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Written | November Responsible Editor | Upper urinary tract urothelial carcinoma (UTUC) accounts for 5% to 10% of all urothelial carcinomas [1]
.
Upper urothelial carcinoma and urothelial bladder carcinoma (UBC) have many common clinicopathological characteristics, but UTUC itself also has obvious characteristics
.
For example, UTUC occurs in the mesodermal epithelium, which may be related to Lynch syndrome.
In addition, studies have shown that UTUC may be caused by aristolochic acid [2,3]
.
However, the molecular mechanism of its pathogenesis is currently poorly understood, and there is a lack of effective biomarkers for accurate diagnosis and molecular classification
.
Not long ago, the Seishi Ogawa research group of Kyoto University in Japan published an article entitled Molecular classification and diagnostics of upper urinary tract urothelial carcinoma.
Through integrated genome analysis of 199 cases of urothelial cancer, the authors discovered 5 gene mutation classifications, gene expression, and tissue analysis.
Scientific characteristics and detection methods of DNA sequencing derived from urine sediments have high diagnostic value for the non-invasive diagnosis of urothelial cancer
.
First, the authors want to build a platform that can perform multiple analyses on UTUC
.
To this end, the authors collected 199 fresh-frozen samples of UTUC tumors from 198 patients.
One patient had two samples of UTUC because of bilateral UTUC
.
All the patients came from three different medical institutions and had not been treated with other medications before the operation
.
The authors subsequently identified somatic mutations in 199 UTUCs samples
.
The authors detected a total of 51,709 mutations, including 48,609 single-nucleotide mutations, 128 di-nucleotide mutations, and 2,972 insertion/deletion mutations
.
After combining the relevant results, the authors created a table for identifying genetic changes in UTUC.
Most of the genes affected include the TERT promoter region, KMT2D, CDKN2A, FGFR3, and TP53
.
The mutated genes in UTUC overlap with UBC to a large extent [4]
.
Although the frequencies between UTUCs and UBCs are generally highly similar, the frequency of several changes between the two tumors is quite different
.
For example, CDKN2A and KMT2D are preferentially affected in UTUC, while ERBB2 is mutated more frequently in UBC
.
The results indicate that upper urothelial carcinoma exhibits a unique pattern of gene changes according to its tumor location and progression status, which is an important basis for molecular clinical diagnosis
.
Figure 1 UTUC mutation subtypes and expression profile subtypes.
Subsequently, the authors classified the subtypes that appeared in UTUC.
The authors classified the mutation cases into hypermutant, TP53/MDM2, and RAS (HRAS/KRAS/NRAS) , FGFR3, and three-negative type (Figure 1)
.
Among them, the type with the largest proportion is the TP53/MDM2 type with 37.
7%
.
Furthermore, the authors hope to analyze the gene expression profile in UTUC
.
Through RNA sequencing of 158 UTUC samples and non-difference cluster analysis, the authors identified five subtypes of expression profiles of C1-C5
.
Most FGFR3 mutations and most hypermutation subtypes are classified into C1 expression profile subtypes, TP53/MDM2 mutations and triple negative subtypes are mainly classified into C3-C5 expression profile subtypes, and in most cases RAS mutations Mutations in one of the subtypes and a subset of FGFR3 belong to the C2 expression profile subtype (Figure 2)
.
In addition, the authors also performed a non-difference cluster analysis based on the DNA methylation status of tumor-specific CpG islands, and obtained three subclasses with different DNA methylation status
.
Finally, the authors used urine sediment DNA to target and sequence 30 common mutations in UTUC, in order to evaluate the potential of molecular classification to diagnose UTUC and achieve the purpose of non-invasive inspection
.
The authors collected urine samples from 41 cases of 1-2 months before surgery and 25 cases of postoperative urine samples of 43 patients, and urine samples of 18 non-urothelial patients, and ensured that these cohorts have Comparability of clinical and genetic backgrounds
.
The authors found that urine sediment sequencing has high accuracy (87.
7%-98.
6%) in predicting non-hypermutated subtypes.
This result suggests that urine sediment sequencing has potential value as a prognostic biomarker and diagnostic tool
.
However, there is no effective threshold for distinguishing the number of mutations between hypermutated subtypes and non-hypermutated subtypes
.
Figure 2 Working model.
In general, this work analyzes a large number of samples through comprehensive multi-omics analysis to analyze the molecular change map of upper urothelial cancer, and for the clinical analysis of upper urothelial cancer and urothelial bladder cancer.
The distinction provides important molecular diagnosis and new ideas for non-invasive diagnosis (Figure 2)
.
At the same time, these results provide a solid theoretical basis and large-scale genomics basis for better diagnosis and treatment of upper urothelial carcinoma.
.
Original link: https://doi.
org/10.
1016/j.
ccell.
2021.
05.
008 Platemaker: 11 References 1 Raman, JD et al.
Altered Expression of the Transcription Factor Forkhead Box A1 (FOXA1) Is Associated With Poor Prognosis in Urothelial Carcinoma of the Upper Urinary Tract.
Urology 94, 314.
e311-317, doi:10.
1016/j.
urology.
2016.
05.
030 (2016).
2 Therkildsen, C.
et al.
Molecular subtype classification of urothelial carcinoma in Lynch syndrome.
Molecular oncology 12, 1286-1295, doi:10.
1002/1878-0261.
12325 (2018).
3 Cerami, E.
et al.
The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data.
Cancer discovery 2, 401 -404, doi:10.
1158/2159-8290.
Cd-12-0095 (2012).
4 Guo, G.
et al.
Whole-genome and whole-exome sequencing of bladder cancer identifies frequent alterations in genes involved in sister chromatid cohesion and segregation.
Nature genetics 45,1459-1463, doi:10.
1038/ng.
2798 (2013).
Reprinting instructions [Original Articles] BioArt original articles, personal sharing is welcome, reprinting is prohibited without permission, the copyright of all published works is owned by BioArt
.
BioArt reserves all statutory rights and offenders must be investigated
.
.
Upper urothelial carcinoma and urothelial bladder carcinoma (UBC) have many common clinicopathological characteristics, but UTUC itself also has obvious characteristics
.
For example, UTUC occurs in the mesodermal epithelium, which may be related to Lynch syndrome.
In addition, studies have shown that UTUC may be caused by aristolochic acid [2,3]
.
However, the molecular mechanism of its pathogenesis is currently poorly understood, and there is a lack of effective biomarkers for accurate diagnosis and molecular classification
.
Not long ago, the Seishi Ogawa research group of Kyoto University in Japan published an article entitled Molecular classification and diagnostics of upper urinary tract urothelial carcinoma.
Through integrated genome analysis of 199 cases of urothelial cancer, the authors discovered 5 gene mutation classifications, gene expression, and tissue analysis.
Scientific characteristics and detection methods of DNA sequencing derived from urine sediments have high diagnostic value for the non-invasive diagnosis of urothelial cancer
.
First, the authors want to build a platform that can perform multiple analyses on UTUC
.
To this end, the authors collected 199 fresh-frozen samples of UTUC tumors from 198 patients.
One patient had two samples of UTUC because of bilateral UTUC
.
All the patients came from three different medical institutions and had not been treated with other medications before the operation
.
The authors subsequently identified somatic mutations in 199 UTUCs samples
.
The authors detected a total of 51,709 mutations, including 48,609 single-nucleotide mutations, 128 di-nucleotide mutations, and 2,972 insertion/deletion mutations
.
After combining the relevant results, the authors created a table for identifying genetic changes in UTUC.
Most of the genes affected include the TERT promoter region, KMT2D, CDKN2A, FGFR3, and TP53
.
The mutated genes in UTUC overlap with UBC to a large extent [4]
.
Although the frequencies between UTUCs and UBCs are generally highly similar, the frequency of several changes between the two tumors is quite different
.
For example, CDKN2A and KMT2D are preferentially affected in UTUC, while ERBB2 is mutated more frequently in UBC
.
The results indicate that upper urothelial carcinoma exhibits a unique pattern of gene changes according to its tumor location and progression status, which is an important basis for molecular clinical diagnosis
.
Figure 1 UTUC mutation subtypes and expression profile subtypes.
Subsequently, the authors classified the subtypes that appeared in UTUC.
The authors classified the mutation cases into hypermutant, TP53/MDM2, and RAS (HRAS/KRAS/NRAS) , FGFR3, and three-negative type (Figure 1)
.
Among them, the type with the largest proportion is the TP53/MDM2 type with 37.
7%
.
Furthermore, the authors hope to analyze the gene expression profile in UTUC
.
Through RNA sequencing of 158 UTUC samples and non-difference cluster analysis, the authors identified five subtypes of expression profiles of C1-C5
.
Most FGFR3 mutations and most hypermutation subtypes are classified into C1 expression profile subtypes, TP53/MDM2 mutations and triple negative subtypes are mainly classified into C3-C5 expression profile subtypes, and in most cases RAS mutations Mutations in one of the subtypes and a subset of FGFR3 belong to the C2 expression profile subtype (Figure 2)
.
In addition, the authors also performed a non-difference cluster analysis based on the DNA methylation status of tumor-specific CpG islands, and obtained three subclasses with different DNA methylation status
.
Finally, the authors used urine sediment DNA to target and sequence 30 common mutations in UTUC, in order to evaluate the potential of molecular classification to diagnose UTUC and achieve the purpose of non-invasive inspection
.
The authors collected urine samples from 41 cases of 1-2 months before surgery and 25 cases of postoperative urine samples of 43 patients, and urine samples of 18 non-urothelial patients, and ensured that these cohorts have Comparability of clinical and genetic backgrounds
.
The authors found that urine sediment sequencing has high accuracy (87.
7%-98.
6%) in predicting non-hypermutated subtypes.
This result suggests that urine sediment sequencing has potential value as a prognostic biomarker and diagnostic tool
.
However, there is no effective threshold for distinguishing the number of mutations between hypermutated subtypes and non-hypermutated subtypes
.
Figure 2 Working model.
In general, this work analyzes a large number of samples through comprehensive multi-omics analysis to analyze the molecular change map of upper urothelial cancer, and for the clinical analysis of upper urothelial cancer and urothelial bladder cancer.
The distinction provides important molecular diagnosis and new ideas for non-invasive diagnosis (Figure 2)
.
At the same time, these results provide a solid theoretical basis and large-scale genomics basis for better diagnosis and treatment of upper urothelial carcinoma.
.
Original link: https://doi.
org/10.
1016/j.
ccell.
2021.
05.
008 Platemaker: 11 References 1 Raman, JD et al.
Altered Expression of the Transcription Factor Forkhead Box A1 (FOXA1) Is Associated With Poor Prognosis in Urothelial Carcinoma of the Upper Urinary Tract.
Urology 94, 314.
e311-317, doi:10.
1016/j.
urology.
2016.
05.
030 (2016).
2 Therkildsen, C.
et al.
Molecular subtype classification of urothelial carcinoma in Lynch syndrome.
Molecular oncology 12, 1286-1295, doi:10.
1002/1878-0261.
12325 (2018).
3 Cerami, E.
et al.
The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data.
Cancer discovery 2, 401 -404, doi:10.
1158/2159-8290.
Cd-12-0095 (2012).
4 Guo, G.
et al.
Whole-genome and whole-exome sequencing of bladder cancer identifies frequent alterations in genes involved in sister chromatid cohesion and segregation.
Nature genetics 45,1459-1463, doi:10.
1038/ng.
2798 (2013).
Reprinting instructions [Original Articles] BioArt original articles, personal sharing is welcome, reprinting is prohibited without permission, the copyright of all published works is owned by BioArt
.
BioArt reserves all statutory rights and offenders must be investigated
.
