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Jinming Cheng – Bioinformatics and ACRF Cancer Biology & Stem Cells divisions

18/06/2024 11:00 am - 18/06/2024 12:00 pm
Location
Davis Auditorium

WEHI PhD Completion Seminar hosted by Professor Gordon Smyth

Jinming Cheng

PhD Student – Smyth and Chen Laboratories

Bioinformatics and ACRF Cancer Biology & Stem Cells divisions

Computational Biology and Cancer Research & Treatments Themes, WEHI

 

Exploring mammary gland developmental stages and breast cancer heterogeneity using single cell technologies

 

Davis Auditorium

Join via TEAMS

Including Q&A session

 

 

Breast cancer is the most common cancer and the leading cause of cancer mortality in women worldwide. Clinical classification distinguishes invasive breast cancer into ER+, HER2+ and triple-negative breast cancer (TNBC). Histological classification distinguishes invasive breast cancer into two major types: invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC). IDC is the most common type of invasive breast cancer comprising 60-75%, and ILC is the second most common type comprising 10-15% and is mostly ER+. Exploring the heterogeneity of breast cancer tumor cells as well as the stromal and immune microenvironment is a key step to understand breast cancer genesis and development mechanisms. Single-cell RNA sequencing (scRNA-seq) technologies have been rapidly developed and widely used to investigate cell type composition and identify new cell populations. Spatial transcriptomics adds an additional spatial information layer to scRNA-seq, enabling the investigation of interactions between tumor and its microenvironment.

 

During his PhD, Jinming focused on investigating breast cancer development and heterogeneity using scRNA-seq and spatial transcriptomics. In this talk, he will present three projects: (1) comparing human lobular cancer and ER+ ductal cancer using scRNA-seq, (2) exploring mouse mammary gland fibroblast development using scRNA-seq, and (3) comparing different cell type annotation methods for imaging-based spatial transcriptomics data of HER2+ breast cancer. In addition, he developed an R package called scTernary and a pseudotime-course workflow that have been applied to the scRNA-seq data analysis of breast cancer and normal mammary gland.

 

Jinming Cheng is a fourth year PhD student under the supervision of Professor Gordon Smyth and Dr Yunshun Chen. He works closely with the Breast Cancer Lab. His project focuses on exploring cellular heterogeneity in human and mouse mammary gland, as well as understanding cell lineage commitment and breast cancer development. Additionally, he aims to develop new statistical methods for analysing scRNA-seq data.

 

 

All welcome!

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