A typical human cell consists of about 2 x 3.3 billion base pairs of DNA and 600 million bases of mRNA. Usually a mix of millions of cells are used in sequencing the DNA or RNA using traditional methods like Sanger sequencing or Illumina sequencing. By using deep sequencing of DNA and RNA from a single cell, cellular functions can be investigated extensively.
Single-cell Seq: Single-cell DNA genome sequencing involves isolating a single cell, amplifying the whole genome or region of interest, constructing sequencing libraries, and then applying next-generation DNA sequencing (ex. Illumina, Ion Torrent). In mammalian systems, single-cell DNA sequencing has been widely applied to study normal physiology and disease. Single-cell resolution can uncover the roles of genetic mosaicism or intra-tumor genetic heterogeneity in cancer development or treatment response.
Single-cell RNA-Seq: Single-Cell RNA sequencing aims to uncover the transcriptome diversity in heterogeneous cell populations. Cell populations are rarely homogeneous and synchronized in their characteristics. When researchers trying to evaluate the response of cells to internal or external stimuli, standard RNA-Seq won’t help much due to averaging of expression levels between thousands of cells. Using the 10x Genomics@ ChromiumTM platform, we could help the researchers perform transcriptome analysis of tens of thousands of individual cells in a cost-effective way.
Data analysis, including data validation, visualization and quantification, are performed with commercial softwares and Complete Omics’ unique R packages and scripts. Report will be sent to you in Excel format as well as a summary in PDF format. We will also provide you any details you need for your papers’ MATERIALS AND METHODS section. We will make sure you understand your result and help you with your paper writing with free follow-up services.
All Single Cell Omics assays are conducted through our Department of Single Cell, please visit singlecell.com for further details.
Sample types we accept:
1, Cultured cell
2, Primary cell
3, Wet / Frozen tissue
4, Customized sample types (please contact us to discuss)
Jan 12, 2022 | BALTIMORE – Complete Omics’ Clinical Proteomics team announced a collaboration with Professor Marco Sardiello and his team from Washington University in St. Louis on a clinical proteomics…
Some of our impacts
2021–Direct Quantification of Neoantigens Like Never Before — published on Science and Science ImmunologyGenetic changes in human genome are the driving force for all cancers. Different patients have different sets of mutation profiles even when the patients all have the same disease. For decades, doctors, cancer scientists, and pharmaceutical companies have been working tirelessly trying to find a way to treat each person’s unique disease in a highly personalized way that will reach the maximum treatment efficacy with the lowest side effects. Complete Omics, working with leaders in cancer therapeutics, has developed two applications based on our Valid-NEO pipeline through which we clearly saw personalized therapeutic targets on the cancer cell surface before adopting a highly specific treatment, for here bispecific antibodies. Two papers describing our new technologies are puslished on Science (Ref. 1) and Science Immunology (Ref. 2). Our pipeline has been reported by GenomeWeb (Ref. 3)Prediction-FREE Neoantigen Validation Enables Personalized Cancer Therapeutics
2019–First Pipeline for Direct Detection and Quantification of NeoantigensCancer-linked genetic mutations can code for mutant proteins, which can then be processed by proteasomes into peptides that are presented by human leukocyte antigen (HLA) molecules, triggering the body’s immune response. The idea that such mutant peptides can trigger an immune response is fundamental to immunotherapies like checkpoint inhibitors as well as cancer vaccines that present the body with these peptides to generate an immune reaction. However, while the rise of next-generation sequencing has allowed researchers to identify a large number of cancer-linked mutations, actually detecting these mutation-associated neo-antigens, or MANAs, at the peptide level remains difficult. The fact that a mutant is present at the genetic level does not mean it will be produced at the protein level, and, even if it is, that is no guarantee that it will be processed and presented by HLA molecules. This has proved a challenge for, for instance, personalized cancer vaccine development. Our technology (Ref. 1) provide the 1st pipeline for detecting personalized cancer therapeutic targets. Our method has been reported by public media and has a significant impact in cancer research (Ref. 2).Direct Detection and Quantification of Neoantigens
2017–First Pipeline for Proteomics-based Clinical DiagnosticsWe developed the 1st pipeline for discovering and validating proteomic biomarkers from patient plasma samples (Ref 1). With this pipeline, we identified an ovarian cancer biomarker, peptidyl-prolyl cis–trans isomerase A (PPIA), with zero false positive diagnostic value. Our finding was featured on Genomeweb (Ref 2). We quantified 318 peptides in 94 separate samples, 48 from healthy controls, 14 from colorectal cancer cases, 14 from ovarian cancer cases, and 18 from pancreatic cancer cases. We then analyzed this data to see if any of the peptides or combinations of the peptides allowed us to accurately identify their sample of origin, and in this way identified the two PPIA peptides as potential markers for ovarian cancer. We then measured these two peptides in a separate cohort of 73 cases consisting of 35 ovarian cancer cases and 14 healthy controls and 24 pancreatic cancer cases. One of the two peptides was detected in 20 of the 35 ovarian cancer plasma samples, while neither was detected in any of the healthy controls.SAFE-SRM and Ovarian Cancer Diagnostics
2016–Targeted sequencing of both DNA strands barcoded and captured individually by RNA probes to identify genome-wide ultra-rare mutations.Targeted sequencing has been an essential application in Next Generation Sequencing (NGS). However, all target capture commercial technologies on the market have relatively low capturing efficiencies. That being said, after utilizing those capture kits, instead of sequencing a sufficient number of unique molecules, you are actually sequecing a library of nucleic acid amplicons that are amplified from very few DNA molecules captured by those old commercial technologies from initial NGS library, and usually the fraction of molecules that can be captured and subsequently sequenced is less than 9% of the molecules from the initial NGS library. Due to the unsatisfying performance of current commercial capture kits and platforms, Complete Omics has been trying to develop its own target capture technologies, and finally we have something to show you. We believe that this new technology could potentially revolutionize NGS targeted sequencing field. We are proud to anounce DEEPER-Capture, the next generation target capture technology for NGS sequencing. In DEEPER-Capture both DNA strands from the same DNA duplex molecule are captured by a pair of complementary RNA probes, and sequenced, simutanously. Using DEEPER-Capture, we repeatedly achieved an over 3-fold higher capturing efficiency than the best performance ever observed from competing platforms reported by numerous labs.DEEPER-Seq: Capture both DNA strands with dual RNA probes
2010–Mutant Proteins As Cancer Specific BiomarkersCancer biomarkers are currently the subject of intense research because of their potential utility for diagnosis, prognosis, and targeted therapy. In theory, the gene products resulting from somatic mutations are the ultimate protein biomarkers, being not simply associated with tumors but actually responsible for tumorigenesis. In 2010, we developed the 1st pipeline for detecting and quantifying mutant protein as cancer specific biomarkers from human specimens, and it received a broad range of attentions from different disciplines of biomedical sciences [Ref. 1]. We demonstrated that altered protein products resulting from somatic mutations can be identified directly and quantified. As a prototypical example of this approach, we demonstrated that it is possible to quantify the number and fraction of mutant Ras protein present in cancer cell lines. There were an average of 1.3 million molecules of Ras protein per cell, and the ratio of mutant to normal Ras proteins ranged from 0.49 to 5.6. Similarly, we found that mutant Ras proteins could be detected and quantified in clinical specimens such as colorectal and pancreatic tumor tissues as well as in premalignant pancreatic cyst fluids. In addition to answering basic questions about the relative levels of genetically abnormal proteins in tumors, this approach lays the foundation for mutant protein-based cancer diagnostics.
Mutant Proteins As Cancer Specific Biomarkers
- Publication: Mutant proteins as cancer-specific biomarkers.