Demographic and clinical data
The demographic and clinical data of patients enrolled in our cohort were summarized in Table 1. Of the enrolled patients, 72.32% were bladder cancer (81/112), and the rest were diagnosed as upper tract UC (27.68%, 31/112), including carcinoma of the renal pelvis and ureteral. The median age at diagnosed was 67 (range 25–86). The sex ratio between males and females was 2.61:1, which was close to the sex ratio (2.97:1) in Chinese UC patients reported by the national cancer center of China. The amounts of enrolled smoker and non-smoker were the same (56 versus 56).
Somatic Alterations In Chinese Uc Patients
In total, 106 of 112 samples (94.64%) had been identified with valid somatic alterations. The mean and median counts of somatic alterations per sample were 6.05 and 4, respectively. Six samples were negative for somatic mutations identification after excluding the germline alterations. The most frequently mutated genes in our cohort were TP53 (48%), KMT2D (43%), KDM6A (23%), FAT4 (21%), CREBBP (20%), ARID1A (19%) and FAT1 (18%), respectively (Fig. 1A). Notably, 62.50% (70/112) and 86.61% (97/112) patients in our cohort were identified as having actionable and oncogenic alterations according to the OncoKB database, respectively . No significant difference was found in gene prevalence between low- and high-grade urothelial carcinoma. Pathway analysis indicated that the most frequently enriched pathways were Chromatin regulatory (73.21%), RTK-RAS-MAPK (62.50%), cell cycle (53.57%), DNA damage repair (DDR, 47.32%), PI3K-mTOR (33.93%) and Wnt (32.14%), respectively (Fig. 1B). We didn’t find any significant genomic difference between high- and low-grade UC patients.
Excluded of variants identified as benign or likely benign according to the American College of Medical Genetics and Genomics (ACMG) guideline, 75.89% (85/112) patients in our cohort harbored at least one germline alteration (Supplemental Table 3). After exclusion of known and likely benign variants, 244 germline variants were identified. However, only two patients (1.85%) had variants that could be identified as pathogenic or likely pathogenic, including a ERCC4-p. Lys481fs and a BRCA2- p.Thr3030fs (Supplemental Table 3). The patient harbored deleterious BRCA2 germline variants was also concurrent with prostate cancer. None pathogenic or likely pathogenic germline variant associated with Lynch syndrome, including MLH1, MSH2, MSH6 and PMS2 genes, was identified in UTUC and UC patients of our cohort.
Differences of somatic gene alterations in UC patients between our cohort and Western cohort
To determine the potential difference of genomic features between Western and Chinese UC patients, we compared the alterations data of the selected 92 genes between our cohort and Western cohorts (UC data published by TCGA and UTUC data published by MSKCC). The prevalence of alterations in FGFR4, KDM5C, TERT, PDGFRB, FLT3, FLCN, MSH6, FLT1 were higher in UCB patients in our cohort, compared with TCGA (Fig. 2A). As for UTUC, a higher mutated frequency of multiple genes, including TP53, LRP1B, KMT2D, FAT4, BRCA1, FGFR2 and BRIPI, were found in our cohort (Fig. 2B). On the contrary, the mutation frequency of FGFR3 gene in the MSKCC cohort was three times higher than that in our cohort (48.24% versus 16.13%, p < 0.001).
Differences Of Somatic Gene Alterations Between Utuc And Ucb
To elucidate the differences of somatic gene alterations between UTUC and UCB, we compared the alterations from 81 UCB samples and 31 UTUC samples in our cohort. The genomic features of UCB and UTUC were similar, while KMT2D (34.57% vs 64.52%, p < 0.01), HRAS (3.7% vs 19.35%, p < 0.01) and CDKN2A (2.47% vs 12.9%, p < 0.05) were more mutated in UTUC than in UCB (Fig. 2C). A higher mutated frequency of HRAS was also presented in UTUC compared with UCB in Western cohorts, but with additionally significantly different prevalence in FGFR3, TP53, TERT, RB1, LRP1B, FAT4, KMT2A, ARID1A, BRIP1, TSC1 genes (Fig. 2D).
Genomic Alterations In Fgfr Genes
28.57% (32/112) patients had at least one somatic alteration in FGFR genes (including FGFR1, FGFR2, FGFR3 and FGFR4), but only 11 patients’ alternations could be defined as gain of function (Fig. 3A). Notably, six of these patients had multiple oncogenic alterations in FGFR genes. Same to previous studies’ results, the most altered gene was FGFR3 (13.39%). Hotspot variants, including FGFR3-p.Ser249Cys, p.Arg248Cys and p.Tyr373Cys were identified in six samples, while FGFR3-TACC3 fusion was only identified in two patients. Three novel variants (defined as unreported in any other research or single nucleotide polymorphism database before and without ExAC frequency), including p.His349Asn, p.Val166Met and p.Thr755Lys of FGFR3 were identified, though the functions were still unknown (Fig. 3B). Nine patients (8.04%) were identified with FGFR2 alterations, of which only three alterations could be defined oncogenic, including one p.Asn549Lys, one p.Lys659Met and one copy number gain (copy number 32.87). No FGFR2 fusion was identified. Four novel variants with unknown function, including p.Gly305Arg, p.Tyr207Phe, p.Met803Leu and p.Gln683Ter of FGFR2 gene were identified in this study. Only six patients carried FGFR1 gene alterations, and half of them were amplification. Eight patients (all were bladder cancer) carried nonsynonymous single nucleotide variants with unknown function in FGFR4 gene.
Genomic Alterations In Erbb Family
20 of our cases (17.86%) carried somatic alterations in the ERBB genes (EGFR, ERBB2 and ERBB3), and three of them had dual alterations (Fig. 3C). Five patients (4.46%) carried EGFR gene alteration and two of them had EGFR copy number gain. Notably, one patient had an activated EGFR exon 20 insertion (EGFR-p.Val769_Asp770insAspAsnPro) and copy number gain. We observed ERBB2 alterations in 12 patients (10.71%) s, and most of the oncogenic alterations located in furin-like cysteine rich region (amino acid 190–343) and protein tyrosine kinase domain (amino acid 721–975) (Fig. 3D). Two of the five identified ERBB3 alterations were in the furin-like cysteine rich region (amino acid 182–332) and oncogenic.
Somatic Alterations In Dna Repair Pathway
We observed 47.32% of cases had alterations in the DDR pathway as defined by the MSKCC DDR gene panel , including 37 (45.68%, 37/81) UCB patients and 16 (51.61%,16/31) UTUC patients, respectively. Distribution of alterations among specific DDR pathway was similar, with slight enrichment in Fanconi anemia (FA) pathway (Fig. 4A). The most frequently mutated DDR genes were BRCA2 (10.71%), ATM (9.82%), ERCC2 (8.93%), BRCA1 (7.14%) and BRIP1 (6.25%), respectively (Fig. 4B). Among patients carried DDR gene alterations, only 16 of them (14.29%) had at least one known or likely deleterious somatic DDR alterations (Fig. 4C). The distribution of specific genes was exhibited in Fig. 5C, and the most frequently mutated DDR genes with known or likely deleterious variants were ATM (n = 7, 31.82%) and BRCA2 (n = 5, 22.73%). Eighteen patients (16.07%) carried somatic alterations in DNA mismatch repair (MMR) genes, including in MLH1, MSH2, MSH6 and PMS2. The majority of these MMR gene alterations were unknown of function, with four exceptions of alterations in MSH2 and MLH1, which could be defined as loss of function.
Concordance of genetic alterations between ctDNA in serum and matched tumor tissue
Twenty matched tumor tissue and blood samples were collected to comprehend the concordance and discordance of genomic alterations between different sample types in UC. Only three patients’ matched samples were collected with an interval time over one month (7 months for P074, 18 months for P084 and 34 months for P110, respectively). In total, 99 and 91 somatic alterations were identified in tumor and serum ctDNA samples from 20 patients who underwent genomic testing for matched tumor tissue and serum ctDNA samples, respectively. Only one patient’s ctDNA was negative for valid somatic alterations identification, while matched tumor samples were positive for alterations calling. Conversely, in Patient 20, ctDNA analysis revealed oncogenic mutations in PIK3CA, TP53, ARID1A and KDM6A with allele fractions all beyond 3%, for which there was no corresponding valid alteration in the matched tissue sample (Fig. 5A). There was no significant difference between tissue and blood in the median number of genomic alterations (4 versus 4). By comparison of blood and matched tumor tissue, the overall concordance for genomic alterations and altered genes identified in matched samples was 42.97% (0-100%) and 46.83% (0-100%), respectively (Table 2). Among the genomic alterations, 48 of them were in concordance between ctDNA and tumor tissue. Fifteen actionable alterations were identified in tissue defined according to the Oncobkb database, and 60% of them were shared in matched ctDNA (Fig. 5B). Notably, 41 of 91 (48.35%) alterations detected in ctDNA were not detected in the corresponding tissue sample. Specifically, 12 of them (27.27%) were oncogenic mutations and 3 of 44 (6.82%) could be identified as actionable, including a PIK3CA activated hot-spot, PTEN frameshift and KDM6A frameshift mutation.