Last update 01 Nov 2024

TOP2A x Akt-1

Last update 01 Nov 2024

Basic Info

Related Targets

TOP2AAkt-1

Drugs associated with TOP2A x Akt-1

NISC-6

Target

Akt-1 x TOP2A

Mechanism

AKT1 gene inhibitors [+1]

Active Org.

The Pennsylvania State University

Originator Org.

The Pennsylvania State University

Active Indication

Melanoma

Inactive Indication-

Drug Highest PhasePreclinical

First Approval Ctry. / Loc.-

First Approval Date20 Jan 1800

100 Clinical Results associated with TOP2A x Akt-1

100 Translational Medicine associated with TOP2A x Akt-1

0 Patents (Medical) associated with TOP2A x Akt-1

Literatures (Medical) associated with TOP2A x Akt-1

02 Dec 2022·Molecular Cancer Research

Molecular Profile Changes in Patients with Castrate-Resistant Prostate Cancer Pre- and Post-Abiraterone/Prednisone Treatment

Article

Author: Kohli, Manish ; Bhargava, Vipul ; Vedell, Peter T. ; Gormley, Michael ; Bryce, Alan H. ; Kalari, Krishna R. ; Tan, Winston ; Jimenez, Raphael E. ; Sinnwell, Jason P. ; Li, Ying ; Qin, Sisi ; Hillman, David W. ; Dehm, Scott M. ; Carlson, Rachel E. ; Weinshilboum, Richard M. ; Sicotte, Hugues ; Wang, Liewei

AbstractWe identified resistance mechanisms to abiraterone acetate/prednisone (AA/P) in patients with metastatic castration-resistant prostate cancer (mCRPC) in the Prostate Cancer Medically Optimized Genome-Enhanced Therapy (PROMOTE) study.We analyzed whole-exome sequencing (WES) and RNA-sequencing data from 83 patients with metastatic biopsies before (V1) and after 12 weeks of AA/P treatment (V2). Resistance was determined by time to treatment change (TTTC).At V2, 18 and 11 of 58 patients had either short-term (median 3.6 months; range 1.4–4.5) or long-term (median 29 months; range 23.5–41.7) responses, respectively. Nonresponders had low expression of TGFBR3 and increased activation of the Wnt pathway, cell cycle, upregulation of AR variants, both pre- and posttreatment, with further deletion of AR inhibitor CDK11B posttreatment. Deletion of androgen processing genes, HSD17B11, CYP19A1 were observed in nonresponders posttreatment. Genes involved in cell cycle, DNA repair, Wnt-signaling, and Aurora kinase pathways were differentially expressed between the responder and non-responder at V2. Activation of Wnt signaling in nonresponder and deactivation of MYC or its target genes in responders was detected via SCN loss, somatic mutations, and transcriptomics. Upregulation of genes in the AURKA pathway are consistent with the activation of MYC regulated genes in nonresponders. Several genes in the AKT1 axis had increased mutation rate in nonresponders. We also found evidence of resistance via PDCD1 overexpression in responders.Implications:Finally, we identified candidates drugs to reverse AA/P resistance: topoisomerase inhibitors and drugs targeting the cell cycle via the MYC/AURKA/AURKB/TOP2A and/or PI3K_AKT_MTOR pathways.

01 Mar 2020·PROTEOMICSQ3 · BIOLOGY

Proteomics of Long‐Lived Mammals

Q3 · BIOLOGY

Review

Author: Tombline, Gregory ; Zacher, Max ; Seluanov, Andrei ; Zhao, Yang ; Gorbunova, Vera ; Emmrich, Stephan ; Macoretta, Nicholas ; Gigas, Jonathan

AbstractMammalian species differ up to 100‐fold in their aging rates and maximum lifespans. Long‐lived mammals appear to possess traits that extend lifespan and healthspan. Genomic analyses have not revealed a single pro‐longevity function that would account for all longevity effects. In contrast, it appears that pro‐longevity mechanisms may be complex traits afforded by connections between metabolism and protein functions that are impossible to predict by genomic approaches alone. Thus, metabolomics and proteomics studies will be required to understand the mechanisms of longevity. Several examples are reviewed that demonstrate the naked mole rat (NMR) shows unique proteomic signatures that contribute to longevity by overcoming several hallmarks of aging. SIRT6 is also discussed as an example of a protein that evolves enhanced enzymatic function in long‐lived species. Finally, it is shown that several longevity‐related proteins such as Cip1/p21, FOXO3, TOP2A, AKT1, RICTOR, INSR, and SIRT6 harbor posttranslational modification (PTM) sites that preferentially appear in either short‐ or long‐lived species and provide examples of crosstalk between PTM sites. Prospects of enhancing lifespan and healthspan of humans by altering metabolism and proteoforms with drugs that mimic changes observed in long‐lived species are discussed.

01 Jul 2019·Clinical Cancer ResearchQ1 · MEDICINE

Mutational Diversity and Therapy Response in Breast Cancer: A Sequencing Analysis in the Neoadjuvant GeparSepto Trial

Q1 · MEDICINE

Article

Author: Nekljudova, Valentina ; Pfarr, Nicole ; von Minckwitz, Gunter ; Stenzinger, Albrecht ; Karn, Thomas ; Budczies, Jan ; Schmitt, Wolfgang D. ; Fasching, Peter A. ; Furlanetto, Jenny ; Untch, Michael ; Möbs, Markus ; Jackisch, Christian ; Jank, Paul ; Weber, Karsten ; Klauschen, Frederick ; Denkert, Carsten ; Hummel, Michael ; van Mackelenbergh, Marion ; Sers, Christine ; Loibl, Sibylle ; Weichert, Wilko ; Schneeweiss, Andreas ; Schem, Christian ; Treue, Denise

AbstractPurpose:Next-generation sequencing (NGS) can be used for comprehensive investigation of molecular events in breast cancer. We evaluated the relevance of genomic alterations for response to neoadjuvant chemotherapy (NACT) in the GeparSepto trial.Experimental Design:Eight hundred fifty-one pretherapeutic formalin-fixed paraffin-embedded (FFPE) core biopsies from GeparSepto study were sequenced. The panel included 16 genes for mutational (AKT1, BRAF, CDH1, EGFR, ERBB2, ESR1, FBXW7, FGFR2, HRAS, KRAS, NRAS, SF3B1, TP53, HNF1A, PIK3CA, and PTEN) and 8 genes for copy-number alteration analysis (CCND1, ERBB2, FGFR1, PAK1, PIK3CA, TOP2A, TP53, and ZNF703).Results:The most common genomic alterations were mutations of TP53 (38.4%) and PIK3CA (21.5%), and 8 different amplifications (TOP2A 34.9%; ERBB2 30.6%; ZNF703 30.1%; TP53 21.9%; PIK3CA 24.1%; CCND1 17.7%; PAK1 14.9%; FGFR 12.6%). All other alterations had a prevalence of less than 5%. The genetic heterogeneity in different breast cancer subtypes [lum/HER2neg vs. HER2pos vs. triple-negative breast cancer (TNBC)] was significantly linked to differences in NACT response. A significantly reduced pathologic complete response rate was observed in PIK3CA-mutated breast cancer [PIK3CAmut: 23.0% vs. wild-type (wt) 38.8%, P < 0.0001] in particular in the HER2pos subcohort [multivariate OR = 0.43 (95% CI, 0.24–0.79), P = 0.006]. An increased response to nab-paclitaxel was observed only in PIK3CAwt breast cancer, with univariate significance for the complete cohort (P = 0.009) and the TNBC (P = 0.013) and multivariate significance in the HER2pos subcohort (test for interaction P = 0.0074).Conclusions:High genetic heterogeneity was observed in different breast cancer subtypes. Our study shows that FFPE-based NGS can be used to identify markers of therapy resistance in clinical study cohorts. PIK3CA mutations could be a major mediator of therapy resistance in breast cancer.

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