Personalized​

Omics Technologies - Transcriptomics The genome provides the salient information about all body components and the general layout of the regulation of gene expression. Epigenomics controls which parts of the genome are actually to be transcribed at a particular location and time. Transcriptomics is concerned with the actual execution of such regulation causing the production of the RNA transcripts of genomic DNA. However, in addition to Epigenomics there are several layers of control imbedded in Transcriptomics itself. Epigenomics “potentiation” of a region is called that way because the control mechanisms of transcriptomics can only act within potentiated regions. However, the highly complex integrated circuits of transcription control cannot be directly observed. For that reason clinical trnascriptomics is usually concerned with the results of the regulation, i.e. the changing levels of RNA transcripts, most prominently the mRNAs encoding proteins.  What is the major result used in personalized medicine? Steady-state levels of RNAs can be measured either by microarrays (see below) or RNA-seq. This is a special form of Next Generation sequencing (NGS) focusing on the determination of all present RNA sequences in a sample. A healthy cell or organ has a characteristic internal relation of the amounts of most of its RNA molecules, which resembles the natural balance of gene expression. Although exact levels vary among people the overall composition is rather well preserved. In case of severe illness or cancer a number of RNAs go clearly up or down, which is indicative for the disease, often even for the molecular cause of the disease. Therefore, RNA-measurements in blood samples or tissue biopsies can be used to determine if the transcriptome (all RNAs in a cel or tissue sample) is off balance or not.   Which body samples are required to carry out the experimental analysis? Cells from blood contain RNA and often react characteristically to a disease by changing their RNA expression. Tissue samples from tumors or other diseased tissues also exhibit characteristic changes that can be detected. Characteristic  means associated with a disease not necessarily understood in all consequence. Fig. 16 Clinical Transcriptomics Which basic technologies are behind this -omics? The major technologies used to be microarrays, where short DNA probes binding to individual RNAs are fixed onto a glas slide  (20,000 or more genetic loci at once). Binding of the corresponding RNAs produces a semi-quantitative signal. The newer NGS technology of RNA-seq is far superior, avoiding some of the systemic flaws of microarrays (e.g. saturation, or cross-hybridization) and is far more sensitive. However, it is still more expensive and more difficult to perform. Therefore, microarrays are used in parallel with NGS RNA-seq. What are the most likely next advances and how would they improve application for personalized medicine? There are two developments that will increase the medical value of RNA-seq dramatically: The length of a of sequence that can redetermined in one piece used to be rather short, requiring stitching together longer molecules. Now this read length is approaching the whole length of the RNAs allowing much better and more precise detection. The second important development is the perfection of single-cell RNA-seq allowing detection of the complete transcriptome of a single cells. That way, tumor sub-typing from one biopsy becomes possible as the resolution is increased to the level of a single cell. What’s coming up next? Next week we will follow the chain of events further down beyond transcriptomics into the actual production and measurement of proteins. Most biomarkers in clinical use today are proteins. 

Personalized​

Omics Technologies - Epigenomics Epigenomics is concerned with all epigenetic changes in the whole genome of a cell. Epigenetic changes are reversible chemical modifications of the genomic DNA or histones that package the genomic DNA into chromatin. Epigenetic changes have profound and wide-spread effects on gene expression without altering the genomic DNA sequence. Thus, this kind of changes would not be detected by any regular genomics methods.  What is the major result used in personalized medicine? A single driver mutation on its own would not be able to completely reprogram a cell to become a tumor cells evading all growth control signals. This happens in a multistage process where driver mutations induce key epigenetic changes that turn many genes on or off. Epigenetic modifications come in two flavors: repressive and activating. While the tumor needs to activate the cellular growth cycle it also needs to turn off other signals that would put brakes on the process. The most frequently used epigenetic feature today is DNA-methylation usually at a Cytosine residue (base C). Heavy methylation of Cs indicates a shutdown of gene expression in most cases. Not less important but technically more difficult to handle are histone modifications. They indicate on a finer scale activation or depression of individual genes.   Which body samples are required to carry out the experimental analysis? We all have one genome (more or less) but almost every cells or at least tissue has its own epigenome. Therefore, blood samples e.g. of a tumor patient, can only yield accurate epigenetic data about the tumor when, for example, circulating tumor cells can be isolated. Biopsies are the most reliable sources for epigenetic analyses.   Fig. 15 Epigenetics controls the transcriptionHistone H3 is part of an octamer of histones forming a so-called nucleosome. The genomic DNA is wrapped around these nucleosomes. K4 and K27 are lysine amino acids at the respective positions within the H3 protein. The gene promoter is the central processing unit of a gene/transcript and is switched on or off by epigenetics. Genomic DNA is shown in blue, RNA in green-yellow. Which basic technologies are behind this -omics? DNA methylation is usually assessed by a variation of Next Generation Sequencing (NGS), bisulfite sequencing. Here methylated Cs are chemically changed so they read as Ts in the subsequent sequencing. Wherever a C in the reference genome is replaced by a T in the sample’s sequence this is where the C was methylated. Histone modifications are more complicated to detect. The method here is called ChIP-Seq, which stands for Chromatine-Immuno-Precipitation Sequencing. Special antibodies recognize ONE histone modification and can be used to pull out the corresponding small chromatin fragment, the DNA of which is then sequenced by NGS. However, each individual form of histone modification requires a ChIP-seq experiment of its own.  What are the most likely next advances and how would they improve application for personalized medicine? DNA methylation can already be read directly without bisulfite modification in so-called nanopore sequencing, where bases are called based on characteristic variations on electric resistance as the base slides though the pore. Methylated Cs have a different resistance than non-methylated Cs and can be directly detected. It is fair to expect more technological advances that will allow to read epigenetic changes with the the same effort and efficiency than reading genomic sequences. Once that happens epigenomics will become equally important as genomics if not even a bit more important.  What’s coming up next? Next week the field of transcriptomics will be introduced. This is where the actual regulation of transcribing DNA into RNA governed by the genome and the epigenome takes place.​

Personalized​

Omics Technologies - Genomics Genomics is the branch of molecular biology concerned with the structure, function, evolution, and mapping of genomes. With respect to personalized medicine the most relevant part is the analysis of genomic sequences for aberrations (mutations, deletions or insertions of pieces of DNA or even translocation of parts of chromosomes).  What is the major result used in personalized medicine? Aberrations in the genomic sequence that are known to be associated with hereditary diseases or predisposition for diseases can be detected early on. They can be used to choose a preventive lifestyle (e.g. in case of hereditary obesity or allergies). In case of dangerous mutations that cause trouble later in life tight monitoring of the situation can be initiated (e.g. the BRCA mutations that cause breast cancer after a certain age was reached). In case of cancer tumor genomics can elucidate the driving force of the tumor for better selection of the optimal therapy.  There are two approaches most commonly used: the whole exome sequencing (WES), which looks only at the part of the genome that encodes for proteins. Considered most important and easiest to interpret, this covers only about 2% of the genome. Thus it is necessarily missing a lot, which will be covered by whole genome sequencing (WGS), which goes after all 3 billion bp of the genome. However, it is much more difficult to interpret this amount of data. Which body samples are required to carry out the experimental analysis? General diagnostics of genomic mutations can be done on blood samples as early as a few hours after birth. In case of tumors either circulating tumor cells can be found in the blood or a tumor sample (biopsy) is required.  Which basic technologies are behind this -omics? For a long time determining the sequence of genomic DNA was a daunting task causing enormous costs. Today, Next Generation Sequencing (NGS) can deliver a whole human genome in a few days at a cost of US $ 3,000 - 6,000. However, the bioinformatics required to analyze the sequences for informative variations and aberrations is still a difficult task. iEspecially if it aims at new results beyond the easy predefined target regions.  Fig. 14: Omits schematic overview, major results of genome sequence analysis  What are the most likely next advances and how would they improve application for personalized medicine? We all harbor millions of DNA sequence changes as compared to other humans. It is very difficult to determine whether a particular change will cause a disease in the future or not. On top of that many potentially disease-causing variants will do so only in a particular genetic background. Therefore, the connection between several changes needs to be known. The only way to learn about such constellations is to observe and compare the changes in millions of people most of whom will be healthy. These people will help to define the insignificant background of harmless mutations. Further advances in NGS methodologies are already under way, which will allow sequencing genomes of larger and larger groups in an economic way. Technological advance will enable us to gather the enormous amount of data required to reveal many more variation-disease relations that we know today.  However, this will only become a reality if we all are willing to share our genomic sequences with researchers and medical doctors, i.e. we give our consent to such use. In the end we will all benefit from such consent.  What’s coming up next? Next week the topic will be Epigenomics, a rather new field about gene regulation that is strongly influenced by our environment, present and past. ​

Personalized​

Omics Technologies Personalized medicine relies on molecular information about the patient and his genome for selecting smart approaches particularly suitable for the individual or group of individuals. This kind of information is largely provided by molecular techniques and analyses that are summarized as omics-technologies. Omics in this respect stands for analysis of a whole data space called an -ome, This would be, for example, the whole genome, or the whole transcriptome etc., whatever can be found collectively in a cell, and organ or the whole organism. Consequently, analysis of any -ome data is called the respective -omics.  I will introduce the different -omics fields first very briefly and then in a bit more detail in separate blog entries. This should facilitate quickly locating special information for reference.  The major -omics categories covers in this blog: Genomics Determination and analysis of the genomic DNA sequence of a cell, a tissue or an individual in order to detect aberrations from the average. Genomics is used to detect known genetic risks for diseases or predispositions for diseases.  Epigenomics Detection of chromatin changes that do not involve any changes in the genomic DNA but affect the chemistry around the DNA and the proteins that DNA is wrapped around (nucelosomes). Epigenomics detects reprogramming of areas that can lead to disease not by mutation but by changed program execution in the cell or body.  Transcriptomics DNA (double-stranded,the helix) is transcribed into a copy made of RNA (single stranded), which the  detaches from the DNA and can travel through the cell. So-called messenger RNAs (mRNAs) carry the instructions for all proteins a cell produces. The mRNA sequence is read and translating into a protein sequence by special protein factories (ribosomes) assembling amino acids into a protein chain. The nature as well as the relative amount of RNA produced by a cell or tissue is informative for changes in the cell program. Such changes may lead to disease even before the disease becomes clinically apparent. Transcriptomics and Epigenomics are tightly interwoven, both influencing the other.  Fig 13: Relation of the five major -omics fields to events in the cell Proteomics Once mRNA have been translated into proteins these proteins travel to the site of action in the cell. Many proteins are also fine-tuned by chemical modifications (e.g. phosphorylation) which adapts them for a particular job, or serves to activate some function of the protein. Proteins are the most frequently used biomarkers for disease-related changes and can be measured readily in body fluids such as blood, saliva, or urine.  Metabolomics All food we eat is broken down in our stomach and gut into small units that the body can absorb. Later on this processed food is used to produce all the metabolites the body needs to generate energy, build body mass or repair damaged parts (e.g. would healing). The whole collection of these metabolites including the handling proteins constitute the metabolome of a cell, a tissue or a body.  I will concentrate on these five categories although several more such as Lipidomics have been created in the meantime. However, the mentioned five have currently the major impact on personalized medicine and its development.  In the next five blog entries I will go into a bit more detail for each of these major -omics applications highlighting the following points:  What is the major result used in personalized medicine?Which body samples are required to carry out the experimental analysis?Which basic technologies are behind this -omics?What are the most likely next advances and how would they improve application for personalized medicine?  What’s coming up next? Next week the -omics series will focus on the first part, genomics along the four main questions mentioned above. ​

Predictive​

Selection of optimal treatment The information gathered by personalized medicine can be used to select the optimal therapy for a patient. Knowledge of the genetic or epigenetic basis of a chronic ailment (such as irritable bowel syndrome or asthma) allows to select treatments (both drugs as well as supporting lifestyle changes) based on the particular genetic setup. This increases the chance for such therapies to be beneficial for that particular patient or patient group. However, this goes well beyond the selection of the best drug. Also individualized regimes fro dosage and even time of application can be informed by genetic factors and contribute to the efficacy of the treatment. Along the same lines known side effects can be minimized or avoided by the choice of alternative drugs provided they are compatible with the patients genetic setup.  The tumor genome: a mug shot for therapy selection Tumor growth and cancerous diseases are characterized by the presence of cells that do differ from the genetic setup of the healthy cells. One or more mutations in the cancer genome are responsible for the cancer cells to multiply unrestricted and also their potential ability to metastasize, i.e. to shed cells from the primary tumor that travel through the blood stream and colonize distant sites in other organs. Often the ability to metastasize is acquired along with additional mutations in the cancer cells. Molecular analysis of the tumor genome(s) can reveal the driver mutations and thus the mechanism how these cells escape the normal growth control. There are many specialized therapies available now, mostly based on biologicals (antibodies) that target particular signaling pathways highjacked by cancer genomes. Blocking key genes / gene products in the direct line of a cancer growth signal can efficiently block this signaling and break the vicious growth cycle of cancer cells. This way the immune system gets a chance to take care of the rouge cells before the proliferate entirely out of control.  Savior and destroyer rolled into one - the immune system Our main line of defense against virtually all diseases including cancer is our own immune system. This system has the power to destroy not only any intruders or abnormal cells but could also destroy the healthy tissues (as is the case in autoimmune diseases). Therefore, this powerful killing machine is under the control of various internal checks an balances to ensure it does not turn into a suicide machine. Quite a number of diseases, not only cancer, pervert some of these checks and balances to evade detection by or activation of the immune system. They induce a fatal form of immune tolerance where the offending cells are treated as “own” and ignored by the immune surveillance. Personalized medicine can help to detect which parts of the immune system get compromised by a disease. Especially in case of several tumors it was possible to extract immune cells from the patient, retrain them to attack the tumor and reintroduce them into the patient where they actually did their job they were “reminded” of outside the patient. This is called immune therapy and is a great option where possible as it harnesses the patients own immune system to fight the tumor entirely avoiding effects and side effects of external chemicals. This kind of therapy is called “individualized therapy” and it will be discussed in a separate blog entry in a bit more detail later on.  Figure 12: Selection of optimal therapy However, optional therapy in the context of personalized medicine does not necessarily mean the absolute best therapy. Some times the really optional therapy is simply not (yet?) available. Thus, all we can expect from personalized medicine today is the selection of the best available therapy for the patient. In the long run, this will also lead to the development of new therapies but the actual patients triggering such developments are not very likely to benefit themselves from it. However, without the development of the current therapies based on the past experience gathered from former patients, also patients today could not benefit from the therapies already developed. Therefore, sharing their data and tissues samples for research will help future generations of patients as our current one benefits from the same attitude of former generations of patients.  What’s coming up next? Next week we will leave the field of predictive P4-medicine and start with the personalized part, with an introduction into the realm of all the new Omics technologies. ​

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