Journal List > Lab Med Online > v.12(3) > 1516078810

Applying Functional Assay Evidence to Interpret Sequence Variants Identified in Hereditary Cancer Genes

Abstract

The demand for the interpretation of sequence variants identified by next-generation sequencing is gradually increasing in clinical laboratories. The American College of Medical Genetics and the Association for Molecular Pathology (ACMG/AMP) 2015 guidelines provide a basis for using functional assays as strong evidence for variant classification. However, it is challenging to use the evidence because the protein’s function and the functional assays used to prove it are too diverse. Therefore, this study reviewed various functional assays that can aid in classifying sequence variants in clinical laboratories. This review focuses on the 1) general functional assays associated with basic protein functions and processing and 2) functional assays related to the specific pathogenic mechanisms of four genes (TP53, BRCA1, CDH1, and PTEN) associated with hereditary cancer.

초록

임상검사실에서 차세대염기서열분석 검사로 검출된 염기 변이의 해석에 대한 요구가 점차 증가하고 있다. 2015년 ACMG/AMP 지침에서 기능 연구 결과를 변이 분류의 강력한 근거로 제시하고 있다. 하지만 단백질의 기능과 이를 증명하기 위해 사용되는 기능 연구가 매우 다양하여 해당 근거를 적용하는 데 어려움이 있다. 따라서 본 연구에서는 다양한 기능 연구 결과를 검토하여 임상검사실에서 염기 변이를 분류하는 데 도움을 주고자 하였다. 본 논문에서는 1) 단백질의 기본적인 기능 및 처리와 연관된 일반적 기능 연구 및 2) 유전성 암과 연관된 4개 유전자(TP53, BRCA1, CDH1, PTEN)의 특정 병인 기전과 관련된 기능 연구에 초점을 맞추었다.

INTRODUCTION

The American College of Medical Genetics (ACMG) and the Association for Molecular Pathology (AMP) established standards and guidelines for the interpretation of sequence variants [1]. Criteria for classifying pathogenic or benign variants have been developed. However, some evidence, such as PS3/BS3, is somewhat ambiguous, and many laboratories have difficulty applying the criteria in variant interpretation. According to the ACMG/AMP guideline, PS3 and BS3 are defined by “well-established in vitro or in vivo functional studies supportive of a damaging effect on the gene or gene product” and “well-established in vitro or in vivo functional studies show no damaging effect on protein function or splicing,” respectively [1].
Although functional studies can provide evidence to interpret a variant’s effect on protein function, leading to the reclassification of variants of uncertain significance (VUS), detailed guidance on how functional evidence can be evaluated and applied has not been provided by the original ACMG/AMP guidelines. Brnich et al. [2] published a recommendation for applying the PS3/BS3 criterion to provide a more structured approach for evaluating functional evidence. Furthermore, Kanavy et al. [3] evaluated the comparative analysis of PS3/BS3 of six Variant Curation Expert Panels (CDH1, Hearing Loss, Inherited Cardiomyopathy-MYH7, PAH, PTEN, and RASopathy), and these studies can provide guidance for laboratories regarding the application of PS3/BS3 in variant interpretation.
Nevertheless, clinical laboratory practitioners are often unfamiliar with the various experimental procedures used for functional validation. We selected four genes (TP53, BRCA1, CDH1, and PTEN) associated with hereditary cancer for which PS3/BS3 criteria can often be considered when interpreting variants. We selected these four genes because most of their functional mechanisms did not overlap. In addition, a large number of VUS missense variants with insufficient evidence were observed in these genes despite ClinVar data suggesting the presence of numerous likely patho-genic and pathogenic missense variants. Therefore, in most cases, applying PS3/BS3 can serve as significant evidence to help VUS missense variants be classified as either pathogenic or benign. In this review, we discussed the literature on these genes and the functional assays mainly used to understand functional analysis. In Part I, we describe general assays associated with basic protein functions and processing. The functional assays introduced in Part I are summarized in Table 1. The functional assays related to the specific pathogenic mechanisms of individual genes are described in Part II. Recent ClinGen guidelines for PS3/BS3 interpretation in TP53, CDH1, and PTEN are summarized in Table 2 [4-6].

PART I

1. Gene expression and protein turnover assay

Several conditions must be met to assess the impact of a variant on the function of a gene. First, the protein encoded by the gene must be produced, as stated by the central dogma, and carried to the correct subcellular location. Finally, it must not be degraded before it can perform its function. Researchers carrying out functional studies must ensure that these conditions are met before making any hasty interpretations.
Several experimental methods can be used for that purpose proposed. As the central dogma states, a gene must undergo transcription to produce its corresponding mRNA, which in turn must be translated to generate its corresponding protein. The polymerase chain reaction (PCR) can measure the transcription step of the central dogma, while western blotting can prove translation. The correct subcellular localization can be visualized via immunofluorescence. Flow cytometry can also be used if the target organelle is the plasma membrane. Lastly, double fluorescence can be used to verify whether the protein is ubiquitylated and becomes prone to proteasomal degradation [7].

2. Transactivation assay

In the context of gene regulation, transactivation describes the increased expression of specific target genes through an intermediate transactivator protein binding to a response element (RE) located within the promoter or enhancer region. Therefore, transactivation assays can be used to evaluate transcription factor gene variants. They require REs of target genes upstream of either the target genes themselves or reporter genes, such as the green fluorescence protein (GFP), in addition to the transcription factor gene [8].

3. Cell viability assay

Cell viability assays gauge how well or poorly cells proliferate by measuring an indicator of cell life or death. They can assess the physiological, structural, and functional aspects of cultured cells [9]. Cell life indicators include cell number, ATP content, DNA content, dehydrogenase activity, and membrane integrity. Cell death indicators include caspase activity, chromatin condensation, and phospholipid redistribution. Cell proliferation, colony formation, growth suppression, and apoptosis assays are examples of cell viability assays [10].

4. Binding assay

Binding assays are used to quantify interactions between two molecules, such as small molecule-proteins, protein–protein, and protein–DNA. Examples of binding assays include ATP-binding assays (small molecule-protein) and tetramerization assays (protein–protein) [11].

5. Cell motility assay

Motility is an essential cell feature. Thus, methods to study cell migratory behavior are valuable tools to observe cell characteristics, especially in cancer research, which includes migration and invasion through the extracellular matrix, intravasation into blood circulation, attachment to a distant site, and extravasation to form distant foci [12, 13]. Cell aggregation, cell invasion, and wound closure assays are well-known methods for observing cell motility. Cell aggregation assays have frequently been used to test cells’ E-cadherin-dependent cell-cell adhesions, and assess the functionality of the complex in epithelioid cells [14]. A cell aggregation assay is a useful tool for distinguishing between invasive and noninvasive cell types. Cell invasion assays are different from cell migration assays in the field of experimental biology. Invasion is the movement of a cell through a 3D matrix that modifies the cell shape and interacts with the extracellular matrix [15]. Migration is the directed movement of cells on a 2D surface without an obstructive fiber network [15]. Invasion requires adhesion, proteolysis of extracellular matrix components, and migration [16]. Therefore, cell invasion assays help observe how invasive cells penetrate a barrier in response to chemoattractants or inhibiting compounds. The wound closure assay is the simplest method for determining the migration ability of collective cell migration [17]. In the wound closure assay, the migration of cells was measured as a closed distance over time and compared to a control. Observing single-cell lamellipodium formation, tail retraction, and directional movement may reveal any impaired migratory phenotypes [18].

6. Enzyme activity assay

Enzyme assays for the study of enzyme kinetics and enzyme inhibition help measure enzymatic activity. Assays to measure phosphatase activity are a type of enzyme assay. Phosphatase assays can be employed to study the catalytic activity of PTEN against phospholipid substrates [19].

PART II

We selected four genes causing hereditary cancer syndromes, each with different molecular roles: TP53, a transcription factor, BRCA1, which is involved in gene repair, PTEN, a phosphatase, and CDH1, an anchor protein. Part II reviews the functional assays used to evaluate the missense variants of these genes.

1. TP53

The tumor suppressor gene TP53 encodes a 393 amino-acid-long transcription factor, the cellular tumor antigen p53 (p53) [20]. In response to DNA damage, oncogene activation, or hypoxia, various mechanisms stabilize p53 and ultimately inhibit p53 ubiquitination by Mdm2 [21]. Then, p53 becomes active by forming a homotetramer and transactivates downstream genes involved in apoptosis (BAX, BBC3, NOXA, BID, FAS, and APAF1), cell-cycle arrest (PAK2 and E2F1), and senescence by binding to specific DNA sequences [21, 22]. p53 contains a DNA-binding domain (residues 94–312) and an oligomerization domain (residues 323–356) [23-25]. Functional assays used to evaluate TP53 missense variants set their endpoints on either transactivation (transactivation assay), tetramerization (tetramerization assay), or p53 effector functions (colony formation, apoptosis, and growth suppression assays). The ClinGen TP53 expert panel published guidelines to interpret TP53 variants [4]. According to these guidelines, PS3 should be applied if: a) transactivation assays in yeast [26] demonstrated a low functioning allele (<20% activity), and b) the growth suppression assays [27] showed evidence of a dominant-negative effect and loss of function (LOF) or another assay proved low function. In the following paragraphs, we review the assays mentioned in the guidelines.

1) Transactivation assay

Transactivation assays are used to investigate the effects of variants on the transactivation function of transcription factors. In functional studies that employed transactivation assays, transfected cell-lines were used to evaluate how efficiently TP53 variants transactivate downstream genes. The expression of wild-type and TP53 variants were controlled by the ADH1 promoter, which is a constitutive promoter. Yeast cells and/or mammalian cell-lines (Saos-2 and H1299) have mainly been used [26, 28]. In addition to the human wild-type or mutated TP53 gene, p53 REs of known downstream genes (e.g., CDKN1A and MDM2 promoters, enhancer elements of BAX, GADD45, TP53AIP1, etc.) were inserted into a reporter plasmid. They were positioned upstream of reporter genes, such as GFP and Ds-Red, in yeast cells and luciferase in mammalian cells. The fluorescence intensities of each yeast strain expressing mutant TP53 were compared to those of a yeast strain expressing wild-type TP53 [26]. In studies using mammalian cell-lines, the relative luciferase activity of each strain was calculated [29], and the expression level of downstream gene products was measured directly by western blotting [11, 28]. Another study verified the presence of p53/p53 RE in the MDM2 complex via an electrophoretic mobility shift assay instead of using fluorescent reporter proteins or luciferase assays [8]; it was found that some variants, such as p.Arg175His (NP_000537.3:p.R175H), abolished the transactivation function of all downstream genes regardless of which RE was used, and most variants, such as p.Pro177His (p.P177H) and p.Met243Val (p.M243V), affected the transactivation capacity differently depending on the REs [26].

2) Colony formation assay

The colony formation assay is based on the fact that normal cells are prevented from anchorage-independent growth due to anoikis (a type of apoptosis triggered specifically by a lack of cell anchorage), while transformed cells are capable of proliferating without binding to a substrate. In this assay, cells are grown in a soft agar layer mixed with a cell culture medium resting on another layer containing a higher agar concentration. Studies employing this assay used the p53-null non-small-cell carcinoma cell line, H1299, to determine whether transfection with wild-type or mutant TP53 inhibits colony growth. Non-transfected cell-lines and wild-type TP53-transfected cell-lines served as negative controls. Known pathogenic variants p.Ile254Thr (p.I254T) and p.Arg175His (p.R175H) were used as positive controls. The number of colonies was counted using a dissecting microscope and expressed as a percentage relative to the number of colonies of the p53-null strains [8, 10, 30]. p.Glu180Lys (p.E180K), p.Tyr234Cys (p.Y234C), p.Arg267Gln (p.R267Q), and p.Arg342Pro (p.R342P) produced a similar number of colonies as the positive controls [10].

3) Apoptosis assay

Apoptosis assays are based on the fact that apoptotic cells have reduced DNA content and undergo morphological changes making them distinguishable from viable cells via flow cytometry. In particular, the appearance of phosphatidylserine in the outer plasma membrane of early apoptotic cells due to a loss of plasma membrane asymmetry distinguishes early and late apoptotic cells [31]. In the reviewed study [10], H1299 cells co-transfected with a range of TP53 variants and a GFP-expressing vector were stained with a combination of APC Annexin V and DAPI to assay for viable, early apoptotic, and late apoptotic or necrotic cells. Fluorescence intensities measured by flow cytometry in GFP-negative (non-transfected) versus GFP-positive (transfected) cells were compared [10]. The variant p.Arg342Pro (p.R342P) showed decreased number of apoptotic cells compared to wild-type TP53.

4) Tetramerization assay

A tetramerization assay evaluated missense variants within the oligomerization domain (residues 323–356). As p53 needs to form a homotetramer to function as a transcription factor, pathogenic variants that prevent tetramer formation or promote the formation of heterotetramers with p53 can exert a dominant-negative effect or act as gain-of-function mutations [32, 33]. H1299 and U2OS cell-lines transfected with either wild-type TP53 or oligomerization domain mutants were grown and lysed for tetramerization assays. The lysates were divided into two groups: those treated with the protein crosslinking agent glutaraldehyde and those not treated with glutaraldehyde. Western blotting using the anti-p53 antibody of these lysates showed that p53 of all the strains not treated with glutaraldehyde existed as monomers, whereas glutaraldehyde-treated wild-type and p.Leu330Met (p.L330M) lysates formed a tetramer [11].

5) Growth suppression assay

Growth suppression assays aim to verify whether the mutated tumor suppressor genes confer resistance to small molecules and certain drugs, such as nutlin-3 and etoposide. In one study using such an assay, cell cultures at 50% confluence were transfected with either wild-type TP53 or variant TP53 forms and incubated with hygromycin B, an aminoglycoside antibiotic. The number of colonies were counted after 10 days of selection [34]. Giacomelli et al. [27] used nutlin-3 and etoposide. Nutlins are analogs of cis-imidazoline that disrupt the interaction between p53 and Mdm2 [35]. Thus, treatment with nutlin-3 did not affect p53-null strains but impaired the proliferation of p53-wild-type strains. Interestingly, although expression of the variant p.Pro278Ala (p.P278A) did not affect p53-null cells, it rendered p53-wild-type cells partially nutlin-3 resistant, indicating that this allele interferes with wild-type p53 in a dominant-negative fashion.
Etoposide is a DNA double-strand break-inducing agent that activates p53 and induces apoptosis in mouse thymocytes [36]. However, in other contexts, wild-type p53 allows DNA repair via cell-cycle arrest and prevents cell death from unresolved DNA damage [37]; indeed, the authors found that wild-type p53 expression in p53-null cells prevented cell death upon etoposide treatment, whereas mutant p53 expression had no effect. Variant frequencies were measured after 12 days of incubation, and Z-scores were calculated for each variant. Evidence of a dominant negative effect (DNE) and LOF as defined by the ClinGen expert panel saw Z-scores of ≥0.61 and ≤-0.21 for p53-wild-type nutlin-3 and etoposide, respectively. Evidence of no DNE and no LOF was defined by Z-scores of <0.61 and >-0.21 for p53-wild-type nutlin-3 and etoposide, respectively [4].

2. BRCA1

BRCA1 is a tumor suppressor gene, and mutations in BRCA1 leads to the development of breast, ovarian, prostate, and pancreatic cancers. It encodes a protein of 1,863 amino acids that contains a RING domain at its N-terminus and tandem BRCT domains at its C-terminus [38]. BRCA1 interacts with BARD1 through the RING domain to form a complex that functions as an E3 ubiquitin ligase [39]. It also interacts with the phosphorylated abraxas, CtBP-interacting protein (CtIP), and BRCA1-associated carboxyl-terminal helicase (BACH1) through the BRCT domains to form complexes involved in the homologous recombination-mediated repair of double-strand breaks [40-42]. Although it is well known that BRCA1 functions in homologous recombination repair, it is also involved in cell-cycle checkpoint regulation, DNA replication, chromatin remodeling, transcription, centrosome regulation, and apoptosis [38]. Functional assays used to evaluate BRCA1 missense variants include yeast small colony phenotype assays (SCP assays), protein binding assays, ubiquitin ligase assays, recombination assays, and centrosome amplification assays.

1) SCP assay

The SCP assay is based on the observation that BRCA1 expression in yeast Saccharomyces cerevisiae inhibits its growth [43]. Although there is no yeast BRCA1 homolog, the BRCT domain (1648–1863) is conserved in several yeast proteins, including Rad9 [44]. Rad9 is a checkpoint protein required for yeast cell-cycle arrest and transcriptional induction of DNA repair genes in response to DNA damage [45]. Authors who discovered this growth-suppressive phenotype of human BRCA1 in yeast cells showed that while transfection with vectors containing BRCA1 genes with deleted codons 1–302 and 1–1559 retained the ability to inhibit growth in yeast, BRCA1 genes with deleted codons 1–1650 did not [43]. Therefore, it can be inferred that the SCP assay can evaluate missense variants in the BRCT domain. In another study [46], yeast cells were transfected with either an empty vector, wild-type BRCA1, or BRCA1 variants encompassing various domains, including the BRCT domain. Results showed that transfection of yeast cell with an empty vector and BRCA1 mutations located in the BRCT domain did not inhibit growth, while transfection with wild-type BRCA1 and BRCA1 variants not located within the BRCT domain did [46]. However, this finding was refuted when Millot et al. [47] demonstrated that mutations in the RING domain also restored the yeast proliferation rate. As additional truncation studies reported that expressing the BRCT domains alone was not sufficient to cause small colony formation, the authors argued that both the RING and BRCT domains were important but not essential for eliciting growth defects. Variants that affected SCP and thus, resulted in normal-sized colonies in this study were p.Met1Arg (NP_009225.1:M1R), Met18Thr (p.M18T), p.Glu33Ala (p.E33A), p.Cys39Tyr (p.C39Y), p.Cys44Tyr (p.C44Y), p.Cys47Phe (p.C47F), p.Ala1708Glu (p.A1708E), p.Pro1749Arg (p.P1749R), p.Met1775Arg (p.M1775R), and p.Ser1841Ala (p.S1841A).

2) Protein binding assay

Hetero-dimerization of BRCA1 with BARD1 via its RING domain is crucial for homologous recombination-mediated DNA repair. RING variants that disrupt dimerization result in the loss of tumor suppression [48, 49]. There are several ways to study protein–protein interactions, including co-immunoprecipitation and TAP-tag, protein arrays, mass spectrometry, yeast two-hybrid analysis, and split protein complementation assays [50]. Among these, one study used the latter and the split-GFP reassembly method [51]. Folding-reporter GFP (frGFP) was generated from the 5´ fragment (for residues 1–84) of EGFP and the 3´ fragment (residues 85–238) of GFPuv. These were fused with BARD1 and BRCA1. Plasmids carrying these fusion genes were co-transfected into E. coli using the following combination:pET11-BARD1-NfrGFP/pMRBAD-BRCA1-CfrGFP. Using this model, BRCA1 mutations within the RING domain were evaluated by comparing the fluorescence of strains transfected with RING variants to those transfected with wild-type and negative controls. Among the variants tested, p.Val11Ala (p.V11A) and p.Met18Lys (p.M18K) were completely disrupted, while p.Leu52Phe (p.L52F) showed somewhat reduced reassembly [51].
Another study used yeast two-hybrid analysis, where a yeast transcription factor was split into two fragments instead of a fluorescence protein [52]. In this study, the DNA-binding domain of Gal4 was fused to BRCA1, while the activation domain was fused to BARD1. The study was designed in a manner such that the binding of BRCA1 to BARD1 would transactivate the expression of a selectable reporter gene. Thus, yeast strains transfected with BRCA1 RING variants capable of binding to BARD1 would increase during selection, while those expressing nonfunctional variants would decrease. Their findings showed that the residues responsible for the coordination of the zinc ions were the most sensitive to missense variants, except p.His41 (p.H41) [52].

3) E3 ubiquitin ligase assay

The BRCA1/BARD1 complex functions as an E3 ubiquitin ligase [39]. Therefore, E3 ubiquitin ligase activity may also be a BRCA1 functional assay endpoint. In one study using such a functional assay, a fusion protein of BARD1 (residues 26–126) and BRCA1 (residues 2–304) capable of auto-ubiquitination in vitro was used in a phage display assay [52]. BARD1-BRCA1 fusion proteins with different variants of BRCA1 were expressed at the C-terminus of the bacteriophage T7 coat protein. The multiple phage strains displaying BRCA1 variants were incubated in ubiquitination reactions (containing E1, E2, FLAG-tagged ubiquitin, and ATP). Under such conditions, phages carrying active BRCA1 variants became ubiquitinated and were collected using anti-FLAG beads. After washing, bound phages were eluted by competition with a FLAG polypeptide, re-amplified in E. coli, and used in the subsequent selection round. Phage DNA was extracted and sequenced after five selection rounds. The variant frequency before and after each round was used to calculate the selected versus input phage DNA ratio of each variant, which was then used to obtain the slope of log2 ratios over the five selection rounds [52].

4) Recombination assay

The aforementioned assays can only evaluate missense variants in either the BRCT or RING domains. Thus, assays capable of investigating the pathogenicity of variants located throughout BRCA1 were needed. As mentioned above, BRCA1 plays a crucial role in homologous recombination. Assays developed to observe the impact of BRCA1 variants on homologous recombination in yeast cells have been used in several studies [46, 49, 53, 54]. The diploid RS112 strain used in these studies contains the HIS3 gene separated by the LEU2 marker on the same chromosome and ade2-40 and ade2-101 on two separate homologous chromosomes. Thus, intrachromosomal recombination leads to HIS3 reversion and LEU2 loss, while interchromosomal recombination results in a functional ADE2 gene. The HIS3 and ADE2 genes make it convenient to select recombinant yeast cells; the HIS3 gene enables colonies to grow in a medium lacking histidine, and the ADE2 gene makes colonies white in a medium lacking adenine [55]. Studies using this assay transfected RS112 yeast cells with BRCA1 variants under the galactose-inducible promoter GAL1p. Methyl methanesulfonate (MMS) was added to the galactose medium at different doses to promote homologous recombination [53]. In another study using this assay, the authors discovered that p.Met18Thr (p.M18T), p.Cys24Arg (p.C24R), p.Cys27Ala (p.C27A), p.Thr37Arg (p.T37R), p.Cys39Tyr (p.C39Y), p.His41Arg (p.H41R), p.Cys44Phe (p.C44F), p.Cys47Gly (p.C47G), p.Cys61Gly (p.C61G), and p.Cys64Gly (p.C64G) had deleterious effects [49].

5) Transactivation assay

Although homologous recombination is the main function of BRCA1, it also functions as a transcription factor. Therefore, transactivation assays, which have been used to study TP53 function, have also evaluated BRCA1 variants in numerous studies [56-60]. These studies revealed that p.Leu1407Pro (p.L1407P), p.Thr1685Ile (p.T1685I), p.Ala1708Glu (p.A1708E), p.Ala1752Pro (p.A1752P), p.Met1775Arg (p.M1775R), p.Gly1788Val (p.G1788V), p.Val1809Phe (p.V1809F), and p.Trp1837Arg (p.W1837R) had defective transcriptional transactivation functions.

6) Centrosome amplification assay

In addition to its numerous nuclear functions, BRCA1 also has cytoplasmic roles. Having exactly two centrosomes is crucial for the proper segregation of chromosomes in dividing cells. BRCA1 regulates centrosome amplification through its E3 ubiquitin ligase activity by ubiquitylating gamma-tubulin [7] and a gamma-tubulin adapter protein [61], thus preventing centrosome reduplication during the same cell cycle [62]. Functional studies using centrosome amplification assays used GFP-tagged centrins or anti-pericentrin antibodies to visualize centrosomes. Subsequently, the proportion of cells with abnormal numbers of centrosomes in strains transfected with a range of BRCA1 alleles were counted [63, 64]; it was reported that the p.Met18Thr (p.M18T), p.Cys24Arg (p.C24R), p.Cys27Ala (p.C27A), p.Cys39Tyr (p.C39Y), p.His41Arg (p.H41R), p.Ile42Val (p.I42V), p.Cys44Phe (p.C44F), and p.Cys47Gly (p.C47G) variants had deleterious effects.

3. CDH1

The cadherin 1 (CDH1) gene is a tumor suppressor gene located on chromosome 16q22.1 that transcribes a 120-kDa protein called epithelial cadherin (E-cadherin) [65]. E-cadherin belongs to a family of transmembrane glycoproteins called cadherins, which mediate calcium-dependent cell adhesion to form organized tissues by complexing with another set of cytosolic proteins called catenins [66-68]. E-cadherin is necessary for cell proliferation, cell adhesion, cell polarity, and epithelial-mesenchymal transition [68].
Germline mutations in CDH1 are associated with hereditary diffuse gastric cancer and lobular breast cancer [69, 70]. The risks associated with CDH1 mutations are reportedly >70% for gastric cancer and up to 40% for lobular breast cancer in women [71]. More than 150 CDH1 mutations have been identified, approximately 80% of which are truncating, and the remaining 20% are missense mutations [72, 73].
LOF through CDH1 mutation inactivation or promoter methylation disrupts the cadherin-catenin complex and results in cell adhesion loss, causing increased cell motility, uncontrollable cell growth and division, and metastatic ability of the tumor [65, 74-79]. The pathogenic role of non-truncating mutations in the CDH1 gene has not yet been established. Thus, functional studies using cell aggregation, cell invasion, and wound closure assays have been performed.

1) Aggregation/Invasion assay

Cell aggregation depends on cell-cell adhesion, and the cadherin-catenin complex is necessary between epithelial cells [14, 80]. Downregulation of the complex is often observed in tumor cells during tumor progression. It is associated with high tumor infiltrative and metastatic abilities due to cell adhesion loss and increased cell motility [81-83]. Aggregation and collagen invasion assays can be used to evaluate CDH1 mutation effects on the function of E-cadherin, which promotes homotypic cell-cell adhesion and suppresses cell invasion.
Chinese hamster ovary (CHO) cells are often utilized because they do not express CDH1 [84]. According to Suriano et al. [84] CHO cells transfected with the wild-type CDH1 construct displayed cell-to-cell aggregation in an aggregation assay. CHO cells expressing CDH1 mutations, such as NP_004351.1:p.Ala634Val (p.A634V) or p.Thr340Ala (p.T340A) failed to aggregate. Corso et al. [85] evaluated the p.Arg224Cys (p.R224C) missense mutation as non-pathogenic using an aggregation assay, resulting in the ability to form a compact aggregate of CHO cells. Brooks-Wilson et al. [86] tested three missense mutations, p.Trp409Arg (p.W409R), p.Arg732Gln (p.R732Q), and p.Ala298Thr (p.A298T), using both aggregation and collagen invasion assays. The smaller particle diameter measurements after incubation and higher invasion index percentages compared to a wild-type support that all three mutants were pathogenic.

2) Wound closure assay

A wound closure assay, also called wound healing assay, is a simple method to test cell motility. Removing the cells from an area through mechanical, thermal, or chemical damage creates a cell-free area in a confluent monolayer [87]. This assay is usually performed under conditions of suppressed cell proliferation. Introducing a cell-free area next to the cell monolayer induces cell migration into the gap. Suriano et al. [88] used an in vitro wound closure assay to test p.Ala617Thr (p.A617T), p.Thr340Ala (p.T340A), p.Ala634Val (p.A634V), and p.Val832Met (p.V832M) mutations compared to wild-type and mock cells. According to the results, p.Ala617Thr (p.A617T) and wild-type cells showed similar cell motility. p.Thr340Ala (p.T340A) and p.Ala634Val (p.A634V) showed high cell motility. p.Val832Met (p.V832M) and mock cells showed very low cell motility, failing to migrate unidirectionally due to low polarization. However, these results caused the destabilization of the E-cadherin adhesion complex, implying that motile capability is neither necessary nor sufficient for cells to invade.

4. PTEN

The phosphatase and TENsin homolog (PTEN) deleted on chromosome 10 is a classical tumor suppressor gene located on chromosome 10q23.31. This gene encodes a 403-amino acid multifunctional protein that retains lipid and protein phosphatase activity [89]. The lipid phosphatase activity of PTEN downregulates AKT phosphorylation, which increases p27 expression. Protein phosphatase activity downregulates MAPK phosphorylation, decreasing cyclin D1 expression levels [90, 91]. PTEN is primarily localized to the cytoplasm and/or membrane-bound nucleus [92].
The PTEN gene is a well-known negative regulator of the phosphatidylinositol 3 kinase (PI3K)/AKT pathway in the cytoplasm. PTEN dephosphorylates phosphatidylinositol (3,4,5)-trisphosphate (PIP3) to phosphatidylinositol 4,5-biphosphate (PIP2) to prevent unchecked cell survival and proliferation by hampering all AKT/mTOR axis-controlled downstream functions [93-95]. In addition, PTEN protein phosphatase activity resists the action of focal adhesion kinase and Shc to modulate complex pathways affecting cell migration [94, 96]. In the nucleus, PTEN downregulates MAPK phosphorylation and cyclin D1 to arrest cell-cycle progression [91].
Furthermore, PTEN germline mutations are often observed in PTEN hamartoma tumor syndromes, such as Cowden syndrome, Lhermitte-Duclos disease, Bannayan–Riley–Ruvalcaba syndrome, and Proteus syndrome in autosomal dominant inheritance patterns. Although they are different disease entities, they commonly have hamartomatous tumors [97, 98]. In contrast to classical tumor suppressor models, which require complete inactivation to induce cancer, the haploinsufficiency of PTEN is enough for tumor growth [99, 100]. More than half of PTEN mutations are truncating, and approximately 35% are missense mutations [101].

1) Phosphatase activity

Most missense mutations are clustered around the phosphatase domain. Therefore, an assay to measure phosphatase activity is useful for the functional analysis of PTEN. Han et al. [101] tested 42 missense mutations using a phosphatase assay. Of the 42 mutations, 38 showed eliminated or reduced phosphatase activity. Mighell et al. [102] evaluated the effects of PTEN mutations on lipid phosphatase activity. Among the 7,244 single amino acid PTEN variants tested, 2,273, including 1,789 missense mutations, showed reduced lipid phosphatase activity. Although genotype-phenotype matching should be further discussed, no alteration or loss of phosphatase activity observed in the phosphatase assay can serve as evidence for BS3 or PS3.

2) PTEN/pAKT expression level

PTEN dephosphorylates PIP3, preventing the downstream pathway of AKT phosphorylation. Therefore, cells with PTEN mutations demonstrate elevated levels of PIP3 and phosphorylated AKT (pAKT) [103]. pAKT levels can be affected by PTEN phosphatase activity. Thus, decreased PTEN expression levels have also been correlated with pathogenic PTEN variants [104]. Spinelli et al. [105] mea sured PTEN and pAKT expression levels from seven PTEN mutations identified in autism and five mutations in PTEN hamartoma tumor syndrome. PTEN and pAKT expression levels were investigated by immunoblotting with total cell lysates. The results showed that all five mutations in PTEN hamartoma tumor syndrome appeared to inhibit AKT signaling directly, but seven PTEN mutants in autism retained the ability to suppress cellular AKT signaling.

CONCLUSION

This study is intended to help clinical laboratories apply functional evidence criteria when interpreting the sequence variants found in clinical genetic testing. For this purpose, four cancer susceptibility genes with different mechanisms of action (TP53, BRCA1, CDH1, and PTEN) were chosen to include as many functional assays as possible. Then, various experimental designs that used the same or similar functional assays were introduced. In Table 3, we added the literature referenced in Part II and the literature that used the functional assays presented in this review but not referenced in Part II. Future studies are required for the genes and diseases not covered in this review.

Acknowledgements

This study was supported by the Research Fund of the Quality Control Committee of the Korean Society for Laboratory Medicine (KSLM Research Project 2021-05-012).

Notes

Conflicts of Interest

None declared.

REFERENCES

1. Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, et al. 2015; Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med. 17:405–24. DOI: 10.1038/gim.2015.30. PMID: 25741868. PMCID: PMC4544753.
crossref
2. Brnich SE, Abou Tayoun AN, Couch FJ, Cutting GR, Greenblatt MS, Heinen CD, et al. 2019; Recommendations for application of the functional evidence PS3/BS3 criterion using the ACMG/AMP sequence variant interpretation framework. Genome Med. 12:3. DOI: 10.1186/s13073-019-0690-2. PMID: 31892348. PMCID: PMC6938631.
crossref
3. Kanavy DM, McNulty SM, Jairath MK, Brnich SE, Bizon C, Powell BC, et al. 2019; Comparative analysis of functional assay evidence use by ClinGen Variant Curation Expert Panels. Genome Med. 11:77. DOI: 10.1186/s13073-019-0683-1. PMID: 31783775. PMCID: PMC6884856.
crossref
4. Fortuno C, Lee K, Olivier M, Pesaran T, Mai PL, de Andrade KC, et al. 2021; Specifications of the ACMG/AMP variant interpretation guidelines for germline TP53 variants. Hum Mutat. 42:223–36. DOI: 10.1002/humu.24152. PMID: 33300245. PMCID: PMC8374922.
5. Lee K, Krempely K, Roberts ME, Anderson MJ, Carneiro F, Chao E, et al. 2018; Specifications of the ACMG/AMP variant curation guidelines for the analysis of germline CDH1 sequence variants. Hum Mutat. 39:1553–68. DOI: 10.1002/humu.23650. PMID: 30311375. PMCID: PMC6188664.
6. Mester JL, Ghosh R, Pesaran T, Huether R, Karam R, Hruska KS, et al. 2018; Gene-specific criteria for PTEN variant curation: Recommendations from the ClinGen PTEN Expert Panel. Hum Mutat. 39:1581–92. DOI: 10.1002/humu.23636. PMID: 30311380. PMCID: PMC6329583.
7. Starita LM, Machida Y, Sankaran S, Elias JE, Griffin K, Schlegel BP, et al. 2004; BRCA1-dependent ubiquitination of gamma-tubulin regulates centrosome number. Mol Cell Biol. 24:8457–66. DOI: 10.1128/MCB.24.19.8457-8466.2004. PMID: 15367667. PMCID: PMC516733.
crossref
8. Ko JL, Chiao MC, Chang SL, Lin P, Lin JC, Sheu GT, et al. 2002; A novel p53 mutant retained functional activity in lung carcinomas. DNA Repair (Amst). 1:755–62. DOI: 10.1016/S1568-7864(02)00094-0.
9. Gilbert DF, Friedrich O. 2017. Cell viability assays. Springer;New York, NY: DOI: 10.1007/978-1-4939-6960-9.
10. Doffe F, Carbonnier V, Tissier M, Leroy B, Martins I, Mattsson JSM, et al. 2021; Identification and functional characterization of new missense SNPs in the coding region of the TP53 gene. Cell Death Differ. 28:1477–92. DOI: 10.1038/s41418-020-00672-0. PMID: 33257846. PMCID: PMC8166836.
crossref
11. Lang V, Pallara C, Zabala A, Lobato-Gil S, Lopitz-Otsoa F, Farrás R, et al. 2014; Tetramerization-defects of p53 result in aberrant ubiquitylation and transcriptional activity. Mol Oncol. 8:1026–42. DOI: 10.1016/j.molonc.2014.04.002. PMID: 24816189. PMCID: PMC5528522.
crossref
12. Fidler IJ. 2002; Critical determinants of metastasis. Semin Cancer Biol. 12:89–96. DOI: 10.1006/scbi.2001.0416. PMID: 12027580.
crossref
13. Steeg PS. 2006; Tumor metastasis: mechanistic insights and clinical challenges. Nat Med. 12:895–904. DOI: 10.1038/nm1469. PMID: 16892035.
crossref
14. Debruyne D, Boterberg T, Bracke ME. 2014; Cell aggregation assays. Methods Mol Biol. 1070:77–92. DOI: 10.1007/978-1-4614-8244-4_6. PMID: 24092433.
crossref
15. Kramer N, Walzl A, Unger C, Rosner M, Krupitza G, Hengstschläger M, et al. 2013; In vitro cell migration and invasion assays. Mutat Res. 752:10–24. DOI: 10.1016/j.mrrev.2012.08.001. PMID: 22940039.
crossref
16. Friedl P, Wolf K. 2010; Plasticity of cell migration: a multiscale tuning model. J Cell Biol. 188:11–9. DOI: 10.1083/jcb.200909003. PMID: 19951899. PMCID: PMC2812848.
crossref
17. Justus CR, Leffler N, Ruiz-Echevarria M, Yang LV. 2014; In vitro cell migration and invasion assays. J Vis Exp. 51046. DOI: 10.3791/51046. PMID: 24962652. PMCID: PMC4186330.
18. Zhang Y, Feng Y, Justus CR, Jiang W, Li Z, Lu JQ, et al. 2012; Comparative study of 3D morphology and functions on genetically engineered mouse melanoma cells. Integr Biol (Camb). 4:1428–36. DOI: 10.1039/c2ib20153d. PMID: 23064132.
crossref
19. Spinelli L, Leslie NR. 2016; Assays to measure PTEN lipid phosphatase activity in vitro from purified enzyme or immunoprecipitates. Methods Mol Biol. 1447:95–105. DOI: 10.1007/978-1-4939-3746-2_6. PMID: 27514802.
crossref
20. el-Deiry WS, Kern SE, Pietenpol JA, Kinzler KW, Vogelstein B. 1992; Definition of a consensus binding site for p53. Nat Genet. 1:45–9. DOI: 10.1038/ng0492-45. PMID: 1301998.
crossref
21. Zilfou JT, Lowe SW. 2009; Tumor suppressive functions of p53. Cold Spring Harb Perspect Biol. 1:a001883. DOI: 10.1101/cshperspect.a001883. PMID: 20066118. PMCID: PMC2773645.
crossref
22. Riley T, Sontag E, Chen P, Levine A. 2008; Transcriptional control of human p53-regulated genes. Nat Rev Mol Cell Biol. 9:402–12. DOI: 10.1038/nrm2395. PMID: 18431400.
crossref
23. Cho Y, Gorina S, Jeffrey PD, Pavletich NP. 1994; Crystal structure of a p53 tumor suppressor-DNA complex: understanding tumorigenic mutations. Science. 265:346–55. DOI: 10.1126/science.8023157. PMID: 8023157.
crossref
24. Clore GM, Omichinski JG, Sakaguchi K, Zambrano N, Sakamoto H, Appella E, et al. 1994; High-resolution structure of the oligomerization domain of p53 by multidimensional NMR. Science. 265:386–91. DOI: 10.1126/science.8023159. PMID: 8023159.
crossref
25. Jeffrey PD, Gorina S, Pavletich NP. 1995; Crystal structure of the tetramerization domain of the p53 tumor suppressor at 1.7 angstroms. Science. 267:1498–502. DOI: 10.1126/science.7878469. PMID: 7878469.
crossref
26. Kato S, Han SY, Liu W, Otsuka K, Shibata H, Kanamaru R, et al. 2003; Understanding the function-structure and function-mutation relationships of p53 tumor suppressor protein by high-resolution missense mutation analysis. Proc Natl Acad Sci U S A. 100:8424–9. DOI: 10.1073/pnas.1431692100. PMID: 12826609. PMCID: PMC166245.
crossref
27. Giacomelli AO, Yang X, Lintner RE, McFarland JM, Duby M, Kim J, et al. 2018; Mutational processes shape the landscape of TP53 mutations in human cancer. Nat Genet. 50:1381–7. DOI: 10.1038/s41588-018-0204-y. PMID: 30224644. PMCID: PMC6168352.
crossref
28. Kharaziha P, Ceder S, Axell O, Krall M, Fotouhi O, Böhm S, et al. 2019; Functional characterization of novel germline TP53 variants in Swedish families. Clin Genet. 96:216–25. DOI: 10.1111/cge.13564. PMID: 31081129.
crossref
29. Yamada H, Shinmura K, Okudela K, Goto M, Suzuki M, Kuriki K, et al. 2007; Identification and characterization of a novel germ line p53 mutation in familial gastric cancer in the Japanese population. Carcinogenesis. 28:2013–8. DOI: 10.1093/carcin/bgm175. PMID: 17690113.
crossref
30. Li J, Yang L, Gaur S, Zhang K, Wu X, Yuan YC, et al. 2014; Mutants TP53 p.R273H and p.R273C but not p.R273G enhance cancer cell malignancy. Hum Mutat. 35:575–84. DOI: 10.1002/humu.22528. PMID: 24677579.
crossref
31. van Engeland M, Nieland LJ, Ramaekers FC, Schutte B, Reutelingsper-ger CP. 1998; Annexin V-affinity assay: a review on an apoptosis detection system based on phosphatidylserine exposure. Cytometry. 31:1–9. DOI: 10.1002/(SICI)1097-0320(19980101)31:1<1::AID-CYTO1>3.0.CO;2-R.
crossref
32. Willis A, Jung EJ, Wakefield T, Chen X. 2004; Mutant p53 exerts a dominant negative effect by preventing wild-type p53 from binding to the promoter of its target genes. Oncogene. 23:2330–8. DOI: 10.1038/sj.onc.1207396. PMID: 14743206.
crossref
33. Brosh R, Rotter V. 2009; When mutants gain new powers: news from the mutant p53 field. Nat Rev Cancer. 9:701–13. DOI: 10.1038/nrc2693. PMID: 19693097.
crossref
34. Pietenpol JA, Tokino T, Thiagalingam S, el-Deiry WS, Kinzler KW, Vogelstein B. 1994; Sequence-specific transcriptional activation is essential for growth suppression by p53. Proc Natl Acad Sci U S A. 91:1998–2002. DOI: 10.1073/pnas.91.6.1998. PMID: 8134338. PMCID: PMC43296.
crossref
35. Vassilev LT, Vu BT, Graves B, Carvajal D, Podlaski F, Filipovic Z, et al. 2004; In vivo activation of the p53 pathway by small-molecule antagonists of MDM2. Science. 303:844–8. DOI: 10.1126/science.1092472. PMID: 14704432.
crossref
36. Clarke AR, Purdie CA, Harrison DJ, Morris RG, Bird CC, Hooper ML, et al. 1993; Thymocyte apoptosis induced by p53-dependent and independent pathways. Nature. 362:849–52. DOI: 10.1038/362849a0. PMID: 8479523.
crossref
37. Lukin DJ, Carvajal LA, Liu WJ, Resnick-Silverman L, Manfredi JJ. 2015; p53 Promotes cell survival due to the reversibility of its cell-cycle checkpoints. Mol Cancer Res. 13:16–28. DOI: 10.1158/1541-7786.MCR-14-0177. PMID: 25158956. PMCID: PMC4312522.
crossref
38. Takaoka M, Miki Y. 2018; BRCA1 gene: function and deficiency. Int J Clin Oncol. 23:36–44. DOI: 10.1007/s10147-017-1182-2. PMID: 28884397.
39. Hashizume R, Fukuda M, Maeda I, Nishikawa H, Oyake D, Yabuki Y, et al. 2001; The RING heterodimer BRCA1-BARD1 is a ubiquitin ligase inactivated by a breast cancer-derived mutation. J Biol Chem. 276:14537–40. DOI: 10.1074/jbc.C000881200. PMID: 11278247.
crossref
40. Wang B, Matsuoka S, Ballif BA, Zhang D, Smogorzewska A, Gygi SP, et al. 2007; Abraxas and RAP80 form a BRCA1 protein complex required for the DNA damage response. Science. 316:1194–8. DOI: 10.1126/science.1139476. PMID: 17525340. PMCID: PMC3573690.
crossref
41. Yu X, Wu LC, Bowcock AM, Aronheim A, Baer R. 1998; The C-terminal (BRCT) domains of BRCA1 interact in vivo with CtIP, a protein implicated in the CtBP pathway of transcriptional repression. J Biol Chem. 273:25388–92. DOI: 10.1074/jbc.273.39.25388. PMID: 9738006.
42. Cantor SB, Bell DW, Ganesan S, Kass EM, Drapkin R, Grossman S, et al. 2001; BACH1, a novel helicase-like protein, interacts directly with BRCA1 and contributes to its DNA repair function. Cell. 105:149–60. DOI: 10.1016/S0092-8674(01)00304-X.
crossref
43. Humphrey JS, Salim A, Erdos MR, Collins FS, Brody LC, Klausner RD. 1997; Human BRCA1 inhibits growth in yeast: potential use in diagnostic testing. Proc Natl Acad Sci U S A. 94:5820–5. DOI: 10.1073/pnas.94.11.5820. PMID: 9159158. PMCID: PMC20864.
44. Bork P, Hofmann K, Bucher P, Neuwald AF, Altschul SF, Koonin EV. 1997; A superfamily of conserved domains in DNA damage-responsive cell cycle checkpoint proteins. FASEB J. 11:68–76. DOI: 10.1096/fasebj.11.1.9034168. PMID: 9034168.
crossref
45. Elledge SJ. 1996; Cell cycle checkpoints: preventing an identity crisis. Science. 274:1664–72. DOI: 10.1126/science.274.5293.1664. PMID: 8939848.
crossref
46. Caligo MA, Bonatti F, Guidugli L, Aretini P, Galli A. 2009; A yeast recombination assay to characterize human BRCA1 missense variants of unknown pathological significance. Hum Mutat. 30:123–33. DOI: 10.1002/humu.20817. PMID: 18680205.
47. Millot GA, Berger A, Lejour V, Boulé JB, Bobo C, Cullin C, et al. 2011; Assessment of human Nter and Cter BRCA1 mutations using growth and localization assays in yeast. Hum Mutat. 32:1470–80. DOI: 10.1002/humu.21608. PMID: 21922593.
48. Drost R, Bouwman P, Rottenberg S, Boon U, Schut E, Klarenbeek S, et al. 2011; BRCA1 RING function is essential for tumor suppression but dispensable for therapy resistance. Cancer Cell. 20:797–809. DOI: 10.1016/j.ccr.2011.11.014. PMID: 22172724.
crossref
49. Ransburgh DJ, Chiba N, Ishioka C, Toland AE, Parvin JD. 2010; Identification of breast tumor mutations in BRCA1 that abolish its function in homologous DNA recombination. Cancer Res. 70:988–95. DOI: 10.1158/0008-5472.CAN-09-2850. PMID: 20103620. PMCID: PMC2943742.
50. Stynen B, Tournu H, Tavernier J, Van Dijck P. 2012; Diversity in genetic in vivo methods for protein-protein interaction studies: from the yeast two-hybrid system to the mammalian split-luciferase system. Microbiol Mol Biol Rev. 76:331–82. DOI: 10.1128/MMBR.05021-11. PMID: 22688816. PMCID: PMC3372256.
crossref
51. Sarkar M, Magliery TJ. 2008; Re-engineering a split-GFP reassembly screen to examine RING-domain interactions between BARD1 and BRCA1 mutants observed in cancer patients. Mol Biosyst. 4:599–605. DOI: 10.1039/b802481b. PMID: 18493658.
crossref
52. Starita LM, Young DL, Islam M, Kitzman JO, Gullingsrud J, Hause RJ, et al. 2015; Massively parallel functional analysis of BRCA1 RING domain variants. Genetics. 200:413–22. DOI: 10.1534/genetics.115.175802. PMID: 25823446. PMCID: PMC4492368.
crossref
53. Lodovichi S, Vitello M, Cervelli T, Galli A. 2016; Expression of cancer related BRCA1 missense variants decreases MMS-induced recombination in Saccharomyces cerevisiae without altering its nuclear localization. Cell Cycle. 15:2723–31. DOI: 10.1080/15384101.2016.1215389. PMID: 27484786. PMCID: PMC5053555.
crossref
54. Coupier I, Baldeyron C, Rousseau A, Mosseri V, Pages-Berhouet S, Caux-Moncoutier V, et al. 2004; Fidelity of DNA double-strand break repair in heterozygous cell lines harbouring BRCA1 missense mutations. Oncogene. 23:914–9. DOI: 10.1038/sj.onc.1207191. PMID: 14647443.
crossref
55. Cervelli T, Lodovichi S, Bellè F, Galli A. 2020; Yeast-based assays for the functional characterization of cancer-associated variants of human DNA repair genes. Microb Cell. 7:162–74. DOI: 10.15698/mic2020.07.721. PMID: 32656256. PMCID: PMC7328678.
crossref
56. Phelan CM, Dapic V, Tice B, Favis R, Kwan E, Barany F, et al. 2005; Classification of BRCA1 missense variants of unknown clinical significance. J Med Genet. 42:138–46. DOI: 10.1136/jmg.2004.024711. PMID: 15689452. PMCID: PMC1735988.
57. Hayes F, Cayanan C, Barillà D, Monteiro AN. 2000; Functional assay for BRCA1: mutagenesis of the COOH-terminal region reveals critical residues for transcription activation. Cancer Res. 60:2411–8.
58. Di Cecco L, Melissari E, Mariotti V, Iofrida C, Galli A, Guidugli L, et al. 2009; Characterisation of gene expression profiles of yeast cells expressing BRCA1 missense variants. Eur J Cancer. 45:2187–96. DOI: 10.1016/j.ejca.2009.04.025. PMID: 19493677.
59. Monteiro AN, August A, Hanafusa H. 1996; Evidence for a transcriptional activation function of BRCA1 C-terminal region. Proc Natl Acad Sci U S A. 93:13595–9. DOI: 10.1073/pnas.93.24.13595. PMID: 8942979. PMCID: PMC19361.
60. Ostrow KL, McGuire V, Whittemore AS, DiCioccio RA. 2004; The effects of BRCA1 missense variants V1804D and M1628T on transcriptional activity. Cancer Genet Cytogenet. 153:177–80. DOI: 10.1016/j.cancergencyto.2004.01.020. PMID: 15350310.
61. Sankaran S, Crone DE, Palazzo RE, Parvin JD. 2007; BRCA1 regulates gamma-tubulin binding to centrosomes. Cancer Biol Ther. 6:1853–7. DOI: 10.4161/cbt.6.12.5164. PMID: 18087219. PMCID: PMC2643382.
62. Kais Z, Parvin JD. 2008; Regulation of centrosomes by the BRCA1-dependent ubiquitin ligase. Cancer Biol Ther. 7:1540–3. DOI: 10.4161/cbt.7.10.7053. PMID: 18927495. PMCID: PMC2628548.
crossref
63. Lovelock PK, Healey S, Au W, Sum EY, Tesoriero A, Wong EM, et al. 2006; Genetic, functional, and histopathological evaluation of two C-terminal BRCA1 missense variants. J Med Genet. 43:74–83. DOI: 10.1136/jmg.2005.033258. PMID: 15923272. PMCID: PMC2564506.
crossref
64. Kais Z, Chiba N, Ishioka C, Parvin JD. 2012; Functional differences among BRCA1 missense mutations in the control of centrosome duplication. Oncogene. 31:799–804. DOI: 10.1038/onc.2011.271. PMID: 21725363. PMCID: PMC4222025.
crossref
65. Norton JA, Ham CM, Van Dam J, Jeffrey RB, Longacre TA, Huntsman DG, et al. 2007; CDH1 truncating mutations in the E-cadherin gene: an indication for total gastrectomy to treat hereditary diffuse gastric cancer. Ann Surg. 245:873–9. DOI: 10.1097/01.sla.0000254370.29893.e4. PMID: 17522512. PMCID: PMC1876967.
66. Shore EM, Nelson WJ. 1991; Biosynthesis of the cell adhesion molecule uvomorulin (E-cadherin) in Madin-Darby canine kidney epithelial cells. J Biol Chem. 266:19672–80. DOI: 10.1016/S0021-9258(18)55045-6.
crossref
67. van Roy F, Berx G. 2008; The cell-cell adhesion molecule E-cadherin. Cell Mol Life Sci. 65:3756–88. DOI: 10.1007/s00018-008-8281-1. PMID: 18726070.
crossref
68. Shenoy S. 2019; CDH1 (E-cadherin) mutation and gastric cancer: genetics, molecular mechanisms and guidelines for management. Cancer Manag Res. 11:10477–86. DOI: 10.2147/CMAR.S208818. PMID: 31853199. PMCID: PMC6916690.
69. Guilford P, Hopkins J, Harraway J, McLeod M, McLeod N, Harawira P, et al. 1998; E-cadherin germline mutations in familial gastric cancer. Nature. 392:402–5. DOI: 10.1038/32918. PMID: 9537325.
crossref
70. Corso G, Intra M, Trentin C, Veronesi P, Galimberti V. 2016; CDH1 germline mutations and hereditary lobular breast cancer. Fam Cancer. 15:215–9. DOI: 10.1007/s10689-016-9869-5. PMID: 26759166.
71. Pharoah PD, Guilford P, Caldas C. 2001; Incidence of gastric cancer and breast cancer in CDH1 (E-cadherin) mutation carriers from hereditary diffuse gastric cancer families. Gastroenterology. 121:1348–53. DOI: 10.1053/gast.2001.29611. PMID: 11729114.
crossref
72. Barber M, Murrell A, Ito Y, Maia AT, Hyland S, Oliveira C, et al. 2008; Mechanisms and sequelae of E-cadherin silencing in hereditary diffuse gastric cancer. J Pathol. 216:295–306. DOI: 10.1002/path.2426. PMID: 18788075.
crossref
73. Melo S, Figueiredo J, Fernandes MS, Gonçalves M, Morais-de-Sá E, Sanches JM, et al. 2017; Predicting the functional impact of CDH1 missense mutations in hereditary diffuse gastric cancer. Int J Mol Sci. 18:2687. DOI: 10.3390/ijms18122687. PMID: 29231860. PMCID: PMC5751289.
crossref
74. Gottardi CJ, Wong E, Gumbiner BM. 2001; E-cadherin suppresses cellular transformation by inhibiting beta-catenin signaling in an adhesion-independent manner. J Cell Biol. 153:1049–60. DOI: 10.1083/jcb.153.5.1049. PMID: 11381089. PMCID: PMC2174337.
75. Jeanes A, Gottardi CJ, Yap AS. 2008; Cadherins and cancer: how does cadherin dysfunction promote tumor progression? Oncogene. 27:6920–9. DOI: 10.1038/onc.2008.343. PMID: 19029934. PMCID: PMC2745643.
crossref
76. Bruner HC, Derksen PWB. 2018; Loss of E-cadherin-dependent cell-cell adhesion and the development and progression of cancer. Cold Spring Harb Perspect Biol. 10:a029330. DOI: 10.1101/cshperspect.a029330. PMID: 28507022. PMCID: PMC5830899.
crossref
77. Onder TT, Gupta PB, Mani SA, Yang J, Lander ES, Weinberg RA. 2008; Loss of E-cadherin promotes metastasis via multiple downstream transcriptional pathways. Cancer Res. 68:3645–54. DOI: 10.1158/0008-5472.CAN-07-2938. PMID: 18483246.
crossref
78. Yang J, Weinberg RA. 2008; Epithelial-mesenchymal transition: at the crossroads of development and tumor metastasis. Dev Cell. 14:818–29. DOI: 10.1016/j.devcel.2008.05.009. PMID: 18539112.
crossref
79. Berx G, van Roy F. 2009; Involvement of members of the cadherin superfamily in cancer. Cold Spring Harb Perspect Biol. 1:a003129. DOI: 10.1101/cshperspect.a003129. PMID: 20457567. PMCID: PMC2882122.
crossref
80. Saias L, Gomes A, Cazales M, Ducommun B, Lobjois V. 2015; Cell-cell adhesion and cytoskeleton tension oppose each other in regulating tumor cell aggregation. Cancer Res. 75:2426–33. DOI: 10.1158/0008-5472.CAN-14-3534. PMID: 25855380.
crossref
81. Ozawa M, Ringwald M, Kemler R. 1990; Uvomorulin-catenin complex formation is regulated by a specific domain in the cytoplasmic region of the cell adhesion molecule. Proc Natl Acad Sci U S A. 87:4246–50. DOI: 10.1073/pnas.87.11.4246. PMID: 2349235. PMCID: PMC54085.
crossref
82. Takeichi M. 1993; Cadherins in cancer: implications for invasion and metastasis. Curr Opin Cell Biol. 5:806–11. DOI: 10.1016/0955-0674(93)90029-P.
crossref
83. Christofori G, Semb H. 1999; The role of the cell-adhesion molecule E-cadherin as a tumour-suppressor gene. Trends Biochem Sci. 24:73–6. DOI: 10.1016/S0968-0004(98)01343-7.
crossref
84. Suriano G, Oliveira C, Ferreira P, Machado JC, Bordin MC, De Wever O, et al. 2003; Identification of CDH1 germline missense mutations associated with functional inactivation of the E-cadherin protein in young gastric cancer probands. Hum Mol Genet. 12:575–82. DOI: 10.1093/hmg/ddg048. PMID: 12588804.
85. Corso G, Pedrazzani C, Pinheiro H, Fernandes E, Marrelli D, Rinnovati A, et al. 2011; E-cadherin genetic screening and clinico-pathologic characteristics of early onset gastric cancer. Eur J Cancer. 47:631–9. DOI: 10.1016/j.ejca.2010.10.011. PMID: 21106365.
crossref
86. Brooks-Wilson AR, Kaurah P, Suriano G, Leach S, Senz J, Grehan N, et al. 2004; Germline E-cadherin mutations in hereditary diffuse gastric cancer: assessment of 42 new families and review of genetic screening criteria. J Med Genet. 41:508–17. DOI: 10.1136/jmg.2004.018275. PMID: 15235021. PMCID: PMC1735838.
crossref
87. Jonkman JE, Cathcart JA, Xu F, Bartolini ME, Amon JE, Stevens KM, et al. 2014; An introduction to the wound healing assay using live-cell microscopy. Cell Adh Migr. 8:440–51. DOI: 10.4161/cam.36224. PMID: 25482647. PMCID: PMC5154238.
crossref
88. Suriano G, Oliveira MJ, Huntsman D, Mateus AR, Ferreira P, Casares F, et al. 2003; E-cadherin germline missense mutations and cell phenotype: evidence for the independence of cell invasion on the motile capabilities of the cells. Hum Mol Genet. 12:3007–16. DOI: 10.1093/hmg/ddg316. PMID: 14500541.
crossref
89. Worby CA, Dixon JE. 2014; PTEN. Annu Rev Biochem. 83:641–69. DOI: 10.1146/annurev-biochem-082411-113907. PMID: 24905788.
crossref
90. Weng LP, Brown JL, Baker KM, Ostrowski MC, Eng C. 2002; PTEN blocks insulin-mediated ETS-2 phosphorylation through MAP kinase, independently of the phosphoinositide 3-kinase pathway. Hum Mol Genet. 11:1687–96. DOI: 10.1093/hmg/11.15.1687. PMID: 12095911.
crossref
91. Weng LP, Brown JL, Eng C. 2001; PTEN coordinates G(1) arrest by down-regulating cyclin D1 via its protein phosphatase activity and up-regulating p27 via its lipid phosphatase activity in a breast cancer model. Hum Mol Genet. 10:599–604. DOI: 10.1093/hmg/10.6.599. PMID: 11230179.
crossref
92. Planchon SM, Waite KA, Eng C. 2008; The nuclear affairs of PTEN. J Cell Sci. 121:249–53. DOI: 10.1242/jcs.022459. PMID: 18216329.
crossref
93. Stambolic V, Suzuki A, de la Pompa JL, Brothers GM, Mirtsos C, Sasaki T, et al. 1998; Negative regulation of PKB/Akt-dependent cell survival by the tumor suppressor PTEN. Cell. 95:29–39. DOI: 10.1016/S0092-8674(00)81780-8.
crossref
94. Milella M, Falcone I, Conciatori F, Cesta Incani U, Del Curatolo A, Inzerilli N, et al. 2015; PTEN: multiple functions in human malignant tumors. Front Oncol. 5:24. DOI: 10.3389/fonc.2015.00024. PMID: 25763354. PMCID: PMC4329810.
crossref
95. Sansal I, Sellers WR. 2004; The biology and clinical relevance of the PTEN tumor suppressor pathway. J Clin Oncol. 22:2954–63. DOI: 10.1200/JCO.2004.02.141. PMID: 15254063.
96. Hlobilkova A, Guldberg P, Thullberg M, Zeuthen J, Lukas J, Bartek J. 2000; Cell cycle arrest by the PTEN tumor suppressor is target cell specific and may require protein phosphatase activity. Exp Cell Res. 256:571–7. DOI: 10.1006/excr.2000.4867. PMID: 10772829.
97. Eng C. 2003; PTEN: one gene, many syndromes. Hum Mutat. 22:183–98. DOI: 10.1002/humu.10257. PMID: 12938083.
98. Nieuwenhuis MH, Kets CM, Murphy-Ryan M, Yntema HG, Evans DG, Colas C, et al. 2014; Cancer risk and genotype-phenotype correlations in PTEN hamartoma tumor syndrome. Fam Cancer. 13:57–63. DOI: 10.1007/s10689-013-9674-3. PMID: 23934601.
crossref
99. Kwabi-Addo B, Giri D, Schmidt K, Podsypanina K, Parsons R, Greenberg N, et al. 2001; Haploinsufficiency of the PTEN tumor suppressor gene promotes prostate cancer progression. Proc Natl Acad Sci U S A. 98:11563–8. DOI: 10.1073/pnas.201167798. PMID: 11553783. PMCID: PMC58769.
100. Álvarez-Garcia V, Tawil Y, Wise HM, Leslie NR. 2019; Mechanisms of PTEN loss in cancer: It's all about diversity. Semin Cancer Biol. 59:66–79. DOI: 10.1016/j.semcancer.2019.02.001. PMID: 30738865.
crossref
101. Han SY, Kato H, Kato S, Suzuki T, Shibata H, Ishii S, et al. 2000; Functional evaluation of PTEN missense mutations using in vitro phosphoinositide phosphatase assay. Cancer Res. 60:3147–51.
102. Mighell TL, Evans-Dutson S, O'Roak BJ. 2018; A saturation mutagenesis approach to understanding PTEN lipid phosphatase activity and genotype-phenotype relationships. Am J Hum Genet. 102:943–55. DOI: 10.1016/j.ajhg.2018.03.018. PMID: 29706350. PMCID: PMC5986715.
crossref
103. Sun H, Lesche R, Li DM, Liliental J, Zhang H, Gao J, et al. 1999; PTEN modulates cell cycle progression and cell survival by regulating phosphatidylinositol 3,4,5,-trisphosphate and Akt/protein kinase B signaling pathway. Proc Natl Acad Sci U S A. 96:6199–204. DOI: 10.1073/pnas.96.11.6199. PMID: 10339565. PMCID: PMC26859.
crossref
104. Tan MH, Mester J, Peterson C, Yang Y, Chen JL, Rybicki LA, et al. 2011; A clinical scoring system for selection of patients for PTEN mutation testing is proposed on the basis of a prospective study of 3042 probands. Am J Hum Genet. 88:42–56. DOI: 10.1016/j.ajhg.2010.11.013. PMID: 21194675. PMCID: PMC3014373.
crossref
105. Spinelli L, Black FM, Berg JN, Eickholt BJ, Leslie NR. 2015; Functionally distinct groups of inherited PTEN mutations in autism and tumour syndromes. J Med Genet. 52:128–34. DOI: 10.1136/jmedgenet-2014-102803. PMID: 25527629. PMCID: PMC4316932.
crossref

Table 1
Summary of the general functional assays introduced in Part I
Mechanism Endpoint Example Expected result in affected cell-lines
Gene expression and protein turnover mRNA/protein level PCR
Western blot
Genetic material is not amplified.
Protein band is absent.
Transactivation Reporter gene expression level Fluorescent reporter proteins, luciferase assays Fluorescence is not detected.
Cell viability Indicator of cell life or death Colony formation assay
Apoptosis assay
Colonies grow despite lack of cell anchorage.
Cells are resistant to apoptosis.
Binding Interaction between two molecules Tetramerization assay Protein band is detected at a different location on western blot.
Cell motility Indicator of cell movement Cell aggregation assay, cell invasion assay, wound closure assay Cell adhesion loss and increased cell motility
Enzyme activity Indicator of enzyme activity involved in a common pathway Phosphatase assay Varies depending on enzyme kinetics and inhibi- tion in certain pathways.
Table 2
PS3/BS3 interpretation suggested by ClinGen
Gene Criteria Specification
TP53* PS3_Strong Transactivation assays in yeast (IARC classification based on data from Kato et al.) that demonstrate a low functioning allele ( < 20% activity) AND:
-Evidence of a dominant-negative effect (DNE)+evidence of a LOF from Giacomelli et al. data
OR
-There is a second assay showing low function (colony formation assays, apoptosis assays, tetramer assays, knock-in mouse models, and growth suppression assays).
PS3_Moderate A)Transactivation assays in yeast (IARC classification based on data from Kato et al.) that demonstrate a partially functioning allele ( > 20% and ≤ 75% activity) AND:
-Evidence of a DNE+evidence of a LOF from Giacomelli et al. data.
OR
-There is a second assay showing low function.
Do not use code with conflicting evidence.
B)No transactivation assays (IARC classification based on data Kato et al.) available BUT:
-Evidence of a DNE+evidence of a LOF from Giacomelli et al. data.
AND
-There is a second assay showing low function.
Do not use code with conflicting evidence.
BS3_Strong Transactivation assays in yeast (IARC classification based on data from Kato et al.) that show retained function (76–140% activity) or super- transactivation function AND:
-No evidence of a DNE+no evidence of a LOF from Giacomelli et al. data.
OR
-There is a second assay, including colony formation assays, apoptosis assays, tetramer assays, growth suppression, and knock-in mouse models demonstrating retained function.
BS3_Supporting Transactivation assays in yeast (IARC classification based on data from Kato et al.) that demonstrate a partially functioning allele ( > 20% and ≤ 75% activity) AND:
-No evidence of a DNE+no evidence of a LOF from Giacomelli et al. data.
OR
-There is a second assay demonstrating retained function.
Do not use code with conflicting evidence.
CDH1 PS3_Strong RNA assay demonstrating abnormal out-of-frame transcripts.
This rule can only be applied to demonstrate splicing defects.
PS3_Supporting RNA assay demonstrating abnormal in-frame transcripts.
This rule can only be applied to demonstrate splicing defects.
BS3_Strong Functional RNA studies demonstrating no impact on transcript composition
This rule can only be used to demonstrate a lack of splicing and can only be applied to synonymous, intronic, or non-coding variants. BS3 may be downgraded based on data quality.
PTEN PS3_Strong Disease-Specific
Well-established in vitro or in vivo functional studies supportive of a damaging effect on the gene or gene product.
-Phosphatase activity < 50% of wild-type
-RNA, mini-gene, or other assays show impact on splicing
PS3_Supporting Disease-Specific; Strength Modified
Abnormal in vitro cellular assay or transgenic model with a phenotype different from the wild-type that does not meet PS3.
BS3_Strong Disease-Specific
Well-established in vitro or in vivo functional studies show no damaging effect on protein function. To be applied for missense variants with both lipid phosphatase activity AND results from a second assay appropriate to the protein domain demonstrating no statistically significant difference from the wild-type. For intronic or synonymous variants, RNA, mini-gene, or other splicing assays demonstrate no splicing impact.
BS3_Supporting Disease-Specific; Strength Modified
In vitro or in vivo functional study or studies showing no damaging effect on protein function but BS3 not met.

*TP53 PS3/BS3 interpretation is suggested by Fortuno et al.; CDH1 PS3/BS3 interpretation is suggested by Lee et al.; PTEN PS3/BS3 interpretation is suggested by Mester et al.

Table 3
Literature on functional assays used in each gene
Gene Transactivation assay Cell viability assay Binding assay Cell motility assay Enzyme activity assay HDR Centrosome
TP53 7878469, 30224644, 31081129, 17690113, 24816189 24816189, 12509279, 24677579, 19693097, 8479523 17690113
PTEN 26504226 26504226 10866302, 29706350, 21828076, 26504226, 19915616, 25875300, 28263967, 25527629
CDH1 12588804, 21106365, 15235021, 14500541, 22470475, 18772194, 12944922, 16924464
BRCA1 32656256, 15689452, 10811118, 19493677, 8942979, 18087219 11301010, 18680205 23628597, 18493658 18493658 8939848, 22172724, 25823446, 27484786 18087219, 18927495, 15923272

Literatures are represented using PMID number.

Abbreviation: HDR, homology directed repair.

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