Identification of CNGB1 as a Predictor of Response to Neoadjuvant Chemotherapy in Muscle-Invasive Bladder Cancer

Cisplatin-based neoadjuvant chemotherapy (NAC) is recommended prior to radical cystectomy for muscle-invasive bladder cancer (MIBC) patients. Despite a 5–10% survival benefit, some patients do not respond and experience substantial toxicity and delay in surgery. To date, there are no clinically approved biomarkers predictive of response to NAC and their identification is urgently required for more precise delivery of care. To address this issue, a multi-methods analysis approach of machine learning and differential gene expression analysis was undertaken on a cohort of 30 MIBC cases highly selected for an exquisitely strong response to NAC or marked resistance and/or progression (discovery cohort). RGIFE (ranked guided iterative feature elimination) machine learning algorithm, previously demonstrated to have the ability to select biomarkers with high predictive power, identified a 9-gene signature (CNGB1, GGH, HIST1H4F, IDO1, KIF5A, MRPL4, NCDN, PRRT3, SLC35B3) able to select responders from non-responders with 100% predictive accuracy. This novel signature correlated with overall survival in meta-analysis performed using published NAC treated-MIBC microarray data (validation cohort 1, n = 26, Log rank test, p = 0.02). Corroboration with differential gene expression analysis revealed cyclic nucleotide-gated channel, CNGB1, as the top ranked upregulated gene in non-responders to NAC. A higher CNGB1 immunostaining score was seen in non-responders in tissue microarray analysis of the discovery cohort (n = 30, p = 0.02). Kaplan-Meier analysis of a further cohort of MIBC patients (validation cohort 2, n = 99) demonstrated that a high level of CNGB1 expression associated with shorter cancer specific survival (p < 0.001). Finally, in vitro studies showed siRNA-mediated CNGB1 knockdown enhanced cisplatin sensitivity of MIBC cell lines, J82 and 253JB-V. Overall, these data reveal a novel signature gene set and CNGB1 as a simpler proxy as a promising biomarker to predict chemoresponsiveness of MIBC patients.

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The immunomodulatory protein Dickkopf-1 (DKK1) defines a non-neuroendocrine subtype of metastatic castration-resistant prostate cancer (mCRPC) with low AR and low PSA expression.

Journal of Clinical Oncology ◽

10.1200/jco.2017.35.15_suppl.5054 ◽

2017 ◽

Vol 35 (15_suppl) ◽

pp. 5054-5054 ◽

Cited By ~ 1

Author(s):

David Wise ◽

Joshua Armenia ◽

Yu Chen ◽

Peter Nelson ◽

Nikolaus Schultz ◽

...

Keyword(s):

Gene Expression ◽

Prostate Cancer ◽

Tumor Immunity ◽

Gene Expression Analysis ◽

Validation Cohort ◽

Discovery Cohort ◽

Differential Gene Expression Analysis ◽

Dkk1 Expression ◽

Differential Gene

5054 Background: Advanced stagemCRPC can manifest AR-signaling independent growth typified by loss of AR and/or PSA expression in the absence of neuroendocrine (NE) features on biopsy. We sought to identify therapeutically relevant biomarkers of this highly resistant prostate cancer subtype. Methods: An unbiased differential gene expression analysis of non-neuroendocrine mCRPC biopsies was carried out comparing patients with ARlow to patients with ARhigh disease in a discovery cohort (SU2C/PCF, 18 pts: 8 ARlow, 10 ARhigh) and validation cohort (Fred Hutchinson, 76 pts: 12 ARlow, 64 ARhigh). The AR and NE status of the biopsies were defined by AR and PSA mRNA expression and gene signatures representative of AR activity and NE lineage. An RNA sequencing-based signature of immune cell subsets was calculated using the Cibersort algorithm. Results: Differential gene expression analysis identified the secreted Wnt antagonist, DKK1, as significantly upregulated in ARlow cases compared to ARhigh cases (11.2 RPKM vs. 0.28 RPKM, p < 0.03) in our discovery cohort and confirmed in our validation cohort (9.2 FPKM vs. 0.99 FPKM, p < 0.001). DKK1 protein was also found to be increased in non-neuroendocrine ARlow relative to ARhigh prostate cancer in vitro cell and organoid models (858 pg/mg total protein vs. 2 pg/mg total protein, p < 0.05) and patient-derived xenografts (28.6 FPKM vs. 0.78 FPKM, p < 0.0001). Consistent with the role of DKK1 as a negative modulator of anti-tumor immunity, patient biopsies with the highest quartile of DKK1 expression showed an RNA signature consistent with lower levels of active NK cells (0.2% vs. 1.8%, p < 0.005), and lower levels of CD8+ T cells (3.7% vs. 9.7%, p< 0.005) compared to those with the lowest quartile of DKK1 expression. Conclusions: DKK1 represents a secreted biomarker that is disproportionately enriched in non-neuroendocrine mCRPCs that lack AR expression. Because DKK1 has been implicated as a suppressor of anti-tumor immunity and is a target of an existing neutralizing antibody, our results support the clinical evaluation of the role of DKK1 blockade in DKK1-positive AR-negative prostate cancer.

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Machine learning based refined differential gene expression analysis of pediatric sepsis

BMC Medical Genomics ◽

10.1186/s12920-020-00771-4 ◽

2020 ◽

Vol 13 (1) ◽

Author(s):

Mostafa Abbas ◽

Yasser EL-Manzalawy

Keyword(s):

Gene Expression ◽

Machine Learning ◽

Differential Gene Expression ◽

Expression Analysis ◽

Gene Expression Analysis ◽

Differential Gene Expression Analysis ◽

Differential Gene ◽

Pediatric Sepsis

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Apparent plasticity in the biological response to neoadjuvant chemotherapy in muscle-invasive bladder cancer.

Journal of Clinical Oncology ◽

10.1200/jco.2018.36.6_suppl.433 ◽

2018 ◽

Vol 36 (6_suppl) ◽

pp. 433-433

Author(s):

Roland Seiler ◽

Ewan Gibb ◽

Natalie Qiqi Wang ◽

Htoo Zarni Oo ◽

Hung-Ming Lam ◽

...

Keyword(s):

Gene Expression ◽

Bladder Cancer ◽

Neoadjuvant Chemotherapy ◽

Expression Analysis ◽

Gene Expression Analysis ◽

Molecular Subtypes ◽

Invasive Bladder Cancer ◽

Consensus Clustering ◽

Muscle Invasive Bladder Cancer ◽

Muscle Invasive

433 Background: After cisplatin-based neoadjuvant chemotherapy (NAC) almost two thirds of patients have residual muscle-invasive bladder cancer (MIBC) present at radical cystectomy (RC). The alterations induced by NAC in these cisplatin-resistant tumors remain largely unstudied. Here, we aim to investigate the characteristics of cisplatin-resistant tumors. Methods: RC samples were available for gene expression analysis from 133 patients with residual invasive disease after cisplatin-based NAC, of whom 116 had matched pre-NAC samples. In addition, the tumor bed (scar tissue) of 21 post-NAC RC specimens with no residual tumor was profiled. Unsupervised consensus clustering (CC) was performed and the CC were investigated for their biological and clinical characteristics. H&E and immunohistochemistry (KRT5/6, GATA3, KI67 and CD8) were used to confirm tissue sampling and gene expression analysis. Results: Unsupervised consensus clustering yielded four distinct consensus clusters (CC). Consistent basal-(CC1) and luminal-like (CC2) phenotype similar to pre-NAC subtyping was observed in 42% of cases. One third of cases became immune-infiltrated (CC3) in the post-NAC setting but lacked basal and luminal markers. These tumors expressed a strong T-cell signature, chemokine signaling and checkpoint molecules. Conversely, CC4 was associated with healing/scarring. This ‘scar-like’ character of CC4 was consistent with the scar samples. Despite being pathological non-responders, the relative risk of death for CC4 was 2.8 and 3 times less than CC2-Luminal (p = 0.038) and CC3-Infiltrated (p = 0.018), respectively. Luminal-like pre-NAC samples were more likely to adopt a scar-like character (CC4) in the post-NAC setting, while the basal-like tumors were more likely to develop luminal features (CC2). Conclusions: This study expands our knowledge of cisplatin-resistant MIBC by suggesting molecular subtypes to understand the biology of these tumors. Clinical trials are necessary to test the impact of these molecular subtypes with respect to selection of adjuvant and salvage treatments. Post-NAC immune infiltration could have implications for subsequent immunotherapy.

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