Yuanting Zheng

Fudan University

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Leming Shi

State Key Laboratory of Genetic Engineering

Ying Yu

Fudan University

Luyao Ren

Beijing University of Chinese Medicine

Huixiao Hong

United States Food and Drug Administration

Jingcheng Yang

State Key Laboratory of Genetic Engineering

Wanwan Hou

State Key Laboratory of Genetic Engineering

Weida Tong

National Center for Toxicological Research

Wenming Xiao

United States Food and Drug Administration

Andreas Scherer

Institute for Molecular Medicine Finland

Jun Shang

State Key Laboratory of Genetic Engineering

Cooperative Institutions

Fudan University

246

State Key Laboratory of Genetic Engineering

140

Chinese Academy of Sciences

Fudan University Shanghai Cancer Center

Shanghai Medical College of Fudan University

Chinese Academy of Medical Sciences & Peking Union Medical College

University of Chinese Academy of Sciences

Shanghai Jiao Tong University

Sun Yat-sen University

National Institutes of Health

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A comprehensive personal omics clinical interpreter based on genomic and transcriptomic profiles

bioRxiv (Cold Spring Harbor Laboratory) (2024)

Yaqing Liu Qingwang Chen Qiaochu Chen Leqing Sang Yunjin Wang

Abstract Advances in precision medicine rely on the accurate identification and analysis of molecular alterations for personalized diagnostic, prognostic, and therapeutic decision-making. A critical obstacle is the integration of heterogeneous interpretations of clinically actionable alterations from various knowledgebases. Here, we present the Personal Omics Interpreter (POI), a web-based application engineered to aggregate and interpret therapeutic options, including targeted, immunological, and chemotherapeutic agents, by leveraging personal genomic and transcriptomic profiles. POI employs the Precision Medicine Knowledgebase (PreMedKB), an updated harmonized resource we previously reported, to annotate the clinically actionable somatic variants. It further incorporates a predictive algorithm to broaden therapeutic options according to established gene-gene interactions and offers insights into phenotypic responses of chemotherapeutic agents through phasing germline diplotypes. Validated against three cohort datasets encompassing over 22,000 cancer patients, POI demonstrates consistently high matching rates (94.7 ∼ 95.6%) between patients and suggested therapies, highlighting its potential in supporting precision-driven informed treatment strategies.

Personalized Medicine

Identification

Omics

Precision oncology

10.1101/2024.02.22.581482

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Correction to: Similarities and differences between variants called with human reference genome HG19 or HG38

BMC Bioinformatics (2019)

Bohu Pan Rebecca Kusko Wenming Xiao Yuanting Zheng Zhichao Liu

After publication of this supplement article

10.1186/s12859-019-2776-7

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Citations (7)

Additional file 2 of Hidden biases in germline structural variant detection

Figshare (2021)

Michael M. Khayat Sayed Mohammad Ebrahim Sahraeian Samantha Zarate Andrew Carroll Huixiao Hong

Additional file 2: Table S2. Total and average number of SVs with a genic or intergenic only impact.

10.6084/m9.figshare.17305356

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Additional file 4 of Hidden biases in germline structural variant detection

Figshare (2021)

Michael M. Khayat Sayed Mohammad Ebrahim Sahraeian Samantha Zarate Andrew Carroll Huixiao Hong

Additional file 4: Table S4. Distribution of total and singleton SV types per strategy by SV size.

10.6084/m9.figshare.17305368

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Additional file 8 of Hidden biases in germline structural variant detection

Figshare (2021)

Michael M. Khayat Sayed Mohammad Ebrahim Sahraeian Samantha Zarate Andrew Carroll Huixiao Hong

Additional file 8: Table S7. Distribution of SVs prefiltering by mapper, overlapping across mapper call sets and benchmarked with the long-read PacBio SV call set.

10.6084/m9.figshare.17305389

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Additional file 1 of Hidden biases in germline structural variant detection

Figshare (2021)

Michael M. Khayat Sayed Mohammad Ebrahim Sahraeian Samantha Zarate Andrew Carroll Huixiao Hong

Additional file 1: Table S1. General statistics for the LCL5 sample set pre-filtering requiring an overlap between MetaSV and Parliament2 call sets.

10.6084/m9.figshare.17305350

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Pharmacokinetic characterization of ginsenoside Rh2, an anticancer nutrient from ginseng, in rats and dogs

Food and Chemical Toxicology (2009)

Yi Gu Guangji Wang Jianguo Sun Yuanwei Jia Wei Wang

Membrane permeability

Intestinal Permeability

10.1016/j.fct.2009.06.013

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Citations (115)

Overexpression of CD99 is associated with tumor adaptiveness and indicates the tumor recurrence and therapeutic responses in gliomas

Translational Oncology (2023)

Erfei Shang Shanyue Sun Ruolan Zhang Zehui Cao Qingwang Chen

Glioma undergoes adaptive changes, leading to poor prognosis and resistance to treatment. CD99 influences the migration and invasion of glioma cells and plays an oncogene role. However, whether CD99 can affect the adaptiveness of gliomas is still lacking in research, making its clinical value underestimated. Here, we enrolled our in-house and public multiomics datasets for bioinformatic analysis and conducted immunohistochemistry staining to investigate the role of CD99 in glioma adaptive response and its clinical implications. CD99 is expressed in more adaptative glioma subtypes and cell states. Under hypoxic conditions, CD99 is upregulated in glioma cells and is associated with angiogenesis and metabolic adaptations. Gliomas with over-expressed CD99 also increased the immunosuppressive tumor-associated macrophages. The relevance with tumor adaptiveness of CD99 presented clinical significance. We discovered that CD99 overexpression is associated with short-time recurrence and validated its prognostic value. Additionally, Glioma patients with high expression of CD99 were resistant to chemotherapy and radiotherapy. The CD99 expression was also related to anti-angiogenic and immune checkpoint inhibitor therapy response. Inhibitors of the PI3K-AKT pathway have therapeutic potential against CD99-overexpressing gliomas. Our study identified CD99 as a biomarker characterizing the adaptive response in glioma. Gliomas with high CD99 expression are highly tolerant to stress conditions such as hypoxia and antitumor immunity, making treatment responses dimmer and tumor progression. Therefore, for patients with CD99-overexpressing gliomas, tumor adaptiveness should be fully considered during treatment to avoid drug resistance, and closer clinical monitoring should be carried out to improve the prognosis.

CD99

Temozolomide

10.1016/j.tranon.2023.101759

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Citations (8)

Additional file 10 of Assessing reproducibility of inherited variants detected with short-read whole genome sequencing

Figshare (2022)

Bohu Pan Luyao Ren Vitor Onuchic Meijian Guan Rebecca Kusko

Additional file 10: Table S9. Factor contribution analysis by boosted tree.

10.6084/m9.figshare.17798258

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