From the study of single cell gene expression in tumor microenvironment to the map of tumor cell types based on local spatial gene expression-with the arrival of single cell and spatial technology, the research field of breast cancer has made great progress.
Based on hormone receptor positive, HER2 positive and triple negative breast cancer (triple negative breast cancer) [1]? Related gene expression, breast cancer can be subdivided into five molecular subtypes. However, relatively speaking, scientists know little about the complex tumor microenvironment (TME) of breast cancer, how the tumor interacts with the immune system and other surrounding cells and tissues, and what this activity means for prognosis and treatment. With the emergence of single cell and space technology, scientists are bridging this knowledge gap. Here, we have selected four articles, and researchers have made great progress in defining and characterizing breast cancer at the single cell level. Through these studies, we can further understand the mechanism behind the occurrence, development and metastasis of different types of breast cancer, and at the same time push the transformation research and clinical trials to individualized treatment, bringing hope for the treatment of breast cancer.
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Creating Atlas: Drawing Human Breast Cancer with Single Cell and Spatial Resolution
In the first study, "Atlas of Single Cell and Spatial Analysis of Human Breast Cancer" [2], researchers led by Dr. Sunny Wu of Gavin Institute of Medicine used chromium single cell gene expression and Visium spatial gene expression to create a single cell transcriptome atlas of breast cancer with spatial resolution. Single cell RNA sequencing (scRNA-seq) was performed on 26 primary tumors, and all major cell types of all tumors and subtypes were identified. Combining the scRNA-seq compatible method developed by them for subtype typing of intrinsic molecules with the genetic features identified from scRNA-seq data, tumors can be classified and displayed with repetitive gene modules (GM) or genomes that lead to common cell heterogeneity in tumors.
Using Visium spatial gene expression of six samples, it was found that GM3(EMT, IFN, MHC) and GM4 (proliferation marker) were enriched in triple negative breast cancer samples, while GM 1 and GM5(ER, lumen) were enriched in estrogen receptor positive cases. Interestingly, the study found that GM3 and GM4 phenotypes only appeared in breast cancer areas where other phenotypes did not appear. By further describing breast tumors at single cell and spatial level, their maps can be used to improve the classification of breast cancer.
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Characterization of breast cancer metastasis by tracking clonal amplification
In the second study, "The location of breast cancer metastasis determines its clonal composition and reverse transcriptome characteristics" [3], scientists led by Dr. Jean Berthelet of Olivia Newton-John Cancer Institute used optical barcode technology and single cell gene expression profile to study the interaction network of cloned cells in the process of triple negative breast cancer metastasis. Compared with other breast cancer subtypes, triple negative breast cancer has a worse prognosis and a higher risk of recurrence.
ScRNA-seq was performed on the barcode subclones of triple negative breast cancer cell line and two metastatic sites (lung and liver). It was found that metastatic tumor was highly polyclonal in lung, but not in liver. In addition, the changes of subclone transcriptome showed that subclone which was dominant in primary tumor was still dominant in metastatic tissue. By comparing the gene expression profiles of subclones with different bar codes, the driving characteristics of 1, 366 differentially expressed gene transfer sites were determined. Compared with liver metastasis, tumor necrosis factor-α pathway is strongly up-regulated in lung. These results indicate that TME drives the heterogeneity of metastatic lesions.
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Predicting T cell biomarkers for effective immune checkpoint blocking immunotherapy
In the third study, "Single cell map of tumor changes in breast cancer patients during anti-PD 1 treatment" [4], Ayse Bassez, a doctoral student at the VIB- Cullen Center, led scientists to construct a single cell map of tumor changes by using transcriptome and immunoassay. Immune checkpoint blocking (ICB) plus chemotherapy can improve the therapeutic response [5], but not all patients respond to the new auxiliary ICB. In order to explore the reasons, they treated 40 patients with anti-PD 1 (a common ICB antibody therapy) before chemotherapy, and followed up the changes of tumors.
In two cohorts (one receiving anti-PD 1, one receiving chemotherapy and then receiving anti-PD 1), matched pre-treatment and post-treatment biopsies were mapped with scRNA-seq and T cell receptors. Nine patients underwent clonal expansion of T cells after treatment. When selecting the stage of T cell amplification and treatment, using scRNA-seq data, it was found that the number of T cells expressing PD 1 increased after anti-PD 1 treatment. Before treatment, differentially expressed genes were identified between expanded and unexpanded T cells, and it was found that the expression characteristics in T cells could be used to predict the expansion of T cells. Pre-treaTMEnt immune tme map related to anti-PD 1 T cell expansion after treatment can provide in-depth understanding of clinical biomarkers.
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Solve the heterogeneity of ductal carcinoma in situ (early breast cancer)
In the fourth study, "Genome Analysis Reveals Heterogeneous Groups of Breast Ductal Carcinoma in Situ" [6], a group of scientists led by Satoi Nagasawa, MD, University of Tokyo, used Visium spatial gene expression to reveal the cell diversity in breast cancer tumors. Ductal carcinoma in situ (DCIS) is an early stage of breast cancer, which may develop into invasive ductal carcinoma. However, it is difficult to determine who needs high-risk surgery, so it is very important to determine the risk factors for evaluation and treatment.
In this study, researchers first used traditional methods to select and verify the genomic risk factors of DCIS-GATA 3 and PIK3CA mutations. Spatial transcriptome analysis of DCIS using three specific cases shows that DCIS cells with GATA3 mutation sometimes develop into invasive cancer. However, DCIS cells with PIK3CA mutation will not cause cancer. In a word, it is very important to use new markers to classify DCIS more accurately for deciding the correct treatment.
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Better diagnosis and treatment.
Obviously, single cell and space technology are advancing our understanding of the development, progress and treatment of breast cancer beyond the imagination of using traditional methods. Whether using the newly created spatial transcriptome map or using gene expression and immunoassay to better describe the disease state, clinical researchers have more and more mastered the methods of better diagnosis, stratification and personalized treatment of breast cancer.
refer to
? Location and reverse transcription spectrum. Sci Adv 7: eabf4408 (202 1)。 doi: 10. 1 126/sciadv . abf 4408
Bassez A, et al.: Single cell diagram of tumor changes in breast cancer patients during anti-PD 1 treatment. NAT Med 27:820–832(202 1)。 doi: 10. 1038/s 4 159 1-02 1-0 1323-8
Schmid P, et al. Atezolizumab combined with nab-paclitaxel as the first-line treatment for unresectable, locally advanced or metastatic triple-negative breast cancer (assistion 130): the latest efficacy of a randomized, double-blind, placebo-controlled and phase 3 trial. The Lancet tumor 21:44–59 (2020). doi: 10. 10 16/S 1470-2045( 19)30689-8
The genome map reveals the heterogeneous population of breast ductal carcinoma in situ. Bionomics 4: 438 (202 1). doi: 10. 1038/s 42003-02 1-0 1959-9