The culture conditions and outputs from breast cancer cell line in vitro experiments

Transcriptome-wide analysis of the differences between MCF7 cells cultured in DMEM or αMEM

MCF7 cells have been used as an experimental model for breast cancer for decades. Typically, a culture medium is designed to supply cells with the nutrients essential for their continuous proliferation. Each medium has a specific nutritional composition. Therefore, cells cultured in different media may exhibit differences in their metabolism. However, only a few studies have investigated the effects of media on cells. In this study, we compared the effects of Dulbecco's modified Eagle medium (DMEM) and minimum essential medium alpha modification (αMEM) on MCF7 cells. The two media differentially affected the morphology, cell cycle, and proliferation of MCF7 cells, but had no effect on cell death. Replacement of DMEM with αMEM led to a decrease in ATP production and an increase in reactive oxygen species production, but did not affect the cell viability. RNA-sequencing and bioinformatic analyses revealed 721 significantly upregulated and 1247 downregulated genes in cells cultured in αMEM for 48 h compared with that in cells cultured in DMEM. The enriched gene ontology terms were related to mitosis and cell proliferation. Kyoto encyclopedia of genes and genomes analysis revealed cell cycle and DNA replication as the top two significant pathways. MCF7 cells were hypoxic when cultured in αMEM. These results show that the culture medium considerably affects cultured cells. Thus, the stability of the culture system in a study is very important to obtain reliable results.

DAB2IP attenuates chemoresistance of triple-negative breast cancer through sequestration of RAC1 to prevent β-catenin nuclear accumulation

BACKGROUND

Although chemotherapy, the most widely used systemic treatment in triple-negative breast cancer (TNBC), markedly improved the patients' outcome, chemoresistance always occurs. This study purposed to explore new therapeutic strategies for the treatment of chemoresistance.

METHODS AND RESULTS

The expression and prognostic value of DAB2IP were investigated in TNBC tissues and cell lines. Low DAB2IP expression predicted high mortality risk in TNBC. Inhibition of DAB2IP expression conferred cancer stem cell capacity and chemoresistance in TNBC cell lines. Using murine breast cancer (BC) xenograft models, we evaluated the association with DAB2IP and chemoresistance. DAB2IP inhibited TNBC tumourigenesis and chemoresistance in vivo. Further, we revealed that DAB2IP inhibited β-catenin nuclear transport through competitive interaction with RAC1 and decreased β-catenin accumulation in the cell nucleus. Finally, we found that the DNA methylation level was negatively associated with DAB2IP expression in TNBC. Inhibition of DNA methylation restored the DAB2IP expression and attenuated chemoresistance in TNBC.

CONCLUSIONS

We revealed that DAB2IP attenuates chemoresistance of TNBC via inhibition of RAC1-mediated β-catenin nuclear accumulation. Decitabine treatment results in re-expression of DAB2IP by inhibiting DNA methylation and could be a potential therapeutic strategy for chemoresistance in TNBC.

Gene expressions and their significance in organoid cultures obtained from breast cancer patient-derived biopsies

Gene expression changes are one of the hallmarks of malignant cells and such changes in specific genes have been identified for a variety of human cancers. Such an association in gene expression changes becomes very significant for breast cancers due to the genetic heterogeneity seen in such cancers. It is due to such genetic implication that breast cancers are classified into several subtypes; based on the expression and the magnitude of expression of estrogen and progesterone receptor genes. Changes in the expression of ERBB2, ESR1, PLAU, MUC1, PGR, and TP53 are implicated in breast cancers. Of the various models available for cancer research, organoid cultures from patient-derived biopsies are being considered as the most relevant for invitro testing. Organoid cultures derived from patient biopsies mitigate several limitations of other commonly available models such as cancer cell lines. Such organoids retain the functional physiology of solid tumors which include gene expression. Also, utilizing patient derived organoids for in vitro testing paves way for personalized medicine which greatly enhances the effectiveness of cancer therapy for individuals. We present the genes implicated in breast cancers, the ways in which organoids can be derived from breast cancer biopsies and their applications for gene expression studies.

Raman spectroscopy and machine learning for the classification of breast cancers

Breast cancer is a major health threat for women. The drug responses associated with different breast cancer subtypes have obvious effects on therapeutic outcomes; therefore, the accurate classification of breast cancer subtypes is critical. Breast cancer subtype classification has recently been examined using various methods, and Raman spectroscopy has emerged as an effective technique that can be used for noninvasive breast cancer analysis. However, the accurate and rapid classification of breast cancer subtypes currently requires a great deal of effort and experience with the processing and analysis of Raman spectra data. Here, we adopted Raman spectroscopy and machine learning techniques to simplify and accelerate the process used to distinguish normal from breast cancer cells and classify breast cancer subtypes. Raman spectra were obtained from cultured breast cancer cell lines, and the data were analyzed by two machine learning algorithms: principal component analysis (PCA)-discriminant function analysis (DFA) and PCA-support vector machine (SVM). The accuracies with which these two algorithms were able to distinguish normal breast cells from breast cancer cells were both greater than 97%, and the accuracies of breast cancer subtype classification for both algorithms were both greater than 92%. Moreover, our results showed evidence to support the use of characteristic Raman spectral features as cancer cell biomarkers, such as the intensity of intrinsic Raman bands, which increased in cancer cells. Raman spectroscopy combined with machine learning techniques provides a rapid method for breast cancer analysis able to reveal differences in intracellular compositions and molecular structures among subtypes.

In Silico Design and Evaluation of PRAME+FliCΔD2D3 as a New Breast Cancer Vaccine Candidate

Background

The most prevalent cancer in women over the world is breast cancer. Immunotherapy is a promising method to effectively treat cancer patients. Among various immunotherapy methods, tumor antigens stimulate the immune system to eradicate cancer cells. Preferentially expressed antigen in melanoma (PRAME) is mainly overexpressed in breast cancer cells, and has no expression in normal tissues. FliCΔD2D3, as truncated flagellin (FliC), is an effective toll-like receptor 5 (TLR5) agonist with lower inflammatory responses. The objective of the present study was to utilize bioinformatics methods to design a chimeric protein against breast cancer.

Methods

The physicochemical properties, solubility, and secondary structures of PRAME+FliCΔD2D3 were predicted using the tools ProtParam, Protein-sol, and GOR IV, respectively. The 3D structure of the chimeric protein was built using I-TASSER and refined with GalaxyRefine, RAMPAGE, and PROCHECK. ANTIGENpro and VaxiJen were used to evaluate protein antigenicity, and allergenicity was checked using AlgPred and Allergen FP. Major histocompatibility complex )MHC( and cytotoxic T-lymphocytes )CTL( binding peptides were predicted using HLApred and CTLpred. Finally, B-cell continuous and discontinuous epitopes were predicted using ABCpred and ElliPro, respectively.

Results

The stability and solubility of PRAME+FliCΔD2D3 were analyzed, and its secondary and tertiary structures were predicted. The results showed that the derived peptides could bind to MHCs and CTLs. The designed chimeric protein possessed both linear and conformational epitopes with a high binding affinity to B-cell epitopes.

Conclusion

PRAME+FliCΔD2D3 is a stable and soluble chimeric protein that can stimulate humoral and cellular immunity. The obtained results can be utilized for the development of an experimental vaccine against breast cancer.