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You can find more information about artificial intelligence (AI) in MLL and MLL MVZ under Big Data.

You can find more information about Whole genome sequencing (WGS) in MLL and MLL MVZ under Big Data.

You can find more information about Whole exome sequencing (WES) in MLL and MLL MVZ under Big Data.

Each cell in the human body has an identical copy of the genome (DNA) – the full set of genetic material. However, the transcriptomes of the cells differ. RNA sequencing (RNA-Seq) analyzes the transcriptome; i.e. it is a quantitative determination of the transcribed (from DNA to RNA) genes present in the cell. The expression of the transcriptome provides the basis for the identity of a cell and the associated functionality. In the case of an illness such as cancer, abnormal gene regulation occurs, which significantly modifies the transcriptome of the affected cells and influences the proportion of the genes transcribed.

Differentiated cells possess a specific repertoire of biological functions. For example, white blood cells play an important role in the immune system, red blood cells in the transportation of oxygen to the individual organs, and blood platelets in clotting. A particular set of genes is necessary for each of these functions, as well as for regulating the lifetime of a cell. Gene expression is controlled strictly via various mechanisms. In the case of an illness such as cancer, abnormal gene regulation occurs, which significantly modifies the transcriptome of the affected cells and influences the proportion of the genes transcribed. These changes can be detected and quantified using RNA-Seq, for example by comparing the transcriptome of the tumor cells with the profile of healthy cells.

In addition to changes in gene expression, RNA-Seq also allows fusion genes to be detected, which are the result of structural changes (translocations of chromosomal material). A person’s transcriptome contains not only protein-coding transcripts, but also transcripts that do not lead to the formation of a protein. These transcripts can be subdivided into two groups based on their length: short RNAs (microRNA, snoRNA, snaRNA, etc.) with a length of 20–24 bases and the long non-protein-coding RNAs (long non-coding RNAs, lncRNAs) with a length of over 200 bases. These transcripts are involved in the regulation of gene expression, making them a good starting point for interventions and therapies.

Preparing the RNA – Library preparation

As with the analysis of DNA (WGS, WES), library preparation is conducted prior to the sequencing of the transcriptome. This process includes the fragmentation of the RNA, the removal of ribosomal RNA or the enrichment of messenger RNA (mRNA), the synthesis of cDNA from the RNA, the ligation of uniquely identifiable indices that make it possible to tell one sample apart from another, and a subsequent enrichment of the material via PCR. At MLL, library prep is performed in a fully automated procedure by pipette robots (Hamilton NGS Star). This ensures standardized and homogeneous library prep.

Sequencing

The library prepared in this fashion is then input into the sequencing devices and read out using the sequencing by synthesis method. At MLL, the device used is the NovaSeq 6000, the latest generation of sequencing devices from Illumina. In order to achieve sufficient accuracy during the transcriptome analysis, the target is 50 million reads (sequenced fragments) per probe.

Data analysis

Subsequently, data analysis is conducted. At MLL, the data from the sequencing devices is transferred directly to the Amazon Web Services (AWS) cloud in Frankfurt and analyzed in Illumina’s BaseSpace Sequence Hub. Data protection requirements are complied with in accordance with the EU General Data Protection Regulation (GDPR) and ensured via ISO 27001 (Cloud Computing). Firstly, the alignment of the reads (STAR, Illumina) to the reference genome (GRCh37, hg19) takes place, i.e. the mapping of the fragments to their position in the genome. What follows is the determination of the counts, i.e. the number of reads per gene, which are then normalized in an internal MLL pipeline. The normalized counts constitute the starting point for all further analyses. Three fusion callers (Manta, STAR-Fusion, Arriba) are used to detect fusion transcripts and since the number of false positives is comparatively high, only fusion transcripts detected by at least two of these callers are considered for evaluation.

Apart from the DNA in cells, cell-free DNA can also be obtained from bodily fluids. In most cases, this refers to freely circulating DNA from the blood (cfDNA, cell-free DNA). It is assumed that this DNA is released from apoptotic cells. Tumors are characterized by high rates of proliferation and apoptosis. During the process of apoptosis, a cell goes through programmed cell death, which results in the cell breaking apart and DNA being released into the surrounding tissue. This type of diagnostics is called a “liquid biopsy.” It is a non-invasive method that is preferred for monitoring the progress of previously diagnosed instances of cancer and for assessing the response to a therapy without having to perform time-consuming tissue biopsies in the case of solid tumors.

Because the concentration of this cfDNA is extremely low, it must first be replicated using special amplification methods before it can be examined for changes (mutations). This allows tests to be performed on whether cells from the residual tumor are still present in the body, which would increase the risk of recurrence. In addition, intensive work is being done on the development of tests that aim to enable early cancer detection using cell-free DNA from blood. Generally, in addition to cfDNA, a second type of DNA can be obtained using a liquid biopsy: cell-bound DNA from freely circulating tumor cells (CTCs). These indicate a possible metastasis of the primary tumor. The value of the liquid biopsy with the detection of cfDNA in patients with lymphomas is currently being evaluated.

Preparing the DNA – Extraction and library preparation

For extracting cfDNA, 10 ml of blood is drawn from the patient in special blood vials. In these vials, the blood is anticoagulated, stabilized, transported, and can be stored for up to 7 days. In the vials, the hemolysis and apoptosis of the blood cells is inhibited, such that no cellular DNA from decaying blood cells enters the plasma. The cfDNA can now be selectively isolated from the plasma. Special extraction kits allow the cfDNA to be isolated from large volumes (approx. 10 ml of plasma) and eluted in a small volume (20µl) in order to concentrate the cfDNA (which occurs in very low concentrations) in a small volume.

Subsequently, the cfDNA thus obtained can be analyzed using PCR or next-generation sequencing and examined for markers that characterize tumors. For the library preparation preceding the sequencing, it should be emphasized that cfDNA is frequently very highly fragmented (~180 bp long) and present in extremely low concentrations, such that pre-amplification library preps in which the quantity of DNA is first replicated should be used.

You can find more information about Data management/storage (cloud computing) in MLL and MLL MVZ under Big Data.