Next-generation sequencing reveals novel rare fusion events with functional implication in prostate cancer

Oncogene ◽  
2014 ◽  
Vol 34 (5) ◽  
pp. 568-577 ◽  
Author(s):  
I Teles Alves ◽  
T Hartjes ◽  
E McClellan ◽  
S Hiltemann ◽  
R Böttcher ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Next Generation Sequencing ◽  
Next Generation ◽  
Functional Implication ◽  
Generation Sequencing

Next generation sequencing panels to predict response to hormonal therapy in prostate cancer

2016 ◽  
Author(s):  
Heini M L Kallio ◽  
Matti Annala ◽  
Anniina Brofeldt ◽  
Reija Hieta ◽  
Kati Kivinummi ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Next Generation Sequencing ◽  
Hormonal Therapy ◽  
Next Generation ◽  
Generation Sequencing

scholarly journals Transcriptomics Signature from Next-Generation Sequencing Data Reveals New Transcriptomic Biomarkers Related to Prostate Cancer

2019 ◽  
Vol 18 ◽  
pp. 117693511983552 ◽  
Author(s):  
Abedalrhman Alkhateeb ◽  
Iman Rezaeian ◽  
Siva Singireddy ◽  
Dora Cavallo-Medved ◽  
Lisa A Porter ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Next Generation Sequencing ◽  
Cancer Progression ◽  
Machine Learning Techniques ◽  
Next Generation Sequencing Data ◽  
Prognostic Indicators ◽  
Next Generation ◽  
Sequencing Data ◽  
Cancer Data ◽  
Generation Sequencing

Prostate cancer is one of the most common types of cancer among Canadian men. Next-generation sequencing using RNA-Seq provides large amounts of data that may reveal novel and informative biomarkers. We introduce a method that uses machine learning techniques to identify transcripts that correlate with prostate cancer development and progression. We have isolated transcripts that have the potential to serve as prognostic indicators and may have tremendous value in guiding treatment decisions. Analysis of normal versus malignant prostate cancer data sets indicates differential expression of the genes HEATR5B, DDC, and GABPB1-AS1 as potential prostate cancer biomarkers. Our study also supports PTGFR, NREP, SCARNA22, DOCK9, FLVCR2, IK2F3, USP13, and CLASP1 as potential biomarkers to predict prostate cancer progression, especially between stage II and subsequent stages of the disease.

Targeted Next-Generation Sequencing in Men with Metastatic Prostate Cancer: a Pilot Study

2018 ◽  
Vol 13 (4) ◽  
pp. 495-500 ◽  
Author(s):  
Pedro C. Barata ◽  
Prateek Mendiratta ◽  
Brandie Heald ◽  
Stefan Klek ◽  
Petros Grivas ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Next Generation Sequencing ◽  
Pilot Study ◽  
Metastatic Prostate Cancer ◽  
Next Generation ◽  
Targeted Next Generation Sequencing ◽  
Generation Sequencing

Next generation sequencing of primary prostate cancer tumors to reveal potentially actionable opportunities for clinical management: The UNC experience.

2019 ◽  
Vol 37 (7_suppl) ◽  
pp. 305-305
Author(s):  
Daniel James Crona ◽  
Anthony Drier ◽  
Jing Daisy Zhu ◽  
Emily Fox Bell ◽  
Margaret Rose Sketch ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Next Generation Sequencing ◽  
Copy Number Variations ◽  
Precision Oncology ◽  
Next Generation ◽  
Targeted Next Generation Sequencing ◽  
Formalin Fixed Paraffin ◽  
Primary Prostate Cancer ◽  
Formalin Fixed Paraffin Embedded ◽  
Generation Sequencing

305 Background: The Strata trial (NCT03061305) is a multi-institutional precision oncology collaboration structured as an observational protocol that aims to match patients to genomically-guided therapies. Methods: Selected University of North Carolina (UNC) metastatic prostate cancer (mPC) patients were enrolled on this IRB-approved study. Formalin fixed paraffin-embedded primary tumor specimens, without matched germline controls, were sent for targeted next generation sequencing (NGS) to detect actionable variants, including: mutations in 87 genes, copy number variations in 31 genes, and gene fusions in 46 gene drivers. mPC-related genes of particular interest included: AR, ATM, BRCA1/2, ERG, MSH2, MSH6, PTEN, RB1, and TP53. Results: Of the 92 cases sequenced, 5 [5%] failed testing. Of the 87 mPC patients (median age 69 years [47-86]) enrolled: 53 [61%] were white, 28 [32%] were black, 1 [1%] was Asian, and 5 [6%] declined to be identified. NGS data revealed 106 variants in 27 genes: 62 patients (71%) had at least one variant, 21 (24%) had 2 variants, 7 (8%) had 3 variants, and 4 (3%) had 4 variants. Among the 62 patients with at least 1 identified variant, TMPRSS2-ERG fusion occurred most frequently (50%), followed by TP53 (40%), and PTEN (16%). 6% of all sequenced patients had variants in DNA damage repair genes including ATM (3%), BRCA2 (2%) and MSH2 (1%). One patient had a SLC45A3-ERG fusion combined with PTEN deep deletion, which has been associated with a more aggressive phenotype. One patient with a microsatellite-instability high tumor was treated with pembrolizumab. Conclusions: The UNC experience shows that a high proportion of primary prostate cancer tumors from mPC patients have genomic variants, and one patient was treated based on these data. Limited actionability may reflect the landscape of currently FDA approved mPC treatments, and available clinical trials. It may also be due to a short follow-up, and these data could inform treatment planning upon progression.

scholarly journals Next-generation Sequencing of Advanced Prostate Cancer Treated with Androgen-deprivation Therapy

2014 ◽  
Vol 66 (1) ◽  
pp. 32-39 ◽  
Author(s):  
Prabhakar Rajan ◽  
Ian M. Sudbery ◽  
M. Eugenia M. Villasevil ◽  
Ernest Mui ◽  
Janis Fleming ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Next Generation Sequencing ◽  
Androgen Deprivation Therapy ◽  
Advanced Prostate Cancer ◽  
Androgen Deprivation ◽  
Next Generation ◽  
Generation Sequencing

Current Challenges and Implications of Proteogenomic Approaches in Prostate Cancer

2020 ◽  
Vol 20 (22) ◽  
pp. 1968-1980
Author(s):  
Nidhi Shukla ◽  
Narmadhaa Siva ◽  
Babita Malik ◽  
Prashanth Suravajhala
Keyword(s):  
Prostate Cancer ◽  
Next Generation Sequencing ◽  
Candidate Genes ◽  
Next Generation ◽  
Recent Past ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data ◽  
Omic Data ◽  
Generation Sequencing

In the recent past, next-generation sequencing (NGS) approaches have heralded the omics era. With NGS data burgeoning, there arose a need to disseminate the omic data better. Proteogenomics has been vividly used for characterising the functions of candidate genes and is applied in ascertaining various diseased phenotypes, including cancers. However, not much is known about the role and application of proteogenomics, especially Prostate Cancer (PCa). In this review, we outline the need for proteogenomic approaches, their applications and their role in PCa.

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