Breast Cancer (2019) 26:11–28 https://doi.org/10.1007/s12282-018-0894-0

REVIEW ARTICLE

CDKN2A/P16INK4A variants association with breast cancer and their in-silico analysis

Ayesha Aftab1 · Shaheen Shahzad2 · Hafiz Muhammad Jafar Hussain3 · Ranjha Khan3 · Samra Irum1 · Sobia Tabassum1

Received: 30 March 2018 / Accepted: 13 July 2018 / Published online: 23 July 2018 © The Japanese Breast Cancer Society 2018

Abstract CDKN2A was first identified as melanoma predisposition tumour suppressor gene and has been successively studied. The previous researches have not established any noteworthy association with breast cancer. Therefore, through extensive lit- erature search and in-silico analysis, we have tried to focus on the role of CDKN2A in breast cancer. CDKN2A variants in breast cancer were collected from different databases. The overall percentage of variants (approximately 5.8%) and their incidence frequency in breast cancer cases were found to be very low as compared to the number of samples screened in different studies. Exon 2 was identified as the major region of alternations. Approximately 42.8% were entire gene deletions, while 24.2% were missense mutations. These variants cannot be ignored because of their pathogenic effects as interpreted by the bioinformatics tools used in the present study. Earlier studies have shown that CDKN2A excludes the predisposition of germline variants, but interestingly shares common breast cancer germline variants with other carcinomas. Most of the data have revealed this gene as rarely mutated or deleted in breast cancer. However, few association studies have shown that in addition to being a ‘multiple’ tumour suppressor gene, it is mutated/deleted more in breast cancer cell lines as compared to breast cancer tissues or blood samples; thus, this gene cannot be neglected as a breast cancer candidate gene. The deletion/ malfunctioning of CDKN2A in different tumours including breast cancer has recently led to the discovery of many clinical CDK inhibitors. Furthermore, these collected genetic variants will also be helpful in developing diagnostic, preventive, and treatment approaches for patients.

Keywords Breast cancer · Variant analysis · CDKN2A · P16

Introduction incidence and mortality rate after lung cancer and has been ranked second among all of the cancers [1, 2]. Breast cancer is a type of a tumour in which cancerous In general, two genetic oscillations are involved in tumour cells originate from tissues of the breast. Males are at fewer development, one is activation of oncogenes and second risks of getting breast cancer, but like women, the chances is inactivation of tumour suppressor genes [3]. CDKN2A of developing breast cancer increase with age [1]. It is the (cyclin-dependent kinase inhibitor 2A)/p16INK4A/p14ARF most common cancer in females worldwide with the highest is an anti-oncogenic or tumour suppressor gene that was

* Shaheen Shahzad Sobia Tabassum [email protected] [email protected] Ayesha Aftab 1 Department of Bioinformatics and Biotechnology, [email protected] International Islamic University, Islamabad 44000, Pakistan Hafiz Muhammad Jafar Hussain 2 Genomics Research Lab, Department of Bioinformatics [email protected] and Biotechnology, International Islamic University, Ranjha Khan Islamabad 44000, Pakistan [email protected] 3 The CAS Key Laboratory of Innate Immunity and Chronic Samra Irum Diseases, School of Life Sciences, University of Science [email protected] and Technology of China, Hefei 230027, Anhui, China

Vol.:(0123456789)1 3 12 Breast Cancer (2019) 26:11–28 discovered as cyclin-dependent kinase inhibitor (CDKI) 2A5E [10], this protein consists of four Ankyrin repeats in 1993 [4, 5]. The cytological location is the short arm (ANK-REP-I–IV) [10, 11]. In cyclin D/CDK/pRb pathway, of chromosome 9 (9p21) in human and consists of three p16 protein acts as an inhibitor and competes with cyclin D exons [6]. Lately, it is identified that first exon of CDKN2A for binding to CDK4/6. P16 binding with CDK4/6 leaves is unique, i.e., 1α and 1β that shares exon 2 and 3 (Fig. 1a); the pRb non-phosphorylated. A non-phosphorylated pRb therefore, p16/ p16INK4A and p14/p14ARF/ARF are tran- remains attached to the E2F and transcription does not occur scribed by the exon 1α and exon 1β, respectively, from dif- [4, 6]. The ARF/p14 protein also acts as a tumour suppres- ferent promoters [4, 6]. The molecular data that supported sor through its p53/MDM2/p21 pathway, as illustrated in p14 role in tumour suppression are rare, but mutations in Fig. 1. However, the role of p14ARF as a tumour suppressor CDKN2A lead to inactivation of both p16 and p14 proteins gene needs to be further characterized, as some studies have [7–9]. suggested a fewer or not any a tumour suppressive role for Both these proteins have distinct pathways; primarily, p16 p14ARF in breast carcinoma [8] as compared to p16INK4A plays role in G1-to-S-phase cell cycle checkpoint mecha- [9]. nism by its interaction in cyclin D/CDK/pRb pathway [4]. CDKN2A/p16INK4A alternations have been described Focusing on the p16 protein that is 14.5 kDa has PDB ID in many previous and recent studies [11–17]. To ascertain

Fig. 1 Brief illustration of CDKN2A pathway. a Structure of Similarly, P16 inhibits the Rb phosphorylation to keep E2F confined CDKN2A and its two unique transcripts, i.e., p14ARF and p16INK4A. to arrest G1–S-phase cell cycle progression. In crosstalk, p21 deac- b Two tumour suppressor pathways p14/MDM2/p53 and p16/ tivates the CDK2-mediated Rb phosphorylation, while it has been CDK4–6/Rb. The stimulatory signals as shown with green arrows predicted that p16 loss could trigger the p53 by stimulation of E2F- and inhibitory with the red interrupted line. The crosstalk between dependent transcription that would increase the p14 level. Hence, both pathways, shown with blue arrows and interrupted line. P14 acti- CDk4–6/Cyclin D and MDM2-p53 are stimulatory complexes, and vates p53 by inhibiting the Murine double minute 2 (MDM2)–p53 E2F-Rb is inhibitory complex for cell cycle progression complex formation to arrest G1-to-S-phase cell cycle progression.

1 3 Breast Cancer (2019) 26:11–28 13 whether this gene has any association with breast cancer or interest to co-relate genetic association of CDKN2A with not, we have compiled human p16INK4A variants associated breast cancer from the literature. with breast cancer. The sources of variants are germlines, In the previous studies, CDKN2A was found to be somatic cell lines as well as breast cancer variants shared mutated and deleted in breast cancer cases, while LOH and with other tumours. These alterations are then subjected methylation were found to be other factors associated with to in-silico analysis to predict their pathogenic effect. The carcinoma [8]. Exon 1 was evaluated to be a region of CpG findings of this study have shown the prevalence level of island in different studies [8, 39, 40], which has shown a p16INK4A genetic alternations in breast cancer. Further- methylated form in the normal and hypermethylated form more, through in-silico analysis, we have predicted the in tumour cases [41]. A recent study has also shown hyper- pathogenic impact of associated alternations on splicing, methylation of exon 2 in breast cancer [42]. Furthermore, and their structural and functional roles on the protein. We hemizygous was the second cause, followed by a homozy- have also tried to discuss and relate the p16INK4A variants gous minor role in downregulation of p16, while substitu- possible applications in clinical preventions and therapies tions and indels were absent [17]. against breast cancer. Variants collection CDKN2A‑cancer genetics To correlate p16INK4A in breast cancer, we have collected CDKN2A has been reported in controlling tumour growth P16INK4A variants that were evaluated in different breast to be directly involved in cell cycle regulation. Chromo- cancer samples. The collected variants are illustrated in some 9p21 allele has shown a higher frequency for loss of Table 1 according to their sources, i.e., somatic (tissue heterozygosity (LOH) [16–18]. Apart from this, it contains source), cell line, and germline (blood) source. Therefore, inversions, translocations, and homozygous deletions in the variant collection was based on a search from different a number of tumours. This gene was not only found to be databases and published studies. Mainly, the Human Gene involved in different somatic mutations, but also has shown Mutation Database (HGMD) (http://www.hgmd.cf.ac.uk/ germline association in many tumours [6, 18–21]. ac/searc​h.php), Leiden Open (source) Variation Database Loss of function of CDKN2A in multiple tumours was (LOVD) (http://www.lovd.nl/3.0/home), the Catalogue reported first by two separate groups in 1994 [22, 23]. Of Somatic Mutations In Cancer (COSMIC) (http://cance​ CDKN2A association with cancer was also reviewed in r.sange​r.ac.uk/cosmi​c), Domain Mapping of Disease Muta- detail by different authors since 1994 [6, 9, 15, 23]. The tion (DMDM) (http://bioin​f.umbc.edu/dmdm/), Cancer best-associated cancer is melanoma followed by prostate genetic web (http://www.cance​rinde​x.org/genew​eb/) and carcinoma, head and neck carcinoma, non-small lung car- Mutations, Oncogenes and Knowledge & Cancer (MOKCa) cinoma, oesophageal, ovarian, and renal cancer [6, 13, 19, (http://strub​iol.icr.ac.uk/extra​/mokca​/) were accessed. 24]. Low frequency of CDKN2A mutations was also found The type of variants and their number of identification in colon cancer, breast cancer, and bladder cancer [6, 25]. from different researches are also given in Table 1b. The The rate of alteration in CDKN2A varies depending on the deletion of CDKN2A (30/70) from chromosome was found type of cancer, i.e., it is more vulnerable in melanoma and to be a major factor for inactivation of this gene in breast entails histone modifications in addition to DNA methylation cancer. [18, 19, 26, 27]. Gastric cancer has a significant co-relation with CDKN2A hypermethylation [28–30]. Homozygous deletions have been reported in high frequency in primary In‑silico characterization of collected samples and cell lines derived from breast, lung, bladder, p16INK4A variants bone, brain, skin, ovary, and lymphocytes, while frameshift, non-sense, and miss sense mutations have been widely The collected variants (Table 1) were analyzed to predict reported in melanoma cell lines [18, 21, 26, 31]. Thus, like their structural and functional effect on protein through com- previous studies, we emphasize the character of CDKN2A putational analysis. To show the impact of possible vari- as a ‘multiple’ tumour suppressor gene [21, 23]. ants on protein, we have applied the combination of tools to The previous studies reported rare CDKN2A mutations in improve predictive accuracy [43]. breast cancer [32–35]. Sorensen and Hovig stated somatic and germline mutations in CDKN2A for other cancers, but Splice site variants analysis did not find any association with breast cancer [36], while some studies showed CDKN2A-breast cancer association Through data collection we have found only one splice site with some extent [8, 18, 37, 38]. This point has gained our variants (c.151-1G > C) and to know the impact of splice

1 3 14 Breast Cancer (2019) 26:11–28 c [ 67 ] [ 66 ] [ 65 ] [ 64 ] [ 64 ] [ 35 ] [ 35 ] [ 35 ] [ 71 ] [ 8 ] [ 70 ] [ 64 ] [ 69 ] [ 17 ] [ 63 ] [ 63 ] [ 67 ] [ 68 ] [ 62 ] References Cosmic Cosmic Mokca Cosmic Cosmic Cosmic – Cosmic Cosmic, Mokca Cosmic Cosmic Cosmic Cosmic Cosmic Cosmic Cosmic Cosmic – Cosmic Cosmic, Mokca Database -

b 1/22 1/42 1/5 NA NA 1/164 1/164 1/164 1/36 3/18 4/20 1/560 2/3 3/100 NA NA 1/22 2/20 Variants find Variants 1/35 ings/studies ( n ) NA NA NA NA NA Homozygous Homozygous Homozygous NA Homozygous Homozygous NA Homozygous Homozygous NA NA NA Homozygous Zygosity Heterozygous phyllodes tumour phyllodes NS Phyllodes tumour Phyllodes Metaplastic carcinoma Metaplastic Ductal carcinoma Ductal carcinoma NS NS NS ER-positive carcinoma ER-positive Ductal carcinoma Metaplastic carcinoma Metaplastic Ductal carcinoma Benign & malignant Metaplastic carcinoma Metaplastic NS NS NS NS Histological sub-type Histological NS - substitution deletion tion Silent muta Missense Missense Non-sense Non-sense Non-sense Missense Silent Deletion Missense Missense Whole gene Whole gene Gene deletion Missense Gene deletion Gene deletion Deletion Frameshift Frameshift Variant class/ Variant type Missense Exon 2 Exon Exon 2 Exon Exon 1 Exon Exon 2 Exon Exon 2 Exon Exon 2 Exon Exon 2 Exon Exon 2 Exon Exon 2 Exon Exon 2 Exon KO Whole gene Exon 2 Exon KO KO Exon 2 Exon Exon 2 Exon Exon 2 Exon Location Exon 2 Exon Not confirmed Not c. 247C > T 14 Not confirmed Not c.238C > T c.238C > T c.247C > T c.318G > A c.151_457del307 c.224C > T c.365G > T No gene No c.1_471del471 c.322G > A c.1_471del471 c.1_471del471 c.151_457del307 c.407_408insG c.235_236delAC cDNA change cDNA c.155T > A p.A73A p.H83Y p.P48L p.R80* p.R80* p.H83Y p.V106V No protein No p.P75L p.G122V No protein No No protein No p.D108N No protein No No protein No p.T137fs*.5 p.T79fs*40 Variants change Protein p.M52K a ­ name A09I-01 A4E4-01 Tumor A13 Tumor Tumor A1 Tumor 1107901 7-MBC PD18733a PD11336a S88891 S88892 933015 933016 S88890 2556850 2556852 2556857 SC-her2-043 933014 2556845 926676 926683 TCGA-A8- TCGA-LQ- PD11341a 2158001 2158006 2394252 926634 Sample Sample 929692 variants in breast cancer, collected via literature and database collected via literature search cancer, in breast Identified CDKN2A variants (a) Details of variants/mutations source Variant 1 Table Somatic

1 3 Breast Cancer (2019) 26:11–28 15 c [ 73 ] [ 72 ] [ 72 ] [ 72 ] [ 72 ] [ 72 ] [ 67 ] [ 76 ] [ 67 ] [ 75 ] [ 34 ] [ 74 ] [ 34 ] [ 73 ] [ 35 ] [ 73 ] References Cosmic Cosmic Cosmic Cosmic Cosmic Cosmic – Cosmic – Cosmic Cosmic Cosmic Cosmic Mokca – Cosmic Cosmic Database -

b 1/46 8/41 1/41 1/41 1/41 1/41 1/4 1/5 2/4 3/9 5/20 2/5 1/20 1/46 Variants find Variants 2/6 1/46 ings/studies ( n ) NA Homozygous Homozygous Homozygous Homozygous Homozygous NA Homozygous NA Homozygous Homozygous Homozygous Homozygous NA Zygosity Homozygous NA - noma ER–PR-positive carci ER–PR-positive HER-positive carcinoma HER-positive Basal Carcinoma Luminal carcinoma Luminal Luminal carcinoma Luminal Luminal carcinoma Luminal Luminal carcinoma Luminal NS NS NS NS NS NS Luminal carcinoma Luminal Triple negative Triple Histological sub-type Histological NS Missense Missense Gene deletion Gene deletion Deletion Missense Missense Non-sense Gene deletion Deletion Gene deletion Gene deletion Gene deletion Missense Missense Variant class/ Variant type Deletion Exon 1 Exon Exon 2 Exon KO KO Exon 2 Exon Exon 2 Exon Exon 2 Exon Exon 2 Exon KO Exon 2 Exon KO Whole deletion KO Exon 2 Exon Exon 2 Exon Location Exon 2 Exon Not available Not c.332G > C c.1_471del471 c.1_471del471 c.225delC c.156G > C c.203C > T c.262G > T c.1_471del471 c.151_457del307 c.1_471del471 c.1_471del471 c.1_471del471 c.156G > C Not available Not cDNA change cDNA c.151_457del307 p.G6E p.D108H No protein No No protein No p.A76fs*70 p.M52I p.A68V p.E88* No protein No No protein No No protein No No protein No No protein No p.M52I p.G124E Variants change Protein No protein No a ­ name MCF7 Hs-578-T MDA-MB-231 SK-BR-7 SUM102PT SUM1315MO2 SUM149PT SUM229PE MDA-MB-361 BT-20 MCF-7 OCUB-F MDA-MB-361 SUM52PE MCF-12F 184A1 MCF-7 MDA-MB-231 MCF-7 35 Hs-S78T MDA-MB-330 MDA-MB-231 BT-20 MCF-1OF MCF-7 BT-20 MCF-7 Hs-578-T 30 MCF-7 2 MDA-MB-361 CAL-148 Sample Sample MDA-MB-231 1 Table (continued) (a) Details of variants/mutations source Variant Cell lines

1 3 16 Breast Cancer (2019) 26:11–28 c [ 78 ] [ 78 ] [ 33 ] [ 33 ] References [ 21 ] [ 77 ] – – Database – – -

b d NA NA 1/31 1/31 6/9 Variants find Variants ings/studies ( n ) 1/31 NA NA NA NA NA Zygosity NS NS NS NS NS Histological sub-type Histological Missense Missense Missense Missense Splice site Insertion Variant class/ Variant type Exon 2 Exon Exon 1 Exon Exon 2 Exon Exon 2 Exon Intron 1 Intron Exon 2 Exon Location c.241C > A c.47T > G Not available Not Not available Not c.151-1G > C ​ c.336_337insCGT cDNA change cDNA not available not p.P81T p.L16P p.V59G p.A85T – p.113insR Variants change Protein NA a 17 3 9 8 30 2 1 70 / 1191 ­ name not specified, not NS D26 CO1 Case 16 Sample Sample Lund M9 Lund M12 Lund M49 Lund M62 Lund M2 Lund Case 5 Family 543 Family Lund M13 Lund e number of samples screened number of samples Number of studies mentioned in literature work mentioned in literature of studies Number carriedNine malignant melanoma families mutationcontainscancer cases, and all six carried in them,breast 113insArg out of them six families that mutation The germline source mutations that were identified to be common with other cancer type in a patient or family other with common be to identified or patient a germline in The type cancer mutations source that were Sample name or ID taken from database from name or ID taken or literature Sample authorotherstudies (irrespective of author) or the first include first References

(a) Details of variants/mutations source Variant variants cancer in association with types of number of different breast (b) Total Missense mutations mutations Non-sense nucleotides) Indels (few deletions 2 region Exon deletion gene Entire Silent mutations mutations splice region Intronic mutations reported/totalTotal A.Aacid, amino a b c d e 1 Table (continued) Germline

1 3 Breast Cancer (2019) 26:11–28 17

Table 2 In-silico analysis to determine the possible functional impact of CDKN2A variants in breast cancer association (a) Impact of CDKN2A Intronic mutations on splicing. Vari HSFa Sroogleb Netgene2c NNspliced Predic ants HSF matric score range (1–100) Range (1– Range (0–1) Range (0– tion 100) 1) of WT Muta Varia Interpre WT Mut WT Muta W Muta possib nt tion tation ant nt T nt le % functi onal impac tl c.15 91.4 62.51 − Probabl 12.09 4.03 1.0 No 0. No Possi 1- 5 31.65 y (Max (Ma 0 site 95 site bly 1G> effectin entrop x A.S gener A. gener highly C g y) entr c ated S ated delete splicing 88.10 opy) rious (PSS 64.6 M)b 6 (PS SM) (b) Impact of CDKN2A missense mutations on protein stability and function. Polyphen-2e SIFTf FATH Align-GVGDh Prediction of MMg possible functional Vari Scor Predi Score Predicti Predic GVd GD Predi impactl ants e ction (rang on tion d ction (rang e 0– thresh e 0– 1) old is 1) − 0.75 p.M5 0.99 Proba 0.05 Damagi − 1.14 0.00 94. Class Possibly highly 2K 4 bly ng 49 C65 deleterious dama ging p.D1 1.00 Proba 0.1 Tolerat − 5.59 0.00 23. Class Possibly 08N bly ed 01 C15 deleterious dama ging p.P7 1.00 Proba 0.27 Tolerat − 5.74 0.00 97. Class Possibly highly 5L bly ed 78 C65 deleterious dama ging p.H8 1.00 Proba 0.6 Tolerat − 1.60 0.00 83. Class Possibly highly 3Y bly ed 33 C65 deleterious dama ging p.P4 1.00 Proba 0.03 Damagi − 5.74 0.00 97. Class Possibly highly 8L bly ng 78 C65 deleterious dama ging p.G1 1.00 Proba 0.00 Damagi − 5.97 0.00 108 Class Possibly highly 22V bly ng .79 C65 deleterious dama ging

site mutation, the in-silico tools were accessed, i.e., Human from server Berkeley Drosophila Genome Project (BDGP) Splicing Finder HSF (http://www.umd.be/HSF3/), Sroogle (http://www.fruitfly.org/seq_tools​ /splic​ e.html​ ) (Table 2a). (http://sroogle.tau.ac.il/​ ), Netgene2 (http://www.cbs.dtu.dk/ By assessing the default settings, the damaging effect was services/NetGe​ ne2/​ ), and NNSplice 0.9 version were used predicted by the magnitude of the difference of wild-type

1 3 18 Breast Cancer (2019) 26:11–28

Table 2 (continued) p.M5 0.58 Possi 0.16 Tolerat − 0.99 0.00 10. Class Possibly less 2I 9 bly ed 12 C0 deleterious dama ging p.A6 1.00 Proba 0.00 Damagi − 2.91 0.00 64. Class Possibly highly 8V bly ng 43 C55 deleterious dama ging p.D1 1.00 Proba 0.00 Damagi − 5.66 0.00 81. Class Possibly highly 08H bly ng 24 C65 deleterious dama ging p.G6 1.00 Proba 0.33 Tolerat − 2.30 0.00 97. Class Possibly highly E bly ed 85 C65 deleterious dama ging p.A8 1.00 Proba 0.00 Damagi − 2.51 0.00 58. Class Possibly highly 5T bly ng 02 C55 deleterious dama ging p.V5 0.99 Proba 0.00 Damagi − 1.26 0.00 108 Class Possibly highly 9G 8 bly ng .79 C65 deleterious dama ging p.L1 1.00 Proba 0.00 Damagi − 3.13 Possibly highly 6P bly ng 97. Class deleterious 0.00 dama 78 C65 ging p.P8 1.00 Proba 0.00 Damagi − 1.66 0.00 37. Class Possibly highly 1T bly ng 56 C35 deleterious dama ging (c) Impact of CDKN2A substitution mutations on protein domain. Vari SMA InterProj ScanPrositek Prediction of possible functional impactl ants RTi Amin Doma Amino Scores o in acid acid predi cted p.M5 No 12– Ank 16–130 19.598 Possibly less deleterious 2K Ank 148 repeat A contai repea ning t doma dom in ain predi cted p.D1 No 12– Ank 16–130 19.412 Possibly not deleterious 08N effec 148 repeat t on contai Ank ning repea doma ts in

1 3 Breast Cancer (2019) 26:11–28 19

Table 2 (continued) dom ain p.P7 No 12– Ank 16–130 19.545 Possibly not deleterious 5L effec 148 repeat t on contai Ank ning repea doma ts in dom ain p.H8 No 12– Ank 16–130 18.563 Possibly deleterious 3Y Ank 148 repeat repea contai t ning dom doma ain in predi cted p.P4 No 11– Ank 16–130 18.324 Possibly deleterious 8L Ank 136 repeat repea contai t ning dom doma ain in predi cted p.G1 No 12– Ank 16–130 18.245 Possibly less deleterious 22V effec 148 repeat t on contai Ank ning repea doma ts in dom ain p.M5 No 12– Ank 16–130 19.678 Possibly not deleterious 2I effec 148 repeat t on contai Ank ning repea doma ts in dom ain p.A6 No 12– Ank 16–130 19.014 Possibly not deleterious 8V effec 148 repeat t on contai Ank ning repea doma ts in dom ain p.D1 No 12– Ank 16–130 18.855 Possibly less deleterious 08H effec 148 repeat t on contai Ank ning

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Table 2 (continued) repea doma ts in dom ain p.G6 No 12– Ank 16–130 19.678 Possibly not deleterious E effec 148 repeat t on contai Ank ning repea doma ts in dom ain p.A8 No 12– Ank 16–130 18.643 Possibly deleterious 5T Ank 148 repeat repea contai t ning dom doma ain in predi cted p.V5 No 12– Ank 16–130 18.908 Possibly deleterious 9G Ank 148 repeat repea contai t ning dom doma ain in predi cted p.L1 No 12– Ank 19–130 19.173 Possibly not deleterious 6P effec 148 repeat t on contai Ank ning repea doma ts in dom ain p.P8 No 12– Ank 16–130 18.616 Possibly deleterious 1T Ank 148 repeat repea contai t ning dom doma ain in predi cted

(WT) and mutant scores. The score range provided by Analysis of substitution mutations effect on protein each database is mentioned in Table 2a. Furthermore, the stability HSF matric with the percentage less than 10 evaluates that mutation may break the acceptor site. The greater variation From the collected data, we have found 14 missense muta- between WT and mutant scores predicted to be damaging tions. These may cause deleterious effects on protein struc- for splice site. The c.151-1G > C variant may altered the ture and function, and can be predicted by online tools acceptor site and cause an effect on splicing. (Table 2b). For any deleterious effect of non-synonymous

1 3 Breast Cancer (2019) 26:11–28 21

Table 2 (continued) wt wild type a HSF = Human splicing finder, HSF matric scores difference btw WT and mutant, variation % < − 10% predicting mutation breaks the splice site [79] b Sroogle = Predicting effect on splicing through difference between wild-type and mutant scores. The matrices which showed difference in score were selected in above table. PSSM; position-specific scoring matric, http://sroog​le.tau.ac.il/ c Netgene2 = neural network prediction server, predicts the acceptor site (A.S) and donor site (D.S), score near to 1 regarded as more strong splice site. http://www.cbs.dtu.dk/servi​ces/NetGe​ne2/outpu​t.php d NNsplice = NNsplice version 0.9 work on NNSPLICE algorithm, predicts the acceptor site (A.S) and donor site (D.S), score near to 1 regarded as more strong splice site. http://www.fruit​fly.org/seq_tools​/splic​e.html e Polyphen-2 = Polymorphism Phenotyping v2, predictive scale ‘benign, possibly damaging and, probably damaging’. Scores near to 1 predicted to have probably damaging mutation (http://genet​ics.bwh.harva​rd.edu/pph2/) f SIFT = Sorting Intolerant from Tolerant (SIFT) SIFT version 4.0, predictive scale either ‘tolerating or damaging’ (http://sift.jcvi.org/) g FATHMM = Functional Analysis through Hidden Markov Models (v2.3) (FATHMM), mutation with threshold < − 0.75 are interpreted to be associated with cancer. (http://fathm​m.bioco​mpute​.org.uk/) h Align-GVGD = Grantham difference (GD) and Grantham variation (GV). Prediction series from C65 (most likely damaging) to C0 (less likely damaging) and ≥ C25 were predicted as deleterious (http://agvgd​.hci.utah.edu/) i SMARTa​ = Simple Modular Architecture Research Tool (SMART), (http://smart​.embl-heide​lberg​.de/) j InterProb = https​://www.ebi.ac.uk/inter​pro/ k ScanPrositec = http://prosi​te.expas​y.org/scanp​rosit​e/ Wt p16 protein Scores and amino acid coverage by Aanky/ank (Ankyrin) repeat domain predicted by; SMART = Ank-1 from 44 to 72 amino acid (a.a), Ank-2 from 77 to 106 a.a; InterPro = 12–148 a.a, Ankyrin repeat containing domain; ScanProsite = amino acid coverage sequence by Ank repeats region = 16–30 a.a, score = 19.678 l Prediction scale Possibly highly deleterious = mutation predicted to be highly damaging via all tools Possibly deleterious = mutation predicted to be damaging via two tools Possibly less deleterious = mutation predicted to be less damaging via only one tools Possibly not deleterious = mutation predicted to have no impact mutations polyphen-2 (http://genet​ics.bwh.harva​rd.edu/ were predicted as highly damaging and can be designated pph2/) was run, the predictive scale was ‘benign, possibly as possibly ‘pathogenic’. damaging and, probably damaging’ and score range was from 0 to 1. Only one substitution M52I was marked as Analysis of missense mutations effect on protein ‘possibly damaging’, while all others were ‘probably dam- domains aging’ with a score near or equal to 1. The other in-silico tool, Sorting Intolerant From Tolerant (SIFT) version 4.0 The impact of these 14 substitution variants on the domain (http://sift.jcvi.org/) was used for analyzation. In addition, of p16 protein was evaluated using three online tools prediction is classified as either ‘tolerated’ or ‘damaging’. (Table 2c). Simple Modular Architecture Research Tool Functional Analysis Through Hidden Markov Model (v2.3) (SMART) (http://smart​.embl-heide​lberg​.de/), InterPro: (FATHMM) (http://fathm​m.bioco​mpute​.org.uk/) was run protein sequence analysis and classification https( ​://www. with default threshold of − 0.75; according to this soft- ebi.ac.uk/inter​pro/), and ScanProsite (http://prosi​te.expas​ ware, the prediction threshold below this value would be y.org/scanprosit​ e/​ ) were used with default settings. Sequence interpreted as associated with cancer. Furthermore, Gran- analysis was done for variant effect on ankyrin domains of tham difference (GD) relative to the evolutionary differ- the p16 protein. The scores and domains of WT protein pre- ence (Grantham variation, GV) was also examined using dicted from these tools were compared with each variant. A Align-GVGD (http://agvgd.hci.utah.edu/​ ), its output was in large difference between scores and missing domains was an ordered series from class C65 (most likely) to C0 (less predicted to have a damaging effect on the protein domain likely), and variants having class ≥ C25 were considered and stability. According to the expected score, it was pre- deleterious [43]. If three or four tools assign variants to be dicted that these 14 variants may not have a high deleterious damaging, then a variant is predicted as possibly “highly effect on the protein domains. deleterious” (Table 2b). The predictive results of all four tools were found to be consistent, mutation M52I was showed to be very less deleterious, while 12/14 mutations

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Fig. 2 Wild type and mutant model of the p16 protein. a Structure 1 is the wild-type p16 PDB model structure (PDB ID 2a5e), structure 2 and 3 are the Swiss generated model of non-sense mutation p.R80* and p.E88*, respectively. b Struc- ture 1 is the wild-type PDB p16 model compared with CPH model of mutants p.R80* and p.E88*, respectively. Both the models are clearly representing the truncated mutant protein structure

Protein homology modelling and compared with the WT p16 protein standard PDB (ID 2A5E) structure in Swiss PDB viewer v.4.10. The selected The comparative modelling of mutant proteins was done 16 variant structures, including 14 missense substitutions by Swiss model (https​://swiss​model​.expas​y.org/) and and 2 non-sense substitutions (p.E88* and p.R80*), were CPH model 3.2 server (http://www.cbs.dtu.dk/servi​ces/ modelled. The non-sense variants have displayed the trun- CPHmo​dels/). The mutant’s 3D structure was analyzed cated protein structure (Fig. 2). However, all 14 missense

1 3 Breast Cancer (2019) 26:11–28 23 substitutions have shown no visual difference in protein activated due to the loss of tumour suppressor gene activity, structure, but they may have a pathogenic effect as predicted the reactivation of silenced tumour suppressor gene, or inhi- by other in-silico tools (Table 2b, c). bition of the epigenetic repression of the gene [20, 46, 47]. Such methods were applied to the malfunctioned CDKN2A Multiple sequence alignment recently [20, 46, 48, 49] which are summarized in the flow- chart (Fig. 4). Moreover, the reactivation of CDKN2A has Multi-sequence alignment of p16 protein was done with been achieved using regulatory gene such as FOXA1 suc- Clustal Omega program using Align tool of UniProt cessfully. The genistein has also shown remarkable proper- (http://www.unipr​ot.org/align​/). Alignment of human ties of the chemo-preventive agent by epigenetic regula- p16 protein was performed with other nine species, i.e., tion of CDKN2A. In addition, the use of other reagents like Pan troglodytes (Chimpanzee), Nomascus leucogenys doxorubicin and FUMI (5-fluorouracil and mitomycin C) (Northern white-cheeked gibbon), Gorilla gorilla (West- has resulted in the demethylation of the CDKN2A promoter ern lowland gorilla), Macacamulatta (Rhesus macaque), in breast cancer suppression [20]. Above all, the malfunc- Callithrix jacchus (White-tufted-ear marmoset), Pan tion/loss of CDKN2A in breast cancer patients has been troglodytes (Chimpanzee), Tarsiussyrichta (Philippine very efficiently fulfilled by the discovery of FDA approved tarsier), Susscrofa (Pig), and Bostaurus (Bovine). The CDK4/6-inhibitors, i.e., palbociclib (Feb 2015), riboci- protein structure was found to be highly selective and clib (Match, 2017) and abemaciclib (Sep 2017) [50–52]. conservative in nature (Fig. 3). Moreover, the region of These inhibitors can shut down the upregulation of cyclin subjected variants was also evolutionary conserved. All D-CDK4/6 complex by inhibiting the CDK4/6. Hence, the the variants, especially the variants lying in second exon loss of CDKN2A has made CDK4/6 a possible therapeutic (151–457 amino acid), were found to be in conserved target [53, 54]. The phase 1 clinical trials of drug ilora- sequence. While substitutions in exon 1 were shown as sertib (inhibitor of Aurora kinases) for CDKN2A deficient non-conservative mutations. Most of the variants were patients in solid tumours are also under progress (trial ID located in secondary structure consisting of beta strands, NCT02540876) [55]. A question may arise if CDKN2A does turns, bends, and alpha helix, while very few were identi- not show any breast cancer association while proven to be fied in primary structure; thus, these variants were found a principal regulator of cyclin D pathway, then why recent to be more deleterious to protein structure and may play a CDK inhibitors are showing remarkable clinical therapeutic critical role in association with breast cancer. results in breast cancer patients? This is likely to be due to the other factors apart from CDKN2A loss that may cause Physical and chemical properties of amino acid the overexpression or disruption of the cell cycle regulators substitutions like cyclins, CDK, or endogenous CDK inhibitors in breast cancer [50, 56]. Substitution is characterized by physical and chemical CDKN2A is still under consideration as therapeutic tar- properties of amino acid which may affect the protein sta- get, but has been used significantly as a prognostic marker bility and binding activity. The change in size, charge, [48]. As the previous studies have shown that CDKN2A is and hydrophobicity changes the protein reactivity, bind- hypermethylated in many cancers, which plays a magnifi- ing site, and physical properties [44]. We looked at the cent role as a prognostic marker [57–60]. Interestingly, physiochemical properties of amino acid substitution from the CDKN2A was also reported overexpressed in differ- the literature and interpreted the amino acid substitution ent kinds of cancers due to the oncogenic stress mediated preference (Table 3) [44]. According to the evaluation, 8 by Rb disruption [48] and this elevated level has been out of 14 substitutions have a ‘disfavored’ effect on protein recognised as a prognostic marker for breast ductal car- properties. cinoma as well as sub-type of the breast cancer such as basal breast cancer. It has been shown that even a single The significance of CDKN2A and its variants marker can differentiate a tumour from different sub- in prognosis, prevention and therapeutics types of breast cancer [48, 61]. Furthermore, it was also noticed that cancer patients with raised CDKN2A level, The inactivation of tumour suppressor genes has proven when treated with chemotherapeutic drugs, show more to be more challenging to the drug therapy [45]. Different tumour suppression outcome as compared to the patients approaches presented many potential therapeutic targets treated with cytostatic therapies (Fig. 4) [48]. which can overcome the loss of tumour suppressor [46, 47]. We could not find any clinical importance of the col- The best approaches can be: restoring gene function, using lected variants in cancer therapy previously. The reason a dominant negative variant that can serve as an inhibi- may be due to the low frequency of these variants inci- tor, shutting down the pathway that has been abnormally dents. However, the rate of gene deletion in breast cancer

1 3 24 Breast Cancer (2019) 26:11–28

1 3 Breast Cancer (2019) 26:11–28 25

◂Fig. 3 Sequence alignment of human CDKN2A/p16 protein (156 is higher and CDK inhibitors are showing remarkable amino acid) with ten species, by Clustal Omega program using Align therapeutic results [52]. In the future, if the association tool from UniProt (http://www.unipr​ot.org/align​/). Secondary struc- ture is indicated on the top of alignment [10] aided by the key below studies can potentially link these reported variants with left. The reported missense, non-sense substitutions and indels are breast cancer by reasonable frequency, then they can serve shown in red writing positioned with red arrows as the target for the personalized medicines. Finally, a high efficient gene editing tool such as CRISPR/Cas9 system

Table 3 Chemical and physical characteristic change of amino acids and their impact on protein stability

Variants Properties of amino acid substitution Amino acid substi- tution preferences

p.M52K From big, hydrophobic, non-polar, neutral, to big, hydrophilic, polar, positive charged amino acid change Disfavoured p.D108N From small, hydrophilic, polar, negative charged to small, hydrophilic, polar, neutral amino acid change Favoured p.P75L From small, hydrophobic, non-polar to hydrophobic, non-polar, amino acid change Disfavoured p.H83Y From big, hydrophilic, polar, positive charged to big, hydrophilic, polar, neutral amino acid change Favoured p.P48L From small, hydrophobic, non-polar, neutral to big, hydrophobic, non-polar, neutral amino acid change Disfavoured p.G122V From tiny, hydrophobic, non-polar, neutral to small hydrophobic, non-polar, neutral amino acid change Favoured p.M52I From big, hydrophobic, non-polar, neutral, to big, hydrophobic, non-polar, neutral amino acid change Favoured p.A68V From tiny, hydrophobic, non-polar, neutral to small, hydrophobic, non-polar, neutral amino acid change Favoured p.D108H From small, hydrophilic, polar, negative charged to big, hydrophilic, polar, positive charged amino acid change Disfavoured p.G6E From tiny, hydrophobic, non-polar to hydrophilic, polar, negatively charged amino acid change Disfavoured p.A85T From tiny, hydrophobic, non-polar, to big, hydrophilic, polar, neutral charged amino acid change Disfavoured p.V59G From small, hydrophobic, non-polar to tiny, hydrophobic, non-polar amino acid change Favoured p.L16P From big, hydrophobic, non-polar to small, hydrophobic, non-polar amino acid change Disfavoured p.P81T From small, hydrophobic, non-polar to small, hydrophilic, polar, neutral charged amino acid change Disfavoured

Fig. 4 Flowchart illustrating the CDKN2A recent or expected clini- CDKN2A. Asterisk indicates ilorasertib is under phase 1 clinical trials cal prognosis, therapies and preventions in breast cancer. The dotted for CDKN2A-deficient cancer patients line separating the therapy/prevention from prognostic features of

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