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  • 1
    Online Resource
    Online Resource
    Clinical Targeted Next-Generation sequencing Panels for Detection of Somatic Variants in Gliomas
    Korean Cancer Association ; 2020
    In:  Cancer Research and Treatment Vol. 52, No. 1 ( 2020-01-15), p. 41-50
    Details
    In: Cancer Research and Treatment, Korean Cancer Association, Vol. 52, No. 1 ( 2020-01-15), p. 41-50
    Type of Medium: Online Resource
    ISSN: 1598-2998 , 2005-9256
    URL: Article
    DOI: 10.4143/crt.2019.036
    Language: English
    Publisher: Korean Cancer Association
    Publication Date: 2020
    detail.hit.zdb_id: 2514151-X
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  • 2
    Online Resource
    Online Resource
    Pharmacogenomic analysis of patient-derived tumor cells in gynecologic cancers
    Springer Science and Business Media LLC ; 2019
    In:  Genome Biology Vol. 20, No. 1 ( 2019-12)
    Details
    In: Genome Biology, Springer Science and Business Media LLC, Vol. 20, No. 1 ( 2019-12)
    Abstract: Gynecologic malignancy is one of the leading causes of mortality in female adults worldwide. Comprehensive genomic analysis has revealed a list of molecular aberrations that are essential to tumorigenesis, progression, and metastasis of gynecologic tumors. However, targeting such alterations has frequently led to treatment failures due to underlying genomic complexity and simultaneous activation of various tumor cell survival pathway molecules. A compilation of molecular characterization of tumors with pharmacological drug response is the next step toward clinical application of patient-tailored treatment regimens. Results Toward this goal, we establish a library of 139 gynecologic tumors including epithelial ovarian cancers (EOCs), cervical, endometrial tumors, and uterine sarcomas that are genomically and/or pharmacologically annotated and explore dynamic pharmacogenomic associations against 37 molecularly targeted drugs. We discover lineage-specific drug sensitivities based on subcategorization of gynecologic tumors and identify TP53 mutation as a molecular determinant that elicits therapeutic response to poly (ADP-Ribose) polymerase (PARP) inhibitor. We further identify transcriptome expression of inhibitor of DNA biding 2 (ID2) as a potential predictive biomarker for treatment response to olaparib. Conclusions Together, our results demonstrate the potential utility of rapid drug screening combined with genomic profiling for precision treatment of gynecologic cancers.
    Type of Medium: Online Resource
    ISSN: 1474-760X
    URL: Article
    DOI: 10.1186/s13059-019-1848-3
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2019
    detail.hit.zdb_id: 2040529-7
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  • 3
    Online Resource
    Online Resource
    Therapeutic Efficacy of GC1118, a Novel Anti-EGFR Antibody, against Glioblastoma with High EGFR Amplification in Patient-Derived Xenografts
    MDPI AG ; 2020
    In:  Cancers Vol. 12, No. 11 ( 2020-10-31), p. 3210-
    Details
    In: Cancers, MDPI AG, Vol. 12, No. 11 ( 2020-10-31), p. 3210-
    Abstract: We aimed to evaluate the preclinical efficacy of GC1118, a novel anti-epidermal growth factor receptor (EGFR) monoclonal antibody (mAb), against glioblastoma (GBM) tumors using patient-derived xenograft (PDX) models. A total of 15 distinct GBM PDX models were used to evaluate the therapeutic efficacy of GC1118. Genomic data derived from PDX models were analyzed to identify potential biomarkers associated with the anti-tumor efficacy of GC1118. A patient-derived cell-based high-throughput drug screening assay was performed to further validate the efficacy of GC1118. Compared to cetuximab, GC1118 exerted comparable growth inhibitory effects on the GBM tumors in the PDX models. We confirmed that GC1118 accumulated within the tumor by crossing the blood–brain barrier in in vivo specimens and observed the survival benefit in GC1118-treated intracranial models. Genomic analysis revealed high EGFR amplification as a potent biomarker for predicting the therapeutic efficacy of GC1118 in GBM tumors. In summary, GC1118 exerted a potent anti-tumor effect on GBM tumors in PDX models, and its therapeutic efficacy was especially pronounced in the tumors with high EGFR amplification. Our study supports the importance of patient stratification based on EGFR copy number variation in clinical trials for GBM. The superiority of GC1118 over other EGFR mAbs in GBM tumors should be assessed in future studies.
    Type of Medium: Online Resource
    ISSN: 2072-6694
    URL: Article
    DOI: 10.3390/cancers12113210
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2527080-1
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  • 4
    Online Resource
    Online Resource
    Mutation-specific non-canonical pathway of PTEN as a distinct therapeutic target for glioblastoma
    Springer Science and Business Media LLC ; 2021
    In:  Cell Death & Disease Vol. 12, No. 4 ( 2021-04-07)
    Details
    In: Cell Death & Disease, Springer Science and Business Media LLC, Vol. 12, No. 4 ( 2021-04-07)
    Abstract: PTEN is one of the most frequently altered tumor suppressor genes in malignant tumors. The dominant-negative effect of PTEN alteration suggests that the aberrant function of PTEN mutation might be more disastrous than deletion, the most frequent genomic event in glioblastoma (GBM). This study aimed to understand the functional properties of various PTEN missense mutations and to investigate their clinical relevance. The genomic landscape of PTEN alteration was analyzed using the Samsung Medical Center GBM cohort and validated via The Cancer Genome Atlas dataset. Several hotspot mutations were identified, and their subcellular distributions and phenotypes were evaluated. We established a library of cancer cell lines that overexpress these mutant proteins using the U87MG and patient-derived cell models lacking functional PTEN . PTEN mutations were categorized into two major subsets: missense mutations in the phosphatase domain and truncal mutations in the C2 domain. We determined the subcellular compartmentalization of four mutant proteins (H93Y, C124S, R130Q, and R173C) from the former group and found that they had distinct localizations; those associated with invasive phenotypes (‘edge mutations’) localized to the cell periphery, while the R173C mutant localized to the nucleus. Invasive phenotypes derived from edge substitutions were unaffected by an anti-PI3K/Akt agent but were disrupted by microtubule inhibitors. PTEN mutations exhibit distinct functional properties regarding their subcellular localization. Further, some missense mutations (‘edge mutations’) in the phosphatase domain caused enhanced invasiveness associated with dysfunctional cytoskeletal assembly, thus suggesting it to be a potent therapeutic target.
    Type of Medium: Online Resource
    ISSN: 2041-4889
    URL: Article
    DOI: 10.1038/s41419-021-03657-0
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2021
    detail.hit.zdb_id: 2541626-1
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  • 5
    Online Resource
    Online Resource
    NIMG-20. MULTI-HABITAT RADIOMICS UNRAVELS DISTINCT PHENOTYPIC SUBTYPES OF GLIOBLASTOMA WITH CLINICAL AND GENOMIC SIGNIFICANCE
    Oxford University Press (OUP) ; 2020
    In:  Neuro-Oncology Vol. 22, No. Supplement_2 ( 2020-11-09), p. ii151-ii151
    Details
    In: Neuro-Oncology, Oxford University Press (OUP), Vol. 22, No. Supplement_2 ( 2020-11-09), p. ii151-ii151
    Abstract: We aimed to evaluate the potential of radiomics as an imaging biomarker for GBM patients and explore the molecular rationale behind radiomics by radio-genomics approach. METHODS A total of 144 primary GBM patients were included in this study as a training cohort. Using multi-parametric MR images, radiomics features were extracted from multi-habitats of the tumor. We applied Cox-LASSO algorithm to build a survival prediction model and validated this model using an independent validation cohort (56 patients from Vienna). With the selected radiomics features, GBM patients were consensus clustered to reveal inherent phenotypic subtypes. The subtypes were further explored in terms of genomic signatures. RESULTS GBM patients were successfully stratified by the radiomics risk score, a weighted sum of radiomics features, corroborating the potential of radiomics as a prognostic biomarker. Using consensus clustering, we identified three distinct subtypes which significantly differed in the prognosis (‘heterogenous enhancing’, ‘rim-enhancing necrotic’, and ‘cystic’ subtype). Multi-variate cox regression analysis confirmed that radiomics subtype as an independent prognostic factor. Transcriptomic traits enriched in individual subtypes were in accordance with imaging phenotypes summarized by radiomics. For example, rim-enhancing necrotic subtype was well described by radiomics profiling (T2 autocorrelation & flat shape) and highlighted by the inflammatory genomic signatures, which well correlated to its phenotypic peculiarity (necrosis). CONCLUSIONS The present study confirmed the feasibility of radiomics as an imaging biomarker for GBM patients with comprehensible biologic annotation. Imaging subtypes derived from radiomics successfully recapitulate the genomic underpinnings of GBM tumors and in turn reinforce their potential as a prognostic biomarker.
    Type of Medium: Online Resource
    ISSN: 1522-8517 , 1523-5866
    URL: Article
    DOI: 10.1093/neuonc/noaa215.633
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2020
    detail.hit.zdb_id: 2094060-9
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  • 6
    Online Resource
    Online Resource
    GENE-12. ANALYSIS OF FAILURE PATTERNS IN MALIGNANT GLIOMA: EXPLORING THE GENETIC LANDSCAPE OF PATTERN OF FAILURE
    Oxford University Press (OUP) ; 2019
    In:  Neuro-Oncology Vol. 21, No. Supplement_6 ( 2019-11-11), p. vi100-vi100
    Details
    In: Neuro-Oncology, Oxford University Press (OUP), Vol. 21, No. Supplement_6 ( 2019-11-11), p. vi100-vi100
    Abstract: Failure patterns in malignant gliomas have been described in previous literatures, however, studies were limited to analyze clinical features to account for predisposition to distinct failure patterns. Present study aimed to describe the landscape of failure patterns in malignant glioma from large cohort by integrating multi-omics data and investigate the genetic backgrounds of distinct failure patterns. A total of 423 cases from 325 patients who enrolled at the registry of IRCR at SMC were reviewed for their pattern of failure. Failure patterns were categorized into local, distant recurrence and leptomeningeal seeding regarding recurrent tumors’ spatial relation to primary location. Genomic data was available for 327 (DNAseq) and 259 samples (RNAseq), respectively. Glioblastoma was the most prevalent histologic type in study cohort (81.2%)) and majority of cases experienced the recurrence (79.0%). None of clinical parameters (e.g. age, sex, extent of operation and history of prior therapy) failed to show any significant association with failure patterns. Although local recurrence was most prevalent (63.8%) among failure patterns in malignant gliomas, considerable portion of patients (37.8%) demonstrated other types of failure patterns even in their initial relapse. Multivariate analysis demonstrated that failure pattern was significant prognostic factor to overall survival (remote recurrence, HR=1.59, p-value=0.009; leptomeningeal seeding, HR=2.17, p-value 〈 0.001). Genomic analysis including mutational profile revealed distinct molecular landscape of malignant gliomas according to failure patterns, which suggested that innate biologic characteristics of tumors might contribute to develop distinct failure patterns upon recurrence. PTEN mutation was significantly enriched in tumors of distant recurrence (p-value=0.026). We described the landscape of failure patterns in malignant gliomas by integrating clinical and genomic data. Considerable amount of malignant glioma patients experienced distinct failure patterns other than local recurrence and their clinical outcome as well as genetic background demonstrated invasive characteristic of these tumors.
    Type of Medium: Online Resource
    ISSN: 1522-8517 , 1523-5866
    URL: Article
    DOI: 10.1093/neuonc/noz175.414
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2019
    detail.hit.zdb_id: 2094060-9
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  • 7
    Online Resource
    Online Resource
    Multi-Habitat Radiomics Unravels Distinct Phenotypic Subtypes of Glioblastoma with Clinical and Genomic Significance
    MDPI AG ; 2020
    In:  Cancers Vol. 12, No. 7 ( 2020-06-27), p. 1707-
    Details
    In: Cancers, MDPI AG, Vol. 12, No. 7 ( 2020-06-27), p. 1707-
    Abstract: We aimed to evaluate the potential of radiomics as an imaging biomarker for glioblastoma (GBM) patients and explore the molecular rationale behind radiomics using a radio-genomics approach. A total of 144 primary GBM patients were included in this study (training cohort). Using multi-parametric MR images, radiomics features were extracted from multi-habitats of the tumor. We applied Cox-LASSO algorithm to build a survival prediction model, which we validated using an independent validation cohort. GBM patients were consensus clustered to reveal inherent phenotypic subtypes. GBM patients were successfully stratified by the radiomics risk score, a weighted sum of radiomics features, corroborating the potential of radiomics as a prognostic biomarker. Using consensus clustering, we identified three distinct subtypes which significantly differed in the prognosis (“heterogenous enhancing”, “rim-enhancing necrotic”, and “cystic” subtypes). Transcriptomic traits enriched in individual subtypes were in accordance with imaging phenotypes summarized by radiomics. For example, rim-enhancing necrotic subtype was well described by radiomics profiling (T2 autocorrelation and flat shape) and highlighted by the inflammatory genomic signatures, which well correlated to its phenotypic peculiarity (necrosis). This study showed that imaging subtypes derived from radiomics successfully recapitulated the genomic underpinnings of GBMs and thereby confirmed the feasibility of radiomics as an imaging biomarker for GBM patients with comprehensible biologic annotation.
    Type of Medium: Online Resource
    ISSN: 2072-6694
    URL: Article
    DOI: 10.3390/cancers12071707
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2527080-1
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  • 8
    Online Resource
    Online Resource
    Comprehensive pharmacogenomic characterization of gastric cancer
    Springer Science and Business Media LLC ; 2020
    In:  Genome Medicine Vol. 12, No. 1 ( 2020-12)
    Details
    In: Genome Medicine, Springer Science and Business Media LLC, Vol. 12, No. 1 ( 2020-12)
    Abstract: Gastric cancer is among the most lethal human malignancies. Previous studies have identified molecular aberrations that constitute dynamic biological networks and genomic complexities of gastric tumors. However, the clinical translation of molecular-guided targeted therapy is hampered by challenges. Notably, solid tumors often harbor multiple genetic alterations, complicating the development of effective treatments. Methods To address such challenges, we established a comprehensive dataset of molecularly annotated patient derivatives coupled with pharmacological profiles for 60 targeted agents to explore dynamic pharmacogenomic interactions in gastric cancers. Results We identified lineage-specific drug sensitivities based on histopathological and molecular subclassification, including substantial sensitivities toward VEGFR and EGFR inhibition therapies in diffuse- and signet ring-type gastric tumors, respectively. We identified potential therapeutic opportunities for WNT pathway inhibitors in ALK -mutant tumors, a significant association between PIK3CA- E542K mutation and AZD5363 response, and transcriptome expression of RNF11 as a potential predictor of response to gefitinib. Conclusions Collectively, our results demonstrate the feasibility of drug screening combined with tumor molecular characterization to facilitate personalized therapeutic regimens for gastric tumors.
    Type of Medium: Online Resource
    ISSN: 1756-994X
    URL: Article
    DOI: 10.1186/s13073-020-0717-8
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2020
    detail.hit.zdb_id: 2484394-5
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