Proteomic Analysis of Zeb1 Interactome in Breast Carcinoma Cells

Precision unveiled: Synergistic genomic landscapes in breast cancer-Integrating single-cell analysis and decoding drug toxicity for elite prognostication and tailored therapeutics

BACKGROUND

Globally, breast cancer, with diverse subtypes and prognoses, necessitates tailored therapies for enhanced survival rates. A key focus is glutamine metabolism, governed by select genes. This study explored genes associated with T cells and linked them to glutamine metabolism to construct a prognostic staging index for breast cancer patients for more precise medical treatment.

METHODS

Two frameworks, T-cell related genes (TRG) and glutamine metabolism (GM), stratified breast cancer patients. TRG analysis identified key genes via hdWGCNA and machine learning. T-cell communication and spatial transcriptomics emphasized TRG's clinical value. GM was defined using Cox analyses and the Lasso algorithm. Scores categorized patients as TRG_high+GM_high (HH), TRG_high+GM_low (HL), TRG_low+GM_high (LH), or TRG_low+GM_low (LL). Similarities between HL and LH birthed a "Mixed" class and the TRG_GM classifier. This classifier illuminated gene variations, immune profiles, mutations, and drug responses.

RESULTS

Utilizing a composite of two distinct criteria, we devised a typification index termed TRG_GM classifier, which exhibited robust prognostic potential for breast cancer patients. Our analysis elucidated distinct immunological attributes across the classifiers. Moreover, by scrutinizing the genetic variations across groups, we illuminated their unique genetic profiles. Insights into drug sensitivity further underscored avenues for tailored therapeutic interventions.

CONCLUSION

Utilizing TRG and GM, a robust TRG_GM classifier was developed, integrating clinical indicators to create an accurate predictive diagnostic map. Analysis of enrichment disparities, immune responses, and mutation patterns across different subtypes yields crucial subtype-specific characteristics essential for prognostic assessment, clinical decision-making, and personalized therapies. Further exploration is warranted into multiple fusions between metrics to uncover prognostic presentations across various dimensions.

Morphological and cytoskeleton changes in cells after EMT

Epithelial cells undergoing EMT experience significant alterations at transcriptional and morphological levels. However, changes in the cytoskeleton, especially cytoskeleton dynamics are poorly described. Addressing the question we induced EMT in three cell lines (MCF-7, HaCaT and A-549) and analyzed morphological and cytoskeletal changes there using immunostaining and life cell imaging of cells transfected with microtubule and focal adhesion markers. In all studied cell lines, cell area after EMT increased, MCF-7 and A-549 cells became elongated, while HaCaT cells kept the aspect ratio the same. We next analyzed three components of the cytoskeleton: microtubules, stress fibers and focal adhesions. The following changes were observed after EMT in cultured cells: (i) Organization of microtubules becomes more radial; and the growth rate of microtubule plus ends was accelerated; (ii) Actin stress fibers become co-aligned forming the longitudinal cell axis; and (iii) Focal adhesions had decreased area in all cancer cell lines studied and became more numerous in HaCaT cells. We conclude that among dynamic components of the cytoskeleton, the most significant changes during EMT happen in the regulation of microtubules.

Prognostic Value of Tumor Budding for Early Breast Cancer

BACKGROUND

Tumor budding (TB) is a dynamic process associated with the epithelial-mesenchymal transition and a well-established prognostic biomarker for colorectal cancer. As part of the tumor microenvironment, tumor buds demonstrate increased cell motility and invasiveness. Current evidence demonstrates that high levels of TB correlate with disease progression and worst outcomes across different solid tumors. Our work aims to demonstrate the clinical applicability of TB analysis and its utility as a prognostic factor for patients with early breast cancer (EBC).

METHODS

Retrospective, single-center, observational study, enrolling patients with EBC diagnosed in a Portuguese hospital between 2014 and 2015. TB classification was performed according to the International Tumor Budding Conference 2016 guidelines.

RESULTS

A statistically significant relation was found between higher TB score and aggressive clinicopathological features (angiolymphatic/perineural invasion-p < 0.001; tumor size-p = 0.012; nuclear grading-p < 0.001; and Ki-67 index-p = 0.011), higher number of relapses (p < 0.001), and short disease-free survival (DFS) (p < 0.001).

CONCLUSION

We demonstrate that high TB correlates with shorter DFS and aggressive clinicopathological features used in daily practice to decide on the benefit of chemotherapy for EBC. TB represents a needed prognostic biomarker for EBC, comprising a new factor to be considered in the adjuvant decision-making process by identifying patients at a high risk of relapse and with higher benefit on treatment intensification. Clinical trials incorporating TB are needed to validate its prognostic impact.

p53 Affects Zeb1 Interactome of Breast Cancer Stem Cells

P53 is a critical tumor suppressor that protects the integrity of genome and prevents cells from malignant transformation, including metastases. One of the driving forces behind the onset of metastases is the epithelial to mesenchymal transition (EMT) program. Zeb1 is one of the key transcription factors that govern EMT (TF-EMT). Therefore, the interaction and mutual influence of p53 and Zeb1 plays a critical role in carcinogenesis. Another important feature of tumors is their heterogeneity mediated by the presence of so-called cancer stem cells (CSCs). To this end, we have developed a novel fluorescent reporter-based approach to enrich the population of CSCs in MCF7 cells with inducible expression of Zeb1. Using these engineered cell lines, we studied the effect of p53 on Zeb1 interactomes isolated from both CSCs and regular cancer cells. By employing co-immunoprecipitations followed by mass spectrometry, we found that the composition of Zeb1 interactome was affected not only by the p53 status but also by the level of Oct4/Sox2 expression, indicating that stemness likely affects the specificity of Zeb1 interactions. This study, together with other proteomic studies of TF-EMT interactomes, provides a framework for future molecular analyses of biological functions of Zeb1 at all stages of oncogenesis.

Metformin resistant MDA-MB-468 cells exhibit EMT-like phenotype and increased migration capacity

PURPOSE

Metformin is one of the most prescribed drugs for the treatment of type II diabetes. Its anti-proliferative effect is also taken advantage for the treatment of cancer. Despite many of the studies mentioning the positive effects of metformin in inhibiting the proliferation of cancer cells, there are also studies which questions this idea as well.

METHODS

In this study, we investigated the most widely studied breast cancer cell lines, ER (+) MCF7 cells, TNBC MDA-MB-231 and MDA-MB-468 cells in terms of metastatic behavior under long-term metformin treatment. MCF7, MDA-MB-231 and MDA-MB-468 cells were gained resistant to metformin starting from 0.2 to 3.2 mM.

RESULTS

Compared to MCF7 and MDA-MB-231 cell lines, we only observed dramatic changes in MDA-MB-468 cells whose morphology has been changed towards mesenchymal like phenotype. Moreover, migration capacity of these cells was also significantly increased which were validated at both mRNA and protein levels as well as wound healing assay. In addition to EMT like phenotype and increasing migration capacity of metformin resistant MDA-MB-468 cells, they exhibited less sensitivity to PI3K inhibitor.

CONCLUSIONS

All together, our data pointed out that, metformin's effects should be questioned depending on the subtype of the breast cancer that's to be treated.

Zeb1-mediated autophagy enhances resistance of breast cancer cells to genotoxic drugs

Autophagy is a highly conserved process of cellular self-digestion that involves the formation of autophagosomes for the delivery of intracellular components and dysfunctional organelles to lysosomes. This process is induced by different signals including starvation, mitochondrial dysfunction, and DNA damage. The molecular link between autophagy and DNA damage is not well understood yet. Importantly, tumor cells utilize the mechanism of autophagy to cope with genotoxic anti-cancer drug therapy. Another mechanism of drug resistance is provided to cancer cells via the execution of the EMT program. One of the critical transcription factors of EMT is Zeb1. Here we demonstrate that Zeb1 is involved in the regulation of autophagy in several breast cancer cell models. On the molecular level, Zeb1 likely facilitates autophagy through the regulation of autophagic genes, resulting in increased LC3-II levels, augmented staining with Lysotracker, and increased resistance to several genotoxic drugs. The attenuation of Zeb1 expression in TNBC cells led to the opposite effect. Consequently, we propose that Zeb1 augments the resistance of breast cancer cells to genotoxic drugs, at least partially, via autophagy. Collectively, we have uncovered a novel function of Zeb1 in the regulation of autophagy in breast cancer cells.