Unbiased Reconstruction of a Mammalian Transcriptional Network Mediating Pathogen Responses

Models of mammalian regulatory networks controlling gene expression have been inferred from genomic data but have largely not been validated. We present an unbiased strategy to systematically perturb candidate regulators and monitor cellular transcriptional responses. We applied this approach to derive regulatory networks that control the transcriptional response of mouse primary dendritic cells to pathogens. Our approach revealed the regulatory functions of 125 transcription factors, chromatin modifiers, and RNA binding proteins, which enabled the construction of a network model consisting of 24 core regulators and 76 fine-tuners that help to explain how pathogen-sensing pathways achieve specificity. This study establishes a broadly applicable, comprehensive, and unbiased approach to reveal the wiring and functions of a regulatory network controlling a major transcriptional response in primary mammalian cells

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Abstract 4749: Simultaneous multi-omic measurement of nucleic-acids and proteins at 800-plex using single-molecule optical barcodes: Application to cancer immunotherapy

Abstract Both ENCODE and TCGA projects highlighted the value of quantifying multiple biomarker classes (DNA, RNA, protein) from cancer tumor samples. In the case of cancer immunotherapy, the importance of measuring non-DNA markers (e.g., mRNA and proteins) becomes crucial, since cell-signaling, tumor microenvironment, and protein-protein interactions dominate over pure SNP-based (DNA) driver mutations in determining therapeutic response. Combining multiple data types together into a single correlated analysis, however, is adversely effected by the drastically different methodologies utilized for measurement. For example, the fluorescence signal intensity obtained from a camera imaging a protein array (e.g., RPPA) is very difficult to correlate directly with an RNA-Sequencing count of a clonally amplified, cDNA-converted, mRNA molecule. New developments in multiple biomarker-class optical barcode counting significantly reduce this problem. Recent work from the Weissleder-lab [1] has shown how optical barcode technology can be utilized for multiplexed digital counting of proteins, and be combined with simultaneous digital counting of nucleic-acids on a single platform. In this study we describe single-molecule digital counting of mRNA and proteins in a single simultaneous reaction using ∼ 50,000 cells as input (∼ 1000 cells if only protein-targets). Since multiplexed digital protein counting with barcodes is relatively new, a detailed comparison study versus flow cytometry was performed. Short photo-cleavable 60-mer single-stranded DNA-tags that index, and hybridize to, NanoString Optical barcodes were covalently labeled on the following antibody targets: EGFR, pEGFR, HistoneH3, CD45, FoxP3, pAKT, PCNA, GAPDH, Her3, PD-L1, pS6, Her2, ERK, pERK, and a rabbit monoclonal control. Single-target flow cytometry was performed on three cell-lines (A431, A565, H520) using the unlabeled primary antibodies and detected using FITC-dye labeled goat anti-rabbit. The flow-data were then compared to simultaneous 15-plex optical barcode detection. In all cases, high correlation coefficients (&amp;gt; 0.9) were obtained when comparing any single-target (flow vs. 15-plex optical barcode) across all cell-lines (for above-background markers). Additionally, post-translational modifications were both imaged (F-IHC) and digitally counted, revealing a high correlation in response. These multiplexed protein measurements can now be simultaneously combined with the PanCancer Immune Profiling Panel, consisting of 770 mRNAs representing 24 infiltrating immune cell-types, as well as a number of antigen processing pathways, yielding an unprecedented multi-omics measurement of tumor immune response. [1] Ullal et al. Science Translational Medicine 6:219 (Jan 15 2014) Citation Format: Joseph M. Beechem, Gary Geiss, Brian Filanoski, Brian Birditt. Simultaneous multi-omic measurement of nucleic-acids and proteins at 800-plex using single-molecule optical barcodes: Application to cancer immunotherapy. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4749. doi:10.1158/1538-7445.AM2015-4749</jats:p

Abstract A013: Biomarker development for cancer immuno-oncology/immunotherapy: Simultaneous digital counting of nucleic acids and proteins at 800-plex

Abstract The ability of mutated cells to give rise to pathological cancer relies upon the capability of these cells to interact with the immune system and ultimately evade immune recognition, suppress immune activity, and persist in a chronically inflamed environment. There is a clear need for new technologies capable of monitoring these crucial tumor immune-system interactions. The importance of measuring non-DNA markers (e.g., mRNA and proteins) becomes crucial in immuno-oncology (IO), since transcriptional reprogramming, cell-signaling, tumor microenvironment, and protein-protein interactions dominate the immune response. Combining multiple data types together into a single correlated analysis, however, is very difficult, due to the drastically different methodologies utilized for measurement. New developments in multiple biomarker-class optical barcode counting significantly reduce this problem. Recent work from the Weissleder-lab [1] has shown how optical barcode technology can be utilized for multiplexed digital counting of proteins, and be combined with simultaneous digital counting of nucleic-acids on a single platform. NanoString has expanded upon this original work and developed a cancer immune-profiling technology that simultaneously measures 770 mRNA's (unique signatures for 24 infiltrating immune cell types plus extensive immune-signaling pathways) plus 30 key IO proteins (including PD-1, PD-L1, PD-L2, CTLA4, OX40) using small amounts of clinically relevant samples (~ 50,000 PBMCs for mRNA+protein, 1 or 2, 5um slices for mRNA alone). This technology (RNA:Protein) is forming the basis for multi-year collaborations between NanoString and both MD Anderson (Houston TX) and the Cancer Immunotherapy Trials Network (CITN) to discover unique multi-analyte-type (mRNA + protein) biomarker signatures to guide cancer immunotherapy. NanoString gene expression profiling has also been highlighted by Merck (poster # 6017, ASCO 2015) as a method to select patients that will benefit from anti-PD1 based therapy (Keytruda). This technology is also being expanded to work on multi-analyte detection completely from FFPE slices. Several examples of the utilization of RNA:Protein immune-profiling technology to develop biomarker signatures will be presented. Reference: [1] Ullal et al. Science Translational Medicine 6:219 (Jan 15 2014) Citation Format: Joseph Beechem, Liz Manrao, Marty Ross, Gokhan Demirkan, Brian Filanoski, Brian Birditt, Celine Ngouenet, Christina Bailey, Lucas Dennis, Irena Pekker, Gavin Meredith, Dae Kim, Gary Giess. Biomarker development for cancer immuno-oncology/immunotherapy: Simultaneous digital counting of nucleic acids and proteins at 800-plex. [abstract]. In: Proceedings of the CRI-CIMT-EATI-AACR Inaugural International Cancer Immunotherapy Conference: Translating Science into Survival; September 16-19, 2015; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2016;4(1 Suppl):Abstract nr A013.</jats:p

Inter- and intra-tumor heterogeneity of metastatic prostate cancer determined by digital spatial gene expression profiling

AbstractMetastatic prostate cancer (mPC) comprises a spectrum of diverse phenotypes. However, the extent of inter- and intra-tumor heterogeneity is not established. Here we use digital spatial profiling (DSP) technology to quantitate transcript and protein abundance in spatially-distinct regions of mPCs. By assessing multiple discrete areas across multiple metastases, we find a high level of intra-patient homogeneity with respect to tumor phenotype. However, there are notable exceptions including tumors comprised of regions with high and low androgen receptor (AR) and neuroendocrine activity. While the vast majority of metastases examined are devoid of significant inflammatory infiltrates and lack PD1, PD-L1 and CTLA4, the B7-H3/CD276 immune checkpoint protein is highly expressed, particularly in mPCs with high AR activity. Our results demonstrate the utility of DSP for accurately classifying tumor phenotype, assessing tumor heterogeneity, and identifying aspects of tumor biology involving the immunological composition of metastases.</jats:p

Abstract 3878: Subcellular characterization of over 100 proteins in FFPE tumor biopsies with CosMx Spatial Molecular Imager

Abstract The spatial interactions between the immune system and tumor cells greatly influence antitumoral immunity. Characterization of immune cell composition and infiltration within the tumor niche informs prognosis, drug delivery efficiency, and therapeutic efficacy. However, few methods exist to query large numbers of immune biomarkers at subcellular spatial resolution. The CosMx™ Spatial Molecular Imager is the first platform to demonstrate simultaneous single-cell and subcellular detection of over 100 proteins on standard, biobanked, FFPE tissue samples. This high-plex protein panel detects key drivers of cancer progression and immune cell activation states. Here, we apply the CosMx 100-plex immuno-oncology assay on a set of breast cancer biopsies and demonstrate its quantitative and spatial capabilities. Key to CosMx protein technology is an antibody-oligonucleotide-conjugate 64-bit encoding method, not a cyclic exchange method. The encoding scheme is enabled by a 20nm hybridization-based optical barcode. The CosMx system uses a fully automated, cyclic microfluidics imaging system, high-resolution optics and 3D capability. The raw cyclic encoded 4-color tissue images are decoded using a robust automated decoding algorithm that detects protein sub-cellular localization and quantifies expression level. CosMx SMI produces protein localization maps for each target, which characterizes tissue microenvironment heterogeneity while providing spatial information. Additionally, accurate segmentation of individual cells enables spatial single-cell protein expression analysis, facilitating further mining and analyses of cellular subpopulations. The CosMx protein assay reagents were validated on multi-organ FFPE tissue microarrays and 35 human FFPE cell lines, including overexpression lines for key targets and cellular activation states, such as GITR, CD278, PD-L1, and PD-1. Benchmarking to multiple orthogonal datasets (e.g., the Human Protein Atlas, Cancer Cell Line Encyclopedia, and low-plex IHC) demonstrates that the assay is highly sensitive and specific. CosMx SMI protein assay can be coupled with SMI’s 1000-plex RNA-detection assay; together, such a multi-omics platform can generate an unprecedented information-rich view of spatial biology that could usher in novel discoveries about health and disease. FOR RESEARCH USE ONLY. Not for use in diagnostic procedures. Citation Format: Zachary R. Lewis, Tien Phan-Everson, Gary Geiss, Mithra Korukonda, Ruchir Bhatt, Carl Brown, Dwayne Dunaway, Joseph Phan, Alyssa Rosenbloom, Brian Filanoski, Rhonda Meredith, Kan Chantranuvatana, Yan Liang, Emily Brown, Brian Birditt, Giang Ong, Hye Son Yi, Erin Piazza, Vikram Devgan, Nicole Ortogero, Patrick Danaher, Sarah Warren, Michael Rhodes, Joseph Beechem. Subcellular characterization of over 100 proteins in FFPE tumor biopsies with CosMx Spatial Molecular Imager [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3878.</jats:p

Demographic Processes Affect HIV-1 Evolution in Primary Infection before the Onset of Selective Processes

ABSTRACT HIV-1 transmission and viral evolution in the first year of infection were studied in 11 individuals representing four transmitter-recipient pairs and three independent seroconverters. Nine of these individuals were enrolled during acute infection; all were men who have sex with men (MSM) infected with HIV-1 subtype B. A total of 475 nearly full-length HIV-1 genome sequences were generated, representing on average 10 genomes per specimen at 2 to 12 visits over the first year of infection. Single founding variants with nearly homogeneous viral populations were detected in eight of the nine individuals who were enrolled during acute HIV-1 infection. Restriction to a single founder variant was not due to a lack of diversity in the transmitter as homogeneous populations were found in recipients from transmitters with chronic infection. Mutational patterns indicative of rapid viral population growth dominated during the first 5 weeks of infection and included a slight contraction of viral genetic diversity over the first 20 to 40 days. Subsequently, selection dominated, most markedly in env and nef . Mutants were detected in the first week and became consensus as early as day 21 after the onset of symptoms of primary HIV infection. We found multiple indications of cytotoxic T lymphocyte (CTL) escape mutations while reversions appeared limited. Putative escape mutations were often rapidly replaced with mutually exclusive mutations nearby, indicating the existence of a maturational escape process, possibly in adaptation to viral fitness constraints or to immune responses against new variants. We showed that establishment of HIV-1 infection is likely due to a biological mechanism that restricts transmission rather than to early adaptive evolution during acute infection. Furthermore, the diversity of HIV strains coupled with complex and individual-specific patterns of CTL escape did not reveal shared sequence characteristics of acute infection that could be harnessed for vaccine design. </jats:p

Unbiased Reconstruction of a Mammalian Transcriptional Network Mediating Pathogen Responses

Models of mammalian regulatory networks controlling gene expression have been inferred from genomic data but have largely not been validated. We present an unbiased strategy to systematically perturb candidate regulators and monitor cellular transcriptional responses. We applied this approach to derive regulatory networks that control the transcriptional response of mouse primary dendritic cells to pathogens. Our approach revealed the regulatory functions of 125 transcription factors, chromatin modifiers, and RNA binding proteins, which enabled the construction of a network model consisting of 24 core regulators and 76 fine-tuners that help to explain how pathogen-sensing pathways achieve specificity. This study establishes a broadly applicable, comprehensive, and unbiased approach to reveal the wiring and functions of a regulatory network controlling a major transcriptional response in primary mammalian cells.Burroughs Wellcome Fund (Career Award at the Scientific Interface)National Institutes of Health (U.S.) (Pioneer Award)Alfred P. Sloan Foundatio

Unbiased Reconstruction of a Mammalian Transcriptional Network Mediating Pathogen Responses

Models of mammalian regulatory networks controlling gene expression have been inferred from genomic data but have largely not been validated. We present an unbiased strategy to systematically perturb candidate regulators and monitor cellular transcriptional responses. We applied this approach to derive regulatory networks that control the transcriptional response of mouse primary dendritic cells to pathogens. Our approach revealed the regulatory functions of 125 transcription factors, chromatin modifiers, and RNA binding proteins, which enabled the construction of a network model consisting of 24 core regulators and 76 fine-tuners that help to explain how pathogen-sensing pathways achieve specificity. This study establishes a broadly applicable, comprehensive, and unbiased approach to reveal the wiring and functions of a regulatory network controlling a major transcriptional response in primary mammalian cells.Burroughs Wellcome Fund (Career Award at the Scientific Interface)National Institutes of Health (U.S.) (Pioneer Award)Alfred P. Sloan Foundatio