Prediction of Lymph Node Metastasis in Patients with Bladder Cancer Using Whole Transcriptome Gene Expression Signatures.
OBJECTIVE
Clinical staging in patients with muscle invasive bladder cancer misses up to 25% of lymph node metastasis. These patients are at high risk for disease recurrence and improved clinical staging is critical to guide management.


METHODS
Whole transcriptome expression profiles were generated in 199 patients who underwent radical cystectomy and extended pelvic lymph node dissection. The cohort was divided randomly into a discovery set of 133 patients and a validation set of 66. In the discovery set features were identified and modeled in a KNN51 (K-nearest neighbor classifier 51) to predict pathological lymph node metastases. Two previously described bladder cancer gene signatures, including RF15 (15-gene cancer recurrence signature) and LN20 (20-gene lymph node signature), were also modeled in the discovery set for comparison. The AUC and the OR were used to compare the performance of these signatures.


RESULTS
In the validation set KNN51 achieved an AUC of 0.82 (range 0.71-0.93) to predict lymph node positive cases. It significantly outperformed RF15 and LN20, which had an AUC of 0.62 (range 0.47-0.76) and 0.46 (range 0.32-0.60), respectively. Only KNN51 showed significant odds of predicting LN metastasis with an OR of 2.65 (range 1.68-4.67) for every 10% increase in score (p <0.001). RF15 and LN20 had a nonsignificant OR of 1.21 (range 0.97-1.54) and 1.39 (range 0.52-3.77), respectively.


CONCLUSIONS
The new KNN51 signature was superior to previously described gene signatures for predicting lymph node metastasis. If validated prospectively in transurethral resection of bladder tumor samples, KNN51 could be used to guide patients at high risk to early multimodal therapy.
Department of Urologic Sciences, University of British Columbia, Vancouver, British Columbia, Canada; GenomeDx Biosciences, Inc., Vancouver, British Columbia, Canada.
Roland
R
Seiler
GenomeDx Biosciences, Inc., Vancouver, British Columbia, Canada.
Lucia L
LL
Lam
GenomeDx Biosciences, Inc., Vancouver, British Columbia, Canada.
Nicholas
N
Erho
GenomeDx Biosciences, Inc., Vancouver, British Columbia, Canada.
Mandeep
M
Takhar
Institute of Urology and Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California.
Anirban P
AP
Mitra
GenomeDx Biosciences, Inc., Vancouver, British Columbia, Canada.
Christine
C
Buerki
GenomeDx Biosciences, Inc., Vancouver, British Columbia, Canada.
Elai
E
Davicioni
Department of Urology and Stanford Cancer Institute, Stanford University, Stanford, California.
Eila C
EC
Skinner
Institute of Urology and Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California.
Siamak
S
Daneshmand
Department of Urologic Sciences, University of British Columbia, Vancouver, British Columbia, Canada. Electronic address: pblack@mail.ubc.ca.
Peter C
PC
Black
D000368:Aged; D014408:Biomarkers, Tumor / Q000378:metabolism; D002295:Carcinoma, Transitional Cell / Q000235:genetics* / Q000378:metabolism / Q000556:secondary; D018572:Disease-Free Survival; D005260:Female; D006801:Humans; D008197:Lymph Node Excision; D008198:Lymph Nodes / Q000473:pathology*; D008207:Lymphatic Metastasis; D008297:Male; D009367:Neoplasm Staging; D010388:Pelvis; D059467:Transcriptome / Q000235:genetics*; D001749:Urinary Bladder Neoplasms / Q000235:genetics* / Q000378:metabolism / Q000473:pathology
D014408:Biomarkers, Tumor
biomarkers, tumor; genomics; lymph nodes; neoplasm metastasis; urinary bladder neoplasms