Refining Colorectal Cancer Classification and Clinical Stratification Through a Single-Cell Atlas. Refining Colorectal Cancer Classification and Clinical Stratification Through a Single-Cell Atlas

To determine and dissect the extent of tumor, immunological, and stromal heterogeneity in CRC patients, we performed droplet-based scRNA-seq on 16 racially diverse, treatment naïve CRC patient tissue samples and seven adjacent normal colonic tissue samples (totaling 23 samples), yielded 49,589 single cells enabling high-resolution depiction of the cellular diversity and heterogeneity within the tumor and microenvironmental cells. Overall design: Patients with resectable untreated CRC who underwent curative colon resection at Rush University Medical Center (Chicago, IL, USA) were included in this Institutional Review Board (IRB)-approved study. CRC specimens from 16 patients, including nine Caucasian, six African American and one Asian patient with corresponding 8 adjacent normal tissue samples were processed immediately after collection at Rush University Medical Center Biorepository and sent for scRNA-seq. Thus, our scRNA-seq atlas represents a diverse patient population. The study was conducted in accordance with ethical standards and all patients provided written informed consent. Single-cell RNA sequencing (scRNA-seq) was performed using 10X Genomics Single Cell 5' Platform. Tumors and normal colon samples were enzymatically dissociated (Miltenyi), filtered through a 70-micron cell strainer, pelleted after centrifugation at 300 xg and resuspended in DAPI-FACS buffer (PBS, 0.04% BSA). Samples were sorted and viable singlets were gated on the basis of scatter properties and DAPI exclusion. Approximately 3000 cells were pelleted and resuspended in PBS, and cells underwent single cell droplet-based capture on 10X Chromium instruments according to the 10X Genomics Single Cell 5' Platform protocol. Transcriptome libraries were prepared post-fragmentation, end-repair, and A-tailing double-sided size selection, and subsequent adaptor ligation as per the manufacturer’s protocol. Illumina NextSeq 550 was used for library sequencing and data were mapped and counted using Cellranger-v3.1.0 (GRCh38/hg38). ----------------------------------- Author state "we have privacy issues with raw data can we submit only count file and annotation files to the GEO database".