Cell facilitation promotes growth and survival under drug pressure in breast cancer

Abstract

The interplay of positive and negative interactions between drug-sensitive and resistant cells influences the effectiveness of treatment in heterogeneous cancer cell populations. Here, we study interactions between estrogen receptor-positive breast cancer cell lineages that are sensitive and resistant to ribociclib-induced cyclin-dependent kinase 4 and 6 (CDK4/6) inhibition. In mono- and coculture, we find that sensitive cells grow and compete more effectively in the absence of treatment. During treatment with ribociclib, sensitive cells survive and proliferate better when grown together with resistant cells than when grown in monoculture, termed facilitation in ecology. Molecular, protein, and genomic analyses show that resistant cells increase metabolism and production of estradiol, a highly active estrogen metabolite, and increase estrogen signaling in sensitive cells to promote facilitation in coculture. Adding estradiol in monoculture provides sensitive cells with increased resistance to therapy and cancels facilitation in coculture. Under partial inhibition of estrogen signaling through low-dose endocrine therapy, estradiol supplied by resistant cells facilitates sensitive cell growth. However, a more complete blockade of estrogen signaling, through higher-dose endocrine therapy, diminished the facilitative growth of sensitive cells. Mathematical modeling quantifies the strength of competition and facilitation during CDK4/6 inhibition and predicts that blocking facilitation has the potential to control both resistant and sensitive cancer cell populations and inhibit the emergence of a refractory population during cell cycle therapy.

Se-Pair Search for Deciphering Selenium-Encoded Peptide and a Pyrolysis-Thermolysis Dietary Model for Minimizing Loss of “KKSe(M)R” during Processing

“…The pyrolysis-thermolysis intermediate variables (KSe­(M)­R, C 17 H 35 N 7 O 4 Se m / z 482.19885 or KSe­(M)­R, C 17 H 34 N 6 O 4 Se m / z 465.17230) were ascertained based on E a and k via quantitative kinetic analysis, and the E a quantifies the contribution of each intermediate product variable, effectively simplifying the pyrolysis-thermolysis modeling pathway. The selenopeptide KKSe­(M)­R variations under distinct pyrolysis-thermolysis conditions (37 °C, 100 °C, and 200 °C processing) are depicted by Logistic fitting in eq , where L 0 is the KKSe­(M)­R level in the preliminary reaction . KKSe­(M)­R concentrations at different pyrolysis-thermolysis periods (100 and 200 °C processing: 0, 20, 40, 60, 80, 100, and 120 min; 37 °C processing: 0, 12, 24, 36, 48, 60, and 72 h) were fitted by least squares in OriginPro ( version 10.0.5.157) software in eq , in which L z = 6159457.67 and r e = −0.01841 (37 °C) (eq ); L z = 4837401.11 and r e = −0.01296 (100 °C) (eq ); and L z = 512145.80 and r e = −0.0297 (200 °C) (eq ).…”

“…The most severely pyrolyzed behavior, which seemed to be intimately interrelated with the structure of the amide bond (KSe(M)R, where L 0 is the KKSe(M)R level in the preliminary reaction. 46 KKSe(M)R concentrations at different pyrolysis-thermolysis periods (100 and 200 °C processing: 0, 20, 40, 60, 80, 100, and 120 min; 37 °C processing: 0, 12, 24, 36, 48, 60, and 72 h) were fitted by least squares in OriginPro (version 10.0.5.157) software in eq 1, in which L z = 6159457.67 and r e = −0.01841 (37 °C) (eq 2); L z = 4837401.11 and r e = −0.01296 (100 °C) (eq 3); and L z = 512145.80 and r e = −0.0297 (200 °C) (eq 4).…”

Cell-state transitions and frequency-dependent interactions among subpopulations together explain the dynamics of spontaneous epithelial-mesenchymal heterogeneity in breast cancer

“…While this prediction remains to be experimentally tested in these cells, resource competition between drug-sensitive and drug-resistant cells is the fundamental idea underlying adaptive therapy that has already shown promise in delaying the occurrence of resistant in several clinical trials 34 . Furthermore, different tumour clones or phenotypes need not always compete with one another for resources; they may also reciprocally facilitate growth such that their mutual gain leads to highly aggressive and metastatic disease 35,36,38 . Thus, identifying the nature of interaction between different subpopulations within a tumour is crucial to design an optimal treatment strategy.…”

The multifaceted roles of GSDME-mediated pyroptosis in cancer: therapeutic strategies and persisting obstacles

“…Breast cancer is the most prevalent malignancy among adult women [ 130 ]. Xu et al provided preliminary evidence that GW-8510, an inhibitor of cyclin-dependent kinase (CDK) 2, could trigger GSDME-mediated pyroptosis in triple-negative breast cancer (TNBC) cells and mice models [ 131 ].…”