Row data for 1042835.zip

dataset

posted on 2022-12-24, 02:20 authored by Danfang ZhangDanfang Zhang, Huizhi Sun, Yanlei Li, Yanhui Zhang, Xiulan Zhao, Xueyi Dong, Yuhong Guo, Jing Mo, Na Che, Xinchao Ban, Fan Li, Xiaoyu Bai, Yue Li, Jihui Hao

Title: Hypoxia-dependent spatial transcriptomics predicted the prognosis and efficacy of immunotherapy in claudin-low breast cancer

The raw data in this study includes four parts.

Original data list

Part 1

Source data (raw data, original data, individual data points) for the information presented in your tables and figures. This should be in a generally readable format and Excel files are preferred.

This study peformed Spatial Transcriptomics (ST) to demonstrate their spatial distribution in human claudin-low breast cancer MDA-MB-231 engraft. 10x genomics official software Space Ranger 1.0.0 was used for data preprocessing, gene expression quantitative and point identification. The original Space Ranger files for 4 samples were also submitted as additional files in Jianguoyun website (https://www.jianguoyun.com/c/sd/15eabb7/5bdc92d86263a0b7). Software Seurat 4.0 was used to analyze and cluster the four samples. UMAP algorithm were used to reduce the dimension of data and visualize data. The differentially expressed genes and cluster type in 12 clusters listed in Supplementary Table 3.

Part 2

If your raw data were obtained from publicly available datasets, please provide the working sheets used to analyse these data.

RNA-Sequence data and associated clinical data for 1904 breast cancers (METABRIC) were downloaded from the cBioPortal website (http://www.cbioportal.org/datasets). We used these data to validate the relationship between the breast cancer hypoxia-dependent spatial clusters score and immune cell infiltrition, immune funtion and breast cancer subtype. Supplementary table 4 listed the clinicopathological factors and ssGSEA score of each sample. Supplementary table 5 showed the gene sets used in this study.

Part 3

If statistical programs (such as R, SAS, SPSS, MATLAB) were used for the data analysis or figure creation in your manuscript, please provide all the relevant code/script files (such as .R or .SPS) and data sheets to replicate your analyses or figures.

The breast cancer hypoxia-dependent spatial clusters score and immune fuction-related score was calculated based on the ssGSEA R launguage for 1904 human breast cancers. Kaplan–Meier (K-M) analysis were carried out using R language. The R script files for ssGSEA and K-M survival were submitted as additional files in Jianguoyun website（https://www.jianguoyun.com/c/sd/15eabb7/5bdc92d86263a0b7）.

SPSS 20.0 software was used to perform Cox proportional hazards regression, ANOVA test, Chi-squared test, and Pearson correlation. The correlation heatmaps were provided by HIPLOT website (https://hiplot.com.cn/basic/cor-heatmap).

Part 4

This part of data are the original images in Figure 2, Figure 3 and Figure S1. There are immunofluorescence staining pictures and immunohistochemical staining pictures.