scholarly journals Gene Expression Signature Predictive of Neuroendocrine Transformation in Prostate Adenocarcinoma

2020 ◽  
Vol 21 (3) ◽  
pp. 1078 ◽  
Author(s):  
Paola Ostano ◽  
Maurizia Mello-Grand ◽  
Debora Sesia ◽  
Ilaria Gregnanin ◽  
Caterina Peraldo-Neia ◽  
...  
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
De Novo ◽  
Gene Expression Signature ◽  
Prostate Adenocarcinoma ◽  
Transformation Process ◽  
Expression Signature ◽  
Beneficial Effects ◽  
Molecular Features ◽  
Neuroendocrine Transdifferentiation

Neuroendocrine prostate cancer (NEPC) can arise de novo, but much more commonly occurs as a consequence of a selective pressure from androgen deprivation therapy or androgen receptor antagonists used for prostate cancer (PCa) treatment. The process is known as neuroendocrine transdifferentiation. There is little molecular characterization of NEPCs and consequently there is no standard treatment for this kind of tumors, characterized by highly metastases rates and poor survival. For this purpose, we profiled 54 PCa samples with more than 10-years follow-up for gene and miRNA expression. We divided samples into two groups (NE-like vs. AdenoPCa), according to their clinical and molecular features. NE-like tumors were characterized by a neuroendocrine fingerprint made of known neuroendocrine markers and novel molecules, including long non-coding RNAs and components of the estrogen receptor signaling. A gene expression signature able to predict NEPC was built and tested on independently published datasets. This study identified molecular features (protein-coding, long non-coding, and microRNAs), at the time of surgery, that may anticipate the NE transformation process of prostate adenocarcinoma. Our results may contribute to improving the diagnosis and treatment of this subgroup of tumors for which traditional therapy regimens do not show beneficial effects.

scholarly journals Gene expression signature of Gleason score is associated with prostate cancer outcomes in a radical prostatectomy cohort

Oncotarget ◽  
2017 ◽  
Vol 8 (26) ◽  
pp. 43035-43047 ◽  
Author(s):  
Min A. Jhun ◽  
Milan S. Geybels ◽  
Jonathan L. Wright ◽  
Suzanne Kolb ◽  
Craig April ◽  
...  
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
Radical Prostatectomy ◽  
Gleason Score ◽  
Gene Expression Signature ◽  
Cancer Outcomes ◽  
Expression Signature

730 THE ATORVASTATIN TARGET SCD1 IDENTIFIED WITHIN THE GENE EXPRESSION SIGNATURE OF HIGH BMI PROSTATE CANCER PATIENTS

2011 ◽  
Vol 185 (4S) ◽  
Author(s):  
Patrick Parker ◽  
Shashwat Sharad ◽  
Anjali Srivastava ◽  
Suma Ravulapalli ◽  
Yongmei Chen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
Cancer Patients ◽  
Gene Expression Signature ◽  
Expression Signature ◽  
High Bmi

A gene expression signature to predict high-grade prostate cancer response to oxaliplatin.

2012 ◽  
Vol 30 (5_suppl) ◽  
pp. 150-150
Author(s):  
Philippe Pourquier ◽  
Stephane Puyo ◽  
Pierre Richaud ◽  
Jacques Robert ◽  
Nadine Houede
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
Clinical Trials ◽  
Cell Lines ◽  
Gene Expression Signature ◽  
Chemotherapeutic Agents ◽  
Low Grade ◽  
Gleason Grade ◽  
High Grade ◽  
Expression Signature

150 Background: Prostate cancer (PCa) is one of the leading causes of death from cancer in men. High Gleason grade prostate cancers are characterized by aggressive tumors with poorly differentiated cells and a high metastatic potential. They are often refractory to chemical castration but still treated with hormone therapy to which docetaxel or cabazitaxel are added when they become resistant to the anti-androgen. Despite many clinical trials with other chemotherapeutic agents, response rates remain low. Moreover, none of these trials took into account the tumor grade. Methods: We used an in silico approach to screen for drug candidates that could be used as an alternative to taxanes, based on a 86 genes signature which could distinguish between low-grade and high-grade tumors. We extracted from the NCI60 panel databases the expression profiles of the 86 genes across 60 human tumor cell lines and the corresponding in vitro cytotoxicity data of 152 drugs and looked for correlation between their expression level and cell sensitivity to each of these drugs. Results: Among the 86 genes, we identified 9 genes (PCCB, SHMT2, DPM1, RHOT2, RPL13, CD59, EIF4AI, CDKN2C, JUN) for which expression levels across the 60 cell lines was significantly correlated (p< 0.05) to oxaliplatin but not to cisplatin sensitivity. This signature was validated at the functional level since repression of each of these genes conferred a significant change in the sensitivity of PCa cell lines to oxaliplatin but not cisplatin. Conclusions: Our results provide a proof of concept that gene expression signature specific from high grade PCa could be used for the identification of alternative therapies to taxanes. They could also be used to select patients for further clinical trials and as predictive markers of response to these drugs, which represents a further step forward towards personalized therapy of PCa.

Discovery and validation of a 30-gene expression signature to identify prostate cancer patients who are candidates for active surveillance.

2015 ◽  
Vol 33 (7_suppl) ◽  
pp. 10-10
Author(s):  
Travis Gerke ◽  
Svitlana Tyekucheva ◽  
Kathryn Penney ◽  
Christopher Sweeney ◽  
Rosina Lis ◽  
...  
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
Active Surveillance ◽  
Control Sample ◽  
Gene Expression Signature ◽  
Health Study ◽  
Validation Data ◽  
Expression Signature ◽  
Indolent Disease

10 Background: Considerable attention has been devoted to the search for biomarkers of aggressive prostate cancer. While many promising markers have been proposed, it is often unclear whether their ability to risk classify is adequate to reduce overtreatment of indolent cancers. We present and validate a gene expression signature that is highly specific for indolent disease and that, when combined with Gleason, improves upon the prognostic power of Gleason alone. Methods: A 30-gene signature of indolent disease was derived from a case-control sample of men (n=254) from the Health Professionals Follow-Up Study (HPFS) who were followed prospectively from cancer diagnosis for a median of 13.7 years. Cases were defined as men with prostate cancer who experienced a metastatic event or died of cancer during follow-up, while indolent controls survived at least 8 years without metastases. Whole-transcriptome gene expression was quantified from archival formalin-fixed, paraffin-embedded (FFPE) tumor tissue specimens acquired at prostatectomy. Genes were selected by a novel analytic strategy that maximizes a partial area under the curve (pAUC) to accurately identify indolent tumors. We validated the signature in two independent cohorts: the Physicians’ Health Study (PHS; n=150) and a Swedish Watchful Waiting cohort (WW; n=253) with respective median follow-up times of 14.4 and 9.0 years. Results: When compared to a model with Gleason alone, application of the signature to both validation data sets significantly improved prognostic accuracy as measured by pAUC (p=0.003 in PHS and p<0.001 in WW). Performance was particularly strong among men diagnosed with Gleason 7, where unit standard deviation increases in the signature score were associated with odds ratios of indolence of 5.24 (95% CI 2.21-15.75; p<0.001) and 2.37 (95% CI 1.45-4.19; p=0.001) in the PHS and WW cohorts, respectively. Conclusions: We present a signature of indolent prostate cancer that adds prognostic information beyond Gleason and has the potential to guide men to active surveillance and avoid overtreatment. Validation across both treated and untreated cohorts supports the discovery of a robust signature.

scholarly journals A 12-Gene Expression Signature Is Associated with Aggressive Histological in Prostate Cancer

2012 ◽  
Vol 181 (5) ◽  
pp. 1585-1594 ◽  
Author(s):  
Laia Agell ◽  
Silvia Hernández ◽  
Lara Nonell ◽  
Marta Lorenzo ◽  
Eulàlia Puigdecanet ◽  
...  
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
Gene Expression Signature ◽  
Expression Signature

Prediction of metastatic castrate-resistant prostate cancer response to abiraterone or enzalutamide by a baseline blood-based CTC gene expression signature.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e16529-e16529
Author(s):  
Michael Joseph Lariviere ◽  
Naomi B. Haas ◽  
Yauheniya Cherkas ◽  
Karl Nielsen ◽  
Brad Foulk ◽  
...  
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
Prospective Study ◽  
Molecular Mechanisms ◽  
Gene Expression Signature ◽  
Blood Samples ◽  
Expression Signature ◽  
Number Of Patients ◽  
Castrate Resistant Prostate Cancer ◽  
Castrate Resistant

e16529 Background: Prostate cancer is the most common cancer in men in the U.S., with 30% 5-year overall survival (OS) for patients (pts) with metastases. To take a precision medicine approach to the management of metastatic castrate-resistant prostate cancer (mCRPC), we developed a blood circulating tumor cell (CTC)-based test to identify mCRPC pts most likely to benefit from abiraterone (abi) or enzalutamide (enza). Methods: In this multi-institution prospective study, men with mCRPC were enrolled prior to starting abi (1,000 mg/d plus prednisone 10 mg/d) or enza (160 mg/d). At baseline (BL), 12 w, and progression, blood samples were collected for CellSearch-based CTC enumeration and qPCR-based gene expression analysis. Results: 69 pts (median age 68 y [50-82]) received abi (n = 25) or enza (n = 44) and had evaluable blood samples. Consistent with prior publications, among 43 pts with BL CTC > 0, clearance of detectable CTCs (BL CTCs > 0 and 12 w CTCs = 0), was achieved in 24 patients (55.8%), and was associated with greater median OS (31 mo vs. 18 mo, log-rank p = 0.03). The 43 pts with BL CTC > 0 were then randomly divided into training (n = 31) and validation (n = 12) sets. Baseline gene expression data for the training set was used to develop a model to predict CTC clearance, starting with a panel of 141 expressed genes/isoforms including those associated with prostate cancer. Of the models tested, random forest yielded the best performance, with respective training and validation set sensitivity of 0.7 and 1, specificity 0.75 and 0.71, AUC 0.88 and 0.91. Top genes identified include those previously associated with disease – HOXB13, ESRP2, KLK3, GRHL2, and KRT19, among others. Conclusions: A gene expression signature from a baseline blood sample with CellSearch-enriched CTCs can predict clearance of detectable CTCs in response to abi/enza with high AUC and may give insight into molecular mechanisms of response. A prospective study with a larger number of patients will be required to further validate our findings. Ultimately, this blood test has the potential to select the patients most likely to benefit from second-generation antiandrogen vs. non-hormonal systemic treatment.

scholarly journals Obesity and prostate cancer: gene expression signature of human periprostatic adipose tissue

BMC Medicine ◽  
2012 ◽  
Vol 10 (1) ◽  
Author(s):  
Ricardo Ribeiro ◽  
Cátia Monteiro ◽  
Victoria Catalán ◽  
Pingzhao Hu ◽  
Virgínia Cunha ◽  
...  
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
Adipose Tissue ◽  
Gene Expression Signature ◽  
Cancer Gene ◽  
Expression Signature
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