Abstract
PURPOSE
Patients with residual invasive bladder cancer after neoadjuvant chemotherapy (NAC) and radical cystectomy have a poor prognosis. Data on adjuvant therapy for these patients are conflicting. We sought to evaluate the natural history and genomic landscape of chemotherapy-resistant bladder cancer to inform patient management and clinical trials.
METHODS
Data were collected on patients with clinically localized muscle-invasive urothelial bladder cancer treated with NAC and cystectomy at our institution between May 15, 2001, and August 15, 2019, and completed four cycles of gemcitabine and cisplatin NAC, excluding those treated with adjuvant therapies. Survival was estimated using the Kaplan-Meier method, and multivariable Cox proportional hazards models were used to identify predictors of recurrence-free survival (RFS). Genomic alterations were identified in targeted exome sequencing (Memorial Sloan Kettering Integrated Mutation Profiling of Actionable Cancer Targets) data from post-NAC specimens from a subset of patients.
RESULTS
Lymphovascular invasion (LVI) was the strongest predictor of RFS (hazard ratio, 2.15 [95% CI, 1.37 to 3.39]) on multivariable analysis. Patients with ypT2N0 disease without LVI had a significantly prolonged RFS compared with those with LVI (70% RFS at 5 years). Lymph node yield did not affect RFS. Among patients with sequencing data (n = 101), chemotherapy-resistant tumors had fewer alterations in DNA damage response genes compared with tumors from a publicly available chemotherapy-naïve cohort (15% v 29%; P = .021). Alterations in CDKN2A/B were associated with shorter RFS. PIK3CA alterations were associated with LVI. Potentially actionable alterations were identified in more than 75% of tumors.
CONCLUSION
Although chemotherapy-resistant bladder cancer generally portends a poor prognosis, patients with organ-confined disease without LVI may be candidates for close observation without adjuvant therapy. The genomic landscape of chemotherapy-resistant tumors is similar to chemotherapy-naïve tumors. Therapeutic opportunities exist for targeted therapies as adjuvant treatment in chemotherapy-resistant disease.
INTRODUCTION
The standard of care for patients with muscle-invasive bladder cancer (MIBC) is cisplatin-based neoadjuvant chemotherapy (NAC), followed by radical cystectomy. Patients with residual muscle-invasive or node-positive bladder cancer after NAC generally have a poor prognosis with 5-year recurrence rates between 38% and 50%, although some have prolonged survival without recurrence or additional treatment.1–3
Recently, nivolumab, a PD-1 inhibitor, became the first US Food and Drug Administration (FDA)–approved adjuvant therapy for patients with residual disease at cystectomy on the basis of improved metastasis-free survival compared with placebo.4 Although PD-L1 staining has some value as a biomarker in this space, it remains incompletely clear which patients derive the most clinical benefit from such treatments, as another large adjuvant trial testing atezolizumab, a PD-L1 inhibitor, failed to demonstrate an improvement in disease-free survival compared with observation.5,6 While preliminary data from the AMBASSADOR pembrolizumab trial (ClinicalTrials.gov identifier: NCT03244384) support a role for adjuvant immunotherapy in some patients after cystectomy, there exists a lack of reliable risk stratification for patients with chemotherapy-resistant disease. Identification of prognostic factors would distinguish patients for whom observation can be safely recommended from those who should strongly consider adjuvant treatment.
Similarly, tumor-specific molecular characteristics that may guide treatment selection for patients with chemotherapy-resistant bladder cancer have been incompletely evaluated. Most molecular characterization efforts in bladder cancer have focused on treatment-naïve samples or on genomic transcriptomic factors associated with response to NAC.7–9 Other studies have evaluated the impact of NAC on residual disease with limited clinical correlation.10–12
Therefore, to inform the interpretation of recently reported and ongoing adjuvant trials and to guide the development of future trials, we sought to determine the extent to which clinicopathologic factors influence recurrence risk and survival in patients with chemotherapy-resistant bladder cancer. Within a subset of this cohort, we analyzed targeted exome sequencing data to better define the genomic landscape and molecular correlates of chemotherapy-resistant bladder cancer.
METHODS
Clinical Cohort
After Institutional Review Board (IRB) approval, we performed a retrospective analysis of patients undergoing cystectomy at Memorial Sloan Kettering Cancer Center from May 15, 2001 (date of data release from the seminal SWOG8710 NAC clinical trial) to August 15, 2019 (date of query). Only patients with predominant urothelial carcinoma histology and clinical stage cT2–4aN0M0 who completed all four planned cycles of gemcitabine and cisplatin NAC followed by cystectomy and pelvic lymph node (LN) dissection with curative intent that demonstrated persistent residual muscle-invasive (ypT2–4Nany) or node-positive (ypTanyN1–3) disease in their post-NAC cystectomy pathology specimen were included. We excluded patients who received adjuvant therapy (any systemic therapy or radiation therapy). Central pathologic or re-review was not performed; however, all specimens were reviewed by fellowship-trained genitourinary pathologists with standard reported variables including the presence or absence of lymphovascular invasion (LVI).
Genomic Sequencing
A subset of the clinical cohort was enrolled on an IRB-approved prospective protocol (ClinicalTrials.gov identifier: NCT01775072) and underwent targeted exome capture sequencing of post-NAC primary bladder tumor obtained from cystectomy using the Memorial Sloan Kettering Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT) assay.13 To increase the number of samples available for sequencing, we expanded our criteria for the genomic analysis to include patients who received three or four cycles of NAC as well as those who received adjuvant therapy. To explore alterations potentially influenced by NAC, we identified a comparator group of patients in the TCGA with bladder cancer who did not receive NAC and had residual invasive disease at the time of radical cystectomy (≥pT2 or any node positive disease).9 DNA damage repair (DDR) genes were defined as previously described using a 34-gene panel.14 Tumor mutational burden (TMB) was measured as the number of nonsynonymous mutations per megabase sequenced. Comparisons of DDR alteration frequency and TMB between cohorts only included genes that were sequenced in both MSK-IMPACT and the TCGA. The functional significance of genomic alterations was categorized according to OncoKB, which assigns a level of supporting evidence to specific alterations on the basis of drug labeling, NCCN guidelines, expert opinion, and the scientific literature.15 All genomic data presented are publicly available at cBioPortal.16
Analysis
Our primary objective was to identify patient and tumor factors associated with recurrence-free survival (RFS) and overall survival (OS). RFS was defined as the time from cystectomy to distant recurrence, soft tissue/pelvic recurrence, or bladder cancer death. Urinary tract recurrences were not considered as events. Deaths from other causes or unknown causes (one patient) were censored at the date of death. OS was defined as the time from cystectomy to death from any cause. Patients who did not experience events were censored at last follow-up date for RFS and OS. The Kaplan-Meier method was used to estimate RFS and OS probabilities, and the log-rank test was used to compare groups. Multivariable Cox regression was used to identify associations between factors of interest and OS and RFS. Genomic alteration frequencies were compared using the chi-squared or Fisher exact test and TMB using the Wilcoxon rank-sum test. P values were adjusted for multiple comparisons using the Benjamini-Hochberg false discovery rate method. All analyses were conducted in R version 4.1.0 (R Core Development Team, Vienna, Austria).
RESULTS
Natural History of Chemotherapy-Resistant Bladder Cancer
In total, 3,097 patients with bladder cancer underwent cystectomy at Memorial Sloan Kettering (MSK) between May 15, 2001, and August 15, 2019 (Fig 1A). We focused our analysis on 202 patients who had ypT2–T4a and/or node-positive bladder cancer after four cycles of gemcitabine and cisplatin who were initially managed with observation without any adjuvant therapy (clinicodemographics presented in Table 1; Appendix Table A8). Of the total cohort, the median age at surgery was 66 (IQR, 59–71) years, and 147 patients (73%) were male. A total of 102 patients (51%) experienced disease recurrence, and 79 patients (39%) died, of whom 69 patients (34%) died of bladder cancer. Nine patients died of other causes, and one patient died of unknown cause. The median follow-up calculated among those alive at last follow-up was 3 years (range, <1 week to 11 years). The median RFS was 2.5 years (95% CI, 1.6 to 4.5 years), with a 2-year RFS of 52% (95% CI, 45 to 60; Fig 1B). The median OS was 3.9 years (95% CI, 3.4 to 4.6 years), with a 2-year OS of 70% (95% CI, 64 to 77; Fig 1C). While this cohort excluded patients who received any adjuvant therapy, treatments after disease recurrence were diverse and reflect the evolving therapeutic and clinical trial landscape during this period (Appendix Table A1).
FIG 1.
Clinical cohort and outcomes. (A) Flow diagram of patients included in the clinical (n = 202) and genomic (n = 101) analyses. (B) RFS and (C) OS in the clinical analysis. (D) Sankey diagram illustrating the flow of clinical stage, pathologic stage at radical cystectomy, and recurrence status at 2 years among patients included in the clinical analysis. (E) RFS stratified according to the presence of LVI among patients with clinically localized (ypT2N0) disease (n = 54). GC, gemcitabine/cisplatin; LTFU, lost to follow-up; LVI, lymphovascular invasion; MIBC, muscle-invasive bladder cancer; MSKCC, Memorial Sloan Kettering Cancer Center; NAC, neoadjuvant chemotherapy; OS, overall survival; RFS, recurrence-free survival; TCGA, The Cancer Genome Atlas.
TABLE 1.
Clinical and Demographic Characteristics of the Overall Cohort
| Characteristic | N = 202 |
|---|---|
| Sex, No. (%) | |
| Female | 55 (27) |
| Male | 147 (73) |
| Age at surgery, median (IQR) | 66 (59–71) |
| Primary v secondary, No. (%) | |
| Primary | 161 (80) |
| Secondary | 41 (20) |
| Clinical stage, No. (%) | |
| T2 | 132 (65) |
| T3 | 58 (29) |
| T4a | 12 (5.9) |
| Variant histology, No. (%) | 89 (44) |
| Pathologic stage groups, No. (%) | |
| ≤pT2 | 68 (34) |
| pT3 | 107 (53) |
| pT4 | 27 (13) |
| Concurrent carcinoma in situ,a No. (%) | 122 (61) |
| Lymphovascular invasion, No. (%) | 97 (48) |
| Positive soft tissue surgical margins, No. (%) | 17 (8.4) |
| Lymph node involvement, No. (%) | 61 (30) |
Abbreviation: CIS, carcinoma in situ.
One patient with unknown CIS status.
Patient and Tumor Characteristics Associated With Clinical Outcomes
To refine risk stratification of chemotherapy-resistant bladder cancer for adjuvant treatment and clinical trials, we sought to identify clinicopathologic correlates of RFS. Consistent with non-NAC studies, our univariate analysis found that pathologic T stage, positive soft tissue surgical margins (STSM), LVI, and LN involvement and percent positive LNs were associated with an increased risk of disease recurrence and OS (Appendix Table A2).17 Secondary muscle-invasive disease was not associated with worse RFS in this cohort potentially because we intentionally selected a high-risk cohort with chemotherapy-resistant disease that likely reduced differences in outcomes between primary and secondary disease.18 On multivariable analysis, LVI and LN involvement had a strong association with both RFS (hazrad ratio [HR], 2.15 [95% CI, 1.37 to 3.39]; HR, 1.87 [95% CI, 1.20 to 2.90]) and OS (HR, 2.33 [95% CI, 1.38 to 3.93]; HR, 1.79 [95% CI, 1.10 to 2.91]) after adjusting for other known prognostic factors (Table 2). No statistical interaction was identified between LVI and LN involvement (LVI × LN; P = .4). We found no univariable association for RFS with the number of LN removed during surgery, whether stratified by the median LN yield (24 nodes), divided into quartiles, or analyzed as continuous variable or using restricted cubic splines (data not shown).
TABLE 2.
Multivariable Cox Proportional Hazards Analysis of Factors Associated With RFS and OS (N = 202)
| RFS |
OS |
|||
|---|---|---|---|---|
| Variable | HR (95% Cl) | P | HR (95% Cl) | P |
|
| ||||
| Pathologic stage groups | ||||
|
| ||||
| ≤pT2 | - | - | ||
|
| ||||
| pT3 | 1.77 (1.03 to 3.04) | .038 | 1.52 (0.83 to 2.80) | .2 |
|
| ||||
| pT4 | 3.02 (1.53 to 5.97) | .002 | 1.85 (0.84 to 4.08) | .13 |
|
| ||||
| Lymphovascular invasion | 2.15 (1.37 to 3.39) | <.001 | 2.33 (1.38 to 3.93) | .002 |
|
| ||||
| Soft tissue surgical margins | ||||
|
| ||||
| Negative | - | - | ||
|
| ||||
| Positive | 1.35 (0.68 to 2.68) | .4 | 1.45 (0.66 to 3.19) | .4 |
|
| ||||
| Lymph node involvement | 1.87 (1.20 to 2.90) | .005 | 1.79 (1.10 to 2.91) | .02 |
NOTE. Bold values are statistically significant.
Abbreviations: HR, hazard ratio; OS, overall survival; RFS, recurrence-free survival.
To better determine which patients with chemotherapy-resistant bladder cancer could be safely observed without the need for adjuvant therapy, we evaluated outcomes among the subgroup of 54 patients with organ-confined ypT2N0 disease (Fig 1D). The demographics of this subgroup were similar to those of the overall cohort, although a smaller proportion had LVI (13% v 48%; Appendix Table A3). At a median follow-up of 3.5 years (range, 1 month-10 years), a total of 14 patients in this subgroup experienced disease recurrence. Univariate analysis showed that positive STSM was significantly associated with RFS within this subset, and LVI was associated with both risk of recurrence and risk of death (Appendix Table A4; Fig 1E).
Genomic Landscape of Chemotherapy-Resistant Bladder Cancer
To characterize the molecular landscape of chemotherapy-resistant bladder cancer, we analyzed targeted exome sequencing (MSK-IMPACT) data from post-NAC cystectomy tumor specimens from the 101 patients with such data available and compared them with existing TCGA data on 357 chemotherapy-naïve patients with pT2–4a and/or node-positive disease (Fig 2A). Consistent with the known association between DDR alterations and cisplatin sensitivity, we identified significantly fewer oncogenic DDR alterations in the chemotherapy-resistant cohort (15/101, 14.9% v 104/357, 29%; P = .021; Fig 2B), although the frequency of alterations in any single gene did not significantly differ.14 There was only one patient with a chemotherapy-resistant tumor harboring a somatic ERCC2 N238S missense mutation, which has been associated with cisplatin sensitivity.19,20 To investigate this further, targeted exome sequencing was performed on this patient’s pre-NAC biopsy specimen, which revealed the same ERCC2 N238S mutation. This patient had ypT3N0 disease but has remained recurrence-free for over 4 years after cystectomy, suggesting a benefit of chemotherapy despite residual disease. To support our findings for a reduction in DDR alterations after NAC, we also queried a publicly available data set from an analysis of clonal evolution in advanced and metastatic bladder cancer that included 20 chemotherapy-resistant samples after NAC with whole-exome sequencing data.11 Similarly, we found no DDR alterations after excluding variants of unknown significance.
FIG 2.
Comparison of genomic features between chemotherapy-resistant patients with sequencing data (n = 101) and chemotherapy-naïve patients in TCGA. (A) Oncoprint comparing clinical and molecular characteristics as well as genomic alterations. (B) Comparison of DDR alterations included in a 34-gene panel.13 (C) Comparison of TMB calculated using only alterations in genes sequenced in MSK-IMPACT. DDR, DNA damage repair; LNI, lymph node involvement; LVI, lymphovascular invasion; MSKCC, Memorial Sloan Kettering Cancer Center; MSK-IMPACT, Memorial Sloan Kettering Integrated Mutation Profiling of Actionable Cancer Targets; NS, not significant; TCGA, The Cancer Genome Atlas; TMB, tumor mutational burden.
Alterations in DDR genes may give rise to higher mutational burden and may influence immunotherapy response.20 Despite a significant difference in DDR alteration frequency between the chemotherapy-resistant and chemotherapy-naïve cohorts, no significant difference in TMB was observed (9.7 v 7.1 mut/mb; P = .77; Fig 2C) in our cohort.
Genomic Correlates of Recurrence and Actionable Genomic Alterations in Chemotherapy-Resistant Bladder Cancer
To identify potential molecular biomarkers in chemotherapy-resistant bladder cancer, we evaluated the association with RFS of genes in which at least 10 oncogenic or likely oncogenic alterations (>10% prevalence) were observed in our cohort (Fig 3A). We found that CDKN2A/B deletions carried the strongest association with recurrence, although this did not reach statistical significance (n = 13/ 101; HR, 1.89 [95% CI, 0.96 to 3.75]; P = .068; Fig 3B). Of note, these associations were exclusive to the chemotherapy-resistant cohort and were not identified in the TCGA chemotherapy-naïve cohort (Appendix Table A5).
FIG 3.
Genomic correlates of recurrence and actionable genomic alterations. (A) Swimmer’s plot and oncoprint stratified by presence of CDKN2A/ B deletions. (B) RFS according to CDKN2A/B deletion status. (C) Fraction of patients with potentially actionable alterations in specific genes as categorized by OncoKB. (D) Number of specific alterations and OncoKB level. LN, lymph node; LVI, lymphovascular invasion; NA, not applicable; RC, radical cystectomy; RFS, recurrence-free survival; STSM, soft tissue surgical margins.
Given the strong associations between LVI, LN involvement, and clinical outcomes (both RFS and OS), we investigated genomic differences between these groups and found that PIK3CA alterations were more prevalent in patients with LVI (11/55, 20%) versus those without LVI (2/45, 4.4%), although the difference was not significant after false discovery rate correction (P = .021; q = 0.3). Rates of CDKN1A mutations and CDKN2A/B deletions were higher in patients with LVI; however, differences were not statistically significant (Appendix Table A6). There were no significant differences in prevalence in tested genes between those with and without LN involvement (Appendix Table A7).
Finally, we explored the prevalence and co-occurrence patterns of potentially actionable genomic alterations in the MSK chemotherapy-resistant cohort to guide current and future adjuvant treatment strategies. Of 101 patients, 78 (77%) had oncogenic or likely oncogenic alterations with annotated levels. Nine (9%) had at least one level 1 alteration, six (6%) had level 3A, 39 (39%) had level 3B, and 24 (24%) had level 4 as highest level alteration as defined by OncoKB, suggesting several potential therapeutic options (Fig 3C). A total of 163 oncogenic or likely oncogenic alterations were identified with level 4 or above classification, with level 4 KDM6A and level 4 ARID1A being the most prevalent (Fig 3D). Importantly, alterations in FGFR3 and ERBB2 were mutually exclusive and present in 10 (9.9%; eight mutations, two fusions) and 12 (12%; seven mutations, five amplifications) patients, respectively.
DISCUSSION
Patients with chemotherapy-resistant muscle-invasive or node-positive bladder cancer are often candidates for adjuvant immunotherapy after radical cystectomy. Our study found that in patients with pathologically localized chemotherapy-resistant disease (ie, ypT2N0), the absence of LVI was associated with an overall favorable prognosis. We also provide benchmark outcomes data in a homogenous population of patients with chemotherapy-resistant localized MIBC (defined as ≥ypT2 or ypN1). Approximately 50% of patients experienced recurrence within 2 years, underscoring the need for better risk stratification and effective adjuvant treatment options. Among the 101 chemotherapy-resistant tumors with genomic data available, oncogenic DDR gene alterations were less frequent than among chemotherapy-naïve tumors in the TCGA (especially in ERCC2, although this was not statistically significant). Genomic landscapes were otherwise similar, and more than 75% of patients with chemotherapy-resistant tumors had clinically actionable alterations that could inform treatment strategies and future clinical trials.
Several previous studies have found the presence of LVI to be independently associated with worse RFS, cancer-specific survival, and OS.21,22 In our study, the absence of LVI in patients with clinically localized disease (ypT2N0) was associated with near 70% RFS at 5 years. However, LVI status is not a criterion for adjuvant therapy and is not included in the AJCC staging system.23 While ypT2N0 patients are now candidates for adjuvant immunotherapy in the United States based on the recently published Checkmate 274 data, our data suggest that patients with ypT2N0 disease after chemotherapy without LVI may be able to forgo treatment with adjuvant therapy and instead be monitored by close observation.4 Circulating cell-free tumor DNA has been shown to potentially identify high-risk patients that benefit from adjuvant immunotherapy after radical cystectomy, and our results suggest that LVI may also identify a cohort of high-risk localized ypT2N0 patients who would benefit from additional therapy.24 Therefore, the presence of LVI should thus be evaluated and compared with circulating cell-free tumor DNA as a possible complementary or supplementary biomarker.
Our exploration of the genomic landscape of chemotherapy-resistant bladder cancer provides a lens through which we can interpret the existing data for adjuvant therapy in NAC-treated patients. First, we found a lower frequency of oncogenic DDR alterations in the chemotherapy-resistant cohort compared with the TCGA chemotherapy-naïve cohort, which likely results from DDR-mutated tumors being more likely to respond to chemotherapy and thus absent from post-NAC tumors.14 This carries treatment selection implications as fewer oncogenic DDR alterations may be associated with lower TMB and, in turn, poorer responses to checkpoint blockade.25 However, a recently reported adjuvant trial of nivolumab, a PD-1 inhibitor, found no association between the receipt of NAC and response to checkpoint blockade.4 The relatively short course of NAC (usually 9–12 weeks) may not result in significant clonal evolution compared with longer courses of systemic therapy for metastatic disease.10 To support this, we found no significant differences in TMB between the MSK chemotherapy-resistant cohort and the TCGA chemotherapy-naïve cohort despite significant differences in oncogenic DDR alterations between the two groups, suggesting that additional factors beyond DDR influence mutational burden and immunotherapy response.
While our findings that alterations in CDKN2A/B are associated with worse RFS in a chemotherapy-resistant cohort requires further validation, these findings also suggest unique therapeutic opportunities for adjuvant therapies in these patients at highest risk for recurrence. For example, loss of CDKN2A/B may be sensitizing to CDK4/6 inhibitors and often co-occurs with deletion of adjacent genes, including methylthioadenosine phosphorylase, which creates synthetic lethality vulnerabilities.23–25 While FGFR3 alterations have previously been associated with lower responses to chemotherapy and worse RFS, these alterations also provide rationale for treatment with an FGFR2–3 inhibitor that is FDA-approved for more advanced disease.26,27
The implications of associations of specific alterations with features of invasiveness are less clear. We found that PIK3CA alterations are more common in patients with LVI compared with those without LVI. This is corroborated by several studies that have demonstrated an association between PIK3CA overexpression and epithelial-to-mesenchymal transitions and increased metastasis in mouse models, human cell lines, and in human data sets, including increased lymphatic metastasis in human bladder cancer cell lines.26–28 Although previous clinical studies using PIK inhibitors in metastatic urothelial cancer demonstrated significant toxicity, it is possible that newer less toxic agents could be developed and warrant revisiting in urothelial cancer.29 These associations require further validation in larger cohorts and mechanistic interrogation through functional studies.
Our study has several advantages compared with prior studies that included heterogeneous patient cohorts and treatment regimens.1,2 For our clinical analysis, we included only patients who received four cycles of gemcitabine and cisplatin to capture biologically chemotherapy-resistant disease. We also excluded patients treated with adjuvant therapy to accurately study its natural history. Still, our study has limitations. First, patients were treated at a high-volume cancer center, and therefore, our data may not be generalizable. Our data also may not apply to patients treated with regimens other than four cycles of gemcitabine and cisplatin. Exclusion of patients unable to complete four cycles of NAC may have selected for patients with more aggressive disease who are less likely to respond to treatment. Our study period also did not include cases after the approval of antibody-drug conjugates and erdafitinib which may affect the OS analysis. Second, our genomic analysis is limited by small numbers despite a study period of 18 years from a high-volume cancer center. Furthermore, we compare targeted exome sequencing data from the MSK cohort with whole-exome sequencing data from TCGA, which have different sequencing depths and assess alterations in different sets of genes. Fusions and structural variant data were also available and analyzed for all but six cases in the MSK chemotherapy-resistant cohort, whereas that data were not available from TCGA. While our study only evaluated genomic data, additional multi-omics including transcriptomics and an analysis of molecular subtypes may be needed to fully characterize biologically chemotherapy-resistant bladder cancer to define biomarkers to guide adjuvant treatment selection. Finally, while no interaction between LVI and LN involvement was identified, small numbers limit our ability to detect such an interaction and further analysis in larger cohorts is warranted.
In conclusion, patients with residual muscle-invasive or node-positive bladder cancer after NAC and radical cystectomy have a poor prognosis. However, patients with localized chemotherapy-resistant disease (ypT2N0) without LVI had favorable outcomes, potentially warranting close observation rather than adjuvant immunotherapy. Compared with chemotherapy-naïve tumors from the TCGA, chemotherapy-resistant tumors had fewer DDR alterations but similar TMB. Finally, potentially actionable alterations are common (approximately 75%) in chemotherapy-resistant tumors, supporting the use of next-generation sequencing to determine eligibility for clinical trials and novel treatment options for these high-risk patients.
CONTEXT.
Key Objective
What are the clinical outcomes, molecular characteristics, and actionable genomic alterations present in chemotherapy-resistant bladder cancer?
Knowledge Generated
We found that chemotherapy-resistant tumors have fewer DNA damage response alterations yet similar tumor mutational burden compared with chemotherapy-naïve tumors. Chemotherapy-resistant yet localized tumors without evidence of lymphovascular invasion (LVI) have recurrence-free survival near 70%. PIK3CA alterations were associated with LVI, and CDKN2A/B alterations were associated with worse outcomes. More than three quarters of chemotherapy-resistant tumors had potentially actionable alterations.
Relevance
Our findings suggest that patients with chemotherapy-resistant yet localized disease without lymphovascular invasion may be observed closely without adjuvant therapy. Chemotherapy-resistant tumors have fewer DNA damage repair alterations but many have other actionable alterations that could guide adjuvant therapy.
SUPPORT
Supported in part by the National Institutes of Health/National Cancer Institute (NIH/NCI) with a Cancer Center Support Grant to Memorial Sloan Kettering Cancer Center (P30 CA008748) and by the Sidney Kimmel Center for Prostate and Urologic Cancers at MSK, NIH/NCI R01CA276946, NCI Specialized Programs of Research Excellence (SPORE) in Bladder Cancer (P50 CA221745), MSKCC Bladder Cancer SPORE Career Enhancement Award, NIH/NCI K12 Paul Calabresi Career Development Award for Clinical Oncology (K12 CA184746), Cycle for Survival, Marie-Joseé and Henry R Kravis Center for Molecular Oncology, MSKCC Department of Surgery Research Award, Wofchuck Family Young Investigator Award, the Bladder Cancer Advocacy Network Young Investigator Award, and the AUA Urology Care Foundation SUO Research Scholar.
APPENDIX
TABLE A1.
Treatment at First Recurrence in Patients With Chemotherapy-Resistant Bladder Cancer (n = 102)
| Line of Therapy | Category | Drug | n |
|---|---|---|---|
| 1 | Chemotherapy (n = 44) | Pemetrexed | 10 |
| Paclitaxel | 13 | ||
| Gemcitabine/carboplatin | 5 | ||
| Docetaxel | 2 | ||
| Ifosfamide/paclitaxel/cisplatin | 2 | ||
| MVAC | 2 | ||
| 5-FU/MMC with radiotherapy | 1 | ||
| Carboplatln | 1 | ||
| Carboplatin/etoposide | 1 | ||
| Carboplatin/paclitaxel | l | ||
| Cisplatin/gemcitabine | 1 | ||
| Cisplatin/gemcitabine/docetaxel | 1 | ||
| Docetaxel/ramicirumab | 1 | ||
| Gemcitabine | 1 | ||
| Paclitaxel/carboplatin/bevacizumab | 1 | ||
| Pemetrexed/docetaxel | 1 | ||
| 1 | Immunotherapy (n = 32) | Pembrolizumab | 18 |
| Atezolizumab | 8 | ||
| Nivolumab | 4 | ||
| Ipilimumab/nivolumab | 2 | ||
| 1 | Targeted therapy (n = 5) | Sunitinib | 1 |
| Everolimus | 1 | ||
| Buparlisib | 1 | ||
| Rucaparib | 1 | ||
| Clinical trial | 1 | ||
| 1 | Unknown (n = 1) | Treatment at outside facility | 1 |
| 1 | Palliative care (n = 20) | ||
| 2 | Chemotherapy (n = 10) | Paclitaxel | 5 |
| Docetaxel | 2 | ||
| Pemetrexed | 2 | ||
| Cisplatin | 1 | ||
| 5-FU/leucovorin | 1 | ||
| 2 | Immunotherapy (n = 8) | Atezolizumab | 7 |
| Ipilumumab/nivolumab | 2 | ||
| Pembrolizumab | 1 | ||
| Nivolumab/cabozantinib | 1 | ||
| 2 | Targeted therapy (n = 4) | Enfortumab vedotin | 2 |
| Erdafitinib | 1 | ||
| Infigratinib | 1 | ||
| Sunitinib | 1 | ||
| 3 | Chemotherapy (n = 2) | Carboplatin/paclitaxel | 1 |
| 5-FU/leucovorin | 1 | ||
| 3 | Targeted therapy (n = 1) | Mocetinostat | 1 |
Abbreviations: 5-FU, 5-fluorouracil; MMC, mitomycin C; MVAC, methotrexate, vinblastine, adriamycin, cisplastin.
TABLE A2.
Univariable Associations With RFS and OS
| Variable | RFS |
OS |
|||
|---|---|---|---|---|---|
| N | HR (95% CI) | P | HR (95% CI) | P | |
|
| |||||
| Sex | 202 | ||||
|
| |||||
| Female | - | - | |||
|
| |||||
| Male | 1.08 (0.69 to 1.68) | .7 | 1 (0.60 to 1.67) | >.9 | |
|
| |||||
| Age at surgery | 202 | 1.01 (0.99 to 1.03) | .4 | 1.02 (0.99 to 1.05) | .14 |
|
| |||||
| Primary v secondary | 202 | ||||
|
| |||||
| Primary | - | - | |||
|
| |||||
| Secondary | 1.45 (0.93 to 2.26) | .1 | 1.33 (0.79 to 2.23) | .3 | |
|
| |||||
| Variant histology | 202 | 1.19 (0.80 to 1.75) | .4 | 1.1 (0.71 to 1.72) | .7 |
|
| |||||
| Pathologic stage groups | 202 | ||||
|
| |||||
| ≤pT2 | - | - | |||
|
| |||||
| pT3 | 2.52 (1.52 to 4.19) | <.001 | 2.31 (1.31 to 4.07) | .004 | |
|
| |||||
| pT4 | 4.33 (2.36 to 7.94) | <.001 | 2.91 (1.42 to 5.98) | .004 | |
|
| |||||
| Concurrent carcinoma in situ | 201 | 1.31 (0.87 to 1.97) | .2 | 1.51 (0.94 to 2.43) | .092 |
|
| |||||
| Lymphovascular invasion | 202 | 3.1 (2.06 to 4.67) | <.001 | 3.12 (1.94 to 5.03) | <.001 |
|
| |||||
| Positive soft tissue surgicalmargins | 202 | 2.82 (1.57 to 5.06) | <.001 | 2.42 (1.21 to 4.87) | .013 |
|
| |||||
| Lymph node involvement | 202 | 2.48 (1.66 to 3.71) | <.001 | 2.34 (1.48 to 3.71) | <.001 |
NOTE. Bold values are statistically significant.
Abbreviations: HR, hazard ratio; OS, overall survival; RFS, recurrence-free survival.
TABLE A3.
Clinical and Demographic Characteristics of MSK Patients With Chemotherapy-Resistant, Pathologically Localized Bladder Cancer (ypT2N0; n = 54)
| Characteristic | N = 54 |
|---|---|
| Sex, No. (%) | |
| Female | 14 (26) |
| Male | 40 (74) |
| Age at surgery, years, median (IQR) | 66 (59–73) |
| Primary v secondary, No. (%) | |
| Primary | 42 (78) |
| Secondary | 12 (22) |
| Variant histology, No. (%) | 1 5 (28) |
| Concurrent carcinoma in situ, No. (%) | 24 (44) |
| Clinicalstage, No. (%) | |
| T2 | 48 (89) |
| T3 | 5 (9.3) |
| T4a | 1 (19) |
| Lymphovascular invasion, No. (%) | 7(13) |
| Positive soft tissue surgicalmargins, No. (%) | 1 (19) |
| Percent positive LNs,a No. (%) | 0 (0) |
| Total number of LNs,a median (IQR) | 24 (14–34) |
Abbreviations: LN, lymph node; MSK, Memorial Sloan Kettering.
Data only available for n = 49 patients.
TABLE A4.
Univariable Cox Proportional Hazards Analysis of Factors Associated With RFS and OS Among Patients With Pathologically Localized Disease (ypT2N0; n = 54)
| RFS |
OS |
|||
|---|---|---|---|---|
| Variable | HR (95% CI) | P | HR (95% CI) | P |
|
| ||||
| Sex | ||||
|
| ||||
| Female | - | - | ||
|
| ||||
| Male | 1.85 (0.41 to 8.31) | .4 | 1.55 (0.34 to 7.07) | .6 |
|
| ||||
| Age at surgery | 0.98 (0.93 to 1.04) | .6 | 1.02 (0.96 to 1.08) | .6 |
|
| ||||
| Primary v secondary | ||||
|
| ||||
| Primary | - | - | ||
|
| ||||
| Secondary | 0.81 (0.23 to 2.93) | .8 | 0.48 (0.10 to 2.16) | .3 |
|
| ||||
| Variant histology | 1.14 (0.36 to 3.63) | .8 | 0.82 (0.22 to 2.97) | .8 |
|
| ||||
| Concurrent carcinoma in situ | 0.37 (0.12 to 1.19) | .1 | 0.64 (0.21 to 1.97) | .4 |
|
| ||||
| Lymphovascular invasion | 6.35 (1.72 to 23.5) | .006 | 5.99 (1.68 to 21.3) | .006 |
|
| ||||
| Positive soft tissue surgicalmargins | 11.8 (1.32 to 105) | .027 | 5.61 (0.69 to 45.8) | .11 |
NOTE. Bold values are statistically significant.
Abbreviations: HR, hazard ratio; OS, overall survival; RFS, recurrence-free survival.
TABLE A5.
Univariable Associations Between Genomic Alterations and RFS
| RFS |
||||||||
|---|---|---|---|---|---|---|---|---|
| MSK (n = 101) | TCGA (n = 357) | |||||||
|
|
|
|||||||
| Gene | N Alt, No. (%) | HR (95% CI) | P | q | N Alt, No. (%) | HR (95% CI) | P | q |
|
| ||||||||
| CDKN2B.Del | 13 (13) | 1.89 (0.95 to 3.75) | .068 | 0.4 | 116 (32) | 1.18 (0.88 to 1.58) | .3 | 0.7 |
|
| ||||||||
| CDKN2A.Del | 13 (13) | 1.89 (0.95 to 3.75) | .068 | 0.4 | 118 (33) | 1.13 (0.84 to 1.51) | .4 | 0.7 |
|
| ||||||||
| CDKN1A | 13(13) | 1.96 (0.92 to 4.19) | .08 | 0.4 | 26 (7.3) | 0.88 (0.49 to 1.58) | .7 | 0.9 |
|
| ||||||||
| ARID1A | 24 (24) | 1.62 (0.90 to 2.92) | .11 | 0.4 | 71 (20) | 1.25 (0.89 to 1.75) | .2 | 0.7 |
|
| ||||||||
| KMT2D | 16(16) | 1.55 (0.80 to 2.99) | .2 | 0.4 | 74 (21) | 0.97 (0.69 to 1.36) | .8 | >0.9 |
|
| ||||||||
| KDM6A | 28 (28) | 1.44 (0.83 to 2.48) | .2 | 0.4 | 78 (22) | 1.18 (0.85 to 1.64) | .3 | 0.7 |
|
| ||||||||
| TP53 | 63 (62) | 1.3 (0.76 to 2.23) | .3 | 0.6 | 1 67 (47) | 1.02 (0.77 to 1.35) | .9 | >0.9 |
|
| ||||||||
| ELF3a | 10 (14) | 1.53 (0.62 to 3.76) | .4 | 0.6 | 23 (6.4) | 1.31 (0.78 to 2.18) | .3 | 0.7 |
|
| ||||||||
| Unknown | 27 | |||||||
|
| ||||||||
| KMT2C | 10 (9.9) | 0.73 (0.33 to 1.63) | .4 | 0.6 | 32 (9.0) | 0.77 (0.45 to 1.33) | .4 | 0.7 |
|
| ||||||||
| CREBBP | 12(12) | 1.3 (0.66 to 2.57) | .4 | 0.6 | 29 (8.1) | 0.98 (0.58 to 1.65) | >.9 | >0.9 |
|
| ||||||||
| PIK3CA | 13(13) | 0.79 (0.34 to 1.85) | .6 | 0.8 | 70 (20) | 0.78 (0.55 to 1.12) | .2 | 0.7 |
|
| ||||||||
| TERT | 63 (62) | 0.91 (0.54 to 1.52) | .7 | 0.8 | - | - | - | - |
|
| ||||||||
| RB1 | 20 (20) | 0.89 (0.47 to 1.68) | .7 | 0.8 | 59 (17) | 1.15 (0.79 to 1.67) | .5 | 0.7 |
|
| ||||||||
| STAG2 | 11 (11) | 0.93 (0.40 to 2.17) | .9 | 0.9 | 38 (11) | 0.53 (0.30 to 0.95) | .034 | 0.4 |
NOTE. Bold values are statistically significant.
NOTE. Only alterations with >10% alteration prevalence in the MSK chemotherapy-resistant cohort were evaluated. False discovery rate corrected for multiple testing. All alterations in table are mutations unless specified.
Abbreviations: HR, hazard ratio; MSK, Memorial Sloan Kettering; RFS, recurrence-free survival; TCGA, The Cancer Genome Atlas.
Del. N = 74.
TABLE A6.
Frequency of Alterations Stratified by the Presence of LVI
| Gene | Overall (N = 100), No. (%) | No LVI (n = 45), No. (%) | LVI (n = 55), No. (%) | P a | q b |
|---|---|---|---|---|---|
| TP53 | 62 (62) | 25 (56) | 37 (67) | .2 | 0.5 |
| TERT | 63 (63) | 25 (56) | 38 (69) | .2 | 0.5 |
| KDM6A | 28 (28) | 10 (22) | 18 (33) | .2 | 0.5 |
| ARID1A | 24 (24) | 9 (20) | 1 5 (27) | .4 | 0.7 |
| RB1 | 20 (20) | 9 (20) | 11 (20) | >.9 | >0.9 |
| KMT2D | 16 (16) | 7 (16) | 9 (16) | >.9 | >0.9 |
| PIK3CA | 13 (13) | 2 (4.4) | 11 (20) | .021 | 0.3 |
| CDKN1A | 13 (13) | 4 (8.9) | 9 (16) | .3 | 0.5 |
| CDKN2B.Del | 13 (13) | 4 (8.9) | 9 (16) | .3 | 0.5 |
| CDKN2A.Del | 13 (13) | 4 (8.9) | 9 (16) | .3 | 0.5 |
| CREBBP | 12 (12) | 5 (11) | 7 (13) | .8 | >0.9 |
| STAG2 | 11 (11) | 4 (8.9) | 7 (13) | .7 | >0.9 |
| KMT2C | 10 (10) | 3 (6.7) | 7 (13) | .5 | 0.8 |
| ELF3 | 10 (14) | 5 (16) | 5 (12) | .7 | >0.9 |
| Unknown | 27 | 13 | 14 |
Abbreviation: LVI, lymphovascular invasion.
Pearson Chi-squared test; Fisher exact test.
False discovery rate correction for multiple testing.
TABLE A7.
Frequency of Alterations Stratified by the Presence of LN Involvement
| Gene | Overall (N = 101), No. (%) | No LN Involvement (n = 58), No. (%) | LN Involvement (n = 43), No. (%) | P a | q b |
|---|---|---|---|---|---|
| TP53 | 63 (62) | 33 (57) | 30 (70) | .2 | >0.9 |
| TERT | 63 (62) | 35 (60) | 28 (65) | .6 | >0.9 |
| KDM6A | 28 (28) | 16 (28) | 12 (28) | >.9 | >0.9 |
| ARID1A | 24 (24) | 14 (24) | 10 (23) | >.9 | >0.9 |
| RB1 | 20 (20) | 12 (21) | 8 (19) | .8 | >0.9 |
| KMT2D | 16(16) | 10 (17) | 6 (14) | .7 | >0.9 |
| PIK3CA | 13 (13) | 10 (17) | 3 (7.0) | .13 | >0.9 |
| CDKN1A | 13 (13) | 8 (14) | 5 (12) | .7 | >0.9 |
| CDKN2B.Del | 13 (13) | 8 (14) | 5 (12) | .7 | >0.9 |
| CDKN2A.Del | 13 (13) | 8 (14) | 5 (12) | .7 | >0.9 |
| CREBBP | 12 (12) | 5 (8.6) | 7 (16) | .2 | >0.9 |
| STAG2 | 11 (11) | 7 (12) | 4 (9.3) | .8 | >0.9 |
| KMT2C | 10 (9.9) | 4 (6.9) | 6 (14) | .3 | >0.9 |
| ELF3 | 10 (14) | 5 (12) | 5 (16) | .7 | >0.9 |
| Unknown | 27 | 16 | 11 |
Abbreviation: LN, lymph node.
Pearson Chi-squared test; Fisher exact test.
False discovery rate correction for multiple testing.
TABLE A8.
Variant Histology Classification in Clinical Cohort
| Variant Histology | N = 82, No. (%)a |
|---|---|
| Squamous | 29 (35) |
| Nested | 17 (21) |
| Sarcomatoid | 6 (7.3) |
| Glandular | 3 (3.7) |
| Micropapillary | 3 (3.7) |
| Plasmacytoid | 3 (3.7) |
| Squamous/glandular | 3 (3.7) |
| Glandular/neuroendocrine | 2 (2.4) |
| Squamous/sarcomatoid | 2 (2.4) |
| Anaplastic/glandular | 1 (12) |
| Basaloid | 1 (12) |
| Giant cell | 1 (12) |
| Nested/plasmacytoid | 1 (12) |
| Nested/squamous | 1 (12) |
| Neuroendocrine | 1 (12) |
| Neuroendocrine/glandular/lymphoepithelial-like | 1 (12) |
| Plasmacytoid/sarcomatoid/glandular | 1 (12) |
| Poorly differentiated/sarcomatoid | 1 (12) |
| Sarcomatoid/glandular | 1 (12) |
| Squamous/sarcomatoid | 1 (12) |
| Squamous/glandular/plasmacytoid | 1 (12) |
| Squamous/glandular/sarcomatoid | 1 (12) |
| Trophoblastic | 1 (12) |
Seven variant histology patients have unknown type.
Footnotes
AUTHORS’ DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST
The following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated unless otherwise noted. Relationships are self-held unless noted. I = Immediate Family Member, Inst = My Institution. Relationships may not relate to the subject matter of this manuscript. For more information about ASCO’s conflict of interest policy, please refer to www.asco.org/rwcorascopubs.org/po/author-center.
Open Payments is a public database containing information reported by companies about payments made to US-licensed physicians (Open Payments).
Andrew Katims
Stock and Other Ownership Interests: Exelixis
Leon Telis
Travel, Accommodations, Expenses: Boston Scientific, Coloplast
Shawn Dason
Consulting or Advisory Role: Bristol Myers Squibb/Roche
Other Relationship: Intuitive Surgical
Victor McPherson
Honoraria: Tersera, AbbVie, Knight Pharmaceuticals, Bayer
Consulting or Advisory Role: Tersera, Knight Pharmaceuticals
Travel, Accommodations, Expenses: Tersera
Min Yuen Teo
Consulting or Advisory Role: Janssen Oncology, AstraZeneca
Research Funding: Bristol Myers Squibb (Inst), Clovis Oncology (Inst), Pharmacyclics (Inst)
Samuel Funt Employment: ByHeart
Stock and Other Ownership Interests: Kite, a Gilead company, Urogen Pharma, Allogene Therapeutics, Neogene Therapeutics, Kronos Bio, Vida Ventures, IconOVir Bio, Doximity, 76Bio
Consulting or Advisory Role: Merck, Immunai, BioNtech
Research Funding: Genentech/Roche (Inst), AstraZeneca (Inst), Decibel Therapeutics (Inst), ALX Oncology (Inst), Merck (Inst)
Travel, Accommodations, Expenses: Bristol Myers Squibb, AstraZeneca/ edImmune
David Aggen
Consulting or Advisory Role: Boehringer Ingelheim, Seagen, Astellas Pharma, Bristol Myers Squibb Foundation, Alphasights, Aptitude Health, MJH Life Sciences, Guidepoint Global Advisors
Patents, Royalties, Other Intellectual Property: University of Illinois—Urbana Champaign
Open Payments Link: https://openpaymentsdata.cms.gov/physician/4226107
Alvin C. Goh
Consulting or Advisory Role: Medtronic
Travel, Accommodations, Expenses: Medtronic
Nikolaus Schultz Honoraria: OneOncology
Michael F. Berger
This author is a member of the JCO Precision Oncology Editorial Board. Journal policy recused the author from having any role in the peer review of this manuscript.
Honoraria: SOPHiA Genetics
Consulting or Advisory Role: AstraZeneca, PAIGE.AI
Research Funding: Boundless Bio
Patents, Royalties, Other Intellectual Property: Provisional patent pending for “Systems and Methods for Detecting Cancer via cfDNA Screening”
Dean F. Bajorin
Honoraria: Bristol Myers Squibb/Medarex
Consulting or Advisory Role: Merck, Bristol Myers Squibb Foundation
Research Funding: Novartis (Inst), Merck (Inst), Bristol Myers Squibb (Inst), AstraZeneca (Inst), Astellas Pharma (Inst), Seattle Genetics/Astellas (Inst)
Jonathan E. Rosenberg
Honoraria: UpToDate, Medscape, Peerview, Research To Practice, Clinical Care Options, Physicians’ Education Resource, MJH Life Sciences, Pfizer, NCCN/Pfizer
Consulting or Advisory Role: Lilly, Merck, Roche/Genentech, Bristol Myers Squibb, Seagen, Bayer, QED Therapeutics, GlaxoSmithKline, Janssen Oncology, Astellas Pharma, Boehringer Ingelheim, Pfizer/EMD Serono, Mirati Therapeutics, Immunomedics, Tyra Biosciences, Gilead Sciences, Hengrui Pharmaceutical, Alligator Bioscience, Imvax, AstraZeneca, Century Therapeutics
Research Funding: Genentech/Roche (Inst), Seagen (Inst), Bayer (Inst), AstraZeneca (Inst), QED Therapeutics (Inst), Astellas Pharma (Inst), Acrivon Therapeutics
Patents, Royalties, Other Intellectual Property: Predictor of platinum sensitivity (Inst)
Bernard H. Bochner
Consulting or Advisory Role: Olympus
Hikmat Al-Ahmadie
Consulting or Advisory Role: AstraZeneca/MedImmune, Janssen Biotech, PAIGE.AI, Flare Therapeutics
David B. Solit
Stock and Other Ownership Interests: Scorpion Therapeutics, Vividion Therapeutics, Fore Biotherapeutics, Pyramid Biosciences, Function Oncology, Elsie Biotechnologies
Consulting or Advisory Role: Pfizer, BridgeBio Pharma, Scorpion
Therapeutics, Vividion Therapeutics, Fog Therapeutics, Fore Biotherapeutics, Rain Therapeutics, PAIGE.AI, Function Oncology, Pyramid Biosciences, Elsie Biotechnologies
Gopa Iyer
This author is a member of the JCO Precision Oncology Editorial Board. Journal policy recused the author from having any role in the peer review of this manuscript.
Consulting or Advisory Role: Janssen, Mirati Therapeutics, Flare Therapeutics, Loxo/Lilly, Bicycle Therapeutics
Speakers’ Bureau: Gilead Sciences, Lynx Group
Research Funding: Mirati Therapeutics (Inst), Novartis (Inst), Debiopharm Group (Inst), Bayer (Inst), Janssen (Inst), Seagen (Inst)
Eugene J. Pietzak Honoraria: UpToDate
Consulting or Advisory Role: Merck, Chugai Pharma, QED Therapeutics, Janssen, Urogen Pharma
Research Funding: Janssen
No other potential conflicts of interest were reported.
Data analysis and interpretation:
Andrew T. Lenis, Karissa Whiting, Vignesh Ravichandran, Jacob E. Tallman, Syed M. Alam, Hong Truong, Min Yuen Teo, David Aggen, Alvin C. Goh, S. Machele Donat, Harry W. Herr, Guido Dalbagni, Nikolaus Schultz, Michael F. Berger, Dean F. Bajorin, Jonathan E. Rosenberg, Bernard H. Bochner, Irina Ostrovnaya, Hikmat Al-Ahmadie, David B. Solit, Gopa Iyer, Eugene J. Pietzak
REFERENCES
- 1.Bhindi B, Frank I, Mason RJ, et al. : Oncologic outcomes for patients with residual cancer at cystectomy following neoadjuvant chemotherapy: A pathologic stage-matched analysis. Eur Urol 72: 660–664, 2017 [DOI] [PubMed] [Google Scholar]
- 2.Manoharan M, Katkoori D, Kishore TA, et al. : Outcome after radical cystectomy in patients with clinical T2 bladder cancer in whom neoadjuvant chemotherapy has failed. BJU Int 104:1646–1649, 2009 [DOI] [PubMed] [Google Scholar]
- 3.Iyer G, Tully CM, Zabor EC, et al. : Neoadjuvant gemcitabine-cisplatin plus radical cystectomy-pelvic lymph node dissection for muscle-invasive bladder cancer: A 12-year experience. Clin Genitourin Cancer 18:387–394, 2020 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Bajorin DF, Witjes JA, Gschwend JE, et al. : Adjuvant nivolumab versus placebo in muscle-invasive urothelial carcinoma. N Engl J Med 384:2102–2114, 2021 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Bellmunt J, Hussain M, Gschwend JE, et al. : Adjuvant atezolizumab versus observation in muscle-invasive urothelial carcinoma (IMvigor010): A multicentre, open-label, randomised, phase 3 trial. Lancet Oncol 22:525–537, 2021 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Galsky MD, Bajorin DF, Witjes JA, et al. : Disease-free survival analysis for patients with high-risk muscle-invasive urothelial carcinoma from the randomized CheckMate 274 trial by PD-L1 combined positive score and tumor cell score. Eur Urol 83:432–440, 2023 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Gil-Jimene A, van Dorp J, Contreras-Sanz A, et al. l: Assessment of predictive genomic biomarkers for response to cisplatin-based neoadjuvant chemotherapy in bladder cancer. Eur Urol 83: 313–317, 2023 [DOI] [PubMed] [Google Scholar]
- 8.Seiler R, Ashab HAD, Erho N, et al. : Impact of molecular subtypes in muscle-invasive bladder cancer on predicting response and survival after neoadjuvant chemotherapy. Eur Urol 72:544–554, 2017 [DOI] [PubMed] [Google Scholar]
- 9.Robertson AG, Kim J, Al-Ahmadie H, et al. : Comprehensive molecular characterization of muscle-invasive bladder cancer. Cell 171:540–556.e25, 2017 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Liu D, Abbosh P, Keliher D, et al. : Mutational patterns in chemotherapy resistant muscle-invasive bladder cancer. Nat Commun 8:2193, 2017 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Faltas BM, Prandi D, Tagawa ST, et al. : Clonal evolution of chemotherapy-resistant urothelial carcinoma. Nat Genet 48:1490–1499, 2016 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Seiler R, Gibb EA, Wang NQ, et al. : Divergent biological response to neoadjuvant chemotherapy in muscle-invasive bladder cancer. Clin Cancer Res 25:5082–5093, 2019 [DOI] [PubMed] [Google Scholar]
- 13.Cheng DT, Mitchell TN, Zehir A, et al. : Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT): A hybridization capture-based next-generation sequencing clinical assay for solid tumor molecular oncology. J Mol Diagn 17:251–264, 2015 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Teo MY, Bambury RM, Zabor EC, et al. : DNA damage response and repair gene alterations are associated with improved survival in patients with platinum-treated advanced urothelial carcinoma. Clin Cancer Res 23:3610–3618, 2017 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Chakravarty D, Gao J, Phillips SM, et al. : OncoKB: A precision oncology knowledge base. JCO Precis Oncol 10.1200/PO.17.00011 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Gao J, Aksoy BA, Dogrusoz U, et al. : Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Sci Signal 6:pl1-pl1, 2013 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Mitra AP, Cai J, Miranda G, et al. : Management trends and outcomes of patients undergoing radical cystectomy for urothelial carcinoma of the bladder: Evolution of the University of Southern California experience over 3,347 cases. J Urol 207:302–313, 2022 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Pietzak EJ, Zabor EC, Bagrodia A, et al. : Genomic differences between “primary” and “secondary” muscle-invasive bladder cancer as a basis for disparate outcomes to cisplatin-based neoadjuvant chemotherapy. Eur Urol 75:231–239, 2019 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Li Q, Damish AW, Frazier Z, et al. : ERCC2 helicase domain mutations confer nucleotide excision repair deficiency and drive cisplatin sensitivity in muscle-invasive bladder cancer. Clin Cancer Res 25:977–988, 2019 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Van Allen EM, Mouw KW, Kim P, et al. : Somatic ERCC2 mutations correlate with cisplatin sensitivity in muscle-invasive urothelial carcinoma. Cancer Discov 4:1140–1153, 2014 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Mari A, Kimura S, Foerster B, et al. : A systematic review and meta-analysis of lymphovascular invasion in patients treated with radical cystectomy for bladder cancer. Urol Oncol 36:293–305, 2018 [DOI] [PubMed] [Google Scholar]
- 22.Mari A, Kimura S, Foerster B, et al. : A systematic review and meta-analysis of the impact of lymphovascular invasion in bladder cancer transurethral resection specimens. BJU Int 123:11–21, 2019 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Spiess PE, Agarwal N, Bangs R, et al. : Bladder cancer, version 5.2017, NCCN Clinical Practice Guidelines in Oncology. J Natl Compr Cancer Netw 15:1240–1267, 2017 [DOI] [PubMed] [Google Scholar]
- 24.Powles T, Carroll D, Chowdhury S, et al. : An adaptive, biomarker-directed platform study of durvalumab in combination with targeted therapies in advanced urothelial cancer. Nat Med 27:793–801, 2021 [DOI] [PubMed] [Google Scholar]
- 25.Teo MY, Seier K, Ostrovnaya I, et al. : Alterations in DNA damage response and repair genes as potential marker of clinical benefit from PD-1/PD-L1 blockade in advanced urothelial cancers. J Clin Oncol 36:1685–1694, 2018 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Jang S-H, Kim K-J, Oh M-H, et al. : Clinicopathological significance of elevated PIK3CA expression in gastric cancer. J Gastric Cancer 16:85–92, 2016 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Du L, Chen X, Cao Y, et al. : Overexpression of PIK3CA in murine head and neck epithelium drives tumor invasion and metastasis through PDK1 and enhanced TGFb signaling. Oncogene 35: 4641–4652, 2016 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Wang Z, Shang J, Li Z, et al. : PIK3CA is regulated by CUX1, promotes cell growth and metastasis in bladder cancer via activating epithelial-mesenchymal transition. Front Oncol 10:536072, 2020 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.McPherson V, Reardon B, Bhayankara A, et al. : A phase 2 trial of buparlisib in patients with platinum-resistant metastatic urothelial carcinoma. Cancer 126:4532–4544, 2020 [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Andrew T. Lenis, Karissa Whiting, Vignesh Ravichandran, Jacob E. Tallman, Syed M. Alam, Hong Truong, Min Yuen Teo, David Aggen, Alvin C. Goh, S. Machele Donat, Harry W. Herr, Guido Dalbagni, Nikolaus Schultz, Michael F. Berger, Dean F. Bajorin, Jonathan E. Rosenberg, Bernard H. Bochner, Irina Ostrovnaya, Hikmat Al-Ahmadie, David B. Solit, Gopa Iyer, Eugene J. Pietzak