Ding Ma, Fudan University Shanghai Cancer Center,2022.05.01

Description

Hormone receptor positive HER2 negative (HR+/HER2-) is the most prevalent type of breast cancer, in which endocrine therapy resistance and distant relapse remain unmet challenges. An accurate molecular classification is urgently required for precision treatment. Herein, we established the largest multi-omics cohort of Asian HR+/HER2- breast cancer to date. We introduced four novel molecular subtypes by integrating somatic copy number aberrations, somatic mutations, transcriptome, proteomics, metabolomics, and single-cell RNA sequencing of 583 HR+/HER2- breast cancers, namely canonical luminal, immunogenic, proliferative, and receptor tyrosine kinase (RTK)-driven subtypes. Each molecular subtype showed distinct biology, informed therapeutic strategies, and was validated in The Cancer Genome Atlas cohort. The RTK-driven subtype was featured by the activation of the RTK pathways and associated with endocrine therapy resistance. The immunogenic subtype had enriched immune cells and could benefit from immune checkpoint therapy. For clinical access to the molecular classification, we developed convolutional neural network models through deep learning methods based on digital pathology. Altogether, the integrative molecular classification provides novel insights into the biology, guiding precision treatment, and leading to clinical benefit of HR+/HER2- breast cancers.

OEP003358

Ding Ma, Fudan University Shanghai Cancer Center,2022.01.06

Description

Integrated omics in large cohorts has greatly revolutionized the clinical management of breast cancer. However, Asian patients are underrepresented in publicly available studies. Here, we established a multiomic cohort of 773 Chinese breast cancer patients, which is the largest collection of comprehensively profiled Asian breast cancers to date. We systemically analyzed their genomic, transcriptomic, proteomic, metabolomic, radiomic and digital pathology characteristics. Compared with Caucasian breast cancers, Asian cases were much younger with more targetable AKT1 mutations. Integrated analysis revealed a more HER2-enriched subtype and correspondingly more frequent ERBB2 amplification and higher HER2 protein abundance in the Chinese HR+HER2+ cohort, stressing anti-HER2 therapy for these cases. With large-scale proteomic data, we revealed subtype-specific effects of somatic copy number alterations on proteins. Importantly, comprehensive metabolomic and proteomic analyzes highlighted ferroptosis as a potential therapeutic target for basal-like tumors. Furthermore, immunogenomic analysis deciphered the heterogeneity of the tumor microenvironment. Collectively, we provide a comprehensive multiomic atlas that sheds new light on the biology and ethnic specificity of breast cancer in the Asian population and offers clues for precision treatment. The dataset also represents a unique public resource for further discovery.

OEP003049

Yuchen Pei, Fudan University Shanghai Cancer Center,2020.06.22

Description

Remarkable advances in next-generation sequencing technology enable the wide usage of sequencing as a clinical tool. Here, we conducted a large-scale prospective clinical sequencing program using the Fudan-BC panel, and comprehensively analyzed the clinical and genomic characteristics for Chinese breast cancer. The mutational landscape of the 1,134 breast cancers revealed that the most significant differences between Chinese and Western patients occurred in the hormone receptor positive, human epidermal growth factor receptor 2 negative breast cancer subtype. Mutations in p53 and Hippo signaling pathways were more prevalent, and 2 mutually exclusive and 9 co-occurring patterns existed among 9 oncogenic pathways in our cohort. Further preclinical investigation showed that NF2 loss-of-function mutations were sensitive to Hippo-targeted strategy. We established a public database (Fudan Portal) and a precision medicine knowledge base for data exchange and interpretation. Collectively, our study presents a leading approach for Chinese precision oncology treatment and reveals potentially actionable mutations in breast cancer.

OEP001027

development NODE, Shanghai Institute of Nutrition ang Health, CAS-MPG Partner Institute for Computational Biology,2023.10.09

Description

test analysis data security

OEP004612

Xuan Li, Institute of Plant Physiology and Ecology,2023.10.12

Description

Plants are unique with tremendous chemical diversity and metabolic complexity, which is highlighted by estimates that green plants collectively produce metabolites numbering in the millions. Plant metabolites play crucial roles in all aspects of plant biology, like growth, development, stress responses, etc. However, the lack of a reference metabolome for plants, and paucity of high-quality standard compound spectral libraries and related analytical tools, have hindered the discovery and functional study of phytochemicals in plants. Here, by leveraging an advanced LC-MS platform, we generated untargeted mass spectral data from >150 plant species collected across the five major phyla. Using a self-developed computation protocol, we constructed a reference metabolome for 153 plant species.

OEP004638

Xuan Li, Institute of Plant Physiology and Ecology,2022.03.22

Description

The sediment is located in the Mariana Trench,the sampling site was located 5842 meters below sea level.

OEP003217

Jianjun Wang, Nanjing Institute of Geography and Limnology, CAS,2023.09.21

Description

OEP004571

Rong Tang, Fudan University Shanghai Cancer Center,2023.10.11

Description

OEP004636

Meiying Xu, Guangdong Institute of Microbiology,2021.08.16

Description

Transcriptomic profiles of Sphingobium xenophagum strains under different culture conditions were analyzed comparatively.

OEP002610

Meiying Xu, Guangdong Institute of Microbiology,2023.07.31

Description

The genomes of four Sphingobium hydrophobicum strains with different cell surface hydrophobicity (CSH) were sequenced to investigate the variation responsible for CSH.

OEP004335