Germ-line Mutations Vs Somatic Mutations: Understanding The Differences (Essay).

Germ-line mutations vs Somatic mutations

Discuss about the Molecular Biology for Germinal and Somatic Tissue. 

There are differences between the germ-line mutations and the somatic mutations which are important in the animals. This is dedicated to the germ-lines which are involved in producing reproductive cells. Germ-line mutations are not inherited from either of the parents, which are called de novo mutations[1]. These mutations are the first ones to appear in a family member. These are the results of a mutation in the sperm or egg of the parents. This mutation is then passed on to the generation. A somatic mutation is one that is in any cell other than the germ cells, both sperm and egg. It will not be passed on to the next generation[2]. A de novo mutation occurs for the first time in the member of family die to the result of a variant or mutation present in the germ cell of any of the one parent or so called variant. This arises during the phase of early embryogenesis that arises in the egg that is fertilised. This is now called the de novo variant or a new mutation.  

Genes and chromosomes are able to mutate in case of both germinal and somatic tissue. The changes are thereby known as germinal mutations and somatic mutations. Occurring in a single cell, the somatic mutation takes place in a somatic tissue that is developing. The cell is the precursor of the population, which is identical to the mutant cell, which has descended from the mutated cell. Clones are genetically identical cells of a population that derives from a single progenitor cells asexually. The members of a clone most of the time tends to stay in adjacent proximity to each other throughout development. This consequence is observed in a somatic mutation is often referred to a patch of phenotypically similar mutant cells known as mutant sector. 

Mutation that occurs in the germ line is referred to as the germ line mutation[3]. The germ line is a specific tissue that is set separately during the developmental path to form germ cells. If a mutant germ cell takes part in the fertilization, in such case the mutation will be transferred to the next generation.

COSMICis an online database that comprises of mutations that are acquired somatically   and found in human cancer cells. Somatic mutations occurs in non-germline cells[4]. These mutations cannot be transferred to offspring. COSMIC is a short form of Catalogue of Somatic Mutations in Cancer, which is involved in curating data from papers that are found in the scientific literature. Experimental screens of large screen are obtained from the Cancer Genome Project at the Sanger Institute. For the academic researchers, this data available freely and this is commercially licensed to others.

COSMIC and TCGA: Databases for studying cancer mutations

The COSMIC database comprises mainly two main types of data which include the high precision data, manually curated by the experts. The contents are as follows:

• Panels of targeted gene-screening.
• More than 25,000 peer reviewed papers
• Metadata containing environmental factors and patient history
• Focus is given on known and suspected mutations and cancer genes.
• It also contains objective frequency data resulting from mutation of negative samples
• Lastly it contains, full details of the curation process along with the data captured

In addition, there is a genome-wide screen data containing:

• More than 32,000 genomes which consists of:
• peer reviewed  data obtained from large scale genome screening
• other databases such as TCGA and ICGC
• It is involved in providing unbiased and genome-level data of diseases
• Objective frequency data, by interpreting non-mutant genes of each genome
• Can be applied to discover novel driver genes [5]

The variants were partitioned using the COSMIC (catalogue of somatic mutations in cancer). The informations was implemented to classify the already known somatic mutations and the several mutation types. This compiled data provides increased coverage from a somatic perspective, of the cancer genomic landscape.  

The Cancer Genome Atlas (TCGA), is a association projectexisting between the National Cancer Institute (NCI) and National Human Genome Research Institute (NHGRI)[6]. This has created a significant all-inclusive and multi-dimensional map of the major genomic changes that occur in 33 types of cancer. The TCGA dataset contains 2.5 petabytes of data that help to describe tumor tissue and with the normal tissues that match. This data collected from more than 11,000 patients, which is publically available. This data has been used widely by the community of researchers.

The TCGA project successfully created a pipeline for genomic data analysis. This pipeline cannot only effectively collect or select the human tissues but also can and analyse the tissues used for genomic alterations[7]. This is conducted on a very large scale. The model serves for future projects to bring success of this network of research and technology that is national, along with exemplifying the tremendous teamwork efficiencyavailable in science.

New initiatives of NCI genomics have been run through the NCI Center for Cancer Genomics (CCG) that will continue to grow on the successful growth of TCGA project. This will be using the same collaborationmodel that was used for the large-scale genomic analysis. The genomics data will be made publically available.

The authors refers to the Cancer Genome Atlas (TCGA) project in order to gain further insights into colorectal carcinogenesis in respect to its mutational landscape. The Cancer Genome Atlas (TCGA) Network (Cancer Genome Atlas, 2012) authenticates the range of CRC-associated genes that had been described previously. The sequencing data does not only signal towards a considerable intertumoral genetic variety (heterogeneity) of CRC but also portrays the importance of the input of determination that was given by the TCGA project.  

The deterministic events which include the variations involved in the activity of transcriptional of different gene types, contributing to the formation of cell subtypes. The physiology and phenotype of the cell subtypes are alike to those that are found in normal tissues.The stochastic events which include events such as transcriptional noise or variations in the quantity of signalling machineries are responsible for the cell-to-cell heterogeneity[8]. There is also a foundation of heterogeneity that evidently exist in in the microenvironment of tumour. This microenvironment includes the extracellular matrix, the several supporting stromal cells along with the immune cells. Additionally it includes the host-tumor connections that not only takes place within tumors but also in the organism as a whole organism as well. This in turn results in the spreading of the cancer cells. Apart from these factors, the transition of the cancer cells form one phenotypic and molecular state to the other also contributes to the heterogeneity of the colorectal cancer samples. This is due to the divergence that has been perceived through many studies. This mechanism of cell to cell heterogeneity within the tumours might be evolutionary. Through this process the remaining cell populations would overgrow is reaction to an external offence which might refer to administration of drugs.

Cell-free DNA testing: Advancements and limitations

Cell free DNA is present in the blood stream therefore is collected from the bloodstream as biological samples in the form of blood or serum and transferred to the Cell-free DNA BCT tubes. In this study, the peripheral blood was collected as the biological sample, which was then transferred to the Cell-free DNA BCT tubes. This was then labelled according to the unique patient identifier. For isolation of the cell-free DNA, isolation kits are used which are especially designed to enrich the small circulating DNA which are less than 300bp, present in the biological samples. Recently other methods have also developed in order to isolate cell free DNA which includes the automated methods. 

The study successfully provided evidences that showed that cell free DNA testing had an elevated sensitivity along with specificity in comparison to the standard screening methods that were used traditionally in or to detect trisomy 21, which were done in prenatal- screening population. Use of cfDNA testing reduced the rate of false positive results to about 100 times in comparison to the standard methods of detection[9].

The high detection rate of trisomy 21 is the factor that makes noninvasive prenatal testing easier using cell-free DNA screening. However the examination only distinguishes a limited amount of aberrations. The positive prediction value is another advantage of using this method. The method is progressed by the prevalence of the screened abnormalities. There is also a low prevalence of PVV in the method. The study showed that about 45.5 % of trisomy was detected by the method, whereas only 4.2% was obtained by standard screening. The performance of the cfDNA is much greater to that compared to the first-trimester screening which is a traditional method for recognition of trisomy in a population of routine prenatal. 

There is an evident limitation to the contrast of cfDNA testing and standard screening. Only the first-trimester standard screening was used since methods like the integrated first- and second-trimester screening along with biochemical analytes and nuchal translucency. which have increased understanding along with specificity[10].On the other hand cfDNA testing is unable to detect many such abnormalities of the chromosome. In a study carried out with more than 1.3 million women, it was seen that about 17% of chromosome aberrations were recognised but were undetectable by recent approaches of  NIPT that were being implemented. Other major issues includedthe test failure, which generally occurs due to a low fetal fraction that is the quantity of cfDNA involved in the fetal origin maternal blood. Along with this providers who offer cfDNA testing, often lack full education regarding the impact of the optimistic results. Additionally the process of cfDNA testing is quite expensive. Therefore in spite of the various benefits, the explanation of the limitation should be explained to the patient before making a choice of prenatal testing.

Conclusion

There is a requirement for consideration of the expectations for the clinical application of cfDNA testing, especially regarding testing of prenatal genetics. In case of trisomy 21 and other such aneuploidies, the process cfDNA testing is an extremely effective and precise screening option[11]. This is particularly since it can capable of detecting certain sex chromosomal aneuploidies which were not identified withthe process of standard screening.However in conditions of maternal serum and screening of nuchal translucency, there is chance of identifying risk for a widerange of abnormalities. Often these are undetectable on testing of cfDNA.As in case of other studies, it is seen that circumstances of trisomy 21 consisted just over 50% of aneuploidies that is present in this particular population[12]. In case of women who wish for a better and more comprehensive assessment might go for analytical analysis using chromosomal microarray analysis or karyotype. More research is needed in order torecognise the incremental significance of nuchal translucency, the first-trimester ultrasonography along with the serum analytes. This is required for the recognition of atypical aneuploidies and the copy-number variants in addition to the structural anomalies and other such adverse perinatal consequences. In the case of colorectal cancer and factors like genetic alterations, it is the result of genomic instability, which tend to function through three common techniques that includes chromosomal instability (CIN), the microsatellite instability (MSI) and CpG island methylator phenotype (CIMP)[13]. In the course of the phase of development of colorectal cancer, most of the modifications generally seem in separate ways or in arrangement. Examples of such phenomenon can be seen inCIMP that usually appears with MSI[14]. This is primarily due to the methylation of the gene pairs and silencing of mismatch DNA repair genes. This generatesinter-tumor heterogeneity of first level. 

References

Gil, M. M., M. S. Quezada, R. Revello, R. Akolekar, and K. H. Nicolaides. "Analysis of cell?free DNA in maternal blood in screening for fetal aneuploidies: updated meta?analysis." Ultrasound in obstetrics &gynecology 45, no. 3 (2015): 249-266.

Norton, Mary E., Bo Jacobsson, Geeta K. Swamy, Louise C. Laurent, Angela C. Ranzini, Herb Brar, Mark W. Tomlinson et al. "Cell-free DNA analysis for noninvasive examination of trisomy." New England Journal of Medicine 372, no. 17 (2015): 1589-1597.

El Messaoudi, Safia, Fanny Rolet, FlorentMouliere, and Alain R. Thierry. "Circulating cell free DNA: preanalytical considerations." ClinicaChimicaActa 424 (2013): 222-230.

Nicolaides, K. H., D. Wright, L. C. Poon, A. Syngelaki, and M. M. Gil. "First?trimester contingent screening for trisomy 21 by biomarkers and maternal blood cell?free DNA testing." Ultrasound in Obstetrics &Gynecology 42, no. 1 (2013): 41-50.

Budinska, Eva, VladPopovici, Sabine Tejpar, Giovanni D'ario, Nicolas Lapique, KatarzynaOtyliaSikora, Antonio Fabio Di Narzo et al. "Gene expression patterns unveil a new level of molecular heterogeneity in colorectal cancer." The Journal of pathology 231, no. 1 (2013): 63-76.

Ng, Francesca, BalajiGaneshan, Robert Kozarski, Kenneth A. Miles, and Vicky Goh. "Assessment of primary colorectal cancer heterogeneity by using whole-tumor texture analysis: contrast-enhanced CT texture as a biomarker of 5-year survival." Radiology 266, no. 1 (2013): 177-184.

Russo, Mariangela, Giulia Siravegna, Lawrence S. Blaszkowsky, Giorgio Corti, Giovanni Crisafulli, Leanne G. Ahronian, BenedettaMussolin et al. "Tumor heterogeneity and lesion-specific response to targeted therapy in colorectal cancer." Cancer discovery (2015): CD-15.

Allen, Andrew S., Samuel F. Berkovic, Patrick Cossette, Norman Delanty, Dennis Dlugos, Evan E. Eichler, Michael P. Epstein et al. "De novo mutations in epileptic encephalopathies." Nature 501, no. 7466 (2013): 217.

Forbes, Simon A., David Beare, Prasad Gunasekaran, Kenric Leung, NidhiBindal, Harry Boutselakis, Minjie Ding et al. "COSMIC: exploring the world's knowledge of somatic mutations in human cancer." Nucleic acids research 43, no. D1 (2014): D805-D811.

Watson, Ian R., Koichi Takahashi, P. Andrew Futreal, and Lynda Chin. "Emerging patterns of somatic mutations in cancer." Nature reviews Genetics 14, no. 10 (2013): 703.

Palles, Claire, Jean-Baptiste Cazier, Kimberley M. Howarth, Enric Domingo, Angela M. Jones, Peter Broderick, Zoe Kemp et al. "Germline mutations affecting the proofreading domains of POLE and POLD1 predispose to colorectal adenomas and carcinomas." Nature genetics 45, no. 2 (2013): 136.

Zhang, Jinghui, Michael F. Walsh, Gang Wu, Michael N. Edmonson, Tanja A. Gruber, John Easton, Dale Hedges et al. "Germline mutations in predisposition genes in pediatric cancer." New England Journal of Medicine 373, no. 24 (2015): 2336-2346.

Weinstein, John N., Eric A. Collisson, Gordon B. Mills, Kenna R. Mills Shaw, Brad A. Ozenberger, Kyle Ellrott, IlyaShmulevich, Chris Sander, Joshua M. Stuart, and Cancer Genome Atlas Research Network. "The cancer genome atlas pan-cancer analysis project." Nature genetics 45, no. 10 (2013): 1113.

Tomczak, Katarzyna, PatrycjaCzerwi?ska, and MaciejWiznerowicz. "The Cancer Genome Atlas (TCGA): an immeasurable source of knowledge." Contemporary oncology19, no. 1A (2015): A68.