Research Excellence

Genetron Health’s talented research service team consists of experts in cancer genomics, bioinformatics and project management with vast experience in both basic and clinical cancer research. On the global level, Genetron Health has set up a R&D center in Research Triangle Park, North Carolina, U.S. as well as developed long-term collaboration with Duke University and strategic partnership with Professor Bert Vogelstein’s team at Johns Hopkins University. In China, Genetron Health has enjoyed long-term and sound R&D working relationships with top Chinese hospitals and has published dozens of high impact research papers. Our pledge towards giving hope and answers for cancer will motivate us to continuously provide first-class, customized research services to our partners.

Research Services
Sequencing Services
Cancer whole genome sequencing (WGS)
Cancer whole genome sequencing (WGS)

Whole genome sequencing (WGS) uses a high-throughput sequencing platform to sequence the whole human genome and provides comprehensive analysis in genetic variations at the individual level or population level. This can be used to discover new cancer driver genes and study the genetic basis of tumorigenesis.


Technical highlights:

WGS is able to detect copy number variants (CNVs), structural variants (SVs), virus integration sites, and mutations in non-coding regions, with great data coverage and quick turnaround times.


Technical platform:

HiSeq X Ten sequencer


Technical specifications:

• Sample requirement

• Sample types: DNA;  

• Sample amount: >=1.0 ug DNA (extracted from fresh or frozen samples);

• >=1.5 ug DNA (extracted from FFPE samples);

• Sample concentration: >=20 ng/ul;

• Capture platforms: Agilent SureSelect Kit;

• Sequencing platform: HiSeq X Ten;

• Sequencing strategy: HiSeq PE150;

• Sequencing depth: tumor carcinoma tissue (50 x), normal tissue/blood samples (30x), hereditary disease (30 ~ 50 x);Data volume: 1.8 Tb;

• Turnaround time: 48 days.


Cancer whole exome sequencing (WES)
Cancer whole exome sequencing (WES)

Whole exome sequencing is a technique that uses probe hybridization to enrich exon regions of DNA sequences. High-throughput sequencing technology following exon enrichment identifies genetic mutations associated with protein dysfunction. Compared with whole genome sequencing, WES is more cost-effective and efficient.


Technological highlights:

1) Direct sequencing of protein-coding sequences to identify variations that affect protein function;

2) In-depth sequencing that can identify both common variations and rare variations with frequencies lower than 1%;

3) Exome sequencing, which accounts for only 1% of the genome, effectively reduces the cost and turnaround time.


Technical specifications:

• Sample requirement

• Sample types: DNA samples;

• Sample amount: >=1.0 ug DNA (extracted from fresh or frozen samples);

• >= 1.5 ug DNA (extracted from FFPE samples);

• Sample concentration: >=20 ng/ul; 

• Capture platforms: Agilent SureSelect Kit;

• Sequencing strategy: HiSeq PE150;

• Sequencing depth: tumor carcinoma tissue (200 x), normal tissue/blood samples (100x);

• Turnaround time: 42 days.


Cancer targeted panel sequencing
Cancer targeted panel sequencing

Targeted panel sequencing enriches the targeted DNA region followed by high-throughput DNA sequencing. Through studying a large number of samples at targeted regions, cancer-related gene variants can be identified and validated for clinical diagnosis and drug development.


Technical highlights:

1) Guided information: Focusing on targeted genomic regions;

2) High accuracy: Focused sequencing in targeted regions for better coverage and higher accuracy; improved detection sensitivity for rare variants;

3) Cost-effective and efficient: Higher throughput, especially for large sample size studies;

4) Faster: Shortened research period, speeding up study publication and accelerating clinical applications.


Technical specifications:

• Sample requirement

• Sample types: DNA;

• Sample amount: >=1.0 ug DNA (extracted from fresh or frozen samples);

• >=1.5 ug DNA (extracted from FFPE samples);

• Sample concentration: >=20 ng/ul;

• Capture platforms: Agilent SureSelect Kit;

• Sequencing platform: HiSeq X™ Ten;

• Sequencing depth: carcinoma tissue (500 x), normal tissue/blood samples (250x);

• Turnaround time: 42 days.


Cancer transcriptome sequencing (RNAseq)
Cancer transcriptome sequencing (RNAseq)

RNAseq is performed on HiSeq4000 and X Ten platforms by sequencing all mRNA transcripts. This can be used to study known transcripts, identify new transcripts, as well as obtain mRNA sequences quantitatively.


Technical specifications:

• Sample requirement

• RNA sample amount: >= 1.5 ug;

• RNA sample concentration: >= 50 ng/ul;

• Library type: normal RNA-seq library, strand-specific RNA-seq library;

• Sequencing strategy: HiSeq PE150;

• Data volume: >=12Gb;

• Turnaround time: 45 days.


Cancer long non-coding RNA sequencing (LncRNAseq)
Cancer long non-coding RNA sequencing (LncRNAseq)

LncRNA (long non-coding RNA) refers to long non-coding RNA with over than 200nt. By binding to DNA, RNA or protein, it regulates gene expression epigenetically, at the transcriptional or post-transcriptional level. LncRNA has been shown to be related to human cancer. LncRNA - seq analyzes all LncRNA and mRNA in the sample.


Technical specifications:

• Sample requirement

• RNA sample amount: >= 1.5 ug;

• RNA sample concentration: >= 100 ng/ul;

• Sequencing strategy: HiSeq PE150;

• Data volume: 12Gb clean data for normal-depth sequencing and 24Gb clean data for high-depth sequencing;

•Turnaround time: 60 days.



Cancer-related immune repertoire sequencing (TCRseq)
Cancer-related immune repertoire sequencing (TCRseq)

Immune repertoire sequencing (IR SEQ) is the sum total of functionally diverse B and T cells circulating in a person at any given moment. T cell receptor (TCR) and B cell receptor (BCR) are specific antigen recognition and immune response mediating molecules, and the diversity of TCR/BCR directly reflects the status of the body's immune response. Genetron Health uses multiplex PCR and 5 RACE technology to amplify the complementary determining region (CDR) followed by high-throughput sequencing for the determination region in BCR or TCR. Immune repertoire sequencing provides great value in early diagnosis, antibody discovery, vaccine design, immune system development, treatment for infectious diseases and autoimmune diseases, as well as cancer immunotherapy.


Technical specifications:

• Sample requirement

• Sample type: RNA sample;

• RNA sample amount: >= 3 ug(extracted from peripheral blood samples);

• >=5 ug (extracted from tissue samples);

• RNA sample concentration: >= 20 ng/ul;

• Sequencing strategy: HiSeq PE150;

• Data volume: 12Gb clean data for normal-depth sequencing and 24Gb clean data for high-depth sequencing;

• Turnaround time: 60 days.



Applications
Genomics
Profiling of cancer mutational landscape
Profiling of cancer mutational landscape

Tumorigenesis is largely driven by the accumulation of DNA mutations. High Throughput Sequencing (HTS) enables identification of various forms of mutations including SNV, InDel, SCNAs and SV and understanding of the genomic profile of tumor. This lays the foundation for basic cancer research and also paves the way for development of cancer therapy.

Cancer driver gene / biomarker discovery
Cancer driver gene / biomarker discovery

Cancer is a complex disease resulting from the accumulation of cancer cells mutation. These mutations are usually categorized as driver mutation and passenger mutation. Driver mutations usually occur at early stage and power cell with tumorigenic ability such as infinite division, uninhibited adhesion and angiogenesis. In cancer research, driver mutations are often extensively investigated for their potential as target of therapeutic agent. Exploring driver mutations help uncover the mechanism of tumor formation as well as the design of  new therapeutic agent.

Cancer molecular classification
Cancer molecular classification

Different cancer types share certain degree of genotypical as well as phenotypical similarity. Cancer is traditionally viewed as a complex disease caused by the accumulation of DNA mutations which can be highly invasive is classified by its organ origin. As cancer research progresses, the modern medical world believes that cancer in general is similar, but can be a different and complex disease caused by accumulation of different genomic or / and epigenetic changes. Molecular classification based on prevalence of genotypical changes has been accepted as an alternative classification system of cancer. Comparing with organ origin-based classification, molecular classification often leads to better therapeutic strategy. In addition, it is believed that molecular classification will have profound impact on cancer drug development.

Analysis of tumor heterogeneity and clonal evolution
Analysis of tumor heterogeneity and clonal evolution

Most tumors are highly heterogeneous and multiple clones co-exist in the same lesion. Each clone harbors different set of mutations conferring different phenotypical characteristics. Computational approaches take advantage of mutation prevalence of each tumor clone and infer the evolutionary trajectory of tumor tissues (primary tumor vs metastatic tumor; primary tumor vs relapsed tumor).

Transcriptomics
Differential expression and network analysis
Differential expression and network analysis

Tumor evolution is often accompanied by changes of gene expression. Microarray used to be the main approach for such investigation. As sequencing technique advances, RNA-Seq has been widely applied to explore the expression changes of cancer transcriptome which provides hint about the metabolic evolution of tumor. Such transcriptomic analysis are important in shedding light on the mechanism of cancer development.

Figure A: Unsupervised clustering of mRNA differential expression uncovers molecular classification of cancer.

Figure B: Interactive network analysis of differentially expressed genes.

Figure C: Functional enrichment of differentially expressed genes leads to significantly changed metabolic pathway in tumor tissue.

RNA alternative splicing analysis
RNA alternative splicing analysis

RNA alternative splicing regulates gene expression and ensures proteomic diversity. Through alternative splicing, the same gene may produce functionally different proteins. This phenomenon is frequently observed in tumor tissue and believed to be involved in multiple biological process, such as cell apoptosis, cell cycle regulation, adhesion and metastasis. With RNA-Seq, we are able to detect alternative splicing event and explore their role in cancer development.

Figure A: Common forms of alternative splicing.

Figure B: Diagram of RNA alternative splicing event.

Cancer epigenetic (methylation) analysis
Cancer epigenetic (methylation) analysis

DNA methylation / demethylation mediated gene expression regulation is commonly observed in tissue development as well as disease progression. NGS-based DNA methylation analysis detects DNA methylation sites across genome of tumor cell. Recent research has proven its role in cancer early detection, cancer type classification and prognosis.

Figure A: Cancer molecular classification based on DNA methylation clustering.

Figure B: Differential DNA methylation site enrichment analysis implies metabolic changes during tumor development.

Cancer Long non-coding RNA (LncRNA) analysis
Cancer Long non-coding RNA (LncRNA) analysis

LncRNA mediates chromosome modification, X chromosome silencing, gene imprinting and expression. LncRNA analysis identifies both known and novel lncRNA aberrantly expressed in tumor tissue and associates their function with phenotypical outcome of cancer.

Clinical Research
Cancer liquid biopsy
Cancer liquid biopsy

Liquid biopsy has gained its popularity as a non-invasive approach to monitor tumor progression. The consistency between liquid biopsy and tumor tissue biopsy in most cancer types has been widely proven. In addition to its non-invasive nature, liquid biopsy overcomes the tumor heterogeneity issue inherited in tissue biopsy and allows clinician to gain the whole picture of the genomic landscape of tumor. Today, liquid biopsy has extended its application to multiple media including, but not limited to, urine, cerebral fluid, saliva and ascites. Also, liquid biopsy is being extensively researched for its potential on cancer early detection.

Biomarker of cancer immunotherapy
Biomarker of cancer immunotherapy

Cancer immunotherapy aims to correct the immune recognition and clearance against tumor cells. Comparing with traditional therapy, immunotherapy is, in theory, characterized with wide spectrum of tumor recognition and low relapse rate. However, the efficacy of immunotherapy is hard to assess partially because it acts on the complex interaction between the tumor and immune system. The numerous factors that can affect the immune-oncology process include, but not limited to, tumor immunogenicity, the capability of tumor antigen recognition / presentation mediated by MHC / APCs, immune cell activation and recruitment, immune cells infiltration and tumor cell recognition, and the tumor microenvironment modulation by tumor cells. We believe that NGS based multi-omics analysis is mandatory for such immune-oncology evaluation.

Tumor neoantigen discovery
Tumor neoantigen discovery

During tumor evolution, some of the tumor cells die releasing epitopes into peripheral circulation where they may be recognized and captured by antigen presenting cells (APCs). APCs further bring these epitopes to lymph node and initiate immune response. A variety of biotech techniques, such as cancer vaccine, CAR-T and TCR-T, aims to boost immune response by biotechnically tailoring the above process. The precise identification of neoantigen (even immunogenic epitope) is fundamental for these applications. WES and RNA-Seq enable neoantigen identification through multiple steps including tumor mutation identification, expression estimation, HLA typing and peptide-MHC bind affinity estimation.

Publications

Genetron Health‘s dedicated research team has more than 20 years of experience in cancer genomics research as well as clinical and translational research. They are esteemed professors and scholars hailing from world-class universities, talents from the Recruitment Program of Global Experts as well as experienced cancer research clinicians, professionals and scientific research scholars. Today, our scientific research team has completed several notable large research projects in cooperation with our partners and has produced dozens of research papers that were published in respected industry journals such as Science, Nature, New England Journal of Medicine, etc.  Our strong scientific research and development capability along with efficient clinical and translational competence has been highly regarded in the industry.
           

Sequencing Platform

Genetron Health has partnered Thermo Fisher to build world-class laboratories for clinical research. These laboratories house a comprehensive suite of advanced, extensive and diversified testing platforms that can perform quick and accurate molecular tests on clinical samples, including next generation sequencing (NGS), generation sequencing (Sanger) and digital PCR (dPCR), fluorescence quantitative PCR (qPCR), pyrosequencing (Pyrose-quencing), fluorescence capillary electrophoresis, fluorescence in situ hybridization (FISH) and immunohistochemistry (IHC). This undoubtedly enhances the strong support for cancer genomics research and clinical application.

State-of-the-art equipment used include: Novoseq 6000,HiSeq X Ten,HiSeq 4000,MiSeq,NextSeq, QuantStudio,RainDance,PyroMark, etc.. The HiSeq X Ten sequencing system is currently the world‘s most cost-effective sequencing platform, with a capacity of sequencing 18,000 human whole genomes per year. The impressive line-up of testing platforms and equipment demonstrates that Genetron Health can carry out clinical tests covering whole genome sequencing, whole exome sequencing, RNA-seq, and liquid biopsies swiftly and accurately, making this an ideal one-stop solution for cancer genomic studies.

Miseq
Miseq
Nextseq
Nextseq
Hiseq
Hiseq
Novaseq
Novaseq
High-performance Computing Platform
High-performance Computing Platform

Genetron Health runs a high-performance computing center with proprietary software for data analysis. We have also established an exclusive strategic partnership with Personal Genomic Diagnostics (PGDx), a genetic testing company founded by Professor Bert Vogelstein of Johns Hopkins University, to jointly develop cutting-edge technology platforms for analyzing sequencing data. Our robust computing platform can efficiently and effectively store, process and analyze large-scale genomics data. Genetron Health also maintains several cancer genome databases which are synchronized with international databases that ensure updated information on cancer genomic discoveries and therapeutic targets are captured. With these high-calibre capabilities, our partners can be assured of nothing but the best analysis services for them.

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