\r\n\tThis book will be a self-contained collection of scholarly papers targeting an audience of practicing researchers, academics, PhD students and other scientists. The contents of the book will be written by multiple authors and edited by experts in the field. The area of interest and scope of the project can be described with (but are not limited to) the following keywords: Alcoholism, Depression, Addiction, Blackouts, Relapse, Binge Drinking, Genetic basis, Neurological Aspects, Treatment, Organ Damage.
\r\n\r\n\tAuthors are not limited in terms of topic, but encouraged to present a chapter proposal that best suits their current research efforts. Later, when all chapter proposals are collected, the editor will provide a more specific direction of the book.
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Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"878",title:"Phytochemicals",subtitle:"A Global Perspective of Their Role in Nutrition and Health",isOpenForSubmission:!1,hash:"ec77671f63975ef2d16192897deb6835",slug:"phytochemicals-a-global-perspective-of-their-role-in-nutrition-and-health",bookSignature:"Venketeshwer Rao",coverURL:"https://cdn.intechopen.com/books/images_new/878.jpg",editedByType:"Edited by",editors:[{id:"82663",title:"Dr.",name:"Venketeshwer",surname:"Rao",slug:"venketeshwer-rao",fullName:"Venketeshwer Rao"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"4816",title:"Face Recognition",subtitle:null,isOpenForSubmission:!1,hash:"146063b5359146b7718ea86bad47c8eb",slug:"face_recognition",bookSignature:"Kresimir Delac and Mislav Grgic",coverURL:"https://cdn.intechopen.com/books/images_new/4816.jpg",editedByType:"Edited by",editors:[{id:"528",title:"Dr.",name:"Kresimir",surname:"Delac",slug:"kresimir-delac",fullName:"Kresimir Delac"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"51587",title:"Casein Proteins: Structural and Functional Aspects",doi:"10.5772/64187",slug:"casein-proteins-structural-and-functional-aspects",body:'\nIt is now widely known that milk is a complex biological fluid secreted by mammals whose most important biological function is to supply nutrients for the nourishment of the offspring. The term “micelle” has been applied to the dispersed phase of milk, that is the casein‐protein complex. Casein protein component of milk is made up of different proteins, which possess different functions despite having no well‐defined secondary and tertiary structure. These proteins, which include αS1‐, αS2‐, β‐, and k‐casein, have a primary amino acid sequence different from each other and occupy different positions in micelle and perform specific functions. Some of the proteins are involved in calcium phosphate transport while others in stability of other caseins and micelle. The structure and properties of casein micelle as a whole and individual casein proteins, which constitute the micelle, are discussed.
\nMilk is a complex biological fluid with high content of proteins, minerals, and lipids secreted by mammals to supply nutrition and to provide immunological protection to the newborn. The differences in the metabolic processes of the lactating mother and the nutritive requirements of the newborn are thought to be responsible for the interspecies differences in the composition of milk [1]. The main function of milk is to provide essential amino acids and minerals that are vital for the development and therefore function of muscular and other tissues in new born mammals. It also includes active proteins providing antibodies, metal and vitamin‐binding proteins, and several protein hormones [2]. Milk proteins coagulate very rapidly in the stomach of newborn as they are structurally built in a way that they form large complexes with calcium phosphate. Normal bovine milk contains almost 3.2–3.7% protein which varies in composition and concentration during different stages of lactation [3, 4]. Milk proteins are divided into two classes and are no more thought to be a homogeneous protein [2]. Caseins constitute about 75–80% of total protein and precipitate at pH 4.6 at 30°C. The remaining fraction, serum or whey protein, is soluble under similar conditions [5]. The rest of proteins found in milk are trace fractions of glycoprotein [6]. Casein proteins and calcium phosphate form large colloidal particles called casein micelles, which have been the subject of interest for many years [7]. The main function of the casein micelle is to provide fluidity to casein molecules and solubilize phosphate and calcium. There is a very large flow of calcium through the mammary epithelial tissue, and despite this, there is rarely any formation of calcium stones in the mammary gland. It has been suggested that the calcification of the mammary gland is prevented by the formation of casein‐micelle complex with calcium phosphate. The primary amino acid sequence of casein proteins and their conformation in solution are therefore thought to prevent calcification of the mammary gland in addition to providing nutrition [8]. In addition to their biological role, which is to provide nutrition, caseins are also studied for their role in human health and other malfunctions such as stone‐forming diseases in bovine animals [9–12].
\nThe casein‐micelle structure is being studied extensively because of its importance in the functional behavior of milk and some milk products [5]. However, the exact structure of casein and its micelles is still under debate. Various physical and biochemical studies of these colloids have mainly focused on the properties, size of the colloids, protein composition, micelle reconstitution, etc. Due to the large size of the casein‐micelles, which interfere with absolute structure determination, different models have been proposed. Models can be classified into three categories: coat–core model, subunit or submicelle model, and internal structure model. Waugh and Nobel in 1965, Payens in 1966, Parry and Carroll in 1969, and Paquin and others in 1987 proposed coat‐core models. Coat‐core model dictates that micelle is an aggregate of caseins with outer and interior of micelle having different composition, and there is an inaccuracy in the identification of inner part of the structure [13–16]. This actually contains two diametrically opposite theories. Waugh and Nobel in 1965 were the first who proposed a model which fits in this class which is based primarily upon the solubilities of various caseins in Ca2+ solutions. According to them, αS1‐ and k‐caseins form low weight ratio complexes in the absence of calcium. Monomers of αS1‐ or β‐caseins with charged phosphate loop form caseinate core due to addition of calcium ions. The αS1‐ or ‐β‐caseins in their monomeric form with charged phosphate loops form limiting size aggregates/caseinate core. The formation of low weight αS1‐k‐complex monolayer leads to the prevention of caseinate precipitation. The k‐casein monomers spread out entirely on the surface of coat/complex formed, and therefore, its amount dictate the size of casein micelle. This model explains the lyophilic nature of the colloidal casein complex and also the ready accessibility of k‐casein to chymosin and therefore is quite appealing [17]. According to Payens (1966) model based on his experimental data on the association of caseins, the densely folded αS1‐caseins remain adhered to loose network of β‐caseins to form micelle core. Unlike the Waugh and Nobel models, colloidal calcium phosphate is present both on the outer surface and in the inner side of the micelle, while k‐casein is confined to the surface of the micelle [7]. In 1969, Parry and Carroll used electron microscopy to locate k‐casein on the surface of micelle as proposed by Waugh. They suggested that k‐casein is present at the interior and acts as a nucleating agent to which calcium‐insoluble caseins might cluster and gets stabilized the colloidal calcium phosphate. They used ferritin‐labeled anti‐k‐casein antibodies to localize kappa casein at the outer surface of casein micelles. They found very little or no concentration of k‐casein protein on the outer surface of the casein micelles as was suggested by previous workers. According to this model of casein micelle, the surface of the micelle comprises αS1‐ and β‐caseins with some colloidal calcium phosphate [18]. Paquin et al. in 1987 proposed a model based on results obtained from experiments using gel chromatography of EDTA‐dissociated casein micelles for identifying two protein fractions by monolayer methods. This model describes the micelle core as a scaffold of colloidal calcium phosphate and αS1‐caseins, while β‐caseins are held by hydrophobic interactions. These models predict a precise distribution of k‐casein and are based upon nucleation around a core which is k‐casein in case of Parry and Carroll and αS1, β‐calcium caseinate in case of Waugh [7].
\nThe submicelle models that were proposed by Shimmin and Hill (1964), Morr (1967), Slattery and Evard (1973), Schmidt (1980), Walstra (1984), and Ono and Obata (1989) considered that casein micelles are composed of uniform subunits that are roughly spherical in shape [19–23]. Shimmin and Hill (1964) were the first who postulated a submicellar structure for the casein micelle [24]. They used electron microscopy to study the ultrathin cross sections of embedded casein micelles and measured a diameter of 10 nm for the submicelles [24]. Another model proposed by Morr (1967) which was based on results obtained from study of oxalate and urea treatment on the disruption of casein micelles and proposed that αS1‐, β‐, and k‐monomers formed small uniform submicelles. These casein micelles are composed of numerous, loosely packed, calcium caseinate complex units, joined in association by a combination of calcium and colloidal calcium phosphate and citrate linkages between casein phosphoserine and carboxyl groups. Hydrophobic bonding and calcium caseinate bridges stabilize the submicelles, while colloidal calcium phosphate helps to aggregate the submicelles into micellar structure [19]. Each of these calcium caseinate complex units is probably composed of an inner core consisting of a αS1‐ and β‐casein, surrounded by an outer layer rich in αS1‐ and k‐casein, as suggested by Waugh and noble [14, 25]. According to Morr, these submicelles have a diameter of ∼30 nm studied by using sedimentation velocity which is somewhat larger than that postulated by Shimmin and Hill. Additional β‐casein could become associated with the outer surfaces of the micelle under appropriate conditions which favor conversion of soluble casein (mainly β‐casein) to micellar casein. A model was proposed for the native casein micelle which consists of numerous loosely packed calcium caseinate complex units joined in association by a combination of calcium and colloidal calcium phosphate–citrate linkages. The colloidal calcium phosphate–citrate is considered to be distributed throughout the micelle rather than as a layer on its outer surface. αS1‐, αS2‐, and β‐casein precipitate when calcium binds to their phosphoserine residues. k‐casein at the other end is not only calcium insoluble, but it also interacts with other calcium‐sensitive caseins and stabilizes them thereby initiates the formation of the stable colloidal state. Various enzymatic, immunological, and chemical techniques usually recognized that while majority of the k‐casein must reside on the outer surface of the casein micelles, other caseins might also occur there as well [26, 27]. k‐casein is thought to be predominantly present on the outer surface of the casein micelle as shown by almost all researchers working in this field till date. Various methods for disruption of casein micelles have been used by several other researchers to study the nature of submicelle. Carroll et al. (1971) used urea, EDTA, sodium fluoride, and sodium lauryl sulfate for the disruption of micelles and found particles ∼8 to 12 nm in diameter [28]. Submicelles of 10 nm diameter were also found by Schmidt and Buchheim (1970) after they dialyzed milk free calcium in cold and using high pressure to disrupt casein micelles [29, 30]. These results were confirmed by Buchheim and Welsch in 1973. Pepper and Farrell (1982) used gel chromatography to study interaction of concentration‐dependent interactions of EDTA dissociated whole‐casein micelles. It was found that with increasing protein concentration at 37°C and pH 6.6, the individual components of casein formed polymers which approached a molecular radius of ∼9.5 nm [31]. These submicelles were thought to be formed by the interaction of SH‐k‐casein monomers with those of αS‐ and β‐caseins as seen by analyzing concentration elution profiles. Carroll et al. (1970) and Farrell and Thompson (1971) also observed particles of ∼10‐nm diameter in the Golgi vacuoles of lactating rat mammary gland and therefore supported the hypothesis of Shimmin and Hill (1964) [28, 32]. Another model for casein micelle structure is based on the results of various experiments on the effect of calcium on the sedimentation behavior of those particles which are formed in mixtures of caseins was proposed by Slattery and Evard in 1973. This model based upon casein interactions combines the best features of most casein micelle models. According to this model, submicelles which are rich in k‐casein are found predominantly on the outer surface of the casein micelle, while those poor in k‐casein content are internalized. They suggested that casein monomers interact to form submicelles of variable composition depending upon their casein content. This model also suggests an inverse relationship between k‐casein content and micelle size. This model predicts large casein micelles which are poor in k‐casein content, k‐casein will occupy position on surface, while in smaller micelles which are rich in k‐casein, k‐casein is uniformly distributed [22]. Walstra (1984) proposed the submicelle model for casein which is the most accepted model for casein. According to this model, spherical subunits or submicelles are the building blocks of casein micelles. Each submicelle is variable in composition with 20–25 casein molecules per submicelle, and the diameter of submicelle is 12–15 nm. Hydrophobic interactions between the constituent proteins and the calcium phosphate linkages keep the submicelle together. According to this model, there are two types of submicelles one consisting of αS‐ and β‐caseins and another αS‐ and k‐caseins, the former is has hydrophobic regions buried in the center while latter is more hydrophilic because of the presence of sugar residues on k‐caseins. Further aggregation of submicelles is avoided by the steric and electrostatic repulsions by the hydrophilic part of the C‐terminal end of k‐casein located near outside of micelle, protruding from the micelle surface as a hairy layer [23]. Carroll and Farrell in 1983 also found that the location of k‐casein is indeed related to casein micelle size using ferritin‐labeled double‐antibody technique coupled with electron microscopy [33]. These results confirm the inverse relationship between micelle size and k‐casein content and also that larger casein micelles contain higher polymers of k‐casein, indicating that k‐k interactions are greater in k‐poor micelles. Since according to this model, k‐casein is not totally precisely localized in the micelles this model therefore contradicts with models proposed by Parry, Waugh, Garnier, and Ribadeau‐Dumas and supports the more flexible model of Slattery and Evard [22, 25, 34].
\nThe internal structure models, which are the last models, were proposed by Rose (1969), Garnier and Ribadeau‐Dumas (1970), Holt (1992), and Horne (1998) indicate the manner in which different caseins aggregate [34–37]. The internal structure model of casein micelle is based upon the properties of isolated protein components which are involved in the formation of internal structure of the micelle. Rose (1969) was the first to propose internal structure model by using the endothermic polymerization of β‐casein as the basis for his casein micelle model. According to this model, αS1‐monomers attach to chain like polymers of β‐casein which are self‐associated from β‐casein monomers. k‐casein interacts with αS1‐monomers. The β‐casein is directed inward, while k‐casein is directed outwards and a small amount of k‐casein is placed in an internal position as these two segments associate. Colloidal calcium phosphate is incorporated as a stabilizing during the formation of micelle. The occurrence of some overall stoichiometry of the various casein components and the role of colloidal calcium phosphate in stabilizing micelle make this model appealing [37]. However, synthetic micelles can be formed from simple k‐ and αS1‐casein complexes in the complete absence of β‐casein which makes β‐casein as the basis of micelle formation questionable. Waugh et al. (1970) have also shown that the αS1‐ and β‐caseins tend to form mixed polymers randomly and β‐casein is structure less in solution. It also forms micellar‐like complexes rather than linear polymers [38]. Garnier and Ribadeau‐Dumas (1970) who proposed another model emphasize on k‐casein as the foundation of micelle structure. According to this model, three chains of αS1‐ and β‐casein are linked to the trimers of k‐casein which radiate from the k‐casein node which is present as a Y‐like structure. There is a formation of loosely packed network when these αS1‐ and β‐caseins connect to other k‐nodes. This model places steric restraints upon k‐casein which posses few secondary structures. This model provides demonstrated porosity and explains a uniform distribution of k‐casein regardless of micelle size. The model assigns no role to calcium caseinate interactions and ignores the role of colloidal calcium phosphate involvement in stabilization of the micelle. Although the submicelle casein model proposed by Walstra in 1999 has been widely accepted, there are two alternative models proposed by Holt in 1992 and Horne in 1998 which fall into internal structure model [6, 35, 36]. According to model proposed by Holt, the casein micelle forms a tangled web of flexible casein networks forming a gel‐like structure with C‐terminal region of k‐casein extending to form a hairy layer and microgranules of colloidal calcium phosphate at center. The surface location of k‐casein and the cementing role of colloidal calcium phosphate are the two main features of this model. The caseins micelles according to this model are stabilized by two main factors one of which is steric stabilization by protruding k‐casein layer hairs and another is by surface potential of approximately -20mV at pH 6.7. In 1998, Horne proposed dual bonding model which suggests that it is a balance between electrostatic repulsions and attractive hydrophobic interactions which held the proteins in casein micelles together. According to this model, hydrophobic interaction is the driving force for the formation of casein micelles and electrostatic repulsions are responsible for limiting the growth of polymers [36]. αS1‐ and β‐caseins self‐associate by hydrophobic interactions as a result of formation of train–loop–train and tail–train like structures, respectively, upon adsorption at hydrophobic interfaces. There occurs a reduction in electrostatic repulsion because of colloidal calcium phosphate which form linkages between casein micelles and neutralizing agents of the negative charge of phosphoserine residues which makes the hydrophobic interaction between caseins a dominant force for the association of proteins. The lack of phosphoserine cluster to bind calcium in k‐casein makes it to interact hydrophobically and act as a propagation terminator.
\nLinderstrom‐Lang in 1929 postulated that mixture of calcium‐insoluble proteins stabilized by calcium‐soluble protein form the colloidal milk complex [39]. The calcium‐soluble protein would be readily split by chymosin which leads to its coagulation due to destabilization of colloid. Such fractions exist as αS1‐, αS2‐, and β‐caseins which are insoluble in calcium and k‐casein which is soluble in presence of calcium and is split readily by chymosin. Sedimentation velocity experiments performed by Waugh et al., in 1971, demonstrated that αS1‐ and k‐casein complexes can be reformed from already isolated fractions [40]. A brief summary of the various types of bonding forces responsible for the stabilization of protein structure will be discussed.
\nThere is presence of large number of hydrophobic residues clustered together in αS1‐, β‐, and k‐casein as found by amino acid sequence analysis of these proteins. Since these are among the most hydrophobic proteins, role of hydrophobic bonding in the stabilization of casein cannot be ignored. The ability of β‐casein to self‐associate was reduced after removal of isoleucine and valine at C‐terminal end of protein which normally self‐associate in the absence of calcium [41]. Additionally, the ability of β‐casein to form polymers was destroyed completely after removal of 20 amino acids at C‐terminal which are mainly hydrophobic in nature [41]. Various investigators have found that αS1‐, β‐ and k‐caseins diffuse out of the micelle at low temperature due to decrease in hydrophobic interactions [42–44]. The micelles containing rare αS1‐A genetic variant which possesses similar physical and solubility properties like that of β‐casein is also less stable in cold. On the basis of light scattering and electron microscopy, it has been found that increased pressure disrupts casein micelle structure which also acts primarily on hydrophobic interactions [42–46]. The dependence of hydrophobic interactions on temperature and pressure also explains the resistance of skim milk to withstand higher temperature which is otherwise destabilized at extremely low temperatures.
\nThere are many potential sites for strong ion bonding in apolar environment that might play a role in the stabilization of casein micelles. It is not possible to exactly assess the role of various inter‐ and intramolecular ionic bonds present in αs‐, β‐, and k‐casein in stabilization of casein micelle structure. The ability of k‐casein to stabilize the αS1‐casein is abolished when there is carbamylation of lysine residues in k‐casein which further demonstrate that ionic interactions play a role in the casein micelle structure [47]. Modification of arginine side chains also affects the casein micelle stability and chymosin‐induced coagulation [48].
\nThe α‐helical and β‐pleated structures in many globular and fibrous structures are stabilized by hydrogen bonding along the polypeptide chain. Since casein proteins posses very little secondary structure and 72–76% of protein exists in aperiodic form, the degree of stabilization by α‐helix and β‐structure is very low [49, 50]. Hydrogen bonds between the various components of casein during the formation of highly aggregated casein micelle are possible but in case of ionizable side chains of monomeric proteins which are accessible to water, their contribution to the stability of these monomeric proteins is very less. For the formation of a residue‐residue hydrogen bond in case of these monomeric proteins, there must be breakage of water‐residue hydrogen bond which has already formed. During the interaction of two subunits of a protein, there are chances of formation of hydrogen bonds between individual monomers as the surface groups are no longer fully hydrated. Hydrogen bond may exist during the formation of aggregated casein micelles and self‐association of αS1‐casein.
\nDisulfide bonds between cysteine residues during folding of pleated sheet structures, helical segments, and unordered structures leads to the formation of tertiary structure. Both αS2‐ and k‐casein contain cysteine but the degree of disulfide cross‐linkages which are normally present in the casein micelle is controversial [51–53]. It has been reported by many investigators that disulfide cross‐linkages contribute to the overall stability of the casein micelle but they are not the driving force for the formation of casein micelle. Slattery in 1978 found that larger micelles have higher molecular weight disulfide‐bonded polymers of k‐casein. These k‐casein molecules are thought to be contiguous with each other and form disulfide‐linked aggregates which compose the casein micelle structure [54].
\nCasein proteins are phosphoproteins which comprise approximately 80% of the total protein present in bovine milk [55]. They were defined as phosphoproteins which precipitate from raw milk upon acidification at pH 4.6 at 20°C [56]. Casein proteins belong to one of the larger family of secretory calcium‐binding phosphoproteins as has been found by the analysis of structure of human genome. Casein proteins provide one of the best example of intrinsically disordered or natively disordered or natively unfolded proteins [57]. The previous assumption that only those proteins which possess a well‐defined folded conformation is able to perform a specific biological function is not valid in case of many intrinsically disordered proteins as they have specific biological functions even in their unfolded state [58]. Furthermore, it has also been found that in case of many of the eukaryotic proteins involved mainly in signaling pathways, there is presence of regions with disordered backbone conformations. The presence of disordered region in a protein involved in signaling provides larger surface area for interactions with other proteins. This property can therefore also help these proteins to interact with multiple proteins or target molecules at one time [59]. All of the casein proteins possess very little secondary and tertiary structure but are still able to perform their function in their disordered state. Caseins belong to the scavenger family of secretory calcium‐binding phosphoproteins as they are involved in trapping of calcium phosphate. The intrinsic disorder of these proteins not only help in forming a thermodynamically stable complex with calcium phosphate but also allow these proteins to form a more tightly packed complex than a globular structure [58]. These casein proteins are post‐translationally phosphorylated at seryl and very less frequently at threonyl residues which is one of their unique characteristic. k‐casein contains only one or two phosphoseryl residues and is only casein which is glycosylated [53]. These calcium‐sensitive caseins are not only able to bind to calcium phosphate crystal surface but are also able to form calcium phosphate nanoclusters which are thermodynamically stable chemical complexes by sequestering amorphous calcium phosphate. Calcium phosphate sequestration also depends upon the formation of phosphate centers in the primary sequence by clustering of phosphorylated residues [60].
\nEarlier principle protein of bovine milk was considered to be homogenous protein casein. Later on it was found that casein proteins are heterogeneous and are composed of distinct fractions like α‐, β‐, and k‐casein [61]. Casein in milk in its native state exists as large associate of macromolecules in colloidal dispersion with a mass of ∼ 108 Da and ∼200 nm in size [62]. The major protein of the casein complex is αS1‐casein which almost 38% followed by β‐casein 36%, k‐casein 13%, and αS2‐casein 10% [63]. Proline which is known to disrupt alpha‐helical and β‐structures is present in higher amount in αS1‐casein. It has been found that 70% of αS1‐casein is in unordered form with only a small amount of α‐helical and β‐structure. αS1‐Casein plays an important role in the ability of milk to transport calcium phosphate. It has also been found that one of its antioxidant peptide has 2,2‐diphenyl‐1‐picrylhydrazyl (DPPH) radical scavenging activity. All casein proteins in their native states do not possess a well‐defined tertiary or secondary structure [49]. Casein is classified as intrinsically disordered proteins implying that the protein is functional in its unstructured form. Further, it has been found by various investigators that αS1‐ and β‐casein possess chaperonic activity and are responsible for the stabilization of micelle by preventing aggregation of αS2‐ and k‐casein, respectively. Various investigators have also found that αs‐casein prevents the stress‐induced aggregation of various proteins like bovine serum albumin, whey proteins, β‐lactoglobulin, carbonic anhydrase, and alcohol dehydrogenase by forming soluble, high molecular weight complexes [64]. The self‐association of αS1‐casein monomers in aqueous solution is attributed to the high degree of hydrophobicity and small amount of structural content [38, 45]. There are ∼43% hydrophobic amino acids in case of αS1‐casein, ∼33% in case of αS2‐casein, ∼52% in β‐casein, and ∼43% in k‐casein. Under the normal pH, ionic strength, and temperature of milk, the major protein components of milk are insoluble. The second most abundant milk protein is β‐casein with five phosphoserine residues and a molecular weight of 23,980 [65]. All the protein\'s net charge, phosphoserine content, and α‐helical residues are restricted to the first 40 amino acid residues present at N‐terminal portion of β‐casein, while C‐terminal contains many apolar residues responsible for its high hydrophobicity [49]. β‐Casein possesses very little secondary structure and is present as a random coil in aqueous solution. The lack of secondary structure is due to the evenly distributed proline found during complete amino acid sequence of β‐casein [66]. β‐Casein plays an important role in determining the surface property of casein micelle. One of its peptide acts as a macrophage activator thereby increase the phagocytic activity of macrophages and their peroxide release. β‐casein also possesses an antioxidant peptide which has antioxidant activity. The last casein sequenced was αS2‐casein which possesses most unique primary structure of all the caseins with a molecular weight of 25,150 [67]. This protein has two cysteine residues with no known carbohydrate. αS2‐Casein exists as a dimer or may have some intrachain disulfide. αS2‐Casein is least susceptible to aggregation because of alternating negatively charged and hydrophobic areas [68]. It also plays important role in the transport of calcium phosphate. Its anti‐microbial peptide casocidin‐I has the ability to inhibit growth of E. coli and other bacteria. k‐casein, which is soluble over a very broad range of calcium ion concentrations unlike other forms of caseins like αS1‐, αS2‐, and β‐casein, is the fourth major component of the milk‐protein complex [69]. Calcium solubility of k‐casein has led workers to assign to it the role of casein micelle stabilization whose other components are insoluble in calcium. It stabilizes micelle formation thereby prevent precipitation of casein in milk. Casoxins peptide possesses opoid antagonist, whereas casoplatelin inhibits platelet aggregation. The molecular weight of reduced k‐casein is about 19,000 [51]. It exists as a high molecular weight mixtures of polymers. It is the only major component of casein which possesses carbohydrates bound to the highly soluble macropeptide portion formed after chymosin hydrolysis. There are only one or two phosphate residues per k‐casein casein monomer which makes it soluble in calcium [70].
\nThere are several genetic variants of casein components with variable numbers of phosphoseryl residues especially in case of αS2‐casein which exhibits a large variability in the extent of phosphorylation [71]. Another unique feature of caseins is the large amount of propyl residues especially in case of β‐casein which greatly affect the secondary and tertiary structure of caseins [53]. In addition, all casein proteins possess different hydrophilic and hydrophobic regions along the protein chain [46]. αS‐Caseins are the major casein proteins with 8–12 seryl phosphate groups, while β‐casein contains about 5 phosphoserine residues and is more hydrophobic than αS‐caseins and k‐casein [49]. Highly phosphorylated αS‐caseins and β‐caseins are very sensitive to the of calcium salt concentration, that is, these proteins precipitate in presence of high Ca2+ ions [40, 72]. Unlike other types of caseins, k‐caseins are glycoproteins [56, 71] with only one phosphoserine group. This makes them stable in the presence of Ca2+ ions thereby playing an important role in protecting other caseins which are calcium sensitive from precipitation and makes casein micelle stable [69]. Casein is insensitive to heat, and it is only temperature above 120°C that causes the casein proteins to become insoluble, whereas it is sensitive to pH and will precipitate at its isoelectric pH [73]. The individual families of casein proteins were identified by alkaline urea gel electrophoresis. Each of the four different caseins may have a variety of numbers of phosphate groups attached through their serine or threonine residues. In terms of the extent of phosphorylation, αS1‐casein may have 8 or 9, αS2‐casein 10–13, β‐casein may have 4 and k‐casein, 1–3. αS1‐ and β‐Casein contain no disulfide bonds, and αS2‐ and k‐casein contain two cysteine residues which form inter‐ or intramolecular disulfide bonds [74, 75]. αS2‐Casein exists as a dimer, and k‐casein can exist from dimer to decamer depending upon the pattern of intermolecular disulfide bonding [68]. There are 10 different molecular forms of k‐casein on the basis of degree of glycosylation and is the only casein which is glycosylated [56, 70, 71]. Another source of variability in caseins is genetic polymorphism. αS1‐Casein has been shown to be present in bovine milk as αS1‐casein A‐D [71]. Caseins are structurally classified as natively or intrinsically disordered proteins which is different from random coil conformation found in some globular proteins [76, 77]. Due to the lack of well‐defined structure, crystallization of casein proteins to provide a three‐dimensional crystal structure is not possible, but at the other end, this lack of structure helps to facilitate proteolysis and therefore ready absorption of amino acids and small peptides in the intestine [2, 78]. Caseins proteins possess very little three dimensional structure but possess some secondary structure [79]. The high number of proline residues which distort protein folding into α‐helices and β‐sheets is responsible for inhibition of higher proportions of secondary and tertiary structure. Casein proteins contain 32–42% non‐polar amino acids which makes them highly hydrophobic but due to the presence of high number of phosphate and sulfur‐containing amino acids and carbohydrates in case of k‐casein, they are quite soluble in aqueous solvents [2]. Casein proteins are homologous in all the species as has been found by various protein and gene sequencing studies [80]. The proportion of various caseins varies widely. All species form colloidal casein micelles for the transport of calcium and phosphate. Casein micelles of most species appear quite similar at the ultra structural level. Despite the variations in casein components, the αS1‐ and αS2‐caseins are calcium sensitive, whereas β‐ and k‐casein are not sensitive to calcium. Casein proteins are important nutritionally because of their high phosphate content due to which they bind significant quantities of calcium and also are rich in lysine which is an essential amino acid in humans. αS1‐ and αS2‐casein possess 14 and 24 lysines, respectively [2]. Each of the caseins possesses significant variability due to extent of their post‐translational modification, disulfide bonding, genetic polymorphism [81]. The properties of milk and various milk products mainly depend on proteins present in it and to some extent on other components like salts, fat, and lactose. Caseins which possess an extraordinary high heat stability make the milk and other milk products highly stable even at higher temperature [61].
\nMammalian milk contains casein micelles that help to provide adequate nutrients to the neonate and at the same time prevent any risk of pathological calcification or amyloidosis. Interestingly, all caseins exhibit a disordered conformation and many have chaperonic activity (αS1‐ and β‐casein) which might be an attribute that help these casein proteins to self‐associate and assembly into functional micelle. The structural disorderness and the chaperonic property would have been evolutionarily selected to make these molecules ideally suitable to thrive under various environmental insults since the milk is secretory product. It might be possible that that in addition to casein, many other milk proteins may also have chaperonic function. Identifying chaperonic function of other proteins present in milk will have many industrial and clinical insights.
\n\nPersonalized medicine is a new approach that allows the identification of patients that can benefit from targeted therapies, since the molecular characteristics of their tumors could be identified. Over the last decade, new drugs have been incorporated into the treatment, including the development of immunotherapy and treatment against specific molecular targets [1]. Thus, patients can receive specific treatments according to the biology of their tumor, turning oncology a tool for personalized medicine. In order to do so, the development of new DNA/RNA sequencing technologies was required, as well as the development of specific antibodies identifying mutated or altered proteins, and the design of new in situ hybridization techniques. The latter has enabled the selection via genetic biomarkers of patients, who can benefit from therapies targeted against specific molecular alterations [2]. Based on the detection of these point molecular alterations, with a clear oncogenic role, treatments have been developed to block the activation of mutated, amplified proteins or product of translocations by specific drugs. The identification of patients with therapeutic molecular targets in their tumors is currently a standard of care. Notwithstanding that, the initial morphological diagnosis and the eventual tumor classification by immunohistochemistry (IHC), as well as the acquisition, handling and processing of tumor tissue play a pivotal role.
In advanced-stage patients, a relatively small amount of tissue obtained at a single procedure must be used most efficiently for all studies [3]. In this sense, consensus exists about making histopathological diagnosis using as little material as possible, which should be kept for molecular studies [4, 5]. The combination of less invasive techniques that provide very small samples to carry out an increasing number of determinations is controversial, since it does not allow to increase the amount of tumor cells. Consequently, more sensitive and specific molecular determinations are required [6].
Although several methods are being developed, such as free tumor DNA detection in peripheral blood, most of these determinations are currently experimental and few are validated for clinical use [7, 8]. Therefore, until more sophisticated techniques for these and other molecular markers are validated, the amount/size of the samples should be considered.
The aim of this chapter is to show the implications of molecular pathology in personalized medicine with an actual approach from the methodological limitations of formalin-fixed paraffin embedded (FFPE) tissues and their pre-analytical conditions.
In molecular pathology, several variables should be considered for optimal results, and pre-analytical conditions are evaluated.
One of the crucial phases in tissue management is the period of time immediately after the sample is extracted from the patient until it is placed in a fixation solution (cold ischemia). In an experimental animal model, significant differences in pH values were found between organs at the same cold-ischemia time, and in the same organ at different times. However, no differences were seen in the RNA quality assessed by its integrity number or absorbance ratios [9]. These results reveal a high pH in tissues undergoing ischemia. Firstly, although RNA integrity number (RIN) is a powerful tool to analyze the ribosomal profile and to further infer RNA quality from fresh and frozen tissues (and to compare samples RIN values given the same organism/tissue/extraction method), it is not enough to predict the integrity of mRNA transcripts or to describe the real biological conditions. Secondly, acidic duodenal pH has been reported to alter gene expression in the pancreas of a cystic fibrosis mouse. Upon correction of duodenal pH, either genetically (breeding CFTR-null with gastrin-null mice) or pharmacologically (proton pump inhibitor omeprazole), expression levels of genes measured by quantitative RT-PCR were significantly normalized [10]. Whether alkalosis is secondary to ischemic cell damage, or it may contribute to ischemic cell damage, is yet unknown. Thus, tissue alkalosis in cold-ischemia time may be an underlying mechanism of gene expression changes. Therefore, tissue-pH regulation after organ removal may minimize biological stress in human tissue samples. To date, no consensus exists about the optimal preservation solution. Further optimization of the composition of preservation solutions is required to prolong organ preservation time, and to maximize the yield of successful transplantations by improving the quality and function of organs [11]. Most laboratories have neither control nor record of how long it takes between tissue removal and immersion in the fixer, and its arrival in the laboratory. In addition, most automatic tissue processor machines include a fixation step that further increases the fixation time, which is not often considered.
Once the tissue has been obtained it should be fixed and 10% Neutral buffered formalin (NBF) fixation is recommended. Pre-fixation in alcohol-based fixative, decalcifying acidic solutions, acidic fixatives (such as Bouin) or those containing metallic salts may alter DNA antigenicity or integrity. Setting a period of more than 6 hours and less than 48 hours is recommended [12]. Short or excessive fixation time may have deleterious effects on DNA and protein antigenic epitopes [13, 14]. The most frequently described effect of formalin in DNA is its fragmentation into small pieces. The use of polymerase chain reaction (PCR) techniques in formalin fixed paraffin embedded (FFPE) tissues is associated with a higher incidence of sequence artifacts and risk of misinterpretation in PCR results, compared with the use of fresh samples [15, 16]. After the inclusion of the tissue in paraffin, the sample remains stable and is preserved against oxidative damage or other degenerative effects. However, in addition to fixation, the type of storage is another documented source that can damage DNA and cause artifacts in the PCR. For a better preservation of DNA, FFEP blocks should be stored below 27°C in humidity-free conditions. Although humidity can affect DNA stability, the acceptable humidity control range is not described. In our experience, up to ten-year-old FFEP blocks have been used. Provided that storage is accurately done and the pre-analytical parameters indicated in this chapter are met, blocks can be preserved up to this time [17]. Since FFPE tissue is currently used for genetic analysis, results should always be carefully interpreted. Mutations detected from FFPE samples by sequencing must be confirmed by independent PCR reaction. Determining the nature and duration of fixation is a great challenge to pathology laboratory, which receives samples from other centers. Therefore, it was suggested that the cold ischemia time, the type and time of tissue fixation should be registered in the pathology report [18].
For a molecular analysis, the following data are required: type of biopsy (primary tumor or metastasis), type of block, and percentage of tumor cells needed for each method.
As above mentioned, fixation breaks the genetic material into small fragments, and then PCR of FFPE tissue needs a design of specific-sequences primers that flank targets with molecular weight less than 300 bp. Should the designed primers flank a fragmented-amplicon, they fail to perform the enzyme amplification because they need the continuity of the DNA/RNA mold to generate a strand, thus leading to lower sensitivity or false-negative results. Thus, the input for a PCR reaction performed from FFPE tissue requires mandatory quantification with DNA/RNA calculator spectrophotometer. Thus, each methodology uses a different sample input to obtain the analytical sensitivity (LOD). Every PCR requires a balance between its reaction components, and then the sample input has a direct relationship with the concentration of the primers.
Therefore, somatic mutations, which are generated in tumors and are not present in normal cells, require a minimum percentage for each method.
Based on the premise that somatic mutations occur, for the most part, in one of the alleles present in human genome, knowing that in humans there are two equal alleles on somatic chromosomes, one of maternal and one of paternal origin, we must understand that if we seek a tumor marker, we must enrich our input in this allele (Figure 1).
Mutant allele fractions (MAFs, or the ‘mutation dose’).
Sequencing of tumors is now routine and guides personalized cancer therapy. Mutant allele fractions (MAFs, or the ‘mutation dose’) of a driver gene may reveal the genomic structure of tumors and influence response to targeted therapies [19]. Mutation fraction can be defined as the ratio between mutant and wild-type (wt) alleles in a tumor sample. Allelic fraction is generally applied to a single mutation in a tumor, and is therefore distinct from allelic frequency, which examines the frequency of an allele in a population. To date, however, these terminuses are unfortunately exchanged. Dideoxynucleotide sequencing is a routine method for identifying genetic changes. Since both alleles are amplified in this method, enough input of mutant allele (as compared to the input of normal allele) must be detected. However, this detection requires at least 10–20% of allelic presence. Mutations below this threshold due to normal cells high contamination or tumor heterogeneity could not be detected by this method [20]. Low percentages of neoplastic cells are sometimes associated with unreliable results. Therefore, the percentage of tumor cells must be estimated either through microdissection technique or selection of block interest region [5, 21]. The normal tissue and the lymphocyte infiltration areas must be removed from the tissue for analysis since both are nucleated elements that provide normal DNA. Areas of necrosis should be also removed, since the cell causing necrosis cannot be identified and may be normal or neoplastic. As we know, cell/tumor free DNA drained by biological mechanisms such as secretion, apoptosis and necrosis can be amplified by new generation methods that require smaller chain fragments, this allows us to infer that necrotic cell DNA can be amplified too, considering that an amount of intact nucleic acid chains still present in necrotic masses, unknowing the normal/tumor cell origin. In case microdissection is performed, higher sensitivity is obtained and more chance to detect a tumor specific mutation.
Depending on the method of extraction, hematic areas might be removed. However, they fail to provide normal DNA, because they are anucled cells, but hemoglobin is one of the main polymerase inhibitors in PCR [22]. Regarding the use of clots, a DNA purification method is required to extract hemoglobin. In this sense, specific columns for FFPE tissues are of value. In several cases, Fine Needle Aspiration (FNA) is the first (and often the sole) diagnostic technique, given its low invasiveness, with the clot being all the material available for molecular studies. Here formalin fixation is recommended, and although some reports propose 70% ethanol as an alternative, as above mentioned, DNA antigenicity or integrity may be altered by alcohol-based fixatives [5, 6, 23]. To increase the sensitivity of Sanger sequencing, and to discriminate from technical background, at least 70% of tumor cells are required [5]. The chromatogram obtained failed to discriminate specific signal from background. Such chromatogram type may be determined by pre-analytical conditions (pre-fixing, fixative type or fixation time).
As expected, there was a statistically significant difference between large and small samples DNA concentration. However, no significant differences were observed in concentration, fragments number or tumor initial percentage among different small sample types [18]. We can infer that all these types of tissue samples are similarly useful and depend on interdisciplinary medical team (surgeons, radiologists, clinicians, pathologists and oncologists) [6]. Large samples are blocks from surgical specimens, while small samples could be a core biopsy (yielding tissue samples approximately 1 mm in diameter), biopsies from bronchoscopy, nodal biopsies obtained by mediastinoscopy, and fine needle aspiration resulting in cytological specimens and clots. However, no significant differences were observed in concentration, fragments number or tumor initial percentage among different small sample types. Figure 2 shows that the amount of tissue obtained from small biopsies is often inadequate for a complete evaluation [18].
Performance of IHC and molecular study of large and small biopsies.
Over the last decade, genomic research of various solid tumors has suddenly progressed through the discovery of several molecular biomarkers that eventually impact on the prognosis and treatment of most common cancers. Recent technical innovations, such as “next or second generation” sequencing or “massively parallel” sequencing, have the potential to detect many abnormalities in a single assay, and are probably the solution to tissue shortage [24, 25].
This definitely results into multiple activities for surgeons and pathologists, who must obtain and process samples, write a pathology report, choose the material for molecular biology. In furtherance, those molecular biosciences technicians performing studies must draw up guidelines to standardize these practices, and algorithms to cover cyto- and histopathological diagnoses, IHC and molecular studies [4, 5, 23, 24, 26].
Detection of tumor-derived mutations in FFPE is challenging because the tumor DNA is often scarce, fragmented, at a very low concentration and diluted by the presence of a background of non-mutant DNA (both tumor and non-tumor origin). Once the area of tumor cells is selected to be processed, the method of purification of the macromolecules must be chosen. Although manual non-expensive forms (phenol-chloroform-PK) exist, they fail to provide the necessary amount and quality of DNA. There are affinity columns for DNA, RNA or DNA/RNA together, which can be used on a low scale; and finally automated nucleic acid extraction equipment. Some years ago manual extraction was used for FFPE tissue because the columns were developed only for fresh samples. In the last decade the advent of personalized medicine boosted the development of new methodologies for this purpose. Heydt et al. used FFPE tissue samples for the comparison of five automated DNA extraction systems, the BioRobot M48, the QIAcube and the QIAsymphony SP all from Qiagen (Hilden, Germany), the Maxwell 16 from Promega (Mannheim, Germany) and the InnuPure C16 from Analytik Jena (Jena, Germany). The results revealed that the Maxwell 16 from Promega seems to be the superior system for DNA extraction from FFPE material. This study also evaluated DNA quantification systems using the three most common techniques, UV spectrophotometry, fluorescent dye-based quantification, and quantitative PCR. The comparison of quantification methods showed inter-method variations, but all methods could be used to estimate the right amount for PCR amplification and for massively parallel sequencing. DNA extracts were quantified as follows: NanoDrop 2000c spectrophotometer (Thermo Fisher Scientific), Quant-iT dsDNA HS Assay on the Qubit 2.0 fluorometer (Life Technologies), QuantiFluor dsDNA Sample Kit on the QuantiFluor-ST fluorometer (Promega) and Quant-iT Pico-Green dsDNA reagent (Life Technologies) on the LightCycler 480 Instrument (Roche). No difference was observed in mutation analysis based on the results of the quantification methods. These findings emphasize that it is particularly important to choose the most reliable and constant DNA extraction system, especially when using small biopsies and low elution volumes [27]. Once DNA/RNA has been obtained and quantified, analysis requires highly sensitive and specific assays. Different techniques with their own advantages and disadvantages can be used to identify and monitor mutations.
A real-time PCR or quantitative PCR (qPCR) amplifies, both quantitatively and semi-quantitatively, a targeted DNA molecule during the PCR process. There exist at least two methods for the detection of PCR products: non-specific fluorescent dyes that bind double-stranded DNA molecules by intercalating between the DNA bases. This method is used in qPCR because the fluorescence can be measured at the end of each amplification cycle to determine, either relatively or absolutely, how much DNA has been amplified. The other method is sequence-specific DNA probes consisting of oligonucleotides that are labeled with a f
There is also a revolutionary method that uses PlexZyme™ technology. The revolution in this technology is given by a structure called partzyme (A and B). Each partzyme has 3 different regions: (I) the region that joins the target sequence of DNA, (II) the catalytic constituent region, and (III) the region that joins the probe. Once the primers generate the amplicons, both partzymes join their complementary sequences through the region (I), acquiring a characteristic structure thanks to the region (II) that allows the region (III) to be exposed. The fluorescently labeled reporter probe also binds to the partzymes in the region (III) exposed, and once the active catalytic core is formed, the probe is cleaved, producing a signal that is indicative of successful amplification of the target gene. This technology can produce a robust quintuplex with five target assays into a single reaction tube that contained 10 partzymes (5 A and 5 B), 10 primers (5 forwards and 5 revers), and 5 probes, with a 5 different fluorophores. All consumables required for sample preparation and RT-PCR amplification and detection are provided in a single cartridge loaded into the Idylla™ system. Handling time is less than two minutes per sample, with the liquid-tight, disposable cartridges greatly reducing the risk of contamination (Biocartis NV, Belgium).
In the non-sequencing space, digital PCR (ddPCR), is a highly sensitive and specific technique for the detection of mutations. DNA molecules are split into droplets that form a water oil emulsion. Droplets are like individual test tubes or wells on a plate where a PCR reaction occurs from a DNA template. Each drop is analyzed or read to determine the fraction of positive droplets in the total sample and can accurately and sensitively quantify a mutation. The creation of thousands of drops means that a single sample can generate thousands of data, which are statistically analyzed. For digital PCR the assays are limited to specific single mutations or sets of highly related mutations at the same locus. The analysis of broader genomic regions using ddPCR is not feasible. However, discriminatory multiplex ddPCR assays can be developed, which enable very rapid and cost-effective monitoring for a limited number of mutations in serial plasma samples [28].
Sanger sequencing is a DNA sequencing method based on the selective incorporation of chain-terminating dideoxynucleotides by DNA polymerase during in vitro DNA replication [29, 30]. This method was first developed by Frederick Sanger and colleagues in 1977, and became the most widely used sequencing method for over 40 years. However, the Sanger method remains widely used for smaller-scale projects and for validation of NGS results.
In this decade, the treatment of cancer patients has evolved with the addition of new massive sequencing technologies. This contributed to the study of tumor biology with an accurate and highly covered diagnostic method that allows the selection of those patients likely to benefit most from target-specific targeted therapies. NGS, massively parallel or deep sequencing, refers to a DNA sequencing technology that has revolutionized genomic research. NGS can be used to sequence the whole human genome within a single day. In contrast, the previous Sanger sequencing technology used to decipher the human genome took over a decade to deliver the final draft [31]. Over the last years, massively parallel sequencing has rapidly evolved and has now transitioned into molecular pathology routine laboratories. This is an interesting platform for the simultaneous analysis of multiple genes with low input material. Therefore, laboratories working with FFPE material and high sample throughput largely require high-quality DNA obtained from automated DNA extraction systems. The spectrum of DNA variation in a human genome comprises small base changes (substitutions), insertions and deletions of DNA, large genomic deletions of exons or whole genes and rearrangements, such as inversions and translocations. Traditional Sanger sequencing focuses on the discovery of substitutions and small insertions and deletions.
There are a number of different NGS platforms using different sequencing technologies, but all these platforms sequence millions of small fragments of DNA in parallel. The aim of bioinformatics analyses is to piece together these fragments by mapping the individual reads to the human reference genome (pipelines). Each of the three billion bases in the human genome is sequenced several times, in order to provide accurate data and an insight into unexpected DNA variation. NGS can be used to sequence either whole genomes or specific genomic areas of interest, including all 22,000 coding genes, the whole-genome sequencing (WGS), the whole exome sequencing (WES). This is a genomic technique for sequencing all of the protein-coding regions of genes in a genome, known as the exome; or small numbers of individual genes (NGS panels).
Parallel sequencing requires target enrichment, which is a pre-sequencing step that only allows part of a whole-genome be sequenced, or regions of interest, without sequencing the entire genome of a sample. The two most commonly used techniques for NGS target enrichment are capture hybridization and amplicon-based (multiplex PCR). In capture hybridization, genomic DNA is cut to produce small fragments that join sequencer-specific adaptors and indexes to prepare the library, and then the sample is hybridized with biotinylated RNA library primers. Target regions are extracted with magnetic streptavidin beads, amplified and sequenced. Capture hybridization is a screening method for large genetic panels and a large DNA input (more than 1 ug DNA), with a laborious and complex workflow, but a better performance. In amplicon sequencing, custom oligo capture probes are designed to flank DNA specific regions without fragmenting. Extension/ligation takes place between hybridized probes. Finally, the uniquely labeled amplicon library is ready for cluster generation and sequencing. The extension/ligation occurs between hybrid probes which determines a uniquely tagged amplicon library ready for cluster generation and sequencing. Amplification sequencing is used for small gene panels or somatic mutation hotspots (target from kb to Mb), with lower DNA input (100 ng). It has a simple and fast protocol (combining sample preparation and enrichment in one assay), but it is more liable to false positive and negative calls. Considering the WGS method in the same fresh and FFPE samples, hybrid capture sequencing showed higher sensitivity compared to amplicon sequencing, while maintaining 100% specificity using Sanger sequencing as a validation method. Amplicon method has higher target rates. Hybridization capture-based approaches demonstrated that many of them could be false positives or negatives [32]. These results reveal advantages and disadvantages of both methods. Therefore, a greater number of trials must be undertaken to demonstrate both clinical usefulness and socioeconomic benefits. On occasions, an extremely sensitive method is not worth using given its clinical implications.
The basic premise of cancer genomics is that cancer is caused by somatically acquired mutations, and is therefore a disease of the genome. Capillary-based cancer sequencing has been ongoing for over a decade. However, these investigations were restricted to relatively few samples and small numbers of candidate genes. Tumor heterogeneity and the addition of new molecular targets have become a challenge that needs a multidisciplinary approach and learning, with the study of the molecular profile of the tumor at the genomic (DNA), transcriptomic (RNA) or protein (protein) level. NGS technique is a useful and novel tool for the study of molecular profile from DNA/RNA. To do the library using amplicon methods it is only necessary to obtain 10 ng of DNA just from the tumor, and 10 ng of RNA, which is feasible, even from small samples, fixed in formalin and included in paraffin [31].
Thus, three of the major technical drawbacks of the massive analysis required for the approach of multiple specific biomarkers for the treatment are resolved. These drawbacks include the small size of biopsy sample and material scarcity, paraffin fixation of tissues and its effect on DNA/RNA and the impossibility to collect and store fresh material in standard clinical practice. Therefore, this type of studies is necessary to optimize the quality of patient care, avoiding errors and false positives or negatives. Thus, the use of NGS panels with small and overlapping amplicons would solve all these drawbacks, always associated with a bioinformatics algorithm (pipeline) that allows the overlap of the fragments obtained with a reference sequence.
The prevalence of molecular alterations with targeted treatment may vary according to different variables, such as the region of the world, race and gender [33, 34]. About 86% of tumors have molecular alterations that can potentially be treatable with approved or developing drugs, of which approximately 30% have clinically available drugs. The distribution of these alterations in patients with metastatic disease varies compared to those observed in resected tumors at earlier stages [35].
Different analysis options may be combined according to the molecular target to be identified, the type of molecular alteration and the type of sample required. Regarding the KRAS gene, a GTPase which functions as an upstream regulator of the MAPK and PI3K pathways, it is frequently mutated in various cancer types including pancreatic, colorectal and lung cancers [36].
KRAS was one of the first markers to be used as a therapeutic target in colorectal cancer (CRC) in clinical practice since the approval of cetuximad in the second line in 2008. Both the European Medical Agency (EMEA) and the Food and Drug Administration (FDA) in 2008 approved the use of anti-EGFR monoclonal antibodies in patients with tumors with non-mutated KRAS (KRAS-wt). The selection of patients for anti-EGFR treatment based on the mutational status of codons 12 and 13 of the KRAS gene is highly specific to non-responder patients. At that time, the tissue was not macro-dissected, biopsies containing more than 70% of tumor cells were processed by sequencing for the reasons mentioned above, and approximately 30% of cases could not be evaluated since they failed to meet these criteria. Codon 12 and 13 of exon 2 of the KRAS gene were studied and the type of mutation found was irrelevant. For exon 2, 40% of the CRC patients were mutated and 60% were wt (codon 12 and 13). Results showed that 95% of patients with mutated CRC for KRAS did not benefit from anti-EGFR treatment. However, it was not sensitive enough because only half of patients with KRAS-wt tumors responded to treatment [37]. Then, the 59 and 61 codons of exon 3 and the 117 and 146 codons of exon 4 were eventually added. Automated qPCR methods were developed, which covered these hot-spots and dually reported wt or mutated. Nowadays, these binomial methods (wt/mutated) would not serve to identify the G12C amino acid change (c.34G > T p.Gly12Cys). Target therapies like KRAS G12C covalent inhibitors, such as AMG-510, are currently in early phase clinical trials and show promising results for the treatment of KRAS G12 mutant lung cancer patients. However, KRAS G12C colorectal cancer patients have not shown the same response. KRAS mutation testing was carried out using 13 technologies and assays. Limits of detection (LD) of the 13 methods were showed in the following table. Of 13 assays evaluated in this work, 9 showed relatively similar levels of accuracy and reliability in detecting KRAS mutations at low levels with varying sensitivities (50 copies mutant allele frequency by each technology). The best performances were obtained by three assays: Oncomine Focus Assay, Idylla KRAS Mutation Test and UltraSEEK, with high sensitivity and specificity across the entire cell line panel. The worst performances in detection were Illumina Nextera Rapid Capture Custom Lung Panel and Sanger capillary sequencing [38].
Real-time quantitative PCR | MALDI-TOF | NGS | ddPCR | Sanger | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | |
LD | 5 | 5 | 5 | 10 | 0,1 | 5 | 5 | 5 | 10 | 5 | 5 | 0.001 | 20 |
|
The NGS study may infer biological mechanisms that may explain primary resistance (absence of response to tyrosine kinase inhibitors and disease progression as a better response). This information is required for decision-making of the allelic frequency data for DNA sequence variants, amplified reads for fusions, or the number of copies of amplified genes, since in order to determine that a sequence variant has a clear oncogenic role in the tumor, its representative presence is required. One of the most common false positives with NGS, partly due to its high sensitivity, is the amplification and sequencing of variants from clonal hematopoiesis. Obtaining DNA from FFPE is a methodology used for more than decades, with satisfactory results, since the DNA obtained was degraded by fixation-paraffinization process, as well as its opposite effect which is the deparafinization of tissue. Obtaining RNA from this type of sample is most controversial given its increased lability, and was recently accepted due to the incorporation of new purification strategies. Therefore, obtaining RNA from FFPE was the greatest difficulty of this DNA/RNA NGS method, and required this minimum learning curve to achieve optimal 80% performance (Figure 3). The effectiveness of RNA isolation was calculated, taking into account criterion >5000 reads as evaluable sample, for each run/chip. Increased performance was achieved as the long runs occurred. The initial yield was less than 50%, reaching 80% maximum, because the fixation of the tissue as well as the deparanization process are counterproductive effects for obtaining RNA. Pre-analytical pathological processes for NGS take a crucial role.
RNA performance (1= > 5000 reads, 0 < 5000 reads).
This has been especially relevant in RNA sequencing from paraffin block. A learning curve is required before using this methodology in the clinical field. The acquisition of macromolecules management is critical. On the other hand, multidisciplinary work is crucial for the correct interpretation of the information provided by these new technologies. Crude data alone, without associated bioinformatics information, should not be used for the treatment of patients. The main pitfall of NGS in the clinical setting is the infrastructure, such as computer capacity and storage, and personnel trained in comprehensive analyses and interpretation of the subsequent data. In addition, and in order to obtain clinically relevant information in a clear and robust interface, the volume of data needs to be proficiently managed. However, to make NGS cost effective one would have to run large batches of samples which may require supra-regional centralization. The objective of implementing new technologies is to develop personalized treatment strategies that result in prolongation of survival of patients with a better quality of life.
The analysis of the biology of tumors, using NGS, allows to expand the number of molecular alterations to be studied, and allows to detect more patients who can benefit from targeted treatments, modifying the survival in patients with detected and treated molecular alterations. A continuous and inexorable shift in surgical pathology can be observed, with histological diagnosis being just one of its components. The molecular profile is nowadays an essential tool for anatomic pathology practice, which invariably requires highly trained specialists. The in-depth study of molecular alterations in patients allows optimizing molecular diagnosis and selecting patients to receive novel treatments, targeted against specific molecular targets for the clinical benefit of patients, through a multidisciplinary approach and learning.
The author thanks Dr. Boris Elsner & Dr. Alejandra Avagnina for their mentorship; Dr. Alejo Garcia† for being an excellent scientific partner; and Valeria Melia for proofreading of the manuscript.
The author declares no conflict of interest.
IntechOpen is the first native scientific publisher of Open Access books, with more than 116,000 authors worldwide, ranging from globally-renowned Nobel Prize winners to up-and-coming researchers at the cutting edge of scientific discovery. Established in Europe with the new headquarters based in London, and with plans for international growth, IntechOpen is the leading publisher of Open Access scientific books. The values of our business are based on the same ones that any scientist applies to their research -- we have created a culture of respect, collegiality and collaboration within an atmosphere that’s relaxed, friendly and progressive.
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