Breast Cancer Radiogenomics: Association of Enhancement Pattern at DCE MRI with Deregulation of mTOR Pathway

Abstract Background Lymphovascular invasion (LVI) is an important risk factor for prognosis of breast cancer and an unfavorable prognostic factor in node-negative invasive breast cancer patients. The purpose of this study was to evaluate the association between LVI and pre-operative features of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) in node-negative invasive breast cancer. Methods Data were collected retrospectively from 132 cases who had undergone pre-operative MRI and had invasive breast carcinoma confirmed on the last surgical pathology report. MRI and DWI data were analyzed for the size of tumor, mass shape, margin, internal enhancement pattern, kinetic enhancement curve, high intratumoral T2-weighted signal intensity, peritumoral edema, DWI rim sign, and apparent diffusion coefficient (ADC) values. We calculated the relationship between presence of LVI and various prognostic factors and MRI features. Results Pathologic tumor size, mass margin, internal enhancement pattern, kinetic enhancement curve, DWI rim sign, and the difference between maximum and minimum ADC were significantly correlated with LVI (p < 0.05). Conclusions We suggest that DCE-MRI with DWI would assist in predicting LVI status in node-negative invasive breast cancer patients.

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Radiomic Analysis of the Heterogeneous Tumor and Surrounding Parenchyma Based on DCE-MRI Decomposition to Predict HER2 Expression in Breast Cancer

10.21203/rs.3.rs-638341/v1 ◽

2021 ◽

Author(s):

Peng Zhang ◽

Juan Yan ◽

Zhongqi Liu ◽

Xiangsheng Li ◽

Qianxiang Zhou

Keyword(s):

Breast Cancer ◽

Contrast Enhancement ◽

Cross Validation ◽

Test Group ◽

Her2 Expression ◽

Breast Cancer Patients ◽

Enhancement Pattern ◽

Dce Mri ◽

Validation Test ◽

Heterogeneous Tumor

Abstract Background Human epidermal growth factor receptor-2 (HER2) correlates with cancer heterogeneity, and the identification of HER2 expression is invasive immunohistochemistry in the clinic. To determine whether noninvasive predictors of HER2 expression are implied in the dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).Methods 189/47 breast cancer patients collected from The Cancer Imaging Archive (TCIA) were used as a cross-validation/test group. A convex analysis of mixtures (CAM) was conducted to decompose heterogeneous tissues inside and outside the tumor. Their DCE-MRI images were decomposed into relatively homogeneous subregions with different contrast enhancement patterns. The predictor of HER2 expression was composed of radiomic features acquired from intratumoural or peritumoural subregions. The area under the curve (AUC) of receiver operating characteristic (ROC) was used to assess the predictive power.Results The predictor formed in the undecomposed tumor was used as a baseline for comparison (AUC=0.691±0.072/0.625±0.056 in cross-validation/test group). The intratumoural subregion with a contrast enhancement pattern corresponding to the plateau of signal intensity formed a more robust predictor (AUC=0.816±0.059/0.785±0.067, P=0.0128/0.0389). Peritumoral parenchyma of <20 mm from the tumor margin was also researched (AUC=0.589±0.083/0.524±0.064). The peritumoural subregion with a contrast enhancement pattern corresponding to steady enhancement also formed a helpful predictor compared to the undecomposed parenchyma (AUC=0.702±0.068/0.681±0.042, P=0.0128/0.0389). The best predictor was formed when two predictors from subregions were fused together (AUC=0.851±0.057/0.812±0.045, P=0.0011/0.0397).Conclusions A subregion rather than a heterogeneous tumor itself provided a more accurate predictor of HER2 expression. Radiomic predictors from intratumoural and peritumoural subregions were complementary to each other.

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Diffusion tensor imaging on 3-T MRI breast: diagnostic performance in comparison to diffusion-weighted imaging

Egyptian Journal of Radiology and Nuclear Medicine ◽

10.1186/s43055-021-00473-6 ◽

2021 ◽

Vol 52 (1) ◽

Author(s):

Dalia Abdelhady ◽

Amany Abdelbary ◽

Ahmed H. Afifi ◽

Alaa-eldin Abdelhamid ◽

Hebatallah H. M. Hassan

Keyword(s):

Breast Cancer ◽

Diffusion Tensor Imaging ◽

Sensitivity And Specificity ◽

Diffusion Weighted Imaging ◽

Diffusion Tensor ◽

Breast Mri ◽

Breast Lesions ◽

Dce Mri ◽

Additional Tool ◽

Diffusion Weighted

Abstract Background Breast cancer is the most prevalent cancer among females. Dynamic contrast-enhanced MRI (DCE-MRI) breast is highly sensitive (90%) in the detection of breast cancer. Despite its high sensitivity in detecting breast cancer, its specificity (72%) is moderate. Owing to 3-T breast MRI which has the advantage of a higher signal to noise ratio and shorter scanning time rather than the 1.5-T MRI, the adding of new techniques as diffusion tensor imaging (DTI) to breast MRI became more feasible. Diffusion-weighted imaging (DWI) which tracks the diffusion of the tissue water molecule as well as providing data about the integrity of the cell membrane has been used as a valuable additional tool of DCE-MRI to increase its specificity. Based on DWI, more details about the microstructure could be detected using diffusion tensor imaging. The DTI applies diffusion in many directions so apparent diffusion coefficient (ADC) will vary according to the measured direction raising its sensitivity to microstructure elements and cellular density. This study aimed to investigate the diagnostic accuracy of DTI in the assessment of breast lesions in comparison to DWI. Results By analyzing the data of the 50 cases (31 malignant cases and 19 benign cases), the sensitivity and specificity of DWI in differentiation between benign and malignant lesions were about 90% and 63% respectively with PPV 90% and NPV 62%, while the DTI showed lower sensitivity and specificity about 81% and 51.7%, respectively, with PPV 78.9% and NPV 54.8% (P-value ≤ 0.05). Conclusion While the DWI is still the most established diffusion parameter, DTI may be helpful in the further characterization of tumor microstructure and differentiation between benign and malignant breast lesions.

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Diagnosing breast cancer tumors using stacked ensemble model

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-219176 ◽

2021 ◽

pp. 1-9

Author(s):

Ahmet Haşim Yurttakal ◽

Hasan Erbay ◽

Türkan İkizceli ◽

Seyhan Karaçavuş ◽

Cenker Biçer

Keyword(s):

Breast Cancer ◽

Deep Learning ◽

Medical Imaging ◽

Early Stage ◽

False Negative ◽

Gradient Boosting ◽

Physical Sign ◽

Ensemble Model ◽

Learning Methods ◽

Dce Mri

Breast cancer is the most common cancer that progresses from cells in the breast tissue among women. Early-stage detection could reduce death rates significantly, and the detection-stage determines the treatment process. Mammography is utilized to discover breast cancer at an early stage prior to any physical sign. However, mammography might return false-negative, in which case, if it is suspected that lesions might have cancer of chance greater than two percent, a biopsy is recommended. About 30 percent of biopsies result in malignancy that means the rate of unnecessary biopsies is high. So to reduce unnecessary biopsies, recently, due to its excellent capability in soft tissue imaging, Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) has been utilized to detect breast cancer. Nowadays, DCE-MRI is a highly recommended method not only to identify breast cancer but also to monitor its development, and to interpret tumorous regions. However, in addition to being a time-consuming process, the accuracy depends on radiologists’ experience. Radiomic data, on the other hand, are used in medical imaging and have the potential to extract disease characteristics that can not be seen by the naked eye. Radiomics are hard-coded features and provide crucial information about the disease where it is imaged. Conversely, deep learning methods like convolutional neural networks(CNNs) learn features automatically from the dataset. Especially in medical imaging, CNNs’ performance is better than compared to hard-coded features-based methods. However, combining the power of these two types of features increases accuracy significantly, which is especially critical in medicine. Herein, a stacked ensemble of gradient boosting and deep learning models were developed to classify breast tumors using DCE-MRI images. The model makes use of radiomics acquired from pixel information in breast DCE-MRI images. Prior to train the model, radiomics had been applied to the factor analysis to refine the feature set and eliminate unuseful features. The performance metrics, as well as the comparisons to some well-known machine learning methods, state the ensemble model outperforms its counterparts. The ensembled model’s accuracy is 94.87% and its AUC value is 0.9728. The recall and precision are 1.0 and 0.9130, respectively, whereas F1-score is 0.9545.

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Inhibition of the PI3K/mTOR Pathway in Breast Cancer to Enhance Response to Immune Checkpoint Inhibitors in Breast Cancer

International Journal of Molecular Sciences ◽

10.3390/ijms22105207 ◽

2021 ◽

Vol 22 (10) ◽

pp. 5207

Author(s):

Chi Yan ◽

Jinming Yang ◽

Nabil Saleh ◽

Sheau-Chiann Chen ◽

Gregory D. Ayers ◽

...

Keyword(s):

Breast Cancer ◽

T Cells ◽

Tumor Growth ◽

Cd8 T Cells ◽

Immune Checkpoint ◽

Immune Checkpoint Inhibitors ◽

Checkpoint Inhibitors ◽

Mtor Pathway ◽

Complete Regression ◽

Mtor Inhibition

Objectives: Inhibition of the PI3K/mTOR pathway suppresses breast cancer (BC) growth, enhances anti-tumor immune responses, and works synergistically with immune checkpoint inhibitors (ICI). The objective here was to identify a subclass of PI3K inhibitors that, when combined with paclitaxel, is effective in enhancing response to ICI. Methods: C57BL/6 mice were orthotopically implanted with syngeneic luminal/triple-negative-like PyMT cells exhibiting high endogenous PI3K activity. Tumor growth in response to treatment with anti-PD-1 + anti-CTLA-4 (ICI), paclitaxel (PTX), and either the PI3Kα-specific inhibitor alpelisib, the pan-PI3K inhibitor copanlisib, or the broad spectrum PI3K/mTOR inhibitor gedatolisib was evaluated in reference to monotherapy or combinations of these therapies. Effects of these therapeutics on intratumoral immune populations were determined by multicolor FACS. Results: Treatment with alpelisib + PTX inhibited PyMT tumor growth and increased tumor-infiltrating granulocytes but did not significantly affect the number of tumor-infiltrating CD8+ T cells and did not synergize with ICI. Copanlisib + PTX + ICI significantly inhibited PyMT growth and increased activation of intratumoral CD8+ T cells as compared to ICI alone, yet did not inhibit tumor growth more than ICI alone. In contrast, gedatolisib + ICI resulted in significantly greater inhibition of tumor growth compared to ICI alone and induced durable dendritic-cell, CD8+ T-cell, and NK-cell responses. Adding PTX to this regimen yielded complete regression in 60% of tumors. Conclusion: PI3K/mTOR inhibition plus PTX heightens response to ICI and may provide a viable therapeutic approach for treatment of metastatic BC.

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Docosahexaenoic acid promotes the formation of autophagosomes in MCF-7 breast cancer cells through oxidative stress-induced growth inhibitor 1 mediated activation of AMPK/mTOR pathway

Food and Chemical Toxicology ◽

10.1016/j.fct.2021.112318 ◽

2021 ◽

pp. 112318

Author(s):

Chia-Han Tsai ◽

Chong-Kuei Lii ◽

Tsu-Shing Wang ◽

Kai-Li Liu ◽

Haw-Wen Chen ◽

...

Keyword(s):

Breast Cancer ◽

Oxidative Stress ◽

Docosahexaenoic Acid ◽

Cancer Cells ◽

Breast Cancer Cells ◽

Growth Inhibitor ◽

Mtor Pathway ◽

Mcf 7

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Phytochemicals from Ajwa dates pulp extract induce apoptosis in human triple-negative breast cancer by inhibiting AKT/mTOR pathway and modulating Bcl-2 family proteins

Scientific Reports ◽

10.1038/s41598-021-89420-z ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Mohsin Ali Khan ◽

Sahabjada Siddiqui ◽

Imran Ahmad ◽

Romila Singh ◽

Durga Prasad Mishra ◽

...

Keyword(s):

Breast Cancer ◽

Triple Negative Breast Cancer ◽

Triple Negative ◽

Mononuclear Cells ◽

Apoptotic Cell ◽

Human Peripheral Blood ◽

Annexin V ◽

Phoenix Dactylifera ◽

Mtor Pathway ◽

Peripheral Blood Mononuclear

AbstractAjwa dates (Phoenix dactylifera L.) have been described in traditional and alternative medicine to provide several health benefits, but their mechanism of apoptosis induction against human triple-negative breast cancer MDA-MB-231 cells remains to be investigated. In this study, we analyzed the phytoconstituents in ethanolic Ajwa Dates Pulp Extract (ADPE) by liquid chromatography-mass spectrometry (LC–MS) and investigated anticancer effects against MDA-MB-231 cells. LC–MS analysis revealed that ADPE contained phytocomponents belonging to classes such as carbohydrates, phenolics, flavonoids and terpenoids. MTT assay demonstrated statistically significant dose- and time-dependent inhibition of MDA-MB-231 cells with IC50 values of 17.45 and 16.67 mg/mL at 24 and 48 h, respectively. Hoechst 33342 dye and DNA fragmentation data showed apoptotic cell death while AO/PI and Annexin V-FITC data revealed cells in late apoptosis at higher doses of ADPE. More importantly, ADPE prompted reactive oxygen species (ROS) induced alterations in mitochondrial membrane potential (MMP) in ADPE treated MDA-MB-231 cells. Cell cycle analysis demonstrated that ADPE induced cell arrest in S and G2/M checkpoints. ADPE upregulated the p53, Bax and cleaved caspase-3, thereby leading to the downregulation of Bcl-2 and AKT/mTOR pathway. ADPE did not show any significant toxicity on normal human peripheral blood mononuclear cells which suggests its safe application to biological systems under study. Thus, ADPE has the potential to be used as an adjunct to the mainline of treatment against breast cancer.

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Tioconazole and Chloroquine Act Synergistically to Combat Doxorubicin-Induced Toxicity via Inactivation of PI3K/AKT/mTOR Signaling Mediated ROS-Dependent Apoptosis and Autophagic Flux Inhibition in MCF-7 Breast Cancer Cells

Pharmaceuticals ◽

10.3390/ph14030254 ◽

2021 ◽

Vol 14 (3) ◽

pp. 254

Author(s):

Afnan H. El-Gowily ◽

Samah A. Loutfy ◽

Ehab M. M. Ali ◽

Tarek M. Mohamed ◽

Mohammed A. Mansour

Keyword(s):

Breast Cancer ◽

Combination Therapy ◽

Cancer Cells ◽

Breast Cancer Cells ◽

Mtor Pathway ◽

Tumor Growth Inhibition ◽

Autophagic Flux ◽

Ki 67 ◽

Mcf 7

Cancer is a complex devastating disease with enormous treatment challenges, including chemo- and radiotherapeutic resistance. Combination therapy demonstrated a promising strategy to target hard-to-treat cancers and sensitize cancer cells to conventional anti-cancer drugs such as doxorubicin. This study aimed to establish molecular profiling and therapeutic efficacy assessment of chloroquine and/or tioconazole (TIC) combination with doxorubicin (DOX) as anew combination model in MCF-7 breast cancer. The drugs are tested against apoptotic/autophagic pathways and related redox status. Molecular docking revealed that chloroquine (CQ) and TIC could be potential PI3K and ATG4B pathway inhibitors. Combination therapy significantly inhibited cancer cell viability, PI3K/AkT/mTOR pathway, and tumor-supporting autophagic flux, however, induced apoptotic pathways and altered nuclear genotoxic feature. Our data revealed that the combination cocktail therapy markedly inhibited tumor proliferation marker (KI-67) and cell growth, along with the accumulation of autophagosomes and elevation of LC3-II and p62 levels indicated autophagic flux blockage and increased apoptosis. Additionally, CQ and/or TIC combination therapy with DOX exerts its activity on the redox balance of cancer cells mediated ROS-dependent apoptosis induction achieved by GPX3 suppression. Besides, Autophagy inhibition causes moderately upregulation in ATGs 5,7 redundant proteins strengthened combinations induced apoptosis, whereas inhibition of PI3K/AKT/mTOR pathway with Beclin-1 upregulation leading to cytodestructive autophagy with overcome drug resistance effectively in curing cancer. Notably, the tumor growth inhibition and various antioxidant effects were observed in vivo. These results suggest CQ and/or TIC combination with DOX could act as effective cocktail therapy targeting autophagy and PI3K/AKT/mTOR pathways in MCF-7 breast cancer cells and hence, sensitizes cancer cells to doxorubicin treatment and combat its toxicity.

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