaining an intact kinase domain, representing potentially active driver kinase targets. To our knowledge, KuNG FU represents to date the largest freely accessible homogeneous and curated database of kinase gene fusions in cell line models.

Comprehensive kinome NGS targeted expression profiling by KING-REX.

BACKGROUND: Protein kinases are enzymes controlling different cellular functions. Genetic alterations often result in kinase dysregulation, making kinases a very attractive class of druggable targets in several human diseases. Existing approved drugs still target a very limited portion of the human 'kinome', demanding a broader functional knowledge of individual and co-expressed kinase patterns in physiologic and pathologic settings. The development of novel rapid and cost-effective methods for kinome screening is therefore highly desirable, potentially leading to the identification of novel kinase drug targets. RESULTS: In this work, we describe the development of KING-REX (KINase Gene RNA EXpression), a comprehensive kinome RNA targeted custom assay-based panel designed for Next Generation Sequencing analysis, coupled with a dedicated data analysis pipeline. We have conceived KING-REX for the gene expression analysis of 512 human kinases; for 319 kinases, paired assays and custom analysis pipeline features allow the evaluation of 3'- and 5'-end transcript imbalances as readout for the prediction of gene rearrangements. Validation tests on cell line models harboring known gene fusions demonstrated a comparable accuracy of KING-REX gene expression assessment as in whole transcriptome analyses, together with a robust detection of transcript portion imbalances in rearranged kinases, even in complex RNA mixtures or in degraded RNA. CONCLUSIONS: These results support the use of KING-REX as a rapid and cost effective kinome investigation tool in the field of kinase target identification for applications in cancer biology and other human diseases.

Afatinib Is a New Therapeutic Approach in Chordoma with a Unique Ability to Target EGFR and Brachyury.

Chordomas are rare bone tumors with no approved therapy. These tumors express several activated tyrosine kinase receptors, which prompted attempts to treat patients with tyrosine kinase inhibitors. Although clinical benefit was observed in phase II clinical trials with imatinib and sorafenib, and sporadically also with EGFR inhibitors, therapies evaluated to date have shown modest activity. With the goal of identifying new drugs with immediate therapeutic potential for chordoma patients, we collected clinically approved drugs and other advanced inhibitors of MET, PDGFRß, and EGFR tyrosine kinases, and assessed their antiproliferative activity against a panel of chordoma cell lines. Chordoma cell lines were not responsive to MET and PDGFRß inhibitors. U-CH1 and UM-Chor1 were sensitive to all EGFR inhibitors, whereas the remaining cell lines were generally insensitive to these drugs. Afatinib was the only EGFR inhibitor with activity across the chordoma panel. We then investigated the molecular mechanisms behind the responses observed and found that the antiproliferative IC50s correlate with the unique ability of afatinib to promote degradation of EGFR and brachyury, an embryonic transcription factor considered a key driver of chordoma. Afatinib displayed potent antitumor efficacy in U-CH1, SF8894, CF322, and CF365 chordoma tumor models in vivo In the panel analyzed, high EGFR phosphorylation and low AXL and STK33 expression correlated with higher sensitivity to afatinib and deserve further investigation as potential biomarkers of response. These data support the use of afatinib in clinical trials and provide the rationale for the upcoming European phase II study on afatinib in advanced chordoma. Mol Cancer Ther; 17(3); 603-13. ©2017 AACR.

Establishment and genomic characterization of the new chordoma cell line Chor-IN-1.

Chordomas are rare, slowly growing tumors with high medical need, arising in the axial skeleton from notochord remnants. The transcription factor "brachyury" represents a distinctive molecular marker and a key oncogenic driver of chordomas. Tyrosine kinase receptors are also expressed, but so far kinase inhibitors have not shown clear clinical efficacy in chordoma patients. The need for effective therapies is extremely high, but the paucity of established chordoma cell lines has limited preclinical research. Here we describe the isolation of the new Chor-IN-1 cell line from a recurrent sacral chordoma and its characterization as compared to other chordoma cell lines. Chor-IN-1 displays genomic identity to the tumor of origin and has morphological features, growth characteristics and chromosomal abnormalities typical of chordoma, with expression of brachyury and other relevant biomarkers. Chor-IN-1 gene variants, copy number alterations and kinome gene expression were analyzed in comparison to other four chordoma cell lines, generating large scale DNA and mRNA genomic data that can be exploited for the identification of novel pharmacological targets and candidate predictive biomarkers of drug sensitivity in chordoma. The establishment of this new, well characterized chordoma cell line provides a useful tool for the identification of drugs active in chordoma.

Sensitivity to Entrectinib Associated With a Novel LMNA-NTRK1 Gene Fusion in Metastatic Colorectal Cancer.

In metastatic colorectal cancer (CRC), actionable genetic lesions represent potential clinical opportunities. NTRK1, 2, and 3 gene rearrangements encode oncogenic fusions of the tropomyosin-receptor kinase (TRK) family of receptor tyrosine kinases in different tumor types. The TPM3-NTRK1 rearrangement is a recurring event in CRC that renders tumors sensitive to TRKA kinase inhibitors in preclinical models. We identified abnormal expression of the TRKA protein in tumor and liver metastases of a CRC patient refractory to standard therapy. Molecular characterization unveiled a novel LMNA-NTRK1 rearrangement within chromosome 1 with oncogenic potential, and the patient was treated with the pan-TRK inhibitor entrectinib, achieving partial response with decrease in hepatic target lesions from 6.8 and 8.2cm in longest diameter to 4.7 and 4.3cm, respectively. To our knowledge, this is the first clinical evidence of efficacy for therapeutic inhibition of TRKA in a solid tumor, illuminating a genomic-driven strategy to identify CRCs reliant on this oncogene to be clinically targeted with entrectinib.

The TPM3-NTRK1 rearrangement is a recurring event in colorectal carcinoma and is associated with tumor sensitivity to TRKA kinase inhibition.

The NTRK1 gene encodes Tropomyosin-related kinase A (TRKA), the high-affinity Nerve Growth Factor Receptor. NTRK1 was originally isolated from a colorectal carcinoma (CRC) sample as component of a somatic rearrangement (TPM3-NTRK1) resulting in expression of the oncogenic chimeric protein TPM3-TRKA, but there has been no subsequent report regarding the relevance of this oncogene in CRC. The KM12 human CRC cell line expresses the chimeric TPM3-TRKA protein and is hypersensitive to TRKA kinase inhibition. We report the detailed characterization of the TPM3-NTRK1 genomic rearrangement in KM12 cells and through a cellular screening approach, the identification of NMS-P626, a novel highly potent and selective TRKA inhibitor. NMS-P626 suppressed TPM3-TRKA phosphorylation and downstream signaling in KM12 cells and showed remarkable antitumor activity in mice bearing KM12 tumors. Finally, using quantitative reverse transcriptase PCR and immunohistochemistry (IHC) we identified the TPM3-NTRK1 rearrangement in a CRC clinical sample, therefore suggesting that this chromosomal translocation is indeed a low frequency recurring event in CRC and that such patients might benefit from therapy with TRKA kinase inhibitors.

Cell line identity finding by fingerprinting, an optimized resource for short tandem repeat profile authentication.

The generation of biological data on wide panels of tumor cell lines is recognized as a valid contribution to the cancer research community. However, research laboratories can benefit from this knowledge only after the identity of each individual cell line used in the experiments is verified and matched to external sources. Among the methods employed to assess cell line identity, DNA fingerprinting by profiling Short Tandem Repeat (STR) at variable loci has become the method of choice. However, the analysis of cancer cell lines is sometimes complicated by their intrinsic genetic instability, resulting in multiple allele calls per locus. In addition, comparison of data across different sources must deal with the heterogeneity of published profiles both in terms of number and type of loci used. The aim of this work is to provide the scientific community a homogeneous reference dataset for 300 widely used tumor cell lines, profiled in parallel on 16 loci. This large dataset is interfaced with an in-house developed software tool for Cell Line Identity Finding by Fingerprinting (CLIFF), featuring an original identity score calculation, which facilitates the comparison of STR profiles from different sources and enables accurate calls when multiple loci are present. CLIFF additionally allows import and query of proprietary STR profile datasets.

Abcg2 overexpression represents a novel mechanism for acquired resistance to the multi-kinase inhibitor Danusertib in BCR-ABL-positive cells in vitro.

The success of Imatinib (IM) therapy in chronic myeloid leukemia (CML) is compromised by the development of IM resistance and by a limited IM effect on hematopoietic stem cells. Danusertib (formerly PHA-739358) is a potent pan-aurora and ABL kinase inhibitor with activity against known BCR-ABL mutations, including T315I. Here, the individual contribution of both signaling pathways to the therapeutic effect of Danusertib as well as mechanisms underlying the development of resistance and, as a consequence, strategies to overcome resistance to Danusertib were investigated. Starting at low concentrations, a dose-dependent inhibition of BCR-ABL activity was observed, whereas inhibition of aurora kinase activity required higher concentrations, pointing to a therapeutic window between the two effects. Interestingly, the emergence of resistant clones during Danusertib exposure in vitro occurred considerably less frequently than with comparable concentrations of IM. In addition, Danusertib-resistant clones had no mutations in BCR-ABL or aurora kinase domains and remained IM-sensitive. Overexpression of Abcg2 efflux transporter was identified and functionally validated as the predominant mechanism of acquired Danusertib resistance in vitro. Finally, the combined treatment with IM and Danusertib significantly reduced the emergence of drug resistance in vitro, raising hope that this drug combination may also achieve more durable disease control in vivo.

Cascades of transcriptional induction during dendritic cell maturation revealed by genome-wide expression analysis.

Dendritic cells (DC) are central regulators of immunity. Signal-induced maturation of DCs is assumed to be the starting point for specific immune responses. To further understand this process, we analyzed the alteration of transcript profiles along the time course of CD40 ligand-induced maturation of human myeloid DCs by Affymetrix GeneChip microarrays covering >6800 genes. Besides rediscovery of genes already described as associated with DC maturation proving reliability of the methods used, we identified clusterin as novel maturation marker. Looking across the time course, we observed synchronized kinetics of distinct functional groups of molecules whose temporal coregulation underscores known cellular events during dendritic cell maturation. For example, an early-peaking wave of inflammatory chemokines was followed by a sustained increase of constitutive chemokines and accompanied by slow but continuous induction of survival proteins. After an immediate but transient induction of cytokine-responsive transcripts, there was an increased expression of a group of genes involved in not only the regulation of cytokine effects, but also of transcription in general. Our results demonstrate that microarray studies along time courses combined with real-time PCR not only discover new marker molecules with functional implications, but also dissect the molecular kinetics of biological processes identifying complex pathways of regulation.

Computational dissection of tissue contamination for identification of colon cancer-specific expression profiles.

Microarray profiles of bulk tumor tissues reflect gene expression corresponding to malignant cells as well as to many different types of contaminating normal cells. In this report, we assess the feasibility of querying baseline multitissue transcriptome databases to dissect disease-specific genes. Using colon cancer as a model tumor, we show that the application of Boolean operators (AND, OR, BUTNOT) for database searches leads to genes with expression patterns of interest. The BUTNOT operator for example allows the assignment of "expression signatures" to normal tissue specimens. These expression signatures were then used to computationally identify contaminating cells within conventionally dissected tissue specimens. The combination of several logic operators together with an expression database based on multiple human tissue specimens can resolve the problem of tissue contamination, revealing novel cancer-specific gene expression. Several markers, previously not known to be colon cancer associated, are provided.