Survey of the immunogenomic landscape of solid tumors through clinical DNA and RNA sequencing.

2019 ◽  
Vol 37 (8_suppl) ◽  
pp. 153-153
Author(s):  
Denise Lau ◽  
Alan Chang ◽  
Jason Perera ◽  
Ariane Lozac'hmeur ◽  
Alexandria Bobe ◽  
...  
Keyword(s):  
Dna Sequencing ◽  
Solid Tumors ◽  
Rna Sequencing ◽  
Immune Cells ◽  
Immune Activation ◽  
Clinical Care ◽  
Relative Proportion ◽  
Tumor Infiltration ◽  
Sequencing Data ◽  
Dna And Rna

153 Background: In the past decade, immunotherapy has emerged as an important new modality in cancer treatment. However, studies have shown that only a fraction of patients will experience any clinical benefit when treated with immune checkpoint blockade drugs. Given the cost and potent adverse events associated with immunotherapy, the need for effective biomarkers is clear. We sought to understand the role of key immunotherapy biomarkers, like tumor mutational burden (TMB), microsatellite instability (MSI), and PD-L1 immunohistochemistry (IHC), in the context of the greater immunogenomic landscape of solid tumors in patients. Methods: We analyzed data from a cohort of 500 patients across 10 cancer types who received the Tempus xT 595 gene targeted DNA sequencing assay and whole transcriptome sequencing assay as part of their clinical care. We determined the TMB, MSI status, and neoantigen load for each sample using the DNA sequencing data. We used the RNA expression data to evaluate immune activation and tumor infiltration by determining the expression of inflammatory gene signatures and estimating the relative proportion of key immune cell types. Results: Integrative analysis of the DNA and RNA sequencing data showed that the immunogenicity of the tumor, as measured by TMB or neoantigen load, correlates with levels of immune activation and tumor infiltration. Inflammatory immune cells, like CD8 T cells and M1 polarized macrophages, were significantly higher in TMB-high samples; while non-inflammatory immune cells, like monocytes, were significantly lower in TMB-high samples. Additionally, samples could be clustered into immunologically active “hot” tumors or immunologically silent “cold” tumors based on gene expression. The immunologically “hot” population was enriched for samples that were TMB-high, MSI-high or PD-L1 IHC positive. Conclusions: Paired next generation DNA and RNA sequencing assays allows for the identification of patients that have immunologically active tumors that lack traditional immunotherapy biomarkers. These patients represent an interesting new population who may potentially benefit from immunotherapy.

scholarly journals The Crosstalk Between Malignant Cells and Tumor-Promoting Immune Cells Relevant to Immunotherapy in Pancreatic Ductal Adenocarcinoma

2022 ◽  
Vol 9 ◽  
Author(s):  
Xuefei Liu ◽  
Ziwei Luo ◽  
Xuechen Ren ◽  
Zhihang Chen ◽  
Xiaoqiong Bao ◽  
...  
Keyword(s):  
Pancreatic Ductal Adenocarcinoma ◽  
Rna Sequencing ◽  
Immune Cells ◽  
Immune Checkpoint ◽  
Immune Cell ◽  
Immune Checkpoint Blockade ◽  
Ductal Adenocarcinoma ◽  
Malignant Cells ◽  
Sequencing Data ◽  
Immunosuppressive Microenvironment

Background: Pancreatic ductal adenocarcinoma (PDAC) is dominated by an immunosuppressive microenvironment, which makes immune checkpoint blockade (ICB) often non-responsive. Understanding the mechanisms by which PDAC forms an immunosuppressive microenvironment is important for the development of new effective immunotherapy strategies.Methods: This study comprehensively evaluated the cell-cell communications between malignant cells and immune cells by integrative analyses of single-cell RNA sequencing data and bulk RNA sequencing data of PDAC. A Malignant-Immune cell crosstalk (MIT) score was constructed to predict survival and therapy response in PDAC patients. Immunological characteristics, enriched pathways, and mutations were evaluated in high- and low MIT groups.Results: We found that PDAC had high level of immune cell infiltrations, mainly were tumor-promoting immune cells. Frequent communication between malignant cells and tumor-promoting immune cells were observed. 15 ligand-receptor pairs between malignant cells and tumor-promoting immune cells were identified. We selected genes highly expressed on malignant cells to construct a Malignant-Immune Crosstalk (MIT) score. MIT score was positively correlated with tumor-promoting immune infiltrations. PDAC patients with high MIT score usually had a worse response to immune checkpoint blockade (ICB) immunotherapy.Conclusion: The ligand-receptor pairs identified in this study may provide potential targets for the development of new immunotherapy strategy. MIT score was established to measure tumor-promoting immunocyte infiltration. It can serve as a prognostic indicator for long-term survival of PDAC, and a predictor to ICB immunotherapy response.

scholarly journals SNV identification from single-cell RNA sequencing data

2019 ◽  
Vol 28 (21) ◽  
pp. 3569-3583 ◽  
Author(s):  
Patricia M Schnepp ◽  
Mengjie Chen ◽  
Evan T Keller ◽  
Xiang Zhou
Keyword(s):  
Dna Sequencing ◽  
Single Cell ◽  
Rna Sequencing ◽  
Single Cells ◽  
Specific Gene ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
Single Cell Rna Sequencing ◽  
Sequencing Studies ◽  
Genomic Regions

Abstract Integrating single-cell RNA sequencing (scRNA-seq) data with genotypes obtained from DNA sequencing studies facilitates the detection of functional genetic variants underlying cell type-specific gene expression variation. Unfortunately, most existing scRNA-seq studies do not come with DNA sequencing data; thus, being able to call single nucleotide variants (SNVs) from scRNA-seq data alone can provide crucial and complementary information, detection of functional SNVs, maximizing the potential of existing scRNA-seq studies. Here, we perform extensive analyses to evaluate the utility of two SNV calling pipelines (GATK and Monovar), originally designed for SNV calling in either bulk or single-cell DNA sequencing data. In both pipelines, we examined various parameter settings to determine the accuracy of the final SNV call set and provide practical recommendations for applied analysts. We found that combining all reads from the single cells and following GATK Best Practices resulted in the highest number of SNVs identified with a high concordance. In individual single cells, Monovar resulted in better quality SNVs even though none of the pipelines analyzed is capable of calling a reasonable number of SNVs with high accuracy. In addition, we found that SNV calling quality varies across different functional genomic regions. Our results open doors for novel ways to leverage the use of scRNA-seq for the future investigation of SNV function.

scholarly journals Assessment of long non-coding RNA expression reveals novel mediators of the lung tumour immune response

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Adam P. Sage ◽  
Kevin W. Ng ◽  
Erin A. Marshall ◽  
Greg L. Stewart ◽  
Brenda C. Minatel ◽  
...  
Keyword(s):  
Nk Cells ◽  
Rna Sequencing ◽  
Immune Cells ◽  
Mononuclear Cells ◽  
Expression Patterns ◽  
Lung Tumour ◽  
Sequencing Data ◽  
Non Coding Rna ◽  
Long Non Coding Rna

Abstract The tumour immune microenvironment is a crucial mediator of lung tumourigenesis, and characterizing the immune landscape of patient tumours may guide immunotherapy treatment regimens and uncover novel intervention points. We sought to identify the landscape of tumour-infiltrating immune cells in the context of long non-coding RNA (lncRNAs), known regulators of gene expression. We examined the lncRNA profiles of lung adenocarcinoma (LUAD) tumours by interrogating RNA sequencing data from microdissected and non-microdissected samples (BCCRC and TCGA). Subsequently, analysis of single-cell RNA sequencing data from lung tumours and flow-sorted healthy peripheral blood mononuclear cells identified lncRNAs in immune cells, highlighting their biological and prognostic relevance. We discovered lncRNA expression patterns indicative of regulatory relationships with immune-related protein-coding genes, including the relationship between AC008750.1 and NKG7 in NK cells. Activation of NK cells in vitro was sufficient to induce AC008750.1 expression. Finally, siRNA-mediated knockdown of AC008750.1 significantly impaired both the expression of NKG7 and the anti-tumour capacity of NK cells. We present an atlas of cancer-cell extrinsic immune cell-expressed lncRNAs, in vitro evidence for a functional role of lncRNAs in anti-tumour immune activity, which upon further exploration may reveal novel clinical utility as markers of immune infiltration.

Immunoregulation related gene of CSMD2 and RNA activity as potential predicter of 2-year survival in pancreatic cancer: A DNA and RNA sequencing analysis.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e16212-e16212
Author(s):  
Jiafei Yan ◽  
Si Li ◽  
Wenjing Xi ◽  
Dongsheng Chen ◽  
Mingzhe Xiao
Keyword(s):  
Pancreatic Cancer ◽  
T Cell ◽  
Rna Sequencing ◽  
T Cell Activation ◽  
Cell Activation ◽  
Treatment Options ◽  
Cell Activity ◽  
Sequencing Analysis ◽  
Sequencing Data ◽  
Dna And Rna

e16212 Background: The 5-year survival rate of pancreatic cancer remains as low as 3%-15%. One of the key approaches to enrich current treatment options or improve effectiveness is new biomarker probing. We conducted DNA and RNA sequencing analysis to reveal potential biomarkers related to overall survival. Methods: Whole-exome sequencing, RNA sequencing and clinical data for 209 patients with pancreatic cancer were downloaded from TCGA. Clinical factors and mutational landscape (insertion/ deletion/ single nucleotide variant) were compared between group of OS2+ (OS longer than 2 years) and OS2- (OS longer than 2 years) with T test and Chi-square Test. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted with RNA sequencing data to clarify the functional differences between the two groups. Results: The rates of OS2+ for patients in stage of I/II/III/IV was 43% (9/21), 17.8% (27/152), 0% (0/4), 0% (0/5), respectively. 152 patients in stage II were included for further analysis. No difference of sex and age were found between group of OS2+ and OS2-. Tumor mutation burden was comparable between the two groups. Mutation landscape showed the two groups had the accordance of 50% in top 10 genes. Mutations of CSMD2(18.5% vs. 5.0% , P = 0.026), CMYA5(14.8% vs, 2.5% , P = 0.019) and KCNA6(14.8% vs, 3.3%, P = 0.034) were more frequent in OS2+ group. CSMD2 is thought to be involved in the control of complement cascade of the immune system, and its low expression was significantly associated with differentiation, lymphatic invasion, and tumor size in colorectal cancer. CMYA5 was predicted as novel oncogene in breast cancer with the tool of Moonlight, it may also participate tumor activity in pancreatic cancer. The role of KCNA6 in cancer cell activity is barely known yet. Evaluation of differentially expressed genes between the two groups detected difference in leukocyte differentiation and T cell activation (GO analysis) and MAPK signal pathway (KEGG panalysis), these immunoregulation and MAPK pathways may play critical roles in tumor development and progression and affect the prognosis of pancreatic cancer. Conclusions: Pancreatic cancer with 2-year survival presented significant different DNA and RNA alterations, in which CSMD2 and pathway of leukocyte differentiation and T cell activation are closely associated with immunoregulation. These might provide guidance for prognose management and development of new therapeutic targets. Further mechanistic insights and prospective validation studies are warranted.

scholarly journals Analysis of Bulk RNA Sequencing Data Reveals Novel Transcription Factors Associated With Immune Infiltration Among Multiple Cancers

2021 ◽  
Vol 12 ◽  
Author(s):  
Lei Liu ◽  
Qiuchen Zhao ◽  
Chao Cheng ◽  
Jingwen Yi ◽  
Hongyan Sun ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Rna Sequencing ◽  
Immune Cells ◽  
The Cancer Genome Atlas ◽  
Eqtl Analysis ◽  
Sequencing Data ◽  
Cancer Data ◽  
Immune Infiltration ◽  
Multiple Cancers ◽  
Immune Related Genes

Tumor-infiltrating immune cells shape the tumor microenvironment and are closely related to clinical outcomes. Several transcription factors (TFs) have also been reported to regulate the antitumor activity and immune cell infiltration. This study aimed to quantify the populations of different immune cells infiltrated in tumor samples based on the bulk RNA sequencing data obtained from 50 cancer patients using the CIBERSORT and the EPIC algorithm. Weighted gene coexpression network analysis (WGCNA) identified eigengene modules strongly associated with tumorigenesis and the activation of CD4+ memory T cells, dendritic cells, and macrophages. TF genes FOXM1, MYBL2, TAL1, and ERG are central in the subnetworks of the eigengene modules associated with immune-related genes. The analysis of The Cancer Genome Atlas (TCGA) cancer data confirmed these findings and further showed that the expression of these potential TF genes regulating immune infiltration, and the immune-related genes that they regulated, was associated with the survival of patients within multiple cancers. Exome-seq was performed on 24 paired samples that also had RNA-seq data. The expression quantitative trait loci (eQTL) analysis showed that mutations were significantly more frequent in the regions flanking the TF genes compared with those of non-TF genes, suggesting a driver role of these TF genes regulating immune infiltration. Taken together, this study presented a practical method for identifying genes that regulate immune infiltration. These genes could be potential biomarkers for cancer prognosis and possible therapeutic targets.

Computational Analysis of DNA and RNA Sequencing Data Obtained from Liquid Biopsies

2019 ◽  
pp. 347-368 ◽  
Author(s):  
Francesco Marass ◽  
Francesc Castro-Giner ◽  
Barbara Maria Szczerba ◽  
Katharina Jahn ◽  
Jack Kuipers ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Computational Analysis ◽  
Sequencing Data ◽  
Liquid Biopsies ◽  
Dna And Rna

scholarly journals Evaluating the Genome and Resistome of Extensively Drug-Resistant Klebsiella pneumoniae using Native DNA and RNA Nanopore Sequencing

2018 ◽  
Author(s):  
Miranda E. Pitt ◽  
Son H. Nguyen ◽  
Tânia P.S. Duarte ◽  
Mark A.T. Blaskovich ◽  
Matthew A. Cooper ◽  
...  
Keyword(s):  
Klebsiella Pneumoniae ◽  
Dna Sequencing ◽  
Rna Sequencing ◽  
Resistance Genes ◽  
Acquired Resistance ◽  
Drug Susceptibility ◽  
Drug Resistant ◽  
Dna And Rna ◽  
Extensively Drug Resistant

ABSTRACTKlebsiella pneumoniae frequently harbour multidrug resistance and current methodologies are struggling to rapidly discern feasible antibiotics to treat these infections. While rapid DNA sequencing has been proposed for prediction of resistance profile; the role of rapid RNA sequencing has yet to be fully explored. The MinION sequencer can sequence native DNA and RNA in real-time, providing an opportunity to contrast the utility of DNA and RNA for prediction of drug susceptibility. This study interrogated the genome and transcriptome of four extensively drug-resistant (XDR) K. pneumoniae clinical isolates. The majority of acquired resistance (≥75%) resided on plasmids including several megaplasmids (≥100 kbp). DNA sequencing identified most resistance genes (≥70%) within 2 hours of sequencing. Direct RNA sequencing (with a ∼6x slower pore translocation) was able to identify ≥35% of resistance genes, including aminoglycoside, β-lactam, trimethoprim and sulphonamide and also quinolone, rifampicin, fosfomycin and phenicol in some isolates, within 10 hours of sequencing. Polymyxin-resistant isolates showed a heightened transcription of phoPQ (≥2-fold) and the pmrHFIJKLM operon (≥8-fold). Expression levels estimated from direct RNA sequencing displayed strong correlation (Pearson: 0.86) compared to qRT-PCR across 11 resistance genes. Overall, MinION sequencing rapidly detected the XDR K. pneumoniae resistome and direct RNA sequencing revealed differential expression of these genes.

scholarly journals Comparison of DNA and RNA sequencing of total nucleic acids from human cervix for metagenomics

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Laila Sara Arroyo Mühr ◽  
Joakim Dillner ◽  
Agustin Enrique Ure ◽  
Karin Sundström ◽  
Emilie Hultin
Keyword(s):  
Nucleic Acids ◽  
Dna Sequencing ◽  
Rna Sequencing ◽  
Reverse Transcription ◽  
Rna Viruses ◽  
Dna And Rna ◽  
Dnase Treatment ◽  
Similarities And Differences ◽  
Viral Sequences ◽  
Human Cervix

AbstractAlthough metagenomics and metatranscriptomics are commonly used to identify bacteria and viruses in human samples, few studies directly compare these strategies. We wished to compare DNA and RNA sequencing of bacterial and viral metagenomes and metatranscriptomes in the human cervix. Total nucleic acids from six human cervical samples were subjected to DNA and RNA sequencing. The effect of DNase-treatment before reverse transcription to cDNA were also analyzed. Similarities and differences in the metagenomic findings with the three different sequencing approaches were evaluated. A higher proportion of human sequences were detected by DNA sequencing (93%) compared to RNA sequencing without (76%) and with prior DNase-treatment (11%). On the contrary, bacterial sequences increased 17 and 91 times. However, the number of detected bacterial genera were less by RNA sequencing, suggesting that only a few contribute to most of the bacterial transcripts. The viral sequences were less by RNA sequencing, still twice as many virus genera were detected, including some RNA viruses that were missed by DNA sequencing. Metatranscriptomics of total cDNA provided improved detection of mainly transcribed bacteria and viruses in cervical swabs as well as detection of RNA viruses, compared to metagenomics.

scholarly journals Genotyping Copy Number Alterations from single-cell RNA sequencing

2021 ◽  
Author(s):  
Salvatore Milite ◽  
Riccardo Bergamin ◽  
Giulio Caravagna
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Single Molecule ◽  
Copy Number ◽  
Probabilistic Method ◽  
Real Data ◽  
Copy Number Alterations ◽  
Sequencing Data ◽  
Dna And Rna ◽  
Single Cell Rna Sequencing

AbstractCancers are constituted by heterogeneous populations of cells that show complex genotypes and phenotypes which we can read out by sequencing. Many attempts at deciphering the clonal process that drives these populations are focusing on single-cell technologies to resolve genetic and phenotypic intra-tumour heterogeneity. While the ideal technologies for these investigations are multi-omics assays, unfortunately these types of data are still too expensive and have limited scalability. We can resort to single-molecule assays, which are cheaper and scalable, and statistically emulate a joint assay, only if we can integrate measurements collected from independent cells of the same sample. In this work we follow this intuition and construct a new Bayesian method to genotype copy number alterations on single-cell RNA sequencing data, therefore integrating DNA and RNA measurements. Our method is unsupervised, and leverages on a segmentation of the input DNA to determine the sample subclonal composition at the copy number level, together with clone-specific phenotypes defined from RNA counts. By design our probabilistic method works without a reference RNA expression profile, and therefore can be applied in cases where this information may not be accessible. We implement the method on a probabilistic backend that allows easy running on both CPUs and GPUs, and test it on both simulated and real data. Our analysis shows its ability to determine copy number associated clones and their RNA phenotypes in tumour data from 10x and Smart-Seq assays, as well as in data from the Human Cell Atlas project.

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