Pub Date : 2021-07-01DOI: 10.1158/1538-7445.AM2021-260
Yaoqing Shen, M. Bonakdar, L. Williamson, E. Pleasance, K. Mungall, Richard A. Moore, A. Mungall, S. Yip, Anna F. Lee, C. Dunham, J. Laskin, M. Marra, Steven J. M. Jones, S. Rassekh, R. Deyell
{"title":"Abstract 260: Application of integrated analysis of whole genome sequencing and RNA sequencing to personalized therapy decision making in pediatric and young adult cancer","authors":"Yaoqing Shen, M. Bonakdar, L. Williamson, E. Pleasance, K. Mungall, Richard A. Moore, A. Mungall, S. Yip, Anna F. Lee, C. Dunham, J. Laskin, M. Marra, Steven J. M. Jones, S. Rassekh, R. Deyell","doi":"10.1158/1538-7445.AM2021-260","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-260","url":null,"abstract":"","PeriodicalId":73617,"journal":{"name":"Journal of bioinformatics and systems biology : Open access","volume":"58 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85825829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.1158/1538-7445.AM2021-178
Maayan Baron, T. Ideker
Desmosomes are transmembrane protein complexes that contribute to cell-cell adhesion in the epithelia and other tissues under mechanical stress. Aberrant desmosome expression is often associated with developmental diseases leading to impaired tissue integrity. Recently, similar findings have been reported in cancer; Mutations in desmosomes genes have been observed in various cancer types including skin cancer, head and neck and lung cancer, however mostly epigenetic alterations have been used to associate desmosomes as suppressors of tumor metastasis. Here, we report that desmosomes are frequently mutated in seven cancer types. In melanoma, we find that over 70% of tumors have non-synonymous mutations in desmosomes, and that the desmosome mutational burden is associated with a strong decrease in mRNA expression levels in primary tumor samples (R = -0.23). Differential gene expression analysis and functional characterizations between mutant and wild-type tumors implicates the mutated cells in promoting cell proliferation at early stages of tumorigenesis. These results emerge uniquely from a systems-level analysis integrating multiple proteins in complexes and multiple cell types in heterogeneous tumors. Citation Format: Maayan Baron, Trey Ideker. Desmosome mutations in melanoma promote cellular proliferation and disease progression [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 178.
{"title":"Abstract 178: Desmosome mutations in melanoma promote cellular proliferation and disease progression","authors":"Maayan Baron, T. Ideker","doi":"10.1158/1538-7445.AM2021-178","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-178","url":null,"abstract":"Desmosomes are transmembrane protein complexes that contribute to cell-cell adhesion in the epithelia and other tissues under mechanical stress. Aberrant desmosome expression is often associated with developmental diseases leading to impaired tissue integrity. Recently, similar findings have been reported in cancer; Mutations in desmosomes genes have been observed in various cancer types including skin cancer, head and neck and lung cancer, however mostly epigenetic alterations have been used to associate desmosomes as suppressors of tumor metastasis. Here, we report that desmosomes are frequently mutated in seven cancer types. In melanoma, we find that over 70% of tumors have non-synonymous mutations in desmosomes, and that the desmosome mutational burden is associated with a strong decrease in mRNA expression levels in primary tumor samples (R = -0.23). Differential gene expression analysis and functional characterizations between mutant and wild-type tumors implicates the mutated cells in promoting cell proliferation at early stages of tumorigenesis. These results emerge uniquely from a systems-level analysis integrating multiple proteins in complexes and multiple cell types in heterogeneous tumors. Citation Format: Maayan Baron, Trey Ideker. Desmosome mutations in melanoma promote cellular proliferation and disease progression [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 178.","PeriodicalId":73617,"journal":{"name":"Journal of bioinformatics and systems biology : Open access","volume":"42 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86373588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.1158/1538-7445.AM2021-203
C. Tlemsani, L. Pongor, Fathi Elloumi, L. Girard, K. Huffman, N. Roper, S. Varma, Augustin Luna, V. Rajapakse, P. Boudou-Rouquette, R. Sebastian, K. Kohn, J. Krushkal, M. Aladjem, B. Teicher, P. Meltzer, W. Reinhold, J. Minna, Anish Thomas, Y. Pommier
The typical low life expectancy and limited therapeutic options for patients with small cell lung cancer (SCLC) caused the National Cancer Institute (NCI) to categorize SCLC as “recalcitrant” cancer. SCLC-CellMiner (https://discover.nci.nih.gov/SclcCellMinerCDB) integrates drug sensitivity and genomic data from 118 patient-derived SCLC cell lines, providing a unique genomic and pharmacological resource. Transcriptomic profiling validates the SCLC consensus nomenclature based on expression of 4 master transcription factors NEUROD1, ASCL1, POU2F3 and YAP1 (NAPY classification) and demonstrate differential transcriptional networks driven by these lineage specific transcription factors. Our analyses reveal transcription networks linking SCLC subtypes with MYC and its paralogs MYCL and MYCN and inactivation of the NOTCH pathway in the neuroendocrine SCLC (N, A & P subgroups). By contrast, YAP1-driven SCLC (SCLC-Y) express the NOTCH pathway and co-express both YAP/TAZ and its negative regulator genes driving the Hippo pathway. SCLC-Y cell lines show the greatest resistance to the standard of care drugs (etoposide, cisplatin and topotecan) while PI3K-AKT-mTOR inhibitors show a higher activity in this subgroup. To explore the immune pathways and the potential value of the transciption factors based classification for selecting SCLC patients likely to respond to immune checkpoint inhibitors, we explored a transcriptome signature based on 18 established native immune response and antigen-presenting genes (APM score). The SCLC-Y cell lines are the only subset expressing innate immune response genes. SCLC-CellMiner is a powerfull tool demonstrating the value of cancer cell line genomic and pharmacological databases. Our analyses suggest the potential genomic molecular classifications to select patients for targeted therapies and immunotherapy, such as patients in the SCLC-Y subgroup who may be most responsive to immune checkpoints modulators. Citation Format: Camille Tlemsani, Lorinc Pongor, Fathi Elloumi, Luc Girard, Kenneth Huffman, Nitin Roper, Sudhir Varma, Augustin Luna, Vinodh Rajapakse, Pascaline Boudou-Rouquette, Robin Sebastian, Kurt Kohn, Julia Krushkal, Mirit Aladjem, Beverly Teicher, Paul Meltzer, William Reinhold, John Minna, Anish Thomas, Yves Pommier. SCLC-CellMiner: An extensive cell line genomic and pharmacology resource identifies a subgroup of small cell lung cancers sensitive to targeted therapies and immunotherapies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 203.
小细胞肺癌(SCLC)患者典型的低预期寿命和有限的治疗选择导致美国国家癌症研究所(NCI)将SCLC归类为“顽固性”癌症。SCLC- cellminer (https://discover.nci.nih.gov/SclcCellMinerCDB)整合了118个患者来源的SCLC细胞系的药物敏感性和基因组数据，提供了独特的基因组和药理学资源。转录组学分析验证了基于4个主要转录因子NEUROD1、ASCL1、POU2F3和YAP1表达的SCLC共识命名法(NAPY分类)，并展示了由这些谱系特异性转录因子驱动的差异转录网络。我们的分析揭示了连接SCLC亚型与MYC及其类似物MYCL和MYCN的转录网络，以及神经内分泌SCLC (N, A和P亚组)中NOTCH通路的失活。相比之下，yap1驱动的SCLC (SCLC- y)表达NOTCH通路，并共同表达YAP/TAZ及其驱动Hippo通路的负调控基因。SCLC-Y细胞系对标准护理药物(依泊苷、顺铂和拓扑替康)表现出最大的耐药性，而PI3K-AKT-mTOR抑制剂在该亚组中表现出更高的活性。为了探索免疫途径和基于转录因子的分类在选择可能对免疫检查点抑制剂有反应的SCLC患者中的潜在价值，我们探索了基于18个已建立的天然免疫反应和抗原呈递基因(APM评分)的转录组特征。SCLC-Y细胞系是唯一表达先天免疫应答基因的亚群。SCLC-CellMiner是一个强大的工具，展示了癌细胞系基因组和药理学数据库的价值。我们的分析表明，潜在的基因组分子分类可以选择靶向治疗和免疫治疗的患者，例如SCLC-Y亚组患者，他们可能对免疫检查点调节剂最敏感。引文格式:Camille Tlemsani, Lorinc Pongor, Fathi Elloumi, Luc Girard, Kenneth Huffman, Nitin Roper, Sudhir Varma, Augustin Luna, Vinodh Rajapakse, Pascaline boudoul - rouquette, Robin Sebastian, Kurt Kohn, Julia Krushkal, Mirit Aladjem, Beverly Teicher, Paul Meltzer, William Reinhold, John Minna, Anish Thomas, Yves Pommier。SCLC-CellMiner:广泛的细胞系基因组学和药理学资源鉴定了对靶向治疗和免疫治疗敏感的小细胞肺癌亚群[摘要]。见:美国癌症研究协会2021年年会论文集;2021年4月10日至15日和5月17日至21日。费城(PA): AACR;癌症杂志，2021;81(13 -增刊):摘要第203期。
{"title":"Abstract 203: SCLC-CellMiner: An extensive cell line genomic and pharmacology resource identifies a subgroup of small cell lung cancers sensitive to targeted therapies and immunotherapies","authors":"C. Tlemsani, L. Pongor, Fathi Elloumi, L. Girard, K. Huffman, N. Roper, S. Varma, Augustin Luna, V. Rajapakse, P. Boudou-Rouquette, R. Sebastian, K. Kohn, J. Krushkal, M. Aladjem, B. Teicher, P. Meltzer, W. Reinhold, J. Minna, Anish Thomas, Y. Pommier","doi":"10.1158/1538-7445.AM2021-203","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-203","url":null,"abstract":"The typical low life expectancy and limited therapeutic options for patients with small cell lung cancer (SCLC) caused the National Cancer Institute (NCI) to categorize SCLC as “recalcitrant” cancer. SCLC-CellMiner (https://discover.nci.nih.gov/SclcCellMinerCDB) integrates drug sensitivity and genomic data from 118 patient-derived SCLC cell lines, providing a unique genomic and pharmacological resource. Transcriptomic profiling validates the SCLC consensus nomenclature based on expression of 4 master transcription factors NEUROD1, ASCL1, POU2F3 and YAP1 (NAPY classification) and demonstrate differential transcriptional networks driven by these lineage specific transcription factors. Our analyses reveal transcription networks linking SCLC subtypes with MYC and its paralogs MYCL and MYCN and inactivation of the NOTCH pathway in the neuroendocrine SCLC (N, A & P subgroups). By contrast, YAP1-driven SCLC (SCLC-Y) express the NOTCH pathway and co-express both YAP/TAZ and its negative regulator genes driving the Hippo pathway. SCLC-Y cell lines show the greatest resistance to the standard of care drugs (etoposide, cisplatin and topotecan) while PI3K-AKT-mTOR inhibitors show a higher activity in this subgroup. To explore the immune pathways and the potential value of the transciption factors based classification for selecting SCLC patients likely to respond to immune checkpoint inhibitors, we explored a transcriptome signature based on 18 established native immune response and antigen-presenting genes (APM score). The SCLC-Y cell lines are the only subset expressing innate immune response genes. SCLC-CellMiner is a powerfull tool demonstrating the value of cancer cell line genomic and pharmacological databases. Our analyses suggest the potential genomic molecular classifications to select patients for targeted therapies and immunotherapy, such as patients in the SCLC-Y subgroup who may be most responsive to immune checkpoints modulators. Citation Format: Camille Tlemsani, Lorinc Pongor, Fathi Elloumi, Luc Girard, Kenneth Huffman, Nitin Roper, Sudhir Varma, Augustin Luna, Vinodh Rajapakse, Pascaline Boudou-Rouquette, Robin Sebastian, Kurt Kohn, Julia Krushkal, Mirit Aladjem, Beverly Teicher, Paul Meltzer, William Reinhold, John Minna, Anish Thomas, Yves Pommier. SCLC-CellMiner: An extensive cell line genomic and pharmacology resource identifies a subgroup of small cell lung cancers sensitive to targeted therapies and immunotherapies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 203.","PeriodicalId":73617,"journal":{"name":"Journal of bioinformatics and systems biology : Open access","volume":"96 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89101699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.1158/1538-7445.AM2021-192
Aleksandr Sarachakov, V. Svekolkin, Zoia Antysheva, Jessica H. Brown, A. Bagaev, N. Fowler
{"title":"Abstract 192: MutAnt: Mutation annotation machine learning algorithm for pathogenicity evaluation of single nonsynonymous nucleotide substitutions in cancer cells","authors":"Aleksandr Sarachakov, V. Svekolkin, Zoia Antysheva, Jessica H. Brown, A. Bagaev, N. Fowler","doi":"10.1158/1538-7445.AM2021-192","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-192","url":null,"abstract":"","PeriodicalId":73617,"journal":{"name":"Journal of bioinformatics and systems biology : Open access","volume":"17 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80083665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.1158/1538-7445.AM2021-173
Qian Ke, Wikum Dinalankara, L. Younes, D. Geman, L. Marchionni
{"title":"Abstract 173: Efficient representations of tumor diversity with paired DNA-RNA aberrations","authors":"Qian Ke, Wikum Dinalankara, L. Younes, D. Geman, L. Marchionni","doi":"10.1158/1538-7445.AM2021-173","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-173","url":null,"abstract":"","PeriodicalId":73617,"journal":{"name":"Journal of bioinformatics and systems biology : Open access","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79764673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.1158/1538-7445.AM2021-4
Giorgio Gaglia, S. Kabraji, Danae Argyropoulou, Yang Dai, J. Bergholz, S. Coy, Jia-Ren Lin, E. Winer, D. Dillon, Jean J. Zhao, P. Sorger, S. Santagata
{"title":"Abstract 4: Temporal and spatial topography of cell proliferation in cancer","authors":"Giorgio Gaglia, S. Kabraji, Danae Argyropoulou, Yang Dai, J. Bergholz, S. Coy, Jia-Ren Lin, E. Winer, D. Dillon, Jean J. Zhao, P. Sorger, S. Santagata","doi":"10.1158/1538-7445.AM2021-4","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-4","url":null,"abstract":"","PeriodicalId":73617,"journal":{"name":"Journal of bioinformatics and systems biology : Open access","volume":"36 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86266835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.1158/1538-7445.AM2021-234
A. Jazayeri, Niusha Jafari, Christopher C. Yang, N. Nikita, G. Yao
{"title":"Abstract 234: Risk of sepsis among patients with prostate cancer: A network-based modeling approach","authors":"A. Jazayeri, Niusha Jafari, Christopher C. Yang, N. Nikita, G. Yao","doi":"10.1158/1538-7445.AM2021-234","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-234","url":null,"abstract":"","PeriodicalId":73617,"journal":{"name":"Journal of bioinformatics and systems biology : Open access","volume":"64 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77319839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.1158/1538-7445.AM2021-252
Kim Wager, Dheepa Chari, S. Ho, Tomas J Rees, R. J. Schijvenaars
{"title":"Abstract 252: Navigating networks of oncology biomarkers mined from the scientific literature: A new open research tool","authors":"Kim Wager, Dheepa Chari, S. Ho, Tomas J Rees, R. J. Schijvenaars","doi":"10.1158/1538-7445.AM2021-252","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-252","url":null,"abstract":"","PeriodicalId":73617,"journal":{"name":"Journal of bioinformatics and systems biology : Open access","volume":"45 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84238585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.1158/1538-7445.AM2021-262
Richard E. Grewelle, Kalin L. Wilson, D. Brantley-Sieders
{"title":"Abstract 262: Statistical Bliss: A novel framework for statistical assessment of drug synergy","authors":"Richard E. Grewelle, Kalin L. Wilson, D. Brantley-Sieders","doi":"10.1158/1538-7445.AM2021-262","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-262","url":null,"abstract":"","PeriodicalId":73617,"journal":{"name":"Journal of bioinformatics and systems biology : Open access","volume":"35 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88457008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.1158/1538-7445.AM2021-243
L. Piccotti, L. Mirandola, M. Chiriva-Internati
Adoptive cell therapy has been proven a powerful approach for the cure of cancer and other diseases. In particular, the selection of appropriate immunogenic targets has been key to positive outcomes in clinical settings. The availability of RNA-Seq analysis, the accessibility to large data repositories such as TCGA and GTEx, and the creation of new bioinformatic tools have accelerated the process of neoantigen discovery. However, most of the current algorithms are encumbered by the intrinsic complexity of predicting antigen immunogenicity. Diamond™ is a novel artificial intelligence and cognitive machine and deep learning platform to predict peptide processing, HLA binding, and T cell activation. To validate the predictive value of DIAMOND algorithms, the meta-analyses of expression data of cancer-testis antigen New York Esophageal Squamous Cell Carcinoma 1 (NY-ESO-1) and predictions for the immunogenic peptides were compared to experimental data in the literature. In agreement with published clinical observations, DIAMOND metanalysis showed NY-ESO-1 genic overexpression in skin cutaneous melanoma, lung adenocarcinoma, and sarcoma. Moreover, DIAMOND predicted an MHC binding affinity of 0.289 with Supertype A2 for a new NY-ESO-1 peptide, which has been successfully targeted in clinical trials for patients with HLA-A*02:01, as well as it mirrored published data in its prediction of peptide affinity binding in NY-ESO-1–specific MHC II–restricted T cell receptors. Taken together these data support DIAMOND as a reliable platform for the discovery of new immunogenic targets for cancer therapy. Citation Format: Lucia Piccotti, Leonardo Mirandola, Maurizio Chiriva-Internati. Identification of novel epitopes of NY-ESO-1 for solid malignancies by Kiromic proprietary search engine Diamond [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 243.
{"title":"Abstract 243: Identification of novel epitopes of NY-ESO-1 for solid malignancies by Kiromic proprietary search engine Diamond","authors":"L. Piccotti, L. Mirandola, M. Chiriva-Internati","doi":"10.1158/1538-7445.AM2021-243","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-243","url":null,"abstract":"Adoptive cell therapy has been proven a powerful approach for the cure of cancer and other diseases. In particular, the selection of appropriate immunogenic targets has been key to positive outcomes in clinical settings. The availability of RNA-Seq analysis, the accessibility to large data repositories such as TCGA and GTEx, and the creation of new bioinformatic tools have accelerated the process of neoantigen discovery. However, most of the current algorithms are encumbered by the intrinsic complexity of predicting antigen immunogenicity. Diamond™ is a novel artificial intelligence and cognitive machine and deep learning platform to predict peptide processing, HLA binding, and T cell activation. To validate the predictive value of DIAMOND algorithms, the meta-analyses of expression data of cancer-testis antigen New York Esophageal Squamous Cell Carcinoma 1 (NY-ESO-1) and predictions for the immunogenic peptides were compared to experimental data in the literature. In agreement with published clinical observations, DIAMOND metanalysis showed NY-ESO-1 genic overexpression in skin cutaneous melanoma, lung adenocarcinoma, and sarcoma. Moreover, DIAMOND predicted an MHC binding affinity of 0.289 with Supertype A2 for a new NY-ESO-1 peptide, which has been successfully targeted in clinical trials for patients with HLA-A*02:01, as well as it mirrored published data in its prediction of peptide affinity binding in NY-ESO-1–specific MHC II–restricted T cell receptors. Taken together these data support DIAMOND as a reliable platform for the discovery of new immunogenic targets for cancer therapy. Citation Format: Lucia Piccotti, Leonardo Mirandola, Maurizio Chiriva-Internati. Identification of novel epitopes of NY-ESO-1 for solid malignancies by Kiromic proprietary search engine Diamond [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 243.","PeriodicalId":73617,"journal":{"name":"Journal of bioinformatics and systems biology : Open access","volume":"174 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88031642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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