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      DeSigN: connecting gene expression with therapeutics for drug repurposing and development

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      1 , 2 , 1 , 2 , 3 , 4 , 3 , 4 , 5 , 1 , 6 , 5 , 7 , 1 , 2 ,
      BMC Genomics
      BioMed Central
      The 27th International Conference on Genome Informatics
      3-5 October 2016
      Cell line, Gene expression, DeSigN, Cancer, Drug repurposing

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          Abstract

          Background

          The drug discovery and development pipeline is a long and arduous process that inevitably hampers rapid drug development. Therefore, strategies to improve the efficiency of drug development are urgently needed to enable effective drugs to enter the clinic. Precision medicine has demonstrated that genetic features of cancer cells can be used for predicting drug response, and emerging evidence suggest that gene-drug connections could be predicted more accurately by exploring the cumulative effects of many genes simultaneously.

          Results

          We developed DeSigN, a web-based tool for predicting drug efficacy against cancer cell lines using gene expression patterns. The algorithm correlates phenotype-specific gene signatures derived from differentially expressed genes with pre-defined gene expression profiles associated with drug response data (IC 50) from 140 drugs. DeSigN successfully predicted the right drug sensitivity outcome in four published GEO studies. Additionally, it predicted bosutinib, a Src/Abl kinase inhibitor, as a sensitive inhibitor for oral squamous cell carcinoma (OSCC) cell lines. In vitro validation of bosutinib in OSCC cell lines demonstrated that indeed, these cell lines were sensitive to bosutinib with IC 50 of 0.8–1.2 μM. As further confirmation, we demonstrated experimentally that bosutinib has anti-proliferative activity in OSCC cell lines, demonstrating that DeSigN was able to robustly predict drug that could be beneficial for tumour control.

          Conclusions

          DeSigN is a robust method that is useful for the identification of candidate drugs using an input gene signature obtained from gene expression analysis. This user-friendly platform could be used to identify drugs with unanticipated efficacy against cancer cell lines of interest, and therefore could be used for the repurposing of drugs, thus improving the efficiency of drug development.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12864-016-3260-7) contains supplementary material, which is available to authorized users.

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          Most cited references21

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          The NCI60 human tumour cell line anticancer drug screen.

          The US National Cancer Institute (NCI) 60 human tumour cell line anticancer drug screen (NCI60) was developed in the late 1980s as an in vitro drug-discovery tool intended to supplant the use of transplantable animal tumours in anticancer drug screening. This screening model was rapidly recognized as a rich source of information about the mechanisms of growth inhibition and tumour-cell kill. Recently, its role has changed to that of a service screen supporting the cancer research community. Here I review the development, use and productivity of the screen, highlighting several outcomes that have contributed to advances in cancer chemotherapy.
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            KRAS Mutations and Primary Resistance of Lung Adenocarcinomas to Gefitinib or Erlotinib

            Introduction Genes of the ERBB family encode receptor tyrosine kinases that mediate cellular responses to growth signals. Somatic mutations in the tyrosine kinase domains of two ERBB genes, epidermal growth factor receptor (EGFR) and HER2, have been found in a proportion of lung adenocarcinomas [1,2,3,4]. For EGFR, mutations are associated with sensitivity to the small-molecule kinase inhibitors gefitinib (Iressa) [1,2,3] and erlotinib (Tarceva) [3]. ERBB signaling pathways include downstream GTPases encoded by RAS genes. Some 15%–30% of lung adenocarcinomas contain activating mutations in the RAS family member KRAS. These mutations are most frequently found in codons 12 and 13 in exon 2 [5,6], and may be associated with unfavorable outcomes [7]. Interestingly, EGFR and KRAS mutations are rarely found in the same tumors, suggesting that they have functionally equivalent roles in lung tumorigenesis ([8]; M. Meyerson, personal communication). Furthermore, EGFR mutations are common in tumors from patients who have smoked less than 100 cigarettes in their lifetimes (“never smokers”) [3], while KRAS mutations more commonly occur in individuals with a history of substantial cigarette use [9]. We sought to determine whether KRAS mutations could also be used to predict primary sensitivity or resistance to gefitinib or erlotinib. We systematically evaluated 60 lung adenocarcinomas from patients with known responses to either of these drugs for the presence of mutations in EGFR (exons 18 through 21) and KRAS2 (exon 2). Here, we show that mutations in KRAS are associated with primary resistance to single-agent gefitinib or erlotinib. Our results suggest that a determination of mutational status for both EGFR and KRAS may help define which patients are likely to benefit from receiving gefitinib or erlotinib. Methods Tissue Procurement Tumor specimens were obtained through protocols approved by the institutional review board of Memorial Sloan-Kettering Cancer Center, as previously described [3] (see Protocols S1–S3). Tumor material, obtained from patients prior to kinase inhibitor treatment for lung cancer, was collected retrospectively for patients on gefitinib, who received 250 mg or 500 mg orally once daily (n = 24), and prospectively for patients on erlotinib, who received 150 mg orally once daily (n = 36). The latter cohort of patients was part of a clinical trial of erlotinib for patients with bronchioloalveolar carcinoma. The analysis presented here includes specimens we previously reported on (n = 17 for gefitinib and n = 17 for erlotinib) [3]. All specimens were reviewed by a single reference pathologist (M. F. Z.). Imaging studies were assessed by a single reference radiologist (R. T. H.), who graded responses according to Response Evaluation Criteria in Solid Tumors (RECIST) [10]. Both observers were blinded to patient outcomes. Eight of nine patients with tumors sensitive to gefitinib had objective partial responses as defined by RECIST, i.e., at least a 30% decrease in the sum of the longest diameters of target lesions, taking as reference the sum measured at baseline. The ninth patient had marked clinical improvement, as ascertained by two independent reviewing physicians and manifested by lessened dyspnea and cancer-related pain. However, this individual had radiographic lesions (pleural and bone metastases) that were deemed nonmeasurable by RECIST criteria. As erlotinib-treated patients were all in a clinical trial, all had disease measurable using RECIST guidelines. For both drugs in this study, tumors were considered refractory if they did not undergo sufficient shrinkage to qualify for partial response. This definition includes patients whose “best overall response” was either progression of disease (n = 26) or stable disease (n = 12) as defined by RECIST. No patients had a complete response. Mutational Analyses of EGFR and KRAS in Lung Tumors Genomic DNA was extracted from tumors embedded in paraffin blocks, except for tumor 109T, which was a fresh-frozen tumor specimen. Primers for EGFR analyses (exons 18–21) were as published [3]. For KRAS analyses, the following nested primer sets for exon 2 were used: huKRAS2 ex2F, 5′- GAATGGTCCTGCACCAGTAA-3′; huKRAS2 ex2R, 5′- GTGTGACATGTTCTAATATAGTCA-3′; huKRAS2 ex2Fint, 5′- GTCCTGCACCAGTAATATGC-3′; and huKRAS2 ex2Rint, 5′- ATGTTCTAATATAGTCACATTTTC-3′. For both EGFR and KRAS, PCR was performed using the HotStarTaq Master Mix Kit (Qiagen, Valencia, California, United States), as per manufacturer's instructions. Use of this method often obviated the need for nested PCR sets. All sequencing reactions were performed in both forward and reverse directions, and all mutations were confirmed by PCR amplification of an independent DNA isolate. In 12 cases, exon 19 deletions were also studied by length analysis of fluorescently labeled PCR products on a capillary electrophoresis device, using the following primers: EGFR-Ex19-FWD1, 5′- GCACCATCTCACAATTGCCAGTTA-3′, and EGFR-Ex19-REV1, 5′-Fam- AAAAGGTGGGCCTGAGGTTCA-3′. Using serial dilutions of DNA from the H1650 non-small-cell lung cancer cell line (exon 19 deletion-positive [11]), this assay detects the mutant allele when H1650 DNA comprises 6% or more of the total DNA tested, compared to a sensitivity of 12% for direct sequencing. These same cases were also screened for the exon 21 L858R mutation by a PCR–restriction fragment length polymorphism assay, based on a new Sau96I restriction site created by the L858R mutation (2,573T→G). The Sau96I-digested fluorescently labeled PCR products were analyzed by capillary electrophoresis, and the following primers were used: EGFR-Ex21-FWD1, 5′- CCTCACAGCAGGGTCTTCTCTGT-3′, and EGFR-Ex21-REV1, 5′-Fam- TCAGGAAAATGCTGGCTGACCTA-3′. Using serial dilutions of DNA from the H1975 cell line (L858R-positive [11]), this assay detects the mutant allele when H1975 DNA comprises 3% or more of the total DNA tested, compared to a sensitivity of 6% for direct sequencing (Q. Pan, W. Pao, and M. Ladanyi, unpublished data). Statistics Fisher's Exact Test was used to calculate p-values, and confidence intervals were calculated using Statistics with Confidence software [12]. Results We identified 60 lung adenocarcinomas from individual patients with tumors shown to be sensitive or refractory to single-agent gefitinib or erlotinib and evaluated these tumors for mutations in EGFR and KRAS. Collectively, nine of 38 (24%) tumors refractory to either kinase inhibitor had KRAS mutations, while zero of 21 (0%) drug-sensitive tumors had such mutations (p = 0.02) (Table 1). The 95% confidence intervals (CIs) for these observations are 13%–39% and 0%–16%, respectively. Conversely, 17 of 22 (77%) tumors sensitive to either kinase inhibitor had EGFR mutations, in contrast to zero of 38 (0%) drug-resistant tumors (p = 6.8 × 10−11). The 95% CIs for these observed response rates are 57%–90% and 0%–9%, respectively. All 17 tumors with EGFR mutations responded to gefitinib or erlotinib, while all nine tumors with KRAS mutations did not (p = 3.2 × 10−7). Correlation of EGFR and KRAS mutational status with drug and treatment response is detailed in Table 1. The spectrum of KRAS mutations is shown in Figure 1 and Table 2. Results with gefitinib and erlotinib were similar overall. However, the incidence of KRAS mutations in the patients treated with erlotinib was low, probably because of the fact that all patients treated with this drug had bronchioloalveolar carcinoma, which rarely has RAS mutations [13]. Alternatively, our analyses involving only exon 2 of KRAS2 may have missed some RAS mutations. However, in our analysis of the exonic regions encoding the first 100 amino acids of KRAS in 110 surgically resected early-stage non-small-cell lung cancers, we have found 18 mutations, and all were in either codon 12 or codon 13, encoded by exon 2 (W. Pao, R. Wilson, H. Varmus, unpublished data). Another possibility is that the erlotinib-treated tumors have mutations in other RAS genes, since a minority of RAS mutations in lung cancer have been reported to occur in N- or HRAS [5,6]. Discussion These results have important clinical implications. First, they extend previous data from our group and others showing that lung adenocarcinomas containing EGFR mutations are associated with sensitivity to gefitinib or erlotinib (17 of 17 in this series; 100% observed response rate; 95% CI, 82%–100%). Second, these data show that tumors with KRAS exon 2 mutations (n = 9) are associated with a lack of response to these kinase inhibitors (0% observed response rate; 95% CI, 0%–30%). Third, no drug-sensitive tumors had KRAS exon 2 mutations (n = 21). Whether KRAS mutational status can be used to predict responses to gefitinib or erlotinib in patients whose tumors have wild-type EGFR sequence is still under investigation: our analysis comparing response rates for tumors with neither EGFR nor KRAS mutations versus tumors with wild-type EGFR but mutated KRAS does not reach statistical significance (five of 22 versus zero of nine; p = 0.29). Nevertheless, these findings suggest that patients whose lung adenocarcinomas have KRAS mutations will not experience significant tumor regression with either drug. The incidence of EGFR mutations in tumors responsive to EGFR kinase inhibitors has varied from 71% to 100% ([1,2,3] and this paper). Thus, at this point, patients whose tumors test negative for EGFR mutations should not necessarily be precluded from treatment with either gefitinib or erlotinib. Data presented here suggest that clinical decisions regarding the use of these agents in patients with lung adenocarcinomas might be improved in the future by pre-treatment mutational profiling of both EGFR and KRAS. These findings warrant validation in large prospective trials using standardized mutation detection techniques. Supporting Information Protocol S1 Preclinical Studies of Blood, Urine, Bone Marrow, and Tissues Collected from Patients with Thoracic Malignancies (32 KB PDF). Click here for additional data file. Protocol S2 Multicenter Phase II Trial of OSI-774 (Erlotinib, Tarceva) in Patients with Advanced Bronchioloalveolar Cell Lung Cancer (1.9 MB PDF). Click here for additional data file. Protocol S3 Protocol Approval Letters (60 KB PDF). Click here for additional data file. Accession Numbers The LocusLink (http://www.ncbi.nlm.nih.gov/LocusLink/) accession number for the KRAS2 sequence discussed in this paper is 3845; the GenBank (http://www.ncbi.nlm.nih.gov/Genbank/) accession number for the KRAS2 sequence discussed in this paper is NT_009714.16. Patient Summary Background Two drugs, gefitinib (Iressa) and erlotinib (Tarceva), have been developed that can make lung cancers smaller in some patients. The drugs work by blocking the effect of a molecule called the epidermal growth factor receptor (EGFR), which relays instructions to cells to grow and divide. Recently, researchers found that these drugs most effectively shrink tumors that have acquired abnormal variations (mutations) in the EGFR gene. These mutations somehow allow tumor cells to escape normal safety mechanisms that keep cells from growing out of control. Some lung cancers also have mutations in another gene called KRAS. Interestingly, KRAS mutations and EGFR mutations are rarely ever found in the same tumor. Why Was This Study Done? Unfortunately, EGFR mutations are only found in a minority of patients with lung cancer. This means that gefitinib or erlotinib might be given to a lot of patients who may not benefit from this treatment. Ideally, the drugs would be given only to patients who we know will benefit from them. This study examined whether studying the KRAS gene (to see if it had a mutation) could help predict which patients had tumors that would respond well to the drugs. What Did the Researchers Do? They took 60 lung cancer samples from patients who had been treated with one of the drugs and either responded (that is, their tumors shrunk in size) or not, and tested whether the tumors had normal or abnormal KRAS. What Did They Find? Tumors that got significantly smaller while treated with gefitinib or erlotinib (a total of 22) had a normal KRAS gene. Most of these tumors had EGFR mutations. Conversely, tumors that had abnormal KRAS (a total of nine) did not shrink while treated with gefitinib or erlotinib. What Does This Mean? Both gefitinib and erlotinib are expensive and have side effects. Testing for EGFR and KRAS mutations is relatively straightforward, and one could test for abnormalities in both genes first and then decide which patients should be treated with either of the two drugs. What Next? Before doing EGFR and KRAS tests on a routine basis and taking the results into account when making a decision about who should be treated with gefitinib or erlotinib, larger studies need to be done to see whether the results reported here hold up. More Information Online US Food and Drug Administration information page on Iressa: http://www.fda.gov/cder/drug/infopage/iressa/iressaQ&A.htm Cancer Research UK information page about erlotinib: http://www.cancerhelp.org.uk/help/default.asp?page=10296
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              Mutations in the epidermal growth factor receptor and in KRAS are predictive and prognostic indicators in patients with non-small-cell lung cancer treated with chemotherapy alone and in combination with erlotinib.

              Epidermal growth factor receptor (EGFR) mutations have been associated with tumor response to treatment with single-agent EGFR inhibitors in patients with relapsed non-small-cell lung cancer (NSCLC). The implications of EGFR mutations in patients treated with EGFR inhibitors plus first-line chemotherapy are unknown. KRAS is frequently activated in NSCLC. The relationship of KRAS mutations to outcome after EGFR inhibitor treatment has not been described. Previously untreated patients with advanced NSCLC in the phase III TRIBUTE study who were randomly assigned to carboplatin and paclitaxel with erlotinib or placebo were assessed for survival, response, and time to progression (TTP). EGFR exons 18 through 21 and KRAS exon 2 were sequenced in tumors from 274 patients. Outcomes were correlated with EGFR and KRAS mutations in retrospective subset analyses. EGFR mutations were detected in 13% of tumors and were associated with longer survival, irrespective of treatment (P < .001). Among erlotinib-treated patients, EGFR mutations were associated with improved response rate (P < .05) and there was a trend toward an erlotinib benefit on TTP (P = .092), but not improved survival (P = .96). KRAS mutations (21% of tumors) were associated with significantly decreased TTP and survival in erlotinib plus chemotherapy-treated patients. EGFR mutations may be a positive prognostic factor for survival in advanced NSCLC patients treated with chemotherapy with or without erlotinib, and may predict greater likelihood of response. Patients with KRAS-mutant NSCLC showed poorer clinical outcomes when treated with erlotinib and chemotherapy. Further studies are needed to confirm the findings of this retrospective subset analysis.
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                Author and article information

                Contributors
                sokching.cheong@cancerresearch.my
                Conference
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                25 January 2017
                25 January 2017
                2017
                : 18
                Issue : Suppl 1 Issue sponsor : Publication of this supplement has not been supported by sponsorship. Information about the source of funding for publication charges can be found in the individual articles. The articles have undergone the journal's standard peer review process for supplements. The Supplement Editors declare that they have no competing interests.
                : 934
                Affiliations
                [1 ]ISNI 0000 0001 2308 5949, GRID grid.10347.31, Department of Oral & Maxillofacial Clinical Sciences, , Faculty of Dentistry, University of Malaya, ; 50603 Kuala Lumpur, Malaysia
                [2 ]Oral Cancer Research Group, Cancer Research Malaysia, No. 1, Jalan SS12/1A, 47500 Subang Jaya, Selangor Malaysia
                [3 ]ISNI 0000 0001 2308 5949, GRID grid.10347.31, Data Intensive Computing Centre, Research Management & Innovation Complex, , University of Malaya, ; 50603 Kuala Lumpur, Malaysia
                [4 ]ISNI 0000 0001 2308 5949, GRID grid.10347.31, Department of Computer System & Technology, Faculty of Computer Science & Information Technology, , University of Malaya, ; 50603 Kuala Lumpur, Malaysia
                [5 ]ISNI 0000 0001 2308 5949, GRID grid.10347.31, Centre for Data Science, , University of Malaya, ; 50603 Kuala Lumpur, Malaysia
                [6 ]ISNI 0000 0001 0703 675X, GRID grid.430503.1, Division of Medical Oncology, School of Medicine, , University of Colorado Anschutz Medical Campus, ; Aurora, CO 80045 USA
                [7 ]ISNI 0000 0001 2308 5949, GRID grid.10347.31, Institute of Mathematical Sciences, , University of Malaya, ; 50603 Kuala Lumpur, Malaysia
                Article
                3260
                10.1186/s12864-016-3260-7
                5310278
                28198666
                9a0bd49f-5db4-479a-b15c-2caf094822a9
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                The 27th International Conference on Genome Informatics
                Shanghai, China
                3-5 October 2016
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                © The Author(s) 2017

                Genetics
                cell line,gene expression,design,cancer,drug repurposing
                Genetics
                cell line, gene expression, design, cancer, drug repurposing

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