scholarly journals Comprehensive Analysis of Immune Cell Enrichment In The Tumor Microenvironment of Head And Neck Squamous Cell Carcinoma

2021 ◽  
Author(s):  
Ikko Mito ◽  
Hideyuki Takahashi ◽  
Reika Kawabata-Iwakawa ◽  
Shota Ida ◽  
Hiroe Tada ◽  
...  
Keyword(s):  
T Cells ◽  
Tumor Microenvironment ◽  
Head And Neck ◽  
Immune Cell ◽  
Cell Types ◽  
Gene Set Enrichment Analysis ◽  
Rna Seq ◽  
Immune Microenvironment ◽  
Immune Signatures ◽  
Cancer Tissues

Abstract Background: Head and neck squamous carcinoma (HNSCC) is highly infiltrated by immune cells, including tumor-infiltrating lymphocytes and myeloid lineage cells. In the tumor microenvironment, tumor cells orchestrate a highly immunosuppressive microenvironment by secreting immunosuppressive mediators, expressing immune checkpoint ligands, and downregulating human leukocyte antigen expression. In the present study, we aimed to comprehensively profile the immune microenvironment of HNSCC using RNA-sequencing (RNA-seq) data obtained from The Cancer Genome Atlas (TCGA) database.Methods: We calculated enrichment scores of 33 immune cell types based on RNA-seq data of HNSCC tissues and adjacent non-cancer tissues. Based on these scores, we performed non-supervised clustering and identified three immune signatures, i.e., cold, lymphocyte, and myeloid/dendritic cell (DC), using clustering results. We then compared the clinical and biological features of the three signatures.Results: Among HNSCC and non-cancer tissues, human papillomavirus (HPV)-positive HNSCCs exhibited the highest scores in various immune cell types, including CD4+ T cells, CD8+ T cells, B cells, plasma cells, basophils, and their subpopulations. Among the three immune signatures, the proportions of HPV-positive tumors, oropharyngeal cancers, early T tumors, and N factor positive cases were significantly higher in the lymphocyte signature than in other signatures. Among the three signatures, the lymphocyte signature showed the longest overall survival (OS), especially in HPV-positive patients, whereas the myeloid/DC signature demonstrated the shortest OS in these patients. Gene set enrichment analysis revealed the upregulation of several pathways related to inflammatory and proinflammatory responses in the lymphocyte signature. The expression of PRF1, IFNG, GZMB, PDCD1, LAG3, CTLA4, HAVCR2, and TIGIT was the highest in the lymphocyte signature. Meanwhile, the expression of PD-1 ligand genes CD274 and PDCD1LG2 was highest in the myeloid/DC signature. Conclusions: Herein, our findings revealed the transcriptomic landscape of the immune microenvironment that closely reflects the clinical and biological significance of HNSCC, indicating that molecular profiling of the immune microenvironment can be employed to develop novel biomarkers and precision immunotherapies for HNSCC.

scholarly journals Comprehensive Analysis of Immune Cell Enrichment in the Tumor Microenvironment of Head and Neck Squamous Cell Carcinoma

2021 ◽  
Author(s):  
Ikko Mito ◽  
Hideyuki Takahashi ◽  
Reika Kawabata-Iwakawa ◽  
Shota Ida ◽  
Hiroe Tada ◽  
...  
Keyword(s):  
T Cells ◽  
Tumor Microenvironment ◽  
Head And Neck ◽  
Immune Cell ◽  
Cell Types ◽  
Gene Set Enrichment Analysis ◽  
Rna Seq ◽  
Immune Microenvironment ◽  
Immune Signatures ◽  
Cancer Tissues

Abstract Background: Head and neck squamous carcinoma (HNSCC) is highly infiltrated by immune cells, including tumor-infiltrating lymphocytes and myeloid lineage cells. In the tumor microenvironment, tumor cells orchestrate a highly immunosuppressive microenvironment by secreting immunosuppressive mediators, expressing immune checkpoint ligands, and downregulating human leukocyte antigen expression. In the present study, we aimed to comprehensively profile the immune microenvironment of HNSCC using RNA-sequencing (RNA-seq) data obtained from The Cancer Genome Atlas (TCGA) database.Methods: We calculated enrichment scores of 33 immune cell types based on RNA-seq data of HNSCC tissues and adjacent non-cancer tissues. Based on these scores, we performed non-supervised clustering and identified three immune signatures, i.e., cold, lymphocyte, and myeloid/dendritic cell (DC), using clustering results. We then compared the clinical and biological features of the three signatures.Results: Among HNSCC and non-cancer tissues, human papillomavirus (HPV)-positive HNSCCs exhibited the highest scores in various immune cell types, including CD4+ T cells, CD8+ T cells, B cells, plasma cells, basophils, and their subpopulations. Among the three immune signatures, the proportions of HPV-positive tumors, oropharyngeal cancers, early T tumors, and N factor positive cases were significantly higher in the lymphocyte signature than in other signatures. Among the three signatures, the lymphocyte signature showed the longest overall survival (OS), especially in HPV-positive patients, whereas the myeloid/DC signature demonstrated the shortest OS in these patients. Gene set enrichment analysis revealed the upregulation of several pathways related to inflammatory and proinflammatory responses in the lymphocyte signature. The expression of PRF1, IFNG, GZMB, PDCD1, LAG3, CTLA4, HAVCR2, and TIGIT was the highest in the lymphocyte signature. Meanwhile, the expression of PD-1 ligand genes CD274 and PDCD1LG2 was highest in the myeloid/DC signature. Conclusions: Herein, our findings revealed the transcriptomic landscape of the immune microenvironment that closely reflects the clinical and biological significance of HNSCC, indicating that molecular profiling of the immune microenvironment can be employed to develop novel biomarkers and precision immunotherapies for HNSCC.

scholarly journals Comprehensive analysis of immune cell enrichment in the tumor microenvironment of head and neck squamous cell carcinoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ikko Mito ◽  
Hideyuki Takahashi ◽  
Reika Kawabata-Iwakawa ◽  
Shota Ida ◽  
Hiroe Tada ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Tumor Microenvironment ◽  
Head And Neck ◽  
Gene Expression Data ◽  
Immune Cell ◽  
Cell Types ◽  
Expression Data ◽  
Immune Microenvironment ◽  
Cancer Tissues

AbstractHead and neck squamous carcinoma (HNSCC) is highly infiltrated by immune cells, including tumor-infiltrating lymphocytes and myeloid lineage cells. In the tumor microenvironment, tumor cells orchestrate a highly immunosuppressive microenvironment by secreting immunosuppressive mediators, expressing immune checkpoint ligands, and downregulating human leukocyte antigen expression. In the present study, we aimed to comprehensively profile the immune microenvironment of HNSCC using gene expression data obtained from public database. We calculated enrichment scores of 33 immune cell types based on gene expression data of HNSCC tissues and adjacent non-cancer tissues. Based on these scores, we performed non-supervised clustering and identified three immune signatures—cold, lymphocyte, and myeloid/dendritic cell (DC)—based on the clustering results. We then compared the clinical and biological features of the three signatures. Among HNSCC and non-cancer tissues, human papillomavirus (HPV)-positive HNSCCs exhibited the highest scores in various immune cell types, including CD4+ T cells, CD8+ T cells, B cells, plasma cells, basophils, and their subpopulations. Among the three immune signatures, the proportions of HPV-positive tumors, oropharyngeal cancers, early T tumors, and N factor positive cases were significantly higher in the lymphocyte signature than in other signatures. Among the three signatures, the lymphocyte signature showed the longest overall survival (OS), especially in HPV-positive patients, whereas the myeloid/DC signature demonstrated the shortest OS in these patients. Gene set enrichment analysis revealed the upregulation of several pathways related to inflammatory and proinflammatory responses in the lymphocyte signature. The expression of PRF1, IFNG, GZMB, CXCL9, CXCL10, PDCD1, LAG3, CTLA4, HAVCR2, and TIGIT was the highest in the lymphocyte signature. Meanwhile, the expression of PD-1 ligand genes CD274 and PDCD1LG2 was highest in the myeloid/DC signature. Herein, our findings revealed the transcriptomic landscape of the immune microenvironment that closely reflects the clinical and biological significance of HNSCC, indicating that molecular profiling of the immune microenvironment can be employed to develop novel biomarkers and precision immunotherapies for HNSCC.

scholarly journals OTHR-14. An immunogenomic analysis of melanoma brain metastases (MBM) compared to extracranial metastases (ECM)

2021 ◽  
Vol 3 (Supplement_3) ◽  
pp. iii17-iii17
Author(s):  
Lucy Boyce Kennedy ◽  
Amanda E D Van Swearingen ◽  
Jeff Sheng ◽  
Dadong Zhang ◽  
Xiaodi Qin ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Pathway Analysis ◽  
Immune Cell ◽  
Single Gene ◽  
Enrichment Analysis ◽  
Cell Types ◽  
Gene Set Enrichment Analysis ◽  
Molecular Profile ◽  
Cancer Center ◽  
Rna Seq

Abstract Background MBM have a unique molecular profile compared to ECM. Methods We analyzed a previously published dataset from MD Anderson Cancer Center, including RNA-seq on surgically resected, FFPE MBM and ECM from the same patients. STAR pipeline was used to estimate mRNA abundance. DESeq2 package was used to perform differential gene expression (DGE) analyses. Pathway analysis was performed using Gene Set Enrichment Analysis (GSEA). Paired DGE and GSEA compared MBM vs. lymph node (LN) metastases (n = 16) and MBM vs. skin mets (n = 10). CIBERSORTx estimated relative abundance of immune cell types in MBM and ECM. GATK Mutect2 pipeline was used to call somatic mutations using paired normal tumor samples. Mutations were annotated using the Ensembl Variant Effect Predictor and visualized using the Maftools package in R. RNA-seq was available on 54 human primary cutaneous melanomas (CM). Gene Ontology or KEGG Pathway analysis was performed using goana function of limma package in R. Results Paired GSEA found that autophagy pathways may be up-regulated in MBM vs. LN and MBM vs. skin mets. On a single-gene level, the most strongly up-regulated genes in autophagy pathways were GFAP and HBB. Fold changes in other autophagy-related genes were low and did not reach significance. Comparison between CM which recurred in brain vs. CM which did not recur identified up-regulation of autophagy pathways. CIBERSORTx identified an increased proportion of immune suppressive M2 macrophages compared to tumor suppressive M1 macrophages in MBMs and ECMs. Conclusion Up-regulation of autophagy pathways was observed in patient-matched MBM vs. LN and skin mets. This finding was driven by up-regulation of GFAP and HBB, which could reflect changes in the tumor microenvironment. Higher M2:M1 ratio may contribute to an immune suppressive tumor microenvironment and may be targetable. Validation of our findings in an independent Duke dataset is ongoing.

scholarly journals Identification of an Autophagy-Related Risk Signature Correlates With Immunophenotype and Predicts Immune Checkpoint Blockade Efficacy of Neuroblastoma

2021 ◽  
Vol 9 ◽  
Author(s):  
Wenjuan Kang ◽  
Jiajian Hu ◽  
Qiang Zhao ◽  
Fengju Song
Keyword(s):  
T Cells ◽  
Risk Score ◽  
Immune Checkpoint ◽  
Immune Cell ◽  
Immune Checkpoint Blockade ◽  
Low Risk ◽  
Checkpoint Blockade ◽  
Gene Set Enrichment Analysis ◽  
Immune Microenvironment ◽  
Tumor Tissues

Neuroblastoma is one of the malignant solid tumors with the highest mortality in childhood. Targeted immunotherapy still cannot achieve satisfactory results due to heterogeneity and tolerance. Exploring markers related to prognosis and evaluating the immune microenvironment remain the major obstacles. Herein, we constructed an autophagy-related gene (ATG) risk model by multivariate Cox regression and least absolute shrinkage and selection operator regression, and identified four prognostic ATGs (BIRC5, GRID2, HK2, and RNASEL) in the training cohort, then verified the signature in the internal and external validation cohorts. BIRC5 and HK2 showed higher expression in MYCN amplified cell lines and tumor tissues consistently, whereas GRID2 and RNASEL showed the opposite trends. The correlation between the signature and clinicopathological parameters was further analyzed and showing consistency. A prognostic nomogram using risk score, International Neuroblastoma Staging System stage, age, and MYCN status was built subsequently, and the area under curves, net reclassification improvement, and integrated discrimination improvement showed more satisfactory prognostic predicting performance. The ATG prognostic signature itself can significantly divide patients with neuroblastoma into high- and low-risk groups; differentially expressed genes between the two groups were enriched in autophagy-related behaviors and immune cell reactions in gene set enrichment analysis (false discovery rate q -value < 0.05). Furthermore, we evaluated the relationship of the signature risk score with immune cell infiltration and the cancer-immunity cycle. The low-risk group was characterized by more abundant expression of chemokines and higher immune checkpoints (PDL1, PD1, CTLA-4, and IDO1). The risk score was significantly correlated with the proportions of CD8+ T cells, CD4+ memory resting T cells, follicular helper T cells, memory B cells, plasma cells, and M2 macrophages in tumor tissues. In conclusion, we developed and validated an autophagy-related signature that can accurately predict the prognosis, which might be meaningful to understand the immune microenvironment and guide immune checkpoint blockade.

An immunogenomic analysis of melanoma brain metastases (MBM) compared to extracranial metastases (ECM).

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 9521-9521
Author(s):  
Lucy Kennedy ◽  
Amanda E.D. Van Swearingen ◽  
Jeff Sheng ◽  
Dadong Zhang ◽  
Xiaodi Qin ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Pathway Analysis ◽  
Immune Cell ◽  
Single Gene ◽  
Fold Change ◽  
Gene Set Enrichment Analysis ◽  
Molecular Profile ◽  
Cancer Center ◽  
Rna Seq ◽  
Primary Cutaneous Melanoma

9521 Background: Previous work has shown that MBM have a unique molecular profile compared to ECM. Description of the biology of MBM will facilitate the design of rational therapies for patients (pts) with MBM. Methods: We analyzed a previously published dataset from MD Anderson Cancer Center, which includes RNA-seq on surgically resected FFPE MBM (88 tumors from 74 pts) and surgically resected ECM from the same pts (50 from 34 pts). WES on 18 matched pairs of MBM and ECM was available. The STAR pipeline was used to estimate mRNA abundance. The DESeq2 package was used to perform differential gene expression (DGE) analyses. Pathway analysis was performed using Gene Set Enrichment Analysis (GSEA). Paired DGE and GSEA analyses comparing MBM vs. lymph node metastases (LN mets, n = 16) and MBM vs. skin mets (n = 10) were performed. CIBERSORT estimated relative abundance of immune cell types in MBM and ECM. The GATK Mutect2 pipeline was used to call somatic mutations using paired normal tumor samples. Mutations were annotated using the Ensembl Variant Effect Predictor and visualized using the Maftools package in R. RNA-seq was available on 54 primary cutaneous melanoma (CM) pt samples, including 19 CM which did not recur, 19 CM which recurred as MBM, and 16 CM which recurred as ECM. Gene Ontology or KEGG Pathway analysis was performed using goana function of limma package in R. Results: Comparing MBM vs. LN and MBM vs. skin mets, paired DGE identified 136 and 89 up-regulated genes with a fold change > 2 and false-discovery rate (FDR) q-value < 0.05. Moreover, 308 and 659 down-regulated genes with a fold change < 0.5 were identified in MBM vs. LN and MBM vs. skin mets, respectively (q < 0.05). Paired GSEA found that autophagy signaling pathways may be up-regulated in MBM vs. LN and MBM vs. skin mets. On a single-gene level, comparing both MBM vs. LN and skin mets, the most strongly up-regulated genes in autophagy pathways were GFAP and HBB, whereas fold changes in the majority of other autophagy-related genes were low and did not reach significance. Comparison between CM which recurred in brain vs. CM which did not recur identified up-regulation of autophagy pathways. No difference in autophagy pathway expression was observed comparing between CM with any recurrence vs. without recurrence. CIBERSORT identified an increased proportion of immune suppressive M2 macrophages compared to tumor suppressive M1 macrophages in both MBMs and ECMs. Conclusions: Up-regulation of autophagy pathways was observed in pt-matched MBM vs. LN and skin mets. This finding seemed to be driven by up-regulation of GFAP and HBB, which could reflect changes in the tumor microenvironment (TME). Future studies using single-cell RNA-seq or spatial transcriptomic technology will dissect the TME. A higher M2:M1 ratio may contribute to an immune suppressive tumor microenvironment in MBM and ECM and is targetable. Validation of our findings in an independent Duke dataset is ongoing.

scholarly journals Characterization of T-ALL-Specific Heterogenous Blast Populations Using High Resolution Single Cell Profiling

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 11-12
Author(s):  
Swati S Bhasin ◽  
Ryan J Summers ◽  
Beena E Thomas ◽  
Debasree Sarkar ◽  
Bhakti Dwivedi ◽  
...  
Keyword(s):  
Bone Marrow ◽  
T Cells ◽  
Tumor Microenvironment ◽  
Single Cell ◽  
Prognostic Significance ◽  
Cell Types ◽  
Blast Cell ◽  
Patient Specific ◽  
P Value ◽  
Immune Microenvironment

Introduction: T-cell acute lymphoblastic leukemia (T-ALL) is characterized by proliferation of immature T-cells and accounts for ~15% of pediatric ALL. T-ALL blasts are phenotypically diverse and are sub-classified into pro-, pre-, cortical and mature T-ALL based on the stage of differentiation of the leukemic clone. Early T precursor ALL (ETP-ALL) is a T-ALL subtype associated with higher risk of relapse (Raetz and Teachey, 2016). Bulk sequencing approaches have revealed valuable information about modulated genes in T-ALL; however, little is understood about the interplay between tumor cells and the immune microenvironment. We present a comprehensive single cell RNA sequencing (scRNASeq) analysis of T-ALL samples with the purpose of characterizing the heterogenous tumor and microenvironment cells in order to identify dysregulated genes in leukemia cells and investigate oncogenic signaling pathways. Methods: We profiled 16,280 cells from 5 diagnostic pediatric T-ALL bone marrow samples using the Chromium single cell transcriptomics platform (10x Genomics, Pleasanton, CA). To compare T-ALL versus healthy bone marrow profiles and identify T-ALL-specific malignant blast cell populations, we included data from 3 healthy pediatric bone marrow samples from a recent study (Caron et al, 2020). Dimension reduction using the Uniform Manifold Approximation and Projection (UMAP) approach was used to identify unique cell type clusters (Becht et al, 2018). Using the TARGET dataset (https://ocg.cancer.gov/programs/target), we further evaluated the prognostic significance of identified malignant blast-specific genes by performing Kaplan-Meier survival analysis and compared gene expression patterns and tumor microenvironment makeup between ETP-ALL and non-ETP T-ALL patient samples. Results: We successfully characterized leukemic blasts (CD7+, CD99+ and CD3D+) and other major immune cell types (T cells, B cells, monocytes, erythroid precursors) using the expression of established marker genes (Fig 1A, C). Clustering analysis revealed patient-specific leukemia blast cell clusters (Fig 1B). Differential expression analysis between CD3D+ patient-specific leukemia clusters and CD3D+ clusters comprised of normal T-cells identified a set of 385 promiscuous genes that are significantly differentially expressed between malignant and normal T-cells (p-value &lt;0.05) despite tumor cell heterogeneity. Among the top genes upregulated in the leukemia clusters are HES4 (a downstream target of NOTCH1), CD99, RACK1, and TUBB (Fig 1D), which have previously been implicated in T-ALL leukemogenesis and chemoresistance (DeDecker et al, 2020; Cox et al, 2016; Lei et all 2016). Further, pathways analysis demonstrated significant activation (Z score &gt;1.3, p-value &lt;0.05) of multiple pathways associated with cancer stemness, cellular growth and proliferation including PI3K/AKT, unfolded protein response, and glycolysis, implicating these genes as oncogenic mediators in T-ALL blasts (Fig 2A). Overexpression of S100A4, IFITM2, and CD74 were significantly associated with poor survival in the TARGET cohort of 241 patients (hazard ratio 2.2, 5.8, and 7.1, respectively, p-value &lt;0.05), indicating their prognostic significance (Fig 2B). We additionally evaluated the expression of our gene set across ETP-ALL and non-ETP T-ALL groups in the TARGET dataset. Multiple leukemic blast-specific genes including ARMH1, CD44, CD74, DNAJC1, and IFITM2 were significantly upregulated in ETP-ALL. Further, deconvolution analysis performed on ETP-ALL vs non-ETP T-ALL samples determined that tumor microenvironment cell types are differentially enriched in these T-ALL groups. We observed enrichment of memory B cells, dendritic cells, NK cells, and M2 macrophages in ETP-ALL samples as compared to non-ETP T-ALL samples. Conversely,lower levels of mast cells and T-regulatory cells were observed in ETP-ALL samples. Conclusions: We identified a gene signature characterizing heterogenous T-ALL blast populations. External validation using the TARGET dataset identified genes within the signature that are associated with poor outcomes in T-ALL. Differences in the composition of the immune microenvironment in ETP-ALL versus non-ETP T-ALL samples provide a promising area for future study. Further studies will be carried out with relapsed and non-relapsed T-ALL samples to validate this leukemia signature. Disclosures Bhasin: Canomiiks Inc: Current equity holder in private company, Other: Co-Founder.

scholarly journals ADAMTS12 acts as a tumor microenvironment related cancer promoter in gastric cancer

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yangming Hou ◽  
Yingjuan Xu ◽  
Dequan Wu
Keyword(s):  
Gastric Cancer ◽  
Tumor Microenvironment ◽  
Immune Cell ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Tumor Promoter ◽  
Protein Protein Interaction ◽  
Oxidative Phosphorylation Pathway ◽  
Cox Proportional Hazard Regression

AbstractThe infiltration degree of immune and stromal cells has been shown clinically significant in tumor microenvironment (TME). However, the utility of stromal and immune components in Gastric cancer (GC) has not been investigated in detail. In the present study, ESTIMATE and CIBERSORT algorithms were applied to calculate the immune/stromal scores and the proportion of tumor-infiltrating immune cell (TIC) in GC cohort, including 415 cases from The Cancer Genome Atlas (TCGA) database. The differentially expressed genes (DEGs) were screened by Cox proportional hazard regression analysis and protein–protein interaction (PPI) network construction. Then ADAMTS12 was regarded as one of the most predictive factors. Further analysis showed that ADAMTS12 expression was significantly higher in tumor samples and correlated with poor prognosis. Gene Set Enrichment Analysis (GSEA) indicated that in high ADAMTS12 expression group gene sets were mainly enriched in cancer and immune-related activities. In the low ADAMTS12 expression group, the genes were enriched in the oxidative phosphorylation pathway. CIBERSORT analysis for the proportion of TICs revealed that ADAMTS12 expression was positively correlated with Macrophages M0/M1/M2 and negatively correlated with T cells follicular helper. Therefore, ADAMTS12 might be a tumor promoter and responsible for TME status and tumor energy metabolic conversion.

747 Evaluation of immune microenvironment of primary lung cancer and synchronous liver metastasis with multispectral imaging system

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A795-A795
Author(s):  
Hyeonbin Cho ◽  
Jae-Hwan Kim ◽  
Ji-Hyun Kim
Keyword(s):  
T Cells ◽  
Liver Metastasis ◽  
Multispectral Imaging ◽  
Immune Cell ◽  
Imaging System ◽  
Cytotoxic T Cells ◽  
Primary Lung Cancer ◽  
Helper T Cells ◽  
Synchronous Liver Metastasis ◽  
Immune Microenvironment

BackgroundCancer immunotherapy (CIT) has substantially improved the survival of cancer patients. However, according to recent studies, liver metastasis was reported to predict worse outcomes for CIT. The main objective of the study is to evaluate the differences in the immune microenvironment (IME) between the primary lung cancer (PL) and synchronous liver metastasis (LM) using a multispectral imaging system.MethodsSix immune markers (CD4, CD8, CTLA-4, granzyme B (GZB), Foxp3 and PD-L1) were analyzed using a multiplex IHC system and inForm program (Akoya) on paired lung-liver samples of 10 patients. Cells were categorized into tumor nest and stroma, and cell counts per unit area were measured for comparison.ResultsThe number of tumor-infiltrating cytotoxic T cells (TIL) in PL (262.5 cells/mm2) was higher than that of LM (113.3 cells/mm2). Additionally, the ratio between the number of TIL and non-TIL was greater in PL (0.31) compared to that of LM (0.26). A similar trend appeared for Helper T cells and regulatory T cells (Treg), as PL consisted of higher numbers of T cells (791.8 Helper T cells/mm2, 195.7 Treg/mm2) than LM (626.3 Helper T cells/mm2, 121.3 Treg/mm2). However, cytotoxic T cells exhibiting GZB+ and CTLA-4- were fewer in PL (140.2 cells/mm2) than in LM (203.3 cells/mm2), and the ratio is 0.69. The mean number of GZB+ TIL in PL (32.5 cells/mm2) was lower than in LM (35.3 cells/mm2), and their proportions among total TIL counts were 0.12 and 0.31, respectively. In PL, GZB+: GZB- ratio is 0.16 while the ratio is 1.91 for LM. A fewer number of TILs exhibiting GZB suggests that PL has lower efficiency in immune response than LM. Another crucial checkpoint receptor that inhibits immune response, CTLA-4, was more prevalent in PL, with CTLA-4+: CTLA-4- ratio in Treg being 0.36 in PL, compared to 0.11 in LM. The tumor proportion score (TPS) of PD-L1 was higher in PL than LM (40.0 vs. 6.6).ConclusionsIn our study, we showed the differences in the numbers of TIL or regulatory T cells and expressions of immune checkpoint receptors (PD-L1, CTLA-4), which significantly influence outcomes for CIT. The study is ongoing to confirm different IME between the PL and LM groups in a larger tumor cohort.ReferencesPeng, Jianhong, et al., Immune Cell Infiltration in the Microenvironment of Liver Oligometastasis from Colorectal Cancer: Intratumoural CD8/CD3 Ratio Is a Valuable Prognostic Index for Patients Undergoing Liver Metastasectomy. Cancers 2019 Dec; 11(12): 1922. https://doi.org/10.3390/cancers11121922Tumeh, Paul C., et al., Liver Metastasis and treatment outcome with Anti-PD-1 monoclonal antibody in patients with melanoma and NSCLC. Cancer Immunol Res 2017 May; 5(5): 417–424. doi: 10.1158/2326-6066.CIR-16-0325Parra, E.R., Immune Cell Profiling in Cancer Using Multiplex Immunofluorescence and Digital Analysis Approaches; Streckfus, C.F., Ed.; IntechOpen: London, UK, 2018; pp. 1–13. doi: 10.5772/intechopen.80380Ribas, A., Hu-Lieskovan, S., What does PD-L1 positive or negative mean?. The Journal of Experimental Medicine 2016;213(13):2835–2840. https://doi.org/10.1084/jem.20161462

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