Breast Cancer Research Articles

In-silico Binding, Stability, Pharmacokinetics, and Toxicity Studies on Natural (-)-ambrox Metabolites as Binding Ligands to Luminal B and Triple-negative/basal-like Proteins for Breast Cancer Therapy

Background:: Breast cancer is the most prevalent malignant tumour in women of all races and is the second largest cause of cancer-related death in the majority of races. Based on the pattern of gene expression, five intrinsic or molecular classifications for breast tumours are frequently used. Our research, which is presently being utilized to treat breast cancer and has the potential to significantly change the course of the illness, is focused on two of them: luminal B breast cancer and triplenegative/ basal-like breast cancer. Methods:: Screening a database containing millions of drug molecules or phytochemicals has become rapid and simple due to computer-aided drug design (CADD) techniques. In the current work, nine natural compounds were screened for ambrox from a sperm whale using docking research. Results:: Following docking studies, nine substances were discovered to interact with basal-like and luminal B breast cancer proteins. All nine metabolites, however, adhered to Lipinski's rule of five and had sufficient oral bioavailability. The greatest binding affinities were demonstrated by 13,14,15,16-tetranorlabdane-3-oxo-8,12-diol, 6-β-hydroxy ambrox, 1-α-hydroxy-3-oxoambrox, and 2-α-3-β-dihydroxy ambrox. Conclusion:: Therefore, it can be concluded that research on molecular docking and pharmacological mimics may hasten the discovery of new medications. The use of ambrox metabolites in the treatment of breast cancer also requires future perspectives on their therapeutic use.

Impact of HLA Class I Antigen, Killer Inhibitory Receptor, and FCGR3A Genotypes on Breast Cancer Susceptibility and Tumor Stage.

The identification in breast cancer (BC) of novel genetic biomarkers regulating natural killer (NK) cell function, including the HLA, KIR, and CD16A (FCGR3A), may be still a challenge. We aimed to evaluate whether the combined effect of these polymorphisms has an impact on BC susceptibility and progression. 47 BC Italian patients and healthy individuals (39 females and 66 males/females) were genotyped by Sanger sequencing (HLA-C exon 2-4 and FCGR3A-158V/F, 48L/R/H) and PCR-SSP typing (KIR genes). HLA-C gene allele analysis showed the group C1, with HLA-C*07:02:01 allele, to be significantly associated with tumor progression (16.7% vs. 4.0%, p=0.04, OR=4.867), and instead, group C2, with HLA-C*05:01:01, was protective against disease susceptibility (0.0% vs. 7.2%, p=0.019, OR=0.087). In addition, we highlighted a significant reduction of the KIR2DS4ins in BC patients (pcorr.=0.022) and an increased combined presence of KIR2DL1 and KIR2DS1 genes in advanced BC patients compared to earlier stages (66.7% vs. 19.2%, p=0.002). The concurrent lack of KIR2DL2 and KIR2DS4 genes in the presence of HLA-C2 alleles was significantly associated with increased susceptibility to BC (p=0.012, OR=5.020) or with lymph node involvement (p=0.008, OR=6.375). Lastly, we identified different combinations of the FCGR3A-48/158 variants and KIR genes in BC patients compared to controls. Our findings suggest that in the development of BC probably exists a disorder of the NK innate immunity influenced by KIR/HLA-C gene content and FCGR3A-158 polymorphisms and that the combined analysis of these biomarkers might help predict genetic risk scores for tailored screening of BC patients in therapy.

Apigenin is an anoikis sensitizer with strong anti-metastatic properties in experimental breast cancer

Loss of susceptibility to anoikis signals is a crucial step in metastasis. Anoikis resistance therefore represents a promising adjuvant therapeutic target for cancer management. In this study, we have conducted a rationalized screening to search for novel leading anoikis sensitizer from daily foods. Among 19 tested dietary phytochemicals, the best results were obtained with apigenin, a natural component of celery. Phenotypically, apigenin sensitized breast cancer cells to anoikis, lowered the number of circulating tumor cells, and protected against breast cancer metastasis to lung in mice. Mechanistically, we demonstrated that the thromboxane A2 (TXA2)-TXA2 receptor (TP) axis has a critical role in acquired anoikis resistance by activating PI3K-Akt signaling pathway. Blockage of TXA2 signaling up-regulated p53 as well as its target gene p21, caused a G1 phase arrest, and finally led to apoptosis in breast cancer cells. TXA2 level was positively correlated with breast cancer cell anoikis rate, and apigenin significantly inhibited TXA2 biosynthesis in vitro and in vivo. Collectively, we identified apigenin as a potent anoikis sensitizer with anti-metastatic properties in a mouse model of breast cancer, and these findings might provide a rationale for introducing apigenin supplementation to breast cancer patients.

An Updated Review on the Early Detection and Drug Development Targeting Breast Cancer

Background: Breast cancer is one of the most common types of cancer in women globally, which poses a significant public health threat on a global scale. Continuous updates of the recent development in terms of drug development and diagnosis are the key to decoding the complexity of the location-specific different forms of breast cancer. The aim of this review is to sifter out the current advances and status of drugs, treatments, therapies and technologies related to breast cancer. Methodology: The authors searched for a number of article sources, and all possible data was collected from different databases like MEDLINE, EMBASE, Pub Med, Web of Science and Google Scholar. to identify recent development in drug development and diagnosis. Result: After a detailed literature survey, it was found that in drug discovery, a number of new drug candidates for breast cancer have completed clinical trials; in the diagnosis of breast cancer, a number of new technologies like artificial intelligence (AI), smart bra, smart vest, clinical breast exam have developed. It was found that breast self-awareness has immense importance in the early detection of breast cancer, which is par with the accuracy of modern diagnostic tools. Conclusion: An effort has been made to present all the updated data related to recent drug development, like surveillance status of drugs in clinical trials, diagnosis and social stigma of people with breast cancer recovery. Recent technological advances have led to the development of many devices for the early detection of breast cancer, providing efficacy in line with the diagnostic tools that pave the way for early treatment using effective drug candidates.

A novel machine learning model for breast cancer detection using mammogram images.

The most fatal disease affecting women worldwide now is breast cancer. Early detection of breast cancer enhances the likelihood of a full recovery and lowers mortality. Based on medical imaging, researchers from all around the world are developing breast cancer screening technologies. Due to their rapid progress, deep learning algorithms have caught the interest of many in the field of medical imaging. This research proposes a novel method in mammogram image feature extraction with classification and optimization using machine learning in breast cancer detection. The input image has been processed for noise removal, smoothening, and normalization. The input image features were extracted using probabilistic principal component analysis for detecting the presence of tumors in mammogram images. The extracted tumor region is classified using the Naïve Bayes classifier and transfer integrated convolution neural networks. The classified output has been optimized using firefly binary grey optimization and metaheuristic moth flame lion optimization. The experimental analysis has been carried out in terms of different parameters based on datasets. The proposed framework used an ensemble model for breast cancer that made use of the proposed Bayes + FBGO and TCNN + MMFLO classifier and optimizer for diverse mammography image datasets. The INbreast dataset was evaluated using the proposed Bayes + FBGO and TCNN + MMFLO classifiers, which achieved 95% and 98% accuracy, respectively.

Liposomal Nano-Based Drug Delivery Systems for Breast Cancer Therapy: Recent Advances and Progresses.

Breast cancer is a highly prevalent disease on a global scale, with a 30% incidence rate among women and a 14% mortality rate. Developing countries bear a disproportionate share of the disease burden, while countries with greater technological advancements exhibit a higher incidence. A mere 7% of women under the age of 40 are diagnosed with breast cancer, and the prevalence of this ailment is significantly diminished among those aged 35 and younger. Chemotherapy, radiation therapy, and surgical intervention comprise the treatment protocol. However, the ongoing quest for a definitive cure for breast cancer continues. The propensity for cancer stem cells to metastasize and resistance to treatment constitute their Achilles' heel. The advancement of drug delivery techniques that target cancer cells specifically holds significant promise in terms of facilitating timely detection and effective intervention. Novel approaches to pharmaceutical delivery, including nanostructures and liposomes, may bring about substantial changes in the way breast cancer is managed. These systems offer a multitude of advantages, such as heightened bioavailability, enhanced solubility, targeted tumor destruction, and diminished adverse effects. The application of nano-drug delivery systems to administer anti-breast cancer medications is a significant subject of research. This article delves into the domain of breast cancer, conventional treatment methods, the incorporation of nanotechnology into managerial tactics, and strategic approaches aimed at tackling the disease at its core.

STK3 higher expression association with clinical characteristics in intrinsic subtypes of breast cancer invasive ductal carcinoma patients.

STK3 has a central role in maintaining cell homeostasis, proliferation, growth, and apoptosis. Previously, we investigated the functional link between STK3/MST2, and estrogen receptor in MCF-7 breast cancer cells. To expand the investigation, this study evaluated STK3's higher expression and associated genes in breast cancer intrinsic subtypes using publicly available data. The relationship between clinical pathologic features and STK3 high expression was analyzed using descriptive and multivariate analysis. Increased STK3 expression in breast cancer was significantly associated with higher pathological cancer stages, and a different expression level was observed in the intrinsic subtypes of breast cancer. Kaplan-Meier analysis showed that breast cancer with high STK3 had a lower survival rate in IDC patients than that with low STK3 expression (p < 0.05). The multivariate analysis unveiled a strongcorrelation between STK3 expression and the survival rate among IDC patients, demonstrating hazard ratios for lower expression. In the TCGA dataset, the hazard ratio was 0.56 (95% CI 0.34-0.94, p = 0.029) for patients deceased with tumor, and 0.62 (95% CI 0.42-0.92, p = 0.017) for all deceased patients. Additionally, in the METABRIC dataset, the hazard ratio was 0.76 (95% CI 0.64-0.91, p = 0.003) for those deceased with tumor. From GSEA outcomes 7 gene sets were selected based on statistical significance (FDR < 0.25 and p < 0.05). Weighted Sum model (WSM) derived top 5% genes also have higher expression in basal and lower in luminal A in association with STK3. By introducing a novel bioinformatics approach that combines GSEA and WSM, the study successfully identified the top 5% of genes associated with higher expression of STK3.

Matrix Metalloproteinase 1 Acts as an Independent Prognostic Biomarker Correlated with Immune Infiltration in Breast Cancer

Matrix metalloproteinase 1 (MMP1) is overexpressed in multiple human tumors. However, the role of MMP1 in breast cancer (BRCA) has not been explored. The relationship between MMP1 expression and immune cell infiltration was conducted using Tumor Immune Estimation Resource (TIMER, &lt;ext-link ext-link-type="uri" xlink:href="https://cistrome.shinyapps.io/timer/"&gt;https://cistrome.shinyapps.io/timer/&lt;/ext-link&gt;), and the survival curve was plotted using Kaplan-Meier with log-rank test. The influence of MMP1 on immune infiltration, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses, immunologic infiltration analysis, and drug sensitivity were conducted through R 4.2.0. Immunohistochemistry (IHC) and immunofluorescence (IF) were used to verify MMP1 expression in BC and the correlation between MMP1 and CD20, CD86 immune cells. MMP1 was overexpressed in BRCA tumors (P &lt; 0.05), and its high expression was related to poor prognosis (P = 0.01). In addition, MMP1 was an independent prognostic biomarker in BRCA. Our findings provide information to further understand the biological functions and signaling pathways of MMP1 in BRCA. IHC and IF have proven the relationship between MMP1 and BRCA. These results implied a critical role of MMP1 in the prognosis and immune infiltration of BRCA. In addition, MMP1 expression participated in regulating multiple oncogenes and tumorigenesis.

Comparing survival outcomes between neoadjuvant and adjuvant chemotherapy within T2N1M0 stage hormone receptor-positive, HER2-negative breast cancer: a retrospective cohort study based on SEER database.

Guideline recommendations for the application of neoadjuvant chemotherapy (NACT) in T2N1M0 stage hormone receptor-positive, HER2-negative (HR + /HER2-) breast cancer are ambiguous. The debate continues regarding whether NACT or adjuvant chemotherapy (ACT) offers superior survival outcomes for these patients. Female patients diagnosed with HR + /HER2- breast cancer at T2N1M0 stage between 2010 and 2020, were identified from the Surveillance, Epidemiology, and End Results database and divided into two groups, the NACT group and the ACT group. Propensity score matching (PSM) was utilized to establish balanced cohorts between groups, considering baseline features. Kaplan-Meier (K-M) analysis and the Cox proportional hazards model were executed to assess the efficacy of both NACT and ACT in terms of overall survival (OS) and breast cancer-specific survival (BCSS). A logistic regression model was employed to examine the association between predictive variables and response to NACT. After PSM, 4,682 patients were finally included. K-M curves showed that patients receiving NACT exhibited significantly worse OS and BCSS when compared with patients undergoing ACT. Multivariable Cox analysis indicated that not achieving pathologic complete response (non-pCR) after NACT (versus ACT), was identified as an adverse prognostic factor for OS (HR 1.58, 95% CI 1.36-1.83) and BCSS (HR 1.70, 95% CI 1.44-2. 02). The logistic regression model revealed that low tumor grade independently predicted non-pCR. Among T2N1M0 stage HR + /HER2- patients, OS and BCSS of NACT were inferior to ACT. Patients who attained non-pCR after NACT demonstrated significantly worse survival outcomes compared with those who received ACT.

Breast cancer relapse disease prediction improvements with ensemble learning approaches

Diagnosis and prognosis are especially difficult areas of medical research related to cancer due to the high incidence of breast cancer, which has surpassed all other cancers in terms of female mortality. Another factor that has a substantial influence on the quality of life of cancer patients is the fear that they may experience a relapse of their disease. The objective of the study is to give medical practitioners a more effective strategy for using ensemble learning techniques to forecast when breast cancer may recur. This research aimed to investigate the usage of deep neural networks (DNNs) and artificial neural networks (ANNs) in addition to machine learning (ML) based approaches, including bagging, averaging, and voting, to enhance the efficacy of breast cancer relapse diagnosis on two breast cancer relapse datasets. Results from the empirical study demonstrate that the proposed ensemble learning-enabled approach improves accuracies by 96.31% and 95.81%, precisions by 96.70% and 96.15%, sensitivities by 98.88% and 98.68%, specificities by 84.62% in both, F1-scores by 97.78% and 97.40%, and area under the curve (AUCs) of 0.987 and 0.978, with University Medical Centre, Institute of Oncology (UMCIO) and Wisconsin prognostic breast cancer (WPBC) datasets respectively. Consequently, these improved disease outcomes may encourage physicians to use this model to make better treatment choices.

The Size Differences of Breast Cancer and Benign Tumors Measured by Two-Dimensional Ultrasound and Contrast-Enhanced Ultrasound.

Ultrasound (US) imaging has been observed to underestimate tumor size in clinical practice. This study aims to compare the size measurements of breast cancer and benign tumors using two-dimensional ultrasound (2DUS) and contrast-enhanced ultrasound (CEUS). The study included 42 clinically confirmed breast cancer and 47 benign breast tumors. Two experienced physicians independently measured the maximal longitudinal and transverse diameters of the masses in 2DUS and CEUS. All analyses were performed in R (4.2.2) and GraphPad Prism 6. The maximal longitudinal and transverse diameters of breast cancer measured by CEUS were 26.61 ± 0.21% and 26.24 ± 0.19% larger compared with 2DUS, and benign breast tumors had an 11.74 ± 0.21% and 11.06 ± 0.14% increase in size compared with 2DUS. The area under the curve (AUC) of the receiver operating characteristic curve (ROC) for the difference between 2DUS and CEUS was 0.870 for longitudinal diameters (95% CI: 0.795-0.945, sensitivity 0.842, specificity 0.783, threshold value 0.215), and 0.863 for transverse diameters (95% CI: 0.785-0.942, sensitivity 0.667, specificity 0.936, threshold value 0.203). The size measurements of both breast cancer and benign tumors were larger in CEUS compared with 2DUS, with CEUS measurements of breast cancer being more pronounced than those of benign breast tumors. These findings suggest that CEUS may provide a more precise assessment of tumor size, which is crucial for determining optimal treatment strategies and improving patient outcomes in breast cancer management.

Arnicolide D Inhibits Oxidative Stress-Induced Breast Cancer Cell Growth And Invasion Through Apoptosis, Ferroptosis, And Parthanatos.

Breast cancer is the most common malignant tumor in women, and its pathogenesis is very complicated. More and more studies have found that Traditional Chinese Medicine plays an important role in tumor prevention. To investigate the mechanism of arnicolide D isolated from Centipeda minima in breast cancer. Cell Counting Kit-8 (CCK-8), western blot, RT-qPCR, ELISA, flow cytometry, and Transwell were used to detect the effect of arnicolide D on the biological function of breast cancer cells. Arnicolide D promoted reactive oxygen species (ROS) production and induced a decrease in mitochondrial membrane potential in breast cancer cells, thereby inhibiting cell viability and increasing lactate dehydrogenase (LDH) release. Arnicolide D activated the classical apoptosis pathway to induce cell apoptosis; it significantly promoted PARP-1 expression, enhanced the nuclear translocation of apoptosis-inducing factor (AIF), and reduced the expression of AIF in mitochondria, indicating that it can induce the occurrence of parthanatos in a ROS dependent manner. In addition, arnicolide D down-regulated glutathione peroxidase 4 (GPX4) expression and increased the accumulation of Fe2+ and malondialdehyde (MDA), thereby activating ferroptosis. Apoptosis inhibitor, ferroptosis inhibitor, PARP inhibitor, PARP-1 siRNA, AIF siRNA and GPX4 overexpression vector significantly attenuated the inhibitory effect of arnicolide D on cell viability and reduced LDH release, which indicates that arnicolide D inhibits breast cancer cell growth by inducing apoptosis, parthanatos and ferroptosis. Arnicolide D also reduced breast cancer cell invasion and inhibited the expression of matrix metallopeptidase (MMP)-2 and MMP-9. Arnicolide D can activate a variety of cell death modes by inducing oxidative stress, thereby inhibiting the growth and invasion of breast cancer cells, indicating that arnicolide D has a good anti-tumor effect.

Curcumin and its Derivatives Targeting Multiple Signaling Pathways to Elicit Anticancer Activity: A Comprehensive Perspective.

The uncontrolled growth and spread of aberrant cells characterize the group of disorders known as cancer. According to GLOBOCAN 2022 analysis of cancer patients in either developed countries or developing countries the main concern cancers are breast cancer, lung cancer, and liver cancer which may rise eventually. Natural substances with dietary origins have gained interest for their low toxicity, anti-inflammatory, and antioxidant effects. The evaluation of dietary natural products as chemopreventive and therapeutic agents, the identification, characterization, and synthesis of their active components, as well as the enhancement of their delivery and bioavailability, have all received significant attention. Thus, the treatment strategy for concerning cancers must be significantly evaluated and may include the use of phytochemicals in daily lifestyle. In the present perspective, we discussed one of the potent phytochemicals, that has been used over the past few decades known as curcumin as a panacea drug of the "Cure-all" therapy concept. In our review firstly we included exhausted data from in-vivo and in-vitro studies on breast cancer, lung cancer, and liver cancer which act through various cancer-targeting pathways at the molecular level. Now, the second is the active constituent of turmeric known as curcumin and its derivatives are enlisted with their targeted protein in the molecular docking studies, which help the researchers design and synthesize new curcumin derivatives with respective implicated molecular and cellular activity. However, curcumin and its substituted derivatives still need to be investigated with unknown targeting mechanism studies in depth.

Role of Rhodomyrtus tomentosa (Aiton) Hassk. in regulating the expression of fibroblast growth factor family in the liver of rat in a breast cancer model

Context: Cellular abnormalities in the ducts and breast tissue cause breast cancer to invade nearby tissues like the liver. The fibroblast growth factor (FGF) signals are sent to its receptor and regulate various cellular processes to maintain liver homeostasis. However, this condition has few and inefficient treatments. Breast cancer is characterized by the development of cellular abnormalities within the ducts and breast tissue, leading to the invasion of adjacent tissues, such as the liver. Aims: To examine the impact of Rhodomyrtus tomentosa administration on the expression of the FGF family in cancer animal models, with a specific focus on the liver. Methods: Cancer model rats were administered at dosages of 100, 200, and 300 mg/kg BW for 30 days. Liver tissue and blood serum samples were extracted from the rat. Liver tissue was stained for immunohistochemistry using FGF1, FGF15, FGF19, and FGF21, and blood samples were collected for ELISA analysis. Results: The study found that DMBA in hepatocyte cells degrades parenchyma, making it hydrophilic and necrosating. Hepatocyte cell function improved with the greatest dose of R. tomentosa. The elevation was associated with an area around the portal vein where recently dividing hepatocytes form clusters. Conclusions: The promise of R. tomentosa as a candidate for the development of hepatoprotective medicines in cancer treatment arises from its ability to influence the expression of crucial liver health markers, including FGF1, FGF15, FGF19, and FGF21.

Novel Amide Functionalized Trifluoromethyl thieno[2,3-b]pyridine Derivatives: Anti-cancer Activity and Molecular Docking Studies

Abstract: Our primary research objective is to create and formulate small ring heterocycles with enhanced biological efficacy. Amide functionalized trifluoromethyl thieno[2,3-b]pyridine derivatives as a series were prepared starting from reaction between 1,3 di-ketone and thiocyanoacetamide and obtained pyridine 3. Compound 3 reacts with bromoethyl acetate and obtained compound 4, further compound 4 on reaction with diverse substituted aromatic and aliphatic amines to get amide derivatives 5a-d, 6a-d and 7a-h. All the final compounds evaluated for anti cancer activity against four human cancer cell lines such as ‘HeLa - Cervical cancer (CCL-2); COLO 205- Colon cancer (CCL- 222); HepG2 - Liver cancer (HB-8065); MCF7 - Breast cancer (HTB-22)’ and promising compounds 7d, 7e and 7f have been identified. For compounds 7d, 7e and 7f molecular docking interactions have been identified.

Clinical and molecular predictors of very late recurrence in oestrogen receptor-positive breast cancer patients.

Risk of recurrence from primary ER+ breast cancer continues for at least 20 years. We aimed to identify clinical and molecular features associated with risk of recurrence after 10 years. ER+ breast cancers from patients with and without recurrence were analysed with the BC360 NanoString Panel and an 87 gene targeted-exome panel. Frequency of clinical, pathologic and molecular characteristics was compared between cases (recurred between 10 and 20 years) and controls (no recurrence by 20 years) in the Very Late Recurrence (VLR) cohort. Analogous data from METABRIC were examined to confirm or refute findings. VLR cases had larger tumours and higher node positivity. Both VLR and METABRIC cases had higher clinical treatment score at 5 years (CTS5). There was a trend for fewer GATA3 mutations in cases in both VLR and METABRIC but no statistically significant differences in mutation frequency. Cell cycle and proliferation genes were strongly expressed in VLR cases. Immune-related genes and cell cycle inhibitors were highly expressed in controls. Neither of these changes were significant after correction for multiple testing. Clinicopathologic features are prognostic beyond 10 years. Conversely, molecular features, such as copy number alterations, TP53 mutations and intrinsic subtype which have early prognostic significance, have little prognostic value after 10 years.

Mean Apparent Propagator MRI: Quantitative Assessment of Tumor-Stroma Ratio in Invasive Ductal Breast Carcinoma.

Purpose To determine whether metrics from mean apparent propagator (MAP) MRI perform better than apparent diffusion coefficient (ADC) value in assessing the tumor-stroma ratio (TSR) status in breast carcinoma. Materials and Methods From August 2021 to October 2022, 271 participants were prospectively enrolled (ClinicalTrials.gov identifier: NCT05159323) and underwent breast diffusion spectral imaging and diffusion-weighted imaging. MAP MRI metrics and ADC were derived from the diffusion MRI data. All participants were divided into high-TSR (stromal component < 50%) and low-TSR (stromal component ≥ 50%) groups based on pathologic examination. Clinicopathologic characteristics were collected, and MRI findings were assessed. Logistic regression was used to determine the independent variables for distinguishing TSR status. The area under the receiver operating characteristic curve (AUC) and sensitivity, specificity, and accuracy were compared between the MAP MRI metrics, either alone or combined with clinicopathologic characteristics, and ADC, using the DeLong and McNemar test. Results A total of 181 female participants (mean age, 49 years ± 10 [SD]) were included. All diffusion MRI metrics differed between the high-TSR and low-TSR groups (P < .001 to P = .01). Radial non-Gaussianity from MAP MRI and lymphovascular invasion were significant independent variables for discriminating the two groups, with a higher AUC (0.81 [95% CI: 0.74, 0.87] vs 0.61 [95% CI: 0.53, 0.68], P < .001) and accuracy (138 of 181 [76%] vs 106 of 181 [59%], P < .001) than that of the ADC. Conclusion MAP MRI may serve as a better approach than conventional diffusion-weighted imaging in evaluating the TSR of breast carcinoma. Keywords: MR Diffusion-weighted Imaging, MR Imaging, Breast, Oncology ClinicalTrials.gov Identifier: NCT05159323 Supplemental material is available for this article. © RSNA, 2024.

Effects of Vitamins E and D on Mechanical Properties of Breast Cancerous Cells

Background: Several investigations have demonstrated that vitamins can treat or prevent cancer by altering actin filaments and inhibiting cell migration and proliferation. Vitamins D and E are fat-soluble. This research aims to determine the short-term impact of vitamin D and E on the mechanical properties of breast cancer cells before comparing them with normal breast cells. Methods: Atomic force microscopy (AFM) was used to examine the deformation of MCF-10 normal breast cells, MCF-7 breast cancer cells, and MCF-7 breast cancer cells treated with 0.03 μM vitamin D and 16 μM vitamin E solutions. Young's modulus was calculated employing the Hertz model to determine cell stiffness. Results: The Young's modulus of vitamin D-treated cancer cells (585.8 Pa) was substantially similar to that of normal cells (455.6 Pa). Nevertheless, vitamin E treatment did not affect Young's modulus of cancer cells, which remained remarkably similar to that of untreated cancer cells (216.6 and 203.4 Pa, respectively). Conclusion: Unlike vitamin E, vitamin D enhances the stiffness of tumor cells and makes their mechanical properties similar to normal cells by interfering with actin filaments and cell skeletons, which may inhibit tumor cell migration. Based on these findings, vitamin D appears to be an effective drug for cancer treatment.

Intermittent fasting boosts antitumor immunity by restricting CD11b+Ly6ClowLy6Glow cell viability through glucose metabolism in murine breast tumor model

Intermittent fasting can benefit breast cancer patients undergoing chemotherapy or immunotherapy. However, it is still uncertain how to select immunotherapy drugs to combine with intermittent fasting. Herein we observed that two cycles of fasting treatment significantly inhibited breast tumor growth and lung tissue metastasis, as well as prolonged overall survival in mice bearing 4T1 and 4T07 breast cancer. During this process, both the immunosuppressive monocytic- (M-) and granulocytic- (G-) myeloid-derived suppressor cell (MDSC) decreased, accompanied by an increase in interleukin (IL) 7R+ and granzyme B+ T cells in the tumor microenvironment. Interestingly, we observed that Ly6Glow G-MDSC sharply decreased after fasting treatment, and the cell surface markers and protein mass spectrometry data showed potential therapeutic targets. Mechanistic investigation revealed that glucose metabolism restriction suppressed the splenic granulocyte-monocyte progenitor and the generation of colony-stimulating factors and IL-6, which both contributed to the accumulation of G-MDSC. On the other hand, glucose metabolism restriction can directly induce the apoptosis of Ly6Glow G-MDSC, but not Ly6Ghigh subsets. In summary, these results suggest that glucose metabolism restriction induced by fasting treatment attenuates the immune-suppressive milieu and enhances the activation of CD3+ T cells, providing potential solutions for enhancing immune-based cancer interventions.

A Number of the N-terminal RASSF Family: RASSF7

The Ras association domain family 7 (RASSF7, also named HRC1), a potential tumor-related gene, located on human chromosome 11p15, has been identified as an important member of the N-terminal RASSF family. Whereas, the molecular biological mechanisms of RASSF7 in tumorigenesis remain to be further established. We perform a systematic review of the literature and assessment from PUBMED and MEDLINE databases in this article. RASSF7 plays a significant role in mitosis, microtubule growth, apoptosis, proliferation and differentiation. Many research literature shows that the RASSF7 could promote the occurrence and advance of human tumors by regulating Aurora B, MKK4, MKK7, JNK, YAP, MEK, and ERK, whereas, it might inhibit c-Myc and thus lead to the suppression of tumorigenesis. The pregulation of RASSF7 often occurs in various malignancies such as lung cancer, neuroblastoma, thyroid neoplasm, hepatocellular cancer, breast cancer and gastric cancer. The expression stage of RASSF7 is positively correlated with the tumor TNM stage. In this review, we primarily elaborate on the acknowledged structure and progress in the various biomechanisms and research advances of RASSF7, especially the potential relevant signaling pathways. We hope that RASSF7 , a prospective therapeutic target for human malignancies, could play an available role in future anti-cancer treatment.