Genetic and histological analysis intraplacental choriocarcinoma: a case report

Formalin-fixed paraffin-embedded (FFPE) tissue sections was prepared from the semi-thin section on a slide glass with the pathological block tissue prepared at the time of surgery. The tissue sections were prepared from different block obtained from a patient that include only normal tissue or include mostly tumor tissue. As a control, early gestation villous tissue and full-term villous tissue were prepared during surgery from another patient with the same methods.

Genomic DNA was extracted from FFPE tissue sections of tumor specimens using Maxwell^® RSC DNA FFPE Kit (Promega, Madison, USA) or QIAamp DNA FFPE tissue kit ( QIAGEN, Germany) according to the manufacturer’s instructions.

EZ DNA Methylation Kit was used for bisulfite treatment of genomic DNA. The bisulfite-treated DNA was labeled with fluorescent dye using Infinium Methylation EPIC Bead Chip Kit, and loaded on Infinium Methylation EPIC Bead Chip. GenomeStudio was used for methylation pattern analysis. DNA methylation level was analyzed with Illumina DiffScore referring GenemeStudio Methylation Module v1.8 User Guide (Illumina), and markers which showed top 50 and bottom 50 DiffScore between sample tumor and surrounding normal placenta was extracted. A clustering analysis was performed and a heatmap was drawn with above extracted 100 markers. Bisulfite treatment and methylation array analysis were performed by RIKEN genesis Co., Ltd.

STR analysis was performed using AmpFLSTR™ Identifiler™ Plus PCR Amplification Kit (ThermoFisherScientific) according to the manufactural protocol. Briefly, 1.6 ng of genomic DNA purified from IC tumor tissue or its surrounded normal placental tissue were mixed with primer set and PCR master mix and subjected by PCR thermal program. PCR products were electrophoresed by DNA sequencer DNA3500 Genetic Analyzer (Applied Biosystems). Fragment analysis was performed using GeneMapper fragment analysis software (ThermoFisherScientific) and repeat numbers of each STR marker in IC tissue and surrounded normal placental tissue were compared.

Genomic testing was performed in-house using the PleSSision testing platform (Keio University Hospital, Tokyo, Japan). Libraries were generated from 50 ng of DNA per sample using the Human Comprehensive Cancer Panel, SSEL PreCap Custom Tier2, 6Hybs, SureSelectXT Low Input Reagent Kit, and SureSelectXT HS-LI Enzymatic Frag Kit (Agilent Technologies) and the library quality was assessed using the Agilent High Sensitivity D1000 ScreenTape (Agilent Technologies). Capture sequencing was performed using a 145 cancer-related gene panel (Supplemental Table S1). The enriched libraries were sequenced with a paired-end (150 bp × 2) sequencing method using the NextSeq platform (Illumina, San Diego, CA, USA). Genome annotation and curation for analyzing the sequencing data were performed using an original bioinformatics pipeline called GenomeJack (Mitsubishi Space Software, Tokyo, Japan; http://​genomejack.​net/​english/​index.​html), in which mapping of the NGS reads to the human reference genome (UCSC human genome 19) was performed using the Burrows–Wheeler Aligner [6], and the reads were realigned with ABRA [7]. For identification of single-nucleotide variants (SNVs), SAMtools was used to pile up the sequencing reads, and defective SNVs that showed conflict between pairwise reads were abandoned [8]. The criteria for mutations were as follows: the noise distributions arising from random sequencing errors were determined. Each mutation was evaluated using a binomial test (p < 0.05) to reduce random sequencing errors. We called somatic mutations by comparing the number of mismatch bases in the tumors with those in the normal controls by using the Fisher exact test (p < 0.001). The copy number of each gene was calculated as the median value of all the sequencing reads covering the target genes and compared with the median value of the control samples. We identified cancer-specific somatic gene alterations, such as SNVs, insertions/deletions (Indels), and CNAs. All the detected gene alterations in 145 cancer-related genes were annotated and curated using the COSMIC (https://​cancer.​sanger.​ac.​uk/​cosmic), ClinVar (https://​www.​ncbi.​nlm.​nih.​gov/​clinvar/​), CIViC (https://​civicdb.​org/​home), SnpEff24, and Clinical Knowledgebase (CKB) databases (https://​ckb.​jax.​org/​).

The delivered placenta showed a yellow 2 cm node and a small area of choriocarcinoma (Fig. 1). Microscopic examination showed a choriocarcinoma with a biphasic proliferation of atypical and mitotically active cytotrophoblast and syncytiotrophoblast cells. The neoplasm was restricted to the placenta and did not infiltrate the maternal basal plate (Fig. 2a, b). The placental choriocarcinoma villi were examined, and some carcinomic cell, surrounded by a normal villous mass, expressed hCG by immunohistochemical staining (Fig. 2c). When these malignant trophoblastic cells were observed by an electron microscope, there were shown to have large irregular nuclei intruding into the normal trophoblastic villi (Fig. 2d).

To investigate the origin of IC, we performed DNA STR analysis of IC tumor tissue and normal placental tissue of this case. The result of the STR analysis is shown in Fig. 3. All of analyzed STR alleles in the IC tissue is identical to those of surrounded normal placental tissue, confirming that the IC was derived from concurrent normal chorionic villous trophoblast cells.

Targeted next-generation sequencing of the patient’s trophoblastic tumor tissue was performed using an in-house assay. No somatic pathogenic mutation of 145 cancer-related genes was observed. Meanwhile, MDM2 amplification (estimated copy number, 4) was found Fig. 4.

We performed DNA Methylation analysis with Infinium Methylation EPIC Bead Chip (Illumina), and a heat map of genes with deferentially methylated CpG sites between tumor (Tumor) and surrounding normal placenta (PL) or unrelated early (Early) and term (Term) placenta samples are shown in Fig. 5. In this figure, 50 top genes with the highest methylated CpG sites and top 50 genes with the most hypo-methylated CpG sites between those samples are filtered, then followed by clustering analysis, and deferentially methylated levels were visualized with a tree-view heat map. By this visualization, genes which have deferentially methylated CpG sites between tumor and surrounding normal placenta are recognized Fig. 5.