Induction of Cell Death by Cytokines in Cell Cycle-Synchronous Tumor Cell Populations Restricted to G1and G2

A major confounding issue in the successful treatment of cancer is the existence of tumor cell populations that resist therapeutic agents and regimens. While tremendous effort has gone into understanding the biochemical mechanisms underlying resistance to each traditional and targeted therapeutic, a broader approach to the problem may emerge from the recognition that existing anti-cancer agents elicit their cytotoxic effects almost exclusively through apoptosis. Considering the myriad mechanisms cancer cells employ to subvert apoptotic death, an attractive alternative approach would leverage programmed necrotic mechanisms to side-step therapeutic resistance to apoptosis-inducing agents. Lysosomal cell death (LCD) is a programmed necrotic cell death mechanism that is engaged upon the compromise of the limiting membrane of the lysosome, a process called lysosomal membrane permeabilization (LMP). The release of lysosomal components into the cytosol upon LMP triggers biochemical cascades that lead to plasma membrane rupture and necrotic cell death. Interestingly, the process of cellular transformation appears to render the limiting lysosomal membranes of tumor cells more fragile than non-transformed cells, offering a potential therapeutic window for drug development. Here we outline the concepts of LMP and LCD, and discuss strategies for the development of agents to engage these processes. Importantly, the potential exists for existing cationic amphiphilic drugs such as antidepressants, antibiotics, antiarrhythmics, and diuretics to be repurposed to engage LCD within therapy-resistant tumor cell populations.

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A Proteome-Wide CDK/CRK-Specific Kinase Inhibitor Promotes Tumor Cell Death in the Absence of Cell Cycle Progression

Chemistry & Biology ◽

10.1016/j.chembiol.2005.08.008 ◽

2005 ◽

Vol 12 (10) ◽

pp. 1103-1115 ◽

Cited By ~ 26

Author(s):

Maureen Caligiuri ◽

Frank Becker ◽

Krishna Murthi ◽

Faith Kaplan ◽

Severine Dedier ◽

...

Keyword(s):

Cell Cycle ◽

Cell Death ◽

Tumor Cell ◽

Cell Cycle Progression ◽

Kinase Inhibitor ◽

Tumor Cell Death ◽

Cycle Progression ◽

Specific Kinase Inhibitor

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New di(hetero)arylethers and di(hetero)arylamines in the thieno[3,2-b]pyridine series: Synthesis, growth inhibitory activity on human tumor cell lines and non-tumor cells, effects on cell cycle and on programmed cell death

European Journal of Medicinal Chemistry ◽

10.1016/j.ejmech.2013.09.023 ◽

2013 ◽

Vol 69 ◽

pp. 855-862 ◽

Cited By ~ 18

Author(s):

Maria-João R.P. Queiroz ◽

Daniela Peixoto ◽

Ricardo C. Calhelha ◽

Pedro Soares ◽

Tiago dos Santos ◽

...

Keyword(s):

Cell Cycle ◽

Cell Death ◽

Tumor Cell ◽

Human Tumor ◽

Tumor Cell Lines ◽

Human Tumor Cell ◽

Human Tumor Cell Lines ◽

Growth Inhibitory ◽

Growth Inhibitory Activity ◽

Pyridine Series

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4‐Deoxyraputindole C induces cell death and cell cycle arrest in tumor cell lines

Journal of Cellular Biochemistry ◽

10.1002/jcb.28238 ◽

2018 ◽

Vol 120 (6) ◽

pp. 9608-9623 ◽

Cited By ~ 2

Author(s):

Wagner D. Vital ◽

Heron F. V. Torquato ◽

Larissa de Oliveira Passos Jesus ◽

Wagner Alves de Souza Judice ◽

Maria Fátima das G. F. da Silva ◽

...

Keyword(s):

Cell Cycle ◽

Cell Death ◽

Tumor Cell ◽

Cell Cycle Arrest ◽

Cell Lines ◽

Tumor Cell Lines ◽

Cycle Arrest

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Moment-Based Estimation of State-Switching Rates in Cell Populations

10.1101/2022.01.06.475260 ◽

2022 ◽

Author(s):

Michael M Saint-Antoine ◽

Abhyudai Singh

Keyword(s):

Gene Expression ◽

Cell Cycle ◽

Tumor Cell ◽

Simulated Data ◽

Computational Method ◽

Cell Populations ◽

Biologically Relevant ◽

Fluctuation Test ◽

State Switching

In isogenic cell populations, cells can switch back and forth between different gene expression states. These expression states can be biologically relevant. For example, a certain expression state may cause a tumor cell to be resistant to treatment, while another state may leave it vulnerable to treatment. However, estimating the rates of state-switching can be difficult, because experimentally measuring a cell's transcriptome often involves destroying the cell, so it can only be measured once. In this paper, we propose a computational method to estimate the rate of switching between expression states, given data from a Luria-Delbrück style fluctuation test that is experimentally simple and feasible. We then benchmark this method using simulated data to test its efficacy, with varying assumptions made about cell cycle timing distribution in the simulations.

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