NENicholas Erho

Nicholas Erho

*This is an algorithmically generated author record based on publicly available information.

Nicholas Erho has a total of 307 co-authors. Here are the top co-authors by number of shared publications:


Latest Publications

  • MP54-05 PLASTICITY IN THE BIOLOGICAL RESPONSE TO NEOADJUVANT CHEMOTHERAPY IN MUSCLE-INVASIVE BLADDER CANCER

    by Roland Seiler, Ewan A. Gibb, Natalie Q. Wang, Htoo Zarni Oo, Hung-Ming Lam, Mandeep Takhar, Nicholas Erho, Kim E. van Kessel, Brian Winters, James Douglas, et al.

    Almost two thirds of patients with muscle-invasive bladder cancer (MIBC) undergoing cystectomy after cisplatin-based neoadjuvant chemotherapy (NAC) have invasive disease. Biological alterations of these cisplatin-resistant tumors induced by NAC remain largely unstudied.

  • PD15-01 CHARACTERIZATION OF THE GENOMIC LANDSCAPE OF A PROSPECTIVE MUSCLE-INVASIVE BLADDER CANCER COHORT WITH A FOCUS ON SECONDARY VARIANT HISTOLOGY

    by Vikram Narayan, Ewan Gibb, Nicholas Erho, Andrea Cronican, Tyler Kolisnik, Elai Davicioni, Badrinath Konety

  • MP21-11 IS LOW SOCIOECONOMIC STATUS ASSOCIATED WITH WORSE TUMOR BIOLOGY FOR MEN WITH PROSTATE CANCER?

    by Adam Weiner, Mohammed Alshalalfa, Elai Davicioni, Nicholas Erho, Nick Fishbane, Edward Schaeffer

  • MP34-01 MOLECULAR SUBTYPES OF MUSCLE INVASIVE BLADDER CANCER ARE RELATED TO BENEFIT FROM NEOADJUVANT CHEMOTHERAPY: DEVELOPMENT OF A SINGLE SAMPLE PATIENT ASSAY

    by Roland Seiler, Hussam Al Deen Ashab, Nicholas Erho, Bas W.G. van Rhijn, Brian Winters, James Douglas, Kim Van Kessel, Elisabeth E. Fransen van de Putte, Matthew Sommerlad, Qiqi Wang, et al.

    Different methods for molecular subtyping of muscle-invasive bladder cancer (MIBC) have been described. Our goal was to investigate the impact of molecular subtypes in the context of neoadjuvant cisplatin-based chemotherapy (NAC) and to develop a single sample model for clinical use.

  • PNFBA-09 THE DIVERSE GENOMIC LANDSCAPE OF LOW-RISK PROSTATE CANCER

    by Matthew R. Cooperberg, Nicholas Erho, June M. Chan, Felix Y. Feng, Janet E. Cowan, Kaye Ong, Mohammed Alshalalfa, Tyler Kolisnik, Jennifer Margrave, Maria Aranes, et al.

  • MP57-18 DEVELOPMENT AND VALIDATION OF NOVEL GENOMIC CLASSIFIERS FOR PREDICTION OF ADVERSE PATHOLOGY AFTER PROSTATECTOMY

    by Firas Abdollah, Hussam Al-Deen Ashab, R. Jeffrey Karnes, John W. Davis, Nicholas Erho, Qiqi Wang, Ewan A. Gibb, Zaid Haddad, Voleak Choeurng, Kasra Yousefi, et al.

    To develop and validate novel genomic signatures to predict adverse pathology (AP) after radical prostatectomy (RP).

  • The diverse genomic landscape of low-risk prostate cancer

    by M. Cooperberg, N. Erho, J. Chan, F. Feng, J. Cowan, J. Simko, K. Ong, M. Alshalalfa, T. Kolisnik, J. Margrave, et al.

  • The diverse genomic landscape of low-risk prostate cancer.

    by Matthew R. Cooperberg, Nicholas Erho, June M. Chan, Felix Yi-Chung Feng, Janet E. Cowan, Kaye Ong, Mohammed Alshalalfa, Tyler Kolisnik, Jennifer Margrave, Maria Aranes, et al.

    72 Background: Active surveillance (AS) is becoming standard of care for men with low-risk prostate cancer; however a need exists for better tools to assess which men are optimal candidates for AS. In this study we compare genomic expression profiles of AS candidates against higher-risk radical prostatectomy (RP) patients to characterize the genomics of clinically low-risk prostate cancer. Methods: Biopsies from 473 UCSF patients potentially suitable for AS (stage ≤ cT2N0M0, PSA ≤ 10 ng/ml, Gleason 3+3 or low-volume 3+4 ) were profiled using the Affymetrix HuEx microarray to generate RNA expression data. These cases were compared to 2043 RP cases previously profiled on the same microarray platform. Scores for 21 published prognostic signatures were calculated and pathway associated genes were summarized to provide levels of patient risk and pathway activity. Results: Of the 473 AS biopsies profiled, 408 (86%) passed quality control and were used for analysis. Based on the quartiles of average scores for 21 prognostic signature risk models, 49%, 36%, 11%, and 4%, respectively, were classified into the 1st, 2nd, 3rd, or 4th score quartiles. Considering only the clinically low-risk patients at diagnosis, 356 (87%) were low, 45 (11%) were intermediate and 7 (2%) were high risk. Genomic risk was positively associated with cell cycle related pathways (p < 0.001) and negatively associated with apical junction (p < 0.001), epithelial−mesenchymal transition (p < 0.001), and androgen receptor (p < 0.05) pathways. Clustering of patients based on the expression of 36 pathways revealed two biologic groups corresponding to putative basal and luminal subtypes. Compared to higher risk RP patients, the low risk prostate cancer tumors at diagnosis were enriched for basal-like tumors (20% vs 33%, p < 0.001). Conclusions: Although only 2% of low risk AS candidates have high risk genomic characteristics, very substantial genomic heterogeneity exists in this population, and pathway activation overlaps significantly with higher-risk RP patients. These results suggest that even in potential AS candidates, genomic profiling could eventually be used to better guide management.


  • Luminal and basal subtyping of prostate cancer.

    by Felix Yi-Chung Feng, Shuang Zhao, Seiwon Laura Chang, Nicholas Erho, Jonathan Lehrer, Mohammed Alshalalfa, Matthew R. Cooperberg, Won Kim, Charles J. Ryan, Robert B. Den, et al.

    3 Background: There is a clear need to develop a clinically relevant molecular subtyping approach for prostate cancer. We hypothesized that prostate cancer can be subtyped based on luminal versus basal lineage. Methods: We applied the PAM50 classifier, which is used clinically to identify luminal and basal cancers in breast cancer, to subtype a total of 3,782 prostate cancer samples using a high-density microarray platform run in a CLIA-certified laboratory. We examined the associations of these subtypes and clinical outcomes. Results: We demonstrate that PAM50 segregates prostate cancer into three reproducible subtypes in both retrospective cohorts and on prospective validation: luminal A (33.3%-34.3%), luminal B (28.5%-32.6%), and basal (34.1%-37.1%). Luminal B prostate cancers exhibited the worst clinical prognoses, followed by basal and luminal A subtypes (10-year biochemical recurrence-free survival: 29/39/41%; distant metastasis-free survival: 53/73/73%; prostate cancer-specific survival: 78/86/89%; overall survival: 69/80/82% respectively) on both univariable and multivariable analyses accounting for standard clinicopathologic prognostic factors. Known luminal lineage markers, such as NKX3.1 and KRT18, and the basal lineage CD49f signature, were enriched in luminal- and basal-like cancers respectively, demonstrating the connection between these subtypes and established prostate cancer biology. While both luminal-like subtypes were associated with increased AR expression and signaling, only luminal B prostate cancers were significantly associated with post-operative response to androgen deprivation therapy (ADT) in a subset analysis matching patients based on clinicopathologic variables (interaction p = 0.006, luminal B 10-year metastasis: 33% (treated) vs. 55% (untreated), non-luminal B: 37% (treated) vs. 21% (untreated)). Conclusions: These findings contribute novel insight into the biology of prostate cancer, and provide translatable clinical tools for personalizing post-operative ADT for patients with prostate cancer. Similar to breast cancer, these findings suggest that luminal/basal subtyping may be useful in treatment selection in prostate cancer.


  • Relationships between an androgen receptor output signature (ARoS), AR expression, and poor prostate cancer prognosis in RP tissues.

    by Mohammed Alshalalfa, Maria Santiago-Jimenez, Nicholas Erho, Nicholas Fishbane, Kasra Yousefi, Hussam Al-Deen Ashab, Elai Davicioni, Ashley Ross, Edward M. Schaeffer

    38 Background: The Androgen-receptor (AR) signaling plays a pivotal role in prostate cancer initiation and progression. AR amplification and overexpression have been associated with lethal PCa and CRPC; however, much of the impact of these events on cancer progression is poorly understood with an unclear prognostic significance of down-stream targets of AR. Methods: A total of 2,555 RP expression profiles were extracted from the Decipher GRID database; 262 of which were from retrospective natural history cohort with known metastasic outcomes and the remaining from anonymized prospective cases with basic demographic and pathological data available. We built a 9 gene AR-output signature (ARoS) score based on canonical androgen regulated genes to represent AR-output activity in RP tissues. The 9 genes were weighted based on their distribution skewness in the prospective data (n = 2,293) and then scores were calculating by summing the weighted expression of the 9 genes. Results: AR expression and ARoS score were not strongly correlated with approximately 50% of samples with low ARoS have relatively high AR expression. In a prospective cohort of 2,293 patients, low ARoS was associated with higher Decipher metastasis risk scores (OR: 3.1, p < 0.001), higher Gleason grade (OR: 2.4, p < 0.001), ERG-fusion negative (OR: 1.8, p < 0.001) and SVI (OR: 2.1, p < 0.001). Additionally, low ARoS was associated with higher expression of neuroendocrine biomarkers (NCAM1, ENO2). In a large retrospective cohort with long term clinical follow-up, patients with low ARoS score had a higher probability of 10-year metastasis rate (p = 0.002). In 55 patients from this cohort who received ADT post metastasis, the ARoS signature derived from primary tissue was lower in patients who developed CRPC (p < 0.001). Furthermore, ARoS was significantly lower in mCRPC samples (p < 0.001) compared to primary PCa tissues. Conclusions: ARoS derived from primary prostate cancer tissue is correlated with metastatic outcomes and progression to CRPC. With further validation, such a signature may better predict those patients which require early intensification of systemic therapy.