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Journal articles

Patient-matched analysis identifies deregulated networks in prostate cancer to guide personalized therapeutic intervention

Abstract : Prostate cancer (PrCa) is the second most common malignancy in men. More than 50% of advanced prostate cancers display the TMPRSS2-ERG fusion. Despite extensive cancer genome/transcriptome data, little is known about the impact of mutations and altered transcription on regulatory networks in the PrCa of individual patients. Using patient-matched normal and tumor samples, we established somatic variations and differential transcriptome profiles of primary ERG-positive prostate cancers. Integration of protein-protein interaction and generegulatory network databases defined highly diverse patient-specific network alterations. Different components of a given regulatory pathway were altered by novel and known mutations and/or aberrant gene expression, including deregulated ERG targets, and were validated by using a novel in silico methodology. Consequently, different sets of pathways were altered in each individual PrCa. In a given PrCa, several deregulated pathways share common factors, predicting synergistic effects on cancer progression. Our integrated analysis provides a paradigm to identify druggable key deregulated factors within regulatory networks to guide personalized therapies.
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https://hal.archives-ouvertes.fr/hal-03473404
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Submitted on : Monday, December 13, 2021 - 10:35:58 AM
Last modification on : Monday, July 4, 2022 - 9:31:44 AM
Long-term archiving on: : Monday, March 14, 2022 - 6:15:28 PM

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Akinchan Kumar, yasenya Kasikci, Alaa Badredine, Karim Azzag, Marie L Quintyn Ranty, et al.. Patient-matched analysis identifies deregulated networks in prostate cancer to guide personalized therapeutic intervention. American Journal of Cancer Research, e-Century Publishing, 2021, 11 (11), pp.5299-5318. ⟨hal-03473404⟩

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