5. Results
5.1 Mosaic disorders
5.1.1 PIK3CA mutation spectrum of patients with PROS
Molecular analysis was primarily performed for all patients by traditional Sanger sequencing5. All coding exons with flanking introns of PIK3CA were analysed. Mutant allele ratios of 30-50% were observed in scrapings from epidermal nevi or affected fatty tissue samples. In none of the blood samples PIK3CA mutations were detected by Sanger sequencing. In order to rule out other disorders, hot spot regions including Exon 10 of PIK3R1 and PIK3R2 (megalencephaly-related syndromes), and Exon 4 of AKT1 (Proteus syndrome) were also analysed. All of them were negative and no overlap between the disorders was identified.
A total of 9 missense mutations and 3 small in frame deletions were identified in PIK3CA gene by Sanger sequencing which are described in Table 5.1. Three novel mutations (1 missense and 2 deletions) were identified which have not been described related to PROS until now. All the mutations identified in this study were termed disease causing by different web-based prediction tools. In this study, majority of the mutations lie in the hot spot region
5The Sanger sequencing data was provided by apl. Prof. Dr. Ilse Wieland, Institute of Human Genetics, University Hospital Magdeburg, Germany.
55 of PIK3CA gene i.e. exon 21 and the common mutations already described. Different tissue samples yield different allele ratios for the same mutation in different patients.
Table 5.1: A summary of the identified hot spot mutations in PIK3CA for different tissue samples/blood by Sanger sequencing
Exon cDNA Predicted protein COSMIC / db SNP Samples (n)
2 c.317G>T p.Gly106Val COSM748 / - 1
2 c.317_328del p.(Gly106_Glu109del) - / - 4
2 c.328_330del p.(Glu110del) COSM4971083 / - 4
5 c.1035T>A p.Asn345Lys COSM754 / rs121913284 1
8 c.1338G>C p.Trp446Cys - / - 2
8 c.1340_1366del p.(Pro447_Leu455del) COSM5944102 / - 2 10 c.1624G>A p.Glu542Lys COSM760 / rs121913273 6 10 c.1633G>A p.Glu545Lys COSM763 / rs104886003 1 10 c.1637A>G p.Gln546Arg COSM12459/ rs397517201 2
21 c.3130A>T p.Asn1044Tyr COSM36288 / - 2
21 c.3140A>T p.His1047Leu COSM776 / rs121913279 4 21 c.3140A>G p.His1047Arg COSM775 / rs121913279 19 5.1.1. (A) Confirmation of the causal variants by NGS
For somatic mutation detection in all samples and tissues, the Sanger sequencing results were not sensitive enough. Improved detection methods were required for other tissues with low level of somatic mosaicism. So, a total of 47 samples in Run I and 35 samples in Run II were sequenced by amplicon deep sequencing of the PIK3CA gene on the GS Junior Instrument.
All the mutations in Table 5.1 were confirmed by NGS except for Exon 8 c.1338G>C which was negative in the NGS run. Thus this Exon 8 mutation turned out to probably be a sequencing artifact in Sanger sequencing. From the patients from which multiple tissues were available for testing, one example is shown in figure 5.3 of a patient carrying a mutation at c.3140A>G in PIK3CA showing the different percentage of mutant allele frequencies in different tissues detected by various sequencing methods.
NGS Run I: The first run on the GS junior was performed with all the 47 samples. A shotgun processing was implemented since the position of the mutations was already known and also to get the maximum number of reads from both directions. Though necessary qualitative and quantitative measurements were performed, the run was a failure with only few results. There were more number of short and dot reads than the desired library which spoiled the run. Of the total reads, 91,557 reads (31.94%) could be assembled to the amplicon reference sequences (passed filter wells). There were 50,075 short quality reads around 100-150 bp region which are probably the primer dimers after secondary PCR or unspecific sequences.
56 Figure 5.1 shows the distribution of the failed and passed filtered reads for all the 47 patients included in the run. In summary, 68.06% did not pass the quality filter systems provided in the GS Junior software for various reasons: short read length (17.47%) or incomplete extension and mixed reads (50.26%). All these reads were excluded in further analysis as failed reads reducing the final data set from 286,616 reads to 91,557 passed filtered reads (31.94%). Figure 5.1c shows the distribution of amplicon read lengths for all the 47 patients included in the run.
Figure 5.1: GS Junior Run I summary. (A) The distribution of key pass wells for 47 patients of the run and (B) the summary chart showing the statistics of the failed and passed filtered reads (C) The distribution of amplicon read lengths for 47 patients of the Run I. The frequency of read lengths (bp) is plotted from all the 91,557 reads generated in one run.
NGS Run II: The samples with deletions and few FFPE samples which showed higher background in Run I were not included in this run reducing the sample size to 35. The run was successful with the minimum read count of 2000 reads per sample. The dot and the short quality reads drastically reduced than the first run improving the quality of the run. Of the
(A)
(B)
(C)
57 total reads, 198157 reads (71.76%) could be assembled to the amplicon reference sequences (passed filter wells). There were 31,728 short quality reads around 100-150 bp region which are probably the primer dimers after secondary PCR or unspecific sequences. Figure 5.2 shows the distribution of the failed and passed filtered reads for all the 35 patients included in the run. In summary, only 27.98% did not pass the quality filter systems provided in the GS Junior software for various reasons: short read length (11.49%) or incomplete extension and mixed reads (16.49%). All these reads were excluded in further analysis as failed reads reducing the final data set from 276,128 reads to 198,157 passed filtered reads (71.76%).
Figure 5.2c shows the distribution of amplicon read lengths for all the 35 patients included in the run. Table 5.2 shows the variants frequency for both sequencing methods- Sanger and NGS Run II representing all identified PIK3CA mutations.
(A) (B)
(C)
Figure 5.2: GS Junior Run II summary. (A) The distribution of key pass wells for 35 patients of the run and (B) the summary chart showing the statistics of the failed and passed filtered reads. (C) The distribution of amplicon read lengths for 35 patients of the Run II with median reads length of 467bp. The frequency of read lengths (bp) is plotted from all the 198,157 reads generated in one run.
58 Table 5.2: Variants frequency table for Sanger sequencing and NGS Run II representing all identified PIK3CA mutations. The total number of samples with the total number of reads per sample and percentages of variants showing the mutations are shown below. The patient ID and sample number are in reference to Supplementary table 1. (CLOVES - congenital lipomatous overgrowth, vascular malformations, epidermal nevi, and skeletal abnormalities; HHML- hemihyperplasia-multiple lipomatosis; seq- sequencing)
Exon Patient ID
Classification of Phenotype
Sample
number Tissue
Sanger seq allele %
Number of Reads Variant reads % of Variant Total no
of reads
Variant reads
Forward Reverse Variant Wild type Exon 2
p.(Glu110del)
P3 P2
CLOVES
CLOVES 8
6
Blood Blood
<10
<10
3244 5824
---- ----
---- ----
---- ----
---- ----
100 100 Exon 2
p.Gly106Val P4 CLOVES 9 Blood <10 9408 117 76 41 1.24 98.76
Exon 5
p.Asn345Lys P7 Macrodactyly 14 Bone 30-40 4271 1567 829 738 36.6 63.4
Exon 10 p.Glu542Lys
P8 P12 P10
CLOVES CLOVES CLOVES
15 21 18
Fibroblasts FFPE Fat tissue
20-30
<10 15-25
3818 4363 4769
1382 75 1140
755 46 569
627 29 571
36.1 1.72 23.9
63.9 98.28
76.1 Exon 10
p.Glu545Lys P11 CLOVES 20 Cartilage 30-50 --- ---- --- ---- --- ---
Exon 10
p.Gln546Arg P9 CLOVES 16 Skin 30-40 2577 435 36 399 16.8 83.2
Exon 21
p.Asn1044Tyr P15 HHML 33
34
Fat
Blood 30-40
<10
5810 2737
1652 5
842 4
810 1
28.4 0.18
71.6 99.82
59 Exon 21
p.His1047Leu P18 CLOVES
45 46 47 48
FFPE- tumor FFPE- Bone
Skin Blood
38 35 30
<10
2373 2541 2486 2470
900 769 583 ---
471 379 285 ---
429 390 298 ---
37.9 30.2 23.4 ---
62.1 69.8 76.6 100
Exon 21 p.His1047Arg
P13 CLOVES
24 25 26 27 28 29
Blood Cartilage
Tendon Skin Connective tissue
Epiphyses tissue
<10 25-35 30-40 13-20 30-50 20-30
3047 4420 4097 3301 3975 3483
3 1192 1459 533 1424
774
3 535 688 268 723 398
--- 657 771 265 701 376
0.09 26.9 35.6 16.1 35.8 22.2
99.91 73.1 64.4 83.9 64.2 77.8
P16 CLOVES
35 36 37 38 39 40 41
Blood Skin Adipose neck Adipose cervical
Connective Keratinocytes
Nevus
<10 40 --- 15-30 15-20 34-50 30-40
2448 4116 2680 3523 5724 7614 3966
3 1278
374 602 837 3625 1419
--- 825 192 317 426 1903
736
3 453 182 285 411 1722
683
0.12 31 13.9
17 14.6 47.6 35.7
99.88 69 86.1
83 85.4 52.4 64.3
P17 Macrodactyly
42 43 44
Subcutaneous tissue Deep fat
skin
<10 20-30
<10
2811 2063 2664
117 420 203
57 224 112
60 196
91
4.1 20.3
7.6
95.9 79.7 92.4
P14 HHML
32 30 31
Fat Bone Blood
20-30 7-13
<10
3632 3439 4816
736 283 7
401 142 5
335 141 2
20.2 8.2 0.1
79.8 91.8 99.9 (Classification of the phenotype for the patients and most of the patient samples were provided by Prof. Dr. Sigrid Tinschert, Institute of Clinical Genetics, Technical University of Dresden, Dresden, Germany)
Overall, we identified 11 PIK3CA mutations in 18 individuals which consist of 3 deletions and 8 missense mutations. All the identified missense mutations were previously known pathogenic variants in PROS except for one, p.Asn1044Tyr. From the patient P11 presenting with CLOVES, only cartilage sample was available and by Sanger sequencing one known missense change p.Glu545Lys was identified. The sample could not be included in NGS runs due to presence of high short fragments and degraded DNA quality and only Sanger data is available for this variant.
60 Figure 5.3: (A) A 4-year old boy (P13) with postaxial polydactyly with bilateral extreme overgrowth of feet and lower limbs. The arrow marks indicated are epidermal naevi on the neck and abdomen; (B) Local overgrowth of both extremities with polydactyly; (C) Lipomatosis of soles of feet; (D) Mutation at c.3140A>G in PIK3CA in connective tissue by Sanger sequencing in both forward and reverse directions; (E) GS Junior Flowgram tab for the read displaying the c.3140A>G mutation in PIK3CA in the same tissue; (F) Table showing the different percentage of mutant alleles in different tissues by comparing both sequencing methods for c.3140A>G in PIK3CA. [Picture of the patient reprinted with permission from, Eva Schneckenhaus (2009). Mutationsanalyse des PTEN-Gens bei Proteus-und Proteus-like-Syndrom (Dissertation Thesis). Medizinischen Fakultät, Otto-von-Guericke University, Magdeburg, Germany.]
61 5.1.1. (B) Fragment Analysis
Fragment analysis was also used to detect the presence of deletions in the samples tested for PIK3CA-related overgrowth study. The Genemapper software provided the area under the peak from which the mutant allele ratios were calculated for the deletions. The deletion ratio (%) was calculated using the below formula
Two fragment analysis runs were performed for the deletion patients for all samples from which the mean was taken and compared to the NGS run I. Though Run I had poor read count the data was used for comparison purposes between the different sequencing methods (Table 5.3). In Run II the deletion patients were not included except for blood samples. Different percentages of mutant alleles in different tissues are shown by comparing all the three sequencing methods in Figure 5.4 and Figure 5.5 of exon 2 deletions of PIK3CA gene for two patients.
Figure 5.4: Example showing the deletion c.328_330del; p. (Glu110del) in exon 2 of PIK3CA for a patient (P2) in all samples by different sequencing methods. (A) Table showing the different percentage of mutant alleles in different tissues by comparing all the three sequencing methods. (B) GS Junior Flowgram tab for the read displaying the deletion in Fatty tissue. (C) Fragment analysis showing the wild type and mutated peaks for Fatty tissue and only wild type peak for the blood sample.
Area of mutant peak % =
Combined area (Mutant peak + Wild type peak)
62 Table 5.3: Deletion ratios table for the samples analysed by Sanger sequencing, Fragment analysis and results of NGS Run I for the deletion samples.
Exon Patient
ID
Classification of Phenotype
Sample
number Tissue
Sanger seq DEL
%
Fragment Analysis NGS Run I results Run I
DEL %
Run II DEL %
Mean Total reads
Mutan t reads
DEL
%
WT
%
Exon 2 p.(Glu110del)
P2
P3
CLOVES
CLOVES
5 6 7 8
Fat tissue Blood Fat tissue
Blood
50
<10 20-30
<10
36 --- 26 ---
36 --- 25 ---
36 --- 25.5
---
157 98 129
---
42 -- 27
--
27 -- 21
--
73 100
79 100
Exon 2 p.(Gly106_Glu109
del) P1 CLOVES
1 2 3 4
Subcutaneous Fat tissue
Skin Subcutaneous
tissue Fat tissue
<10
<10 30 30
3.4 10.5
23 23
1.8 7 21 21
2.6 8.8 22 22
635 810 155 397
12 57 35 105
1.9 7 22.5 26.4
98.1 93 77.5 73.6 Exon 8
p.(Pro447_Leu455
del) P5 CLOVES
11 10
Bone Fat tissue
20-40 40
25 33
21 30
23 31.5
268 74
73 25
27 34
73 66 Note: Though the read count was very low in the NGS Run I, the results here were just used for comparison purposes between the different sequencing methods. (DEL- deletion; WT- Wild type allele)
63 Figure 5.5: Example showing the deletion c.317_328del; p. (Gly106_Glu109del) in exon 2 of PIK3CA for a patient (P1) in all samples by different sequencing methods. (A) Table showing the different percentage of mutant alleles in different tissues by comparing all the three sequencing methods. (B) GS Junior Flowgram tab for the read displaying the deletion in one of the tissue. (C) Fragment analysis showing the wild type and mutated peaks for different tissues for the deletion.
64