scholarly journals Deciphering the immunosuppressive tumor microenvironment in ALK- and EGFR-positive lung adenocarcinoma

2021 ◽  
Author(s):  
Jan Budczies ◽  
Martina Kirchner ◽  
Klaus Kluck ◽  
Daniel Kazdal ◽  
Julia Glade ◽  
...  
Keyword(s):  
Gene Expression ◽  
Tumor Microenvironment ◽  
Lung Adenocarcinoma ◽  
Expression Profiling ◽  
Immune Cell ◽  
Expression Profiles ◽  
Immune Therapy ◽  
Immune Reactivity ◽  
Immune Gene ◽  
Alk Positive

Abstract Introduction The advent of immune checkpoint blockade (ICB) has led to significantly improved disease outcome in lung adenocarcinoma (ADC), but response of ALK/EGFR-positive tumors to immune therapy is limited. The underlying immune biology is incompletely understood. Methods We performed comparative mRNA expression profiling of 31 ALK-positive, 40 EGFR-positive and 43 ALK/EGFR-negative lung ADC focused on immune gene expression. The presence and levels of tumor infiltration lymphocytes (TILs) as well as fourteen specific immune cell populations were estimated from the gene expression profiles. Results While total TILs were not lower in ALK-positive and EGFR-positive tumors compared to ALK/EGFR-negative tumors, specific immunosuppressive characteristics were detected in both subgroups: In ALK-positive tumors, regulatory T cells were significantly higher compared to EGFR-positive (fold change: FC = 1.9, p = 0.0013) and ALK/EGFR-negative tumors (FC = 2.1, p = 0.00047). In EGFR-positive tumors, cytotoxic cells were significantly lower compared to ALK-positive (FC =  − 1.7, p = 0.016) and to ALK/EGFR-negative tumors (FC =  − 2.1, p = 2.0E-05). A total number of 289 genes, 40 part of cytokine–cytokine receptor signaling, were differentially expressed between the three subgroups. Among the latter, five genes were differently expressed in both ALK-positive and EGFR-positive tumors, while twelve genes showed differential expression solely in ALK-positive tumors and eleven genes solely in EGFR-positive tumors. Conclusion Targeted gene expression profiling is a promising tool to read out tumor microenvironment characteristics from routine diagnostic lung cancer biopsies. Significant immune reactivity including specific immunosuppressive characteristics in ALK- and EGFR-positive lung ADC, but not a total absence of immune infiltration supports further clinical evaluation of immune-modulators as partners of ICB in such tumors.

scholarly journals 909 Differentiation subgroups within LKB1-deficient lung cancer influence both the immune exclusion phenotype and cellular composition of the immune microenvironment

2021 ◽  
Vol 9 (Suppl 3) ◽  
pp. A954-A955
Author(s):  
Jacob Kaufman ◽  
Doug Cress ◽  
Theresa Boyle ◽  
David Carbone ◽  
Neal Ready ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Lung Adenocarcinoma ◽  
Plasma Cells ◽  
Immune Cell ◽  
Expression Profiles ◽  
Neuroendocrine Differentiation ◽  
Gene Expression Profiles ◽  
Immune Microenvironment ◽  
Immune Exclusion

BackgroundLKB1 (STK11) is a commonly disrupted tumor suppressor in NSCLC. Its loss promotes an immune exclusion phenotype with evidence of low expression of interferon stimulated genes (ISG) and decreased microenvironment immune infiltration.1 2 Clinically, LKB1 loss induces primary immunotherapy resistance.3 LKB1 is a master regulator of a complex downstream kinase network and has pleiotropic effects on cell biology. Understanding the heterogeneous phenotypes associated with LKB1 loss and their influence on tumor-immune biology will help define and overcome mechanisms of immunotherapy resistance within this subset of lung cancer.MethodsWe applied multi-omic analyses across multiple lung adenocarcinoma datasets2 4–6 (>1000 tumors) to define transcriptional and genetic features enriched in LKB1-deficient lung cancer. Top scoring phenotypes exhibited heterogeneity across LKB1-loss tumors, and were further interrogated to determine association with increased or decreased markers of immune activity. Further, immune cell-types were estimated by Cibersort to identify effects of LKB1 loss on the immune microenvironment. Key conclusions were confirmed by blinded pathology review.ResultsWe show that LKB1 loss significantly affects differentiation patterns, with enrichment of ASCL1-expressing tumors with putative neuroendocrine differentiation. LKB1-deficient neuroendocrine tumors had lower expression of Interferon Stimulated Genes (ISG), MHC1 and MHC2 components, and immune infiltration compared to LKB1-WT and non-neuroendocrine LKB1-deficient tumors (figure 1).The abundances of 22 immune cell types assessed by Cibersort were compared between LKB1-deficient and LKB1-WT tumors. We observe skewing of immune microenvironmental composition by LKB1 loss, with lower abundance of dendritic cells, monocytes, and macrophages, and increased levels of neutrophils and plasma cells (table 1). These trends were most pronounced among tumors with neuroendocrine differentiation, and were concordant across three independent datasets. In a confirmatory subset of 20 tumors, plasma cell abundance was assessed by a blinded pathologist. Pathologist assessment was 100% concordant with Cibersort prediction, and association with LKB1 loss was confirmed (P=0.001).Abstract 909 Figure 1Immune-associated Gene Expression Profiles Affected by Neuroendocrine Differentiation within LKB1-Deficient Lung Adenocarcinomas. Gene expression profiles corresponding to five immune-associated phenotypes are shown with bars indicating average GEP scores for tumors grouped according to LKB1 and neuroendocrine status as indicated. P-values represent results from Student’s T-test between groups as indicated.Abstract 909 Table 1LKB1 Loss Affects Composition of Immune Microenvironment. Values indicate log10 P-values comparing LKB1-loss to LKB1-WT tumors. Positive (red) indicates increased abundance in LKB1 loss. Negative (blue) indicates decreased abundance.ConclusionsWe conclude that tumor differentiation patterns strongly influence the immune microenvironment and immune exclusion characteristics of LKB1-deficient tumors. Neuroendocrine differentiation is associated with the strongest immune exclusion characteristics and should be evaluated clinically for evidence of immunotherapy resistance. A novel observation of increased plasma cell abundance is observed across multiple datasets and confirmed by pathology. Causal mechanisms linking differentiation status to immune activity is not well understood, and the functional role of plasma cells in the immune biology of LKB1-deficient tumors is undefined. These questions warrant further study to inform precision immuno-oncology treatments for these patients.AcknowledgementsThis work was funded by SITC AZ Immunotherapy in Lung Cancer grant (SPS256666) and DOD Lung Cancer Research Program Concept Award (LC180633).ReferencesSkoulidis F, Byers LA, Diao L, et al. Co-occurring genomic alterations define major subsets of KRAS-mutant lung adenocarcinoma with distinct biology, immune profiles, and therapeutic vulnerabilities. Cancer Discov 2015;5:860–77.Schabath MB, Welsh EA, Fulp WJ, et al. Differential association of STK11 and TP53 with KRAS mutation-associated gene expression, proliferation and immune surveillance in lung adenocarcinoma. Oncogene 2016;35:3209–16.Skoulidis F, Goldberg ME, Greenawalt DM, et al. STK11/LKB1 mutations and PD-1 inhibitor resistance in KRAS-mutant lung adenocarcinoma. Cancer Discovery 2018;8:822-835.Cancer Genome Atlas Research Network. Comprehensive molecular profiling of lung adenocarcinoma. Nature 2014;511:543–50.Chitale D, Gong Y, Taylor BS, et al. An integrated genomic analysis of lung cancer reveals loss of DUSP4 in EGFR-mutant tumors. Oncogene 2009;28:2773–83.Shedden K, Taylor JM, Enkemann SA, et al. Gene expression-based survival prediction in lung adenocarcinoma: a multi-site, blinded validation study. Nat Med 2008;14:822–7.

scholarly journals 603 Targeted STAT3 degradation leads to remodeling of an immunosuppressive tumor microenvironment and subsequent sensitization to immune checkpoint therapy

2021 ◽  
Vol 9 (Suppl 3) ◽  
pp. A633-A633
Author(s):  
Joyoti Dey ◽  
Phillip Liu ◽  
Michele Mayo ◽  
Rahul Karnik ◽  
Bin Yang ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cell ◽  
Tumor Microenvironment ◽  
Gene Expression Profiling ◽  
Cancer Cell ◽  
Immune Checkpoint ◽  
Expression Profiling ◽  
Immune Cell ◽  
B Cell Lymphoma ◽  
Activation Markers

BackgroundSignal Transducer and Activator of Transcription 3 (STAT3), a multifaceted transcription factor, is aberrantly activated across a variety of malignancies; however, its selective targeting has to-date remained a therapeutic challenge. STAT3 plays a pivotal role in shaping the tumor immune landscape through cancer cell-intrinsic mechanisms, direct regulation of immune cell function and via cancer cell- tumor microenvironment (TME) crosstalk, that collectively result in an immunosuppressive TME. Targeted protein degradation represents a novel therapeutic modality enabling direct targeting of previously undruggable oncoproteins. We have developed potent and selective STAT3 heterobifunctional degraders demonstrating activity across diverse tumor and immune cell types.MethodsWe investigated the immunomodulatory impact of STAT3 degradation on tumorigenesis in syngeneic mouse models representing cancers with heterogeneous immune milieus. Methods included in vivo pharmacological approaches, immunophenotyping and gene expression profiling.ResultsTreatment of CT-26 (colorectal cancer) and A20 (B-cell lymphoma) tumor-bearing mice with a STAT3 degrader resulted in significant tumor growth inhibition compared to controls, with loss of STAT3 protein in both tumor cells and TME. This was accompanied by a decrease in M2 polarized macrophages and concomitant increases in M1 polarized macrophages and tumor infiltrating lymphocytes. The anti-tumor responses were abrogated by antibody mediated CD8+ T cell depletion or by using immunodeficient host-strains implicating the observed efficacy to be predominantly driven by immune-directed mechanisms. Gene expression profiling of STAT3 degrader-treated CT-26 tumors showed marked increases in proinflammatory genes including T cell and M1 macrophage activation markers, compared to controls. Notably, induction of an Ifnγ-responsive gene signature (Ifnγ, Stat1, Cxcl9, Cxcl10, Ido1) suggested that STAT3 degradation results in a T-cell inflamed phenotype associated with responsiveness to immune checkpoint therapy (ICT). Furthermore, on-treatment tumors showed an upregulation of genes such as Pdl1, Ctla4, Lag3 which reflect T cell activation as well as counterregulatory mechanisms. Therefore, we evaluated STAT3 degradation in combination with anti-PD1 in these models which are poorly responsive to anti-PD1 monotherapy. Robust synergy was observed in the CT-26 model with 60% complete responses and development of immunological memory as confirmed by tumor re-challenge studies. Studies are underway to ascertain the applicability of this combination therapy in different tumor-immune contextures and indications, and to elucidate the mechanistic basis of synergy.ConclusionsSTAT3 degradation remodels an immunosuppressed TME activating anti-tumor immunity as monotherapy and effectively combines with anti-PD1. These data provide a rationale for selectively degrading STAT3 as a strategy to sensitize cancers with relevant immune contextures to ICT in the clinic.

scholarly journals Gene Expression Profiles of Multiple Synchronous Lesions in Lung Adenocarcinoma

Cells ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 3484
Author(s):  
Jisun Lim ◽  
Yeon Bi Han ◽  
Soo Young Park ◽  
Soyeon Ahn ◽  
Hyojin Kim ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Adenocarcinoma ◽  
Immune Cell ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Killer Cell ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Stepwise Change

Many studies support a stepwise continuum of morphologic changes between atypical adenomatous hyperplasia (AAH) and lung adenocarcinoma (ADC). Here we characterized gene expression patterns and the association of differentially expressed genes and immune tumor microenvironment behaviors in AAH to ADC during ADC development. Tumor tissues from nine patients with ADC and synchronous multiple ground glass nodules/lesions (GGN/Ls) were analyzed using RNA sequencing. Using clustering, we identified genes differentially and sequentially expressed in AAH and ADC compared to normal tissues. Functional enrichment analysis using gene ontology terms was performed, and the fraction of immune cell types was estimated. We identified up-regulated genes (ACSL5 and SERINC2) with a stepwise change of expression from AAH to ADC and validated those expressions by quantitative PCR and immunohistochemistry. The immune cell profiles revealed increased B cell activities and decreased natural killer cell activities in AAH and ADC. A stepwise change of differential expression during ADC development revealed potential effects on immune function in synchronous precursors and in tumor lesions in patients with lung cancer.

scholarly journals Analysis of Immune Gene Expression Subtypes Reveals Osteosarcoma Immune Heterogeneity

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Ben Wan ◽  
Renxian Wang ◽  
Jingjun Nie ◽  
Yuyang Sun ◽  
Bowen Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Cell ◽  
Structure Learning ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Poor Response ◽  
Immune Gene ◽  
Immune Gene Expression ◽  
Tumor Immune Microenvironment ◽  
Graph Structure Learning

Background. Osteosarcoma (OS) patients have a poor response to immunotherapy due to the sheer complexity of the immune system and the nuances of the tumor-immune microenvironment. Methodology. To gain insights into the immune heterogeneity of OS, we identified robust clusters of patients based on the immune gene expression profiles of OS patients in the TARGET database and assessed their reproducibility in an independent cohort collected from the GEO database. The association of comprehensive molecular characterization with reproducible immune subtypes was accessed with ANOVA. Furthermore, we visualized the distribution of individual patients in a tree structure by the graph structure learning-based dimensionality reduction algorithm. Results. We found that 87 OS samples can be divided into 5 immune subtypes, and each of them was associated with distinct clinical outcomes. The immune subtypes also demonstrated widely different patterns in tumor genetic aberrations, tumor-infiltrating, immune cell composition, and cytokine profiles. The immune landscape of OS uncovered the significant intracluster heterogeneity within each subtype and depicted a continuous immune spectrum across patients. Conclusion. The established five immune subtypes in our study suggested immune heterogeneity in OS patients and may provide optimal individual immunotherapy for patients exhibiting OS.

Genetic and Epigenetic landscape of leukocyte infiltration identifies an immune prognosticator in lung adenocarcinoma

2021 ◽  
pp. 1-13
Author(s):  
Seema Khadirnaikar ◽  
Annesha Chatterjee ◽  
Sudhanshu Kumar Shukla
Keyword(s):  
Lung Adenocarcinoma ◽  
Immune Cell ◽  
Cox Regression ◽  
Strong Association ◽  
Critical Role ◽  
Significant Proportion ◽  
Immune Gene ◽  
Leukocyte Infiltration ◽  
Clinical Genetic ◽  
Factors Affecting

BACKGROUND: Leukocyte infiltration plays an critical role in outcome of various diseases including Lung adenocarcinoma (LUAD). OBJECTIVES: To understand the genetic and epigenetic factors affecting leukocyte infiltration and identification and validation of immune based biomarkers. METHOD: Correlation analysis was done to get the associations of the factors. CIBERSORT analysis was done for immune cell infiltration. Genetic and epigenetic analysis were performed. Cox regression was carried out for survival. RESULTS: We categorized the TCGA-LUAD patients based on Leukocyte fraction (LF) and performed extensive immunogenomic analysis. Interestingly, we showed that LF has a negative correlation with copy number variation (CNV) but not with mutational load. However, several individual genetic mutations, including KRAS and KEAP1, were significantly linked with LF. Also, as expected, patients with high LF showed significantly increased expression of genes involved in leukocyte migration and activation. DNA methylation changes also showed a strong association with LF and regulated a significant proportion of genes associated with LF. We also developed and validated an independent prognostic immune signature using the top six prognostic genes associated with LF. CONCLUSION: Together, we have identified clinical, genetic, and epigenetic variations associated with LUAD LF and developed an immune gene-based signature for disease prognostication.

scholarly journals Predicting Host Immune Cell Dynamics and Key Disease-Associated Genes Using Tissue Transcriptional Profiles

Processes ◽  
2019 ◽  
Vol 7 (5) ◽  
pp. 301
Author(s):  
Muying Wang ◽  
Satoshi Fukuyama ◽  
Yoshihiro Kawaoka ◽  
Jason E. Shoemaker
Keyword(s):  
Gene Expression ◽  
Gene Expression Data ◽  
Immune Cell ◽  
Mean Squared Error ◽  
Expression Profiles ◽  
Statistical Tests ◽  
Critical Factor ◽  
Expression Data ◽  
Cell Dynamics ◽  
Cell Counts

Motivation: Immune cell dynamics is a critical factor of disease-associated pathology (immunopathology) that also impacts the levels of mRNAs in diseased tissue. Deconvolution algorithms attempt to infer cell quantities in a tissue/organ sample based on gene expression profiles and are often evaluated using artificial, non-complex samples. Their accuracy on estimating cell counts given temporal tissue gene expression data remains not well characterized and has never been characterized when using diseased lung. Further, how to remove the effects of cell migration on transcript counts to improve discovery of disease factors is an open question. Results: Four cell count inference (i.e., deconvolution) tools are evaluated using microarray data from influenza-infected lung sampled at several time points post-infection. The analysis finds that inferred cell quantities are accurate only for select cell types and there is a tendency for algorithms to have a good relative fit (R 2 ) but a poor absolute fit (normalized mean squared error; NMSE), which suggests systemic biases exist. Nonetheless, using cell fraction estimates to adjust gene expression data, we show that genes associated with influenza virus replication and increased infection pathology are more likely to be identified as significant than when applying traditional statistical tests.

Angiogenic and T-effector subgroups identified by gene expression profiling (GEP) and propensity for PBRM1 and BAP1 alterations in clear cell renal cell carcinoma (ccRCC).

2021 ◽  
Vol 39 (6_suppl) ◽  
pp. 343-343
Author(s):  
Pedro C. Barata ◽  
Shuchi Gulati ◽  
Andrew Elliott ◽  
Arpit Rao ◽  
Hans J. Hammers ◽  
...  
Keyword(s):  
Gene Expression ◽  
Clinical Trials ◽  
Hierarchical Clustering ◽  
Immune Cell ◽  
Expression Profiles ◽  
Gene Expression Signature ◽  
Predictive Biomarkers ◽  
Primary Tumors ◽  
Metastatic Sites ◽  
Patient Subgroups

343 Background: With the emergence of multiple active treatment options in RCC, predictive biomarkers for optimal treatment selection are lacking. Gene expression data from IMmotion151 and Javelin Renal 101 clinical trials generated anti-angiogenic and immune signatures that warrant further validation. We aimed to describe the genomic and gene expression profiles in a multi-institutional database of patients with ccRCC, and its association with other biomarkers of interest. Methods: Whole transcriptome sequencing was performed for ccRCC patient samples submitted to a commercial CLIA-certified laboratory (Caris Life Sciences, Phoenix, AZ) from February 2019 to September 2020. Tumor GEP and hierarchical clustering based on the validated 66-gene signature (D’Costa et al, 2020) were used to identify patient subgroups. Samples from both primary tumors and metastatic sites were included. Results: A total of 316 patients with ccRCC, median age 62 (range 32-90), 71.8% men, were included. Tissue samples were obtained from primary tumor (46.5%), lung (12.3%), bone (9.5%), liver (4.7%) and other metastatic sites (27%). Gene expression analysis identified angiogenic, mixed and T-effector subgroups in 24.1%, 51.3% and 24.7%, respectively. Patients with angiogenic subgroup tumors compared to those with T-effector subgroup tumors were more likely to be older (63 versus 60 years, p=0.035), female (40.8% versus 16.7%, p=0.0009) and more frequently found in pancreatic/small bowel metastases (75% versus 12.5%, p=0.0103). Biomarkers of potential response to immunotherapy such as PD-L1 (p=0.0021), TMB (not significant), and dMMR/MSI-H status (not significant) were more frequent in the T-effector subgroup. PBRM1 mutations were more common in the angiogenic subgroup (62.0% vs 37.5%, p=0.0034) while BAP1 mutations were more common in the T-effector subgroup (18.6% versus 3.0%, p= 0.0035). Immune cell population abundance (e.g. NK cells, monocytes) and immune checkpoint gene expression (TIM-3, PD-L1, PD-L2, CTLA4) were also increased in the T-effector subgroup. Conclusions: Our hierarchical clustering results based on the 66-gene expression signature were concordant with results from prior studies. Patient subgroups identified by evaluation of angiogenic and T-effector signature scores exhibit significantly different mutations and immune profiles. These findings require prospective validation in future biomarker-selected clinical trials.

scholarly journals 256CONSTRUCTION OF A BOVINE CDNA ARRAY TO MONITOR GENE EXPRESSION PROFILES IN BOVINE PREIMPLANTATION EMBRYOS

2004 ◽  
Vol 16 (2) ◽  
pp. 248
Author(s):  
C. Wrenzycki ◽  
T. Brambrink ◽  
D. Herrmann ◽  
J.W. Carnwath ◽  
H. Niemann
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Expression Profiles ◽  
Cdna Array ◽  
Preimplantation Embryos ◽  
Average Insert Size ◽  
Rt Pcr ◽  
Public Data

Array technology is a widely used tool for gene expression profiling, providing the possibility to monitor expression levels of an unlimited number of genes in various biological systems including preimplantation embryos. The objective of the present study was to develop and validate a bovine cDNA array and to compare expression profiles of embryos derived from different origins. A bovine blastocyst cDNA library was generated. Poly(A+)RNA was extracted from in vitro-produced embryos using a Dynabead mRNA purification kit. First-strand synthesis was performed with SacIT21 primer followed by randomly primed second-strand synthesis with a DOP primer mix (Roche) and a global PCR with 35 cycles using SacIT21 and DOP primers. Complementary DNA fragments from 300 to 1500bp were extracted from the gel and normalized via reassoziation and hydroxyapatite chromatography. Resulting cDNAs were digested with SacI and XhoI, ligated into a pBKs vector, and transfected into competent bacteria (Stratagene). After blue/white colony selection, plasmids were extracted and the inserts were subjected to PCR using vector specific primers. Average insert size was determined by size idenfication on agarose gels stained with ethidium bromide. After purification via precipitation and denaturation, 192 cDNA probes were double-spotted onto a nylon membrane and bound to the membrane by UV cross linking. Amplified RNA (aRNA) probes from pools of three or single blastocysts were generated as described recently (Brambrink et al., 2002 BioTechniques, 33, 3–9) and hybridized to the membranes. Expression profiles of in vitro-produced blastocysts cultured in either SOF plus BSA or TCM plus serum were compared with those of diploid parthenogenetic ones generated by chemical activation. Thirty-three probes have been sequenced and, after comparison with public data bases, 26 were identified as cDNAs or genes. Twelve out of 192 (6%) seem to be differentially expressed within the three groups;; 7/12 (58%) were down-regulated, 3/12 (25%) were up-regulated in SOF-derived embryos, and 2/12 (20%) were up-regulated in parthenogenetic blastocysts compared to their in vitro-generated counterparts. Three of these genes involved in calcium signaling (calmodulin, calreticulin) and regulation of actin cytoskeleton (destrin) were validated by semi-quantitative RT-PCR (Wrenzycki et al., 2001 Biol. Reprod. 65, 309–317) employing poly(A+) RNA from a single blastocyst as starting material. No differences were detected in the relative abundance of the analysed gene transcripts within the different groups. These findings were confirmed employing the aRNA used for hybridization in RT-PCR and showed a good representativity of the selected transcripts. Results indicate that it is possible to construct a homologous cDNA array which could be used for gene expression profiling of bovine preimplantation embryos. Supported by the Deutsche Forschungsgemeinschaft (DFG Ni 256/18-1).

scholarly journals P02.10 FocuSCOPE: a single cell, multi-omics solution to simultaneously analyze tumor variants and microenvironment

2021 ◽  
Vol 9 (Suppl 1) ◽  
pp. A12.1-A12
Author(s):  
Y Arjmand Abbassi ◽  
N Fang ◽  
W Zhu ◽  
Y Zhou ◽  
Y Chen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Tumor Microenvironment ◽  
Single Cell ◽  
High Throughput ◽  
Immune Cells ◽  
Genetic Variants ◽  
Expression Profiles ◽  
Single Cells ◽  
Gene Expression Profiles ◽  
Single Cell Sequencing

Recent advances of high-throughput single cell sequencing technologies have greatly improved our understanding of the complex biological systems. Heterogeneous samples such as tumor tissues commonly harbor cancer cell-specific genetic variants and gene expression profiles, both of which have been shown to be related to the mechanisms of disease development, progression, and responses to treatment. Furthermore, stromal and immune cells within tumor microenvironment interact with cancer cells to play important roles in tumor responses to systematic therapy such as immunotherapy or cell therapy. However, most current high-throughput single cell sequencing methods detect only gene expression levels or epigenetics events such as chromatin conformation. The information on important genetic variants including mutation or fusion is not captured. To better understand the mechanisms of tumor responses to systematic therapy, it is essential to decipher the connection between genotype and gene expression patterns of both tumor cells and cells in the tumor microenvironment. We developed FocuSCOPE, a high-throughput multi-omics sequencing solution that can detect both genetic variants and transcriptome from same single cells. FocuSCOPE has been used to successfully perform single cell analysis of both gene expression profiles and point mutations, fusion genes, or intracellular viral sequences from thousands of cells simultaneously, delivering comprehensive insights of tumor and immune cells in tumor microenvironment at single cell resolution.Disclosure InformationY. Arjmand Abbassi: None. N. Fang: None. W. Zhu: None. Y. Zhou: None. Y. Chen: None. U. Deutsch: None.

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