Abstract The PSMC3IP-MND1 heterodimer promotes RAD51 and DMC1-dependent D-loop formation during meiosis in yeast and mammalian organisms. For this purpose, it catalyzes the DNA strand exchange activities of the recombinases. Interestingly, in a panel of genome-scale CRISPR-Cas9 mutagenesis and interference screens in mitotic cells, we found that depletion of either PSMC3IP or MND1 caused sensitivity to clinical Poly (ADP-Ribose) Polymerase inhibitors (PARPi). A retroviral mutagenesis screen in mitotic cells also identified PSMC3IP and MND1 as genetic determinants of ionizing radiation sensitivity. The role PSMC3IP and MND1 play in preventing PARPi sensitivity in mitotic cells appears to be independent of a previously described role in alternative lengthening of telomeres (ALT). PSMC3IP or MND1 depleted cells accumulate toxic RAD51 foci in response to DNA damage, show impaired homology-directed DNA repair, and become PARPi sensitive, even in cells lacking both BRCA1 and TP53BP1 . Although replication fork reversal is also affected, the epistatic relationship between PSMC3IP-MND1 and BRCA1/BRCA2 suggests that the abrogated D-loop formation is the major cause of PARPi sensitivity. This is corroborated by the fact that a PSMC3IP p.Glu201del D-loop formation mutant associated with ovarian dysgenesis fails to reverse PARPi sensitivity. These observations suggest that meiotic proteins such as MND1 and PSMC3IP could have a greater role in mitotic cells in determining the response to therapeutic DNA damage.
<p>CDK9 inhibitors impair cell viability in 2D and 3D culture. <b>A</b> and <b>B,</b> A total of 4,000 to 8,000 cells were seeded in 96-well tissue culture plates and treated at day 1 and 3 with the CDK9 inhibitors NVP-2 (<b>A</b>) or AZD4573 (<b>B</b>) at the indicated concentrations. Cell viability was assessed using CellTiter-Glo (day 7). Mean values ± SEM. Data represent percentage NVP-2/AZD4573–treated viable cells compared with vehicle control. <i>n</i> = 4 technical replicates; <i>n</i> = 1 biological replicate. <b>C,</b> A total of 2,500 cells were seeded in 96-well ultra-low attachment round-bottomed plates. The resulting spheroids were treated with AZD4573 at days 3 and 6. Cell viability was assessed on day 10 (endpoint). Graphs showing percentage of viable AZD4573-treated cells compared with vehicle control. <i>n</i> = 1 biological replicate; <i>n</i> = 4 technical replicates. Mean values ± SEM. Representative images and quantification of spheroid area at endpoint following treatment with 0 nmol/L, 3 nmol/L, or 30 nmol/L AZD4573 are shown. Scale bar, 1 mm. <b>D,</b> A total of 3,000 to 5,000 MCF7 LTED<sup>WT</sup>, LTED<sup>Y537C</sup>, or LTED<sup>PalboR</sup> cells were seeded in 2D 96-well tissue culture plates and treated with escalating doses of palbociclib and AZD4573 at day 1 and 3. Cell viability was assessed using CellTiter-Glo on day 7. Data representing percentage of viable cells compared with vehicle control. <i>n</i> = 1 biological replicate; <i>n</i> = 3 technical replicates; mean values ± SEM. Top, individual drug responses. Bottom, synergy plots. The Bliss synergy score references the most synergistic area of the plot.</p>
<div>Abstract<p>The combination of endocrine therapy and CDK4/6 inhibitors such as palbociclib is an effective and well-tolerated treatment for estrogen receptor–positive (ER<sup>+</sup>) breast cancer, yet many patients relapse with therapy-resistant disease. Determining the mechanisms underlying endocrine therapy resistance is limited by the lack of ability to fully recapitulate inter- and intratumor heterogeneity <i>in vitro</i> and of availability of tumor samples from women with disease progression or relapse. In this study, multiple cell line models of resistant disease were used for both two-dimensional (2D)– and three-dimensional (3D)–based inhibitor screening. The screens confirmed the previously reported role of pro-proliferative pathways, such as PI3K–AKT–mTOR, in endocrine therapy resistance and additionally identified the transcription-associated cyclin-dependent kinase CDK9 as a common hit in ER<sup>+</sup> cell lines and patient-derived organoids modeling endocrine therapy–resistant disease in both the palbociclib-sensitive and palbociclib-resistant settings. The CDK9 inhibitor, AZD4573, currently in clinical trials for hematologic malignancies, acted synergistically with palbociclib in these ER<sup>+</sup><i>in vitro</i> 2D and 3D models. In addition, in two independent endocrine- and palbociclib-resistance patient-derived xenografts, treatment with AZD4573 in combination with palbociclib and fulvestrant resulted in tumor regression. Tumor transcriptional profiling identified a set of transcriptional and cell-cycle regulators differentially downregulated only in combination-treated tumors. Together, these findings identify a clinically tractable combination strategy for overcoming resistance to endocrine therapy and CDK4/6 inhibitors in breast cancer and provide insight into the potential mechanism of drug efficacy in targeting treatment-resistant disease.</p>Significance:<p>Targeting transcription-associated CDK9 synergizes with CDK4/6 inhibitor to drive tumor regression in multiple models of endocrine- and palbociclib-resistant ER<sup>+</sup> breast cancer, which could address the challenge of overcoming resistance in patients.</p></div>
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
Este trabajo de grado es el resultado de la pasantia interna denominada Medicion de flujo y nivel para liquidos en simuladores de control de procesos utilizados en practicas de laboratorio, el cual se desarrolla de la siguiente manera:
Lo primero que se establece son los antecedentes de los trabajos de grado relacionados con el Sistema de Control de Procesos Amatrol T5552. Luego se procede a traducir la informacion mas relevante de los paquetes de actividades de aprendizaje (Learning Activity Packets – LAPs). Posteriormente se caracterizan los componentes del equipo por medio de las etiquetas con los nombres traducidos al idioma espanol, seguido de la validacion de las guias de trabajo realizadas en otro trabajo de grado.
Finalmente se disenan los diagramas de flujo, que son las ilustraciones basicas de las mediciones que puede ejercer el equipo tecnologico, el cual ofrece una variedad de oportunidades de aprendizaje que aumentan las habilidades para el entorno laboral.
Receptor-interacting serine/threonine-protein kinase 1 (RIPK1) functions as a critical stress sentinel that coordinates cell survival, inflammation, and immunogenic cell death (ICD). Although the catalytic function of RIPK1 is required to trigger cell death, its non-catalytic scaffold function mediates strong pro-survival signaling. Accordingly, cancer cells can hijack RIPK1 to block necroptosis and evade immune detection. We generated a small-molecule proteolysis-targeting chimera (PROTAC) that selectively degraded human and murine RIPK1. PROTAC-mediated depletion of RIPK1 deregulated TNFR1 and TLR3/4 signaling hubs, accentuating the output of NF-κB, MAPK, and IFN signaling. Additionally, RIPK1 degradation simultaneously promoted RIPK3 activation and necroptosis induction. We further demonstrated that RIPK1 degradation enhanced the immunostimulatory effects of radio- and immunotherapy by sensitizing cancer cells to treatment-induced TNF and interferons. This promoted ICD, antitumor immunity, and durable treatment responses. Consequently, targeting RIPK1 by PROTACs emerges as a promising approach to overcome radio- or immunotherapy resistance and enhance anticancer therapies.
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
'%3e%3cpath fill='%23012169' d='M0 0v30h60V0z'/%3e%3cpath stroke='%23fff' stroke-width='6' d='m0 0 60 30m0-30L0 30'/%3e%3cpath stroke='%23C8102E' stroke-width='4' d='m0 0 60 30m0-30L0 30' clip-path='url(%23b)'/%3e%3cpath stroke='%23fff' stroke-width='10' d='M30 0v30M0 15h60'/%3e%3cpath stroke='%23C8102E' stroke-width='6' d='M30 0v30M0 15h60'/%3e%3c/g%3e%3c/svg%3e)
