4-2016-0678 for the 16 NSCLC patients undergoing anti-PD-1 treatment and IRB no. in cancer. Finally, the level in the TI T cells was found to be highly predictive of overall survival and anti-PD-1 efficacy in melanoma and NSCLC. Conclusions We predicted the regulatory factors involved in T cell exhaustion using single-cell transcriptome profiles of human TI lymphocytes. TOX promoted intra-tumoral CD8+ T cell exhaustion via upregulation of IC molecules. This suggested that TOX inhibition can potentially impede T cell exhaustion and improve ICI efficacy. Additionally, expression in the TI T cells can be used for patient stratification during anti-tumor treatments, including anti-PD-1 immunotherapy. increases with the exhaustion of CD8+ T cells. Additionally, TOX positively regulated the expression of PD-1, TIM-3, TIGIT, and CTLA-4 in the human TI CD8+ T cells. This suggested that TOX is a key Isocarboxazid TF that promotes T cell exhaustion by inducing IC molecules in human cancers. Finally, the expression levels of in the TI T cells could predict the overall survival and response to anti-PD-1 therapy in human melanoma and NSCLC. These results suggest that TOX levels can be used for patient stratification during anti-cancer treatment, including immunotherapy, Isocarboxazid and that TOX can be targeted in the background of immune checkpoint inhibitor (ICI) therapy. Methods Preprocessing of single-cell transcriptome data and differential expression analysis We analyzed the single-cell transcriptome data of tumor samples derived from 17 patients with melanoma (“type”:”entrez-geo”,”attrs”:”text”:”GSE72056″,”term_id”:”72056″GSE72056) [6] and 14 patients with NSCLC (“type”:”entrez-geo”,”attrs”:”text”:”GSE99254″,”term_id”:”99254″GSE99254) [7]. The transcriptome data were generated by full-length single-cell RNA sequencing (scRNA-seq) in a single batch. Expression level ((CD4?CD8+). For the human NSCLC dataset, we used only 2123 cells annotated as TTC cell (tumor cytotoxic T cell) for CD8+ T cells. We divided the CD8+ T cells into 2 subsets based on the Isocarboxazid expression level of (also known as PD-1) into value was less than 0.05 (*), 0.01 (**), 0.001 (***), and 0.0001 (****). For both tumor scRNA-seq datasets, we selected the differentially expressed genes (DEGs) with test. Clinical sample collection For the flow cytometric analysis of immune cells, fresh tumor specimens were provided by the Department of Internal Medicine at the Severance Hospital, along with permission to conduct the following study. We enrolled 35 patients with NSCLC and 15 patients with head and neck squamous cell carcinoma (HNSCC) who were treated between 2017 and 2019 in Korea. Detailed information on human subjects has been listed in Additional?file?2: Table S2. An internal cohort of patients with cancer undergoing anti-PD-1 treatment To study the correlation between expression level in the TI T cells and response to anti-PD-1 therapy, we recruited 16 patients with NSCLC from Yonsei Cancer Center, Seoul, Korea. The patients were administered nivolumab or pembrolizumab. Patients exhibiting partial response (PR) or stable disease (SD) for >?6?months were classified as responders, while the patients exhibiting progressive disease (PD) or SD for ?6?months were classified as nonresponders based on the Response Evaluation Criteria in Solid Tumors (RECIST) ver. 1.1 [14]. The tumor samples were obtained from patients before immunotherapy. Patient information is shown in Additional?file?2: Table S3-4. Bulk RNA sequencing data analysis of tumor samples Bulk RNA sequencing was performed for 16 samples from patients treated with the PD-1 inhibitor. Of the 16 tumor samples, 11 were fresh samples and 5 were formalin-fixed paraffin-embedded (FFPE) samples. The library was prepared from Rabbit Polyclonal to HGS the samples using the TruSeq RNA Access Library Prep Guide Part # 15049525 Rev. B with the TruSeq RNA Access Library Prep Kit (Illumina). RNA sequencing was Isocarboxazid performed in HiSeq 2500 (Illumina). The obtained sequencing data were processed as per the manufacturers instructions. The read data were aligned with the reference genome (GENCODE, h19 (GRCh37.p13, release 19)) [15] using STAR-2.5.2a [16]. The transcripts were quantified using featureCounts [17]. The correlation between the read count values of genes between fresh and FFPE samples was evaluated using Pearsons correlation coefficient. The correlations between intra-fresh sample, intra-FFPE sample, and fresh-FFPE samples as evaluated by Wilcoxons rank-sum test were found to be significant. Isolation of TI lymphocytes from the primary tumor Primary tumor tissues were obtained by surgical resection of patient tumors and from tumors developed in mice. The tissues were minced into 1?mm3 pieces and digested with a solution containing 1?mg/mL collagenase type IV (Worthington Biochemical Corp.) and 0.01?mg/mL DNase I (Millipore Sigma Corp.) at 37?C for 20?min. The dissociated tissues were filtered using.