| Literature DB >> 27930669 |
Masahiro Kurobe1, Takahiro Kojima1, Kouichi Nishimura2, Shuya Kandori1, Takashi Kawahara1, Takayuki Yoshino1, Satoshi Ueno3, Yuichi Iizumi3, Koji Mitsuzuka4, Yoichi Arai4, Hiroshi Tsuruta5, Tomonori Habuchi5, Takashi Kobayashi6, Yoshiyuki Matsui6, Osamu Ogawa6, Mikio Sugimoto7, Yoshiyuki Kakehi7, Yoshiyuki Nagumo8, Masakazu Tsutsumi8, Takehiro Oikawa9, Koji Kikuchi9, Hiroyuki Nishiyama1.
Abstract
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Year: 2016 PMID: 27930669 PMCID: PMC5145148 DOI: 10.1371/journal.pone.0165109
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Characteristics of bladder cancer patients
| NMIBC | MIBC | Total | ||
|---|---|---|---|---|
| N | 60 | 44 | 104 | |
| Age (years) | Median (range) | 69 (30–87) | 72 (42–87) | 70 (30–87) |
| Gender | Male (%) | 55 (92) | 32 (73) | 87 (84) |
| Female (%) | 5 (8) | 12 (27) | 17 (16) | |
| T stage | Ta (%) | 43 (72) | ||
| Tis/T1 (%) | 17 (28) | |||
| ≧T2 (%) | 44 (100) | |||
| M stage | M1 (%) | 0 (0) | 4 (10) | |
| Grade | High grade (%) | 26 (47) | ||
| Low grade (%) | 34 (53) | |||
| Multiplicity | Solitary (%) | 24 (40) | 23 (52) | |
| Multiple (%) | 33 (55) | 15 (34) | ||
| Unknown (%) | 3 (5) | 6 (14) | ||
| Tumor size | <3 cm (%) | 41 (68) | 9 (20) | |
| >3 cm (%) | 19 (32) | 35 (80) |
Fig 1Schematic representation of how FGFR3-specific probes and TACC3-specific probes were designed.
Fig 2A schematic figure explaining how bDNA-FISH works.
Fig 3FGFR3-TACC3 fusion transcript detection by RT-PCR.
(A) Schematic representation of FGFR3-TACC3 fusion mRNA and PCR primers position. (B) Agarose gel separation of the FGFR3-TACC3 fusion specific RT-PCR amplicons. (C) Sanger sequencing chromatogram of FGFR3-TACC3 fusion specific RT-PCR products. The arrowhead and solid bar indicate breakdown point or region of the 2 genes.
Fig 4FGFR3-TACC3 fusion transcript detection by RNA-FISH.
RNA-FISH image of RT112 and RT4 (fusion-positive controls) and HSC-39 (negative control) xenograft FFPE tissue. mRNAs of FGFR3 and TACC3 were detected by RNA-ISH using fluorescent probes (Alexa 647 for FGFR3 and Alexa 546 for TACC3, respectively), and signals from FGFR3 and TACC3 were shown as red and green, respectively, in the figure. The small boxed areas are enlarged in the adjacent large boxes. Fusion mRNAs appeared in microscope images as yellow, which are merged signals from red and green colors. Cell nuclei was stained with DAPI and shown as blue. Scale bars in the figure are 10 μm. For the detection of fusion signals for each sample, image data from 2 fluorescent probes were analyzed with IN Cell Analyzer 2000 and the number of overlapped/co-localized signals was counted and divided by the total number of FGFR3 signals and TACC3 signals and plotted in a scatter graph.
Fig 5Detection of FGFR3-TACC3 fusion genes in FFPE clinical samples by RNA-FISH.
Scatter diagram of FGFR3-TACC3 co-localization ratios of 10 non-overlapping fields for each sample. The number of co-localized signals was divided by the number of FGFR3 signals and TACC3 signals, and the quotients were plotted in Y- and X-axis, respectively. Four samples in the right upper quadrant were thought to be fusion positive by RNA-FISH, and were confirmed as fusion positive by RT-PCR analysis. Small gray dots represent cases that were thought to be negative for the fusion gene.
Fig 6Representative RNA-FISH images of fusion-positive case TKB014.
The small boxed areas are enlarged in the adjacent large boxes. Scale bars in the figure are 10 μm.
Fig 7Detection of FGFR3-TACC3 fusion transcripts in clinical samples by RT-PCR.
(A) Agarose gel separation of the FGFR3-TACC3 fusion-specific RT-PCR amplicons. (B) Sanger sequencing chromatogram of FGFR3-TACC3 fusion-specific RT-PCR products. Arrowheads indicate breakdown points of the 2 genes.
Fig 8FGFR3 mutation and FGFR3-TACC3 fusion status.
(A) The heatmap shows the distribution of FGFR3 mutations and FGFR3-TACC3 fusions with respect to T stage and pathological grade. (B) Subgroup analysis of NMIBC by T stage.