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A checkpoint blockade-based therapy is transforming cancer care by encouraging effective immune surveillance and effector cell responses against various types of cancers. Several questions concerning the correct combination of drugs, opioid modality, and effective dose recommendations related to the use of ICB-based therapy for HER2+ patients are unanswered. When treated with anti-HER2; trastuzumab and anti-PD-1/PD-L1 agents, we use a mathematical modeling-based approach to determine the proliferation of HER2+ breast cancer cell colonies. We show that BMS-202 can cause tumor formation suppression not only by mediating immune response but also by interfering with the HER2+ BC growth signaling pathways. However, further studies are required to back up this argument and figure out the possibility of crosstalk between PD-1/PD-L1 inhibitors and HER2 growth signaling pathways in breast cancer.
Source link: https://doi.org/10.20944/preprints202205.0120.v1
Triple-negative breast cancer is the most common BC with the highest incidence of tumor-infiltrating lymphocytes. Hence, Til therapy is seen as a promising way to combat TNBC. TILs with regulatory T cells depletion can enhance TIL therapy's antitumor activity. Pentoxifylline is a xanthine derivative that can modulate the nuclear factor kappa B signaling and possibly influence the Treg percentage in TILs. We wanted to investigate the ex vivo effect of PTXF on the proportion of Treg cells in the TILs that were derived from a mouse model of TNBC. According to our results, ex vivo treatment of TILs with pentoxifylline could reduce the percentage of Tregs in the conventional IL-2-mediated TIL expansion and change the cytokine balance of TILs in favour of anti-tumor immune responses.
Source link: https://doi.org/10.18502/ijaai.v21i2.9224
Breast cancer is the most common cancer in women. One in eight women in Western women has breast cancer. Breast cancer in Iran is lower than in Western countries, but the incidence of breast cancer in it is 5-10 years earlier than in Western countries. Breast cancer is the second leading cause of cancer death among women after lung cancer. This research was conducted in order to investigate the effects of Wharton jelly stem cells secrecy on cancer cell expressions, including CXCR4 and VLA-4 genes. Conclusion: In MDA-MB-231 breast cancer cells, different amounts of Wharton Jelly Stem Cells reduced cancer cell growth and expression of CXCR4 and VLA-4 homing genes. In conclusion, Wharton Jelly Stem Cells can be used as an effective breast cancer treatment.
Source link: https://doi.org/10.18502/ijhoscr.v16i2.9204
Background: The main 3D modalities for X-ray breast imaging are cone-beam breast computed tomography and digital breast tomosynthesis, respectively. The purpose of this review was to objectively assess and meta-analyze the comparison of diagnostic accuracy of CBBCT and DBT to define breast cancers. The results: For the 17 included studies in the DBT arm, respectively, 86. 7%, 87. 0%, 2. 71, 0. 20, and 0. 831 are the pooled sensitivity specificity, LR+, and AUC, respectively, with 87. 7%, 87. 0%, 91. 0%, 1. 4, 0. 21, 0. 31, and 0. 925 are the pooled sensitivity specificity, LR+, 0. 9 84, 82 83. Conclusions: Our report shows that DBT has improved diagnostic results than CBBCT on all estimated diagnostic variables, as shown by the statistical improvement in the AUC of DBT over CBBCT. The CBBCT could be a useful tool for breast cancer diagnosis, and therefore we recommend further prospective studies on CBBCT application.
Source link: https://doi.org/10.3390/s22093594
1 exhibits moderately binding affinity to KRAS G-quadruplex DNA by groove mode, according to spectroscopic and molecular docking experiments. In summary, the ready arene Ru complexes can be used as a promising target for stimulating breast cancer cell proliferation through binding and stabilizing KRAS G-quadruplex conformation on oncogene promoters.
Source link: https://doi.org/10.3390/molecules27103046
SERMs developed picomolar to low nanomolar potencies against ER and were then investigated as antiproliferative agents against BC cell lines as stimulators of p53 expression, as well as BC cell cycle arrest agents. After which 3DPQ-12, 3DPQ-3, 3DPQ-4, 3DPQ-2, and 3DPQ-1 are all prospective candidates for BC therapy, the most active leads were finally identified on administration to female Wistar rats with pre-induced BC, with pre-induced BC, 3DPQ-3, 3DPQ-4, 3DPQ-2, and 3DPQ-1, potential candidates for BC therapy have been placed.
Source link: https://doi.org/10.3390/molecules27092823
The current COVID-19 disease epidemic's breast cancer patients' care is difficult. Both hospitals and home may be affected by myelosuppression as a result of cancer therapy. The completion rate for 43 patients who received nab-paclitaxel therapy was 100%, without interruption or delay in nab-paclitaxel therapy. During COVID-19 pandemic, a wT12AC4 treatment regimen may be considered for breast cancer patients.
Source link: https://doi.org/10.1166/sam.2022.4219
Introduction and Background: Despite rapid advancements in the medical field, histological diagnosis is still used as the benchmark in cancer diagnosis. Manual procedures are biased, time-consuming, labor intensive, and error-prone, but the input image feature extraction that is used to determine the severity of cancer at several magnifications is harrowing, but manual tests are precise, time consuming, labor intensive, and error-prone. Whole photographs display information from current state-of-the-art deep learning technologies for breast histopathology image classification. The current model backbone is a combination of DenseNet201 and VGG16 architectures, which is intended to be an extension of DenseNet201 and VGG16 architecture. Results: A comprehensive analysis of the proposed model's accuracy, reliability, sensitivity, precision, specificity, and f1-score metrics revealed the usefulness of the backbone model and the DEEP_Pachi model for image classification. In all magnifications of BreakHis datasets and an accuracy of 1. 0 on the ICIAR 2018 Challenge dataset, the proposed method outperformed state-of-art classification generators, with a 1. 0 for the benign class and 0. 99 for the malignant class.
Source link: https://doi.org/10.3390/diagnostics12051152
We investigated whether long-term exposure to calcium channel blockers is related to an elevated risk of breast cancer. Based on reports from the Clalit electronic database, the largest Israeli Health Services company, we created a nested case-control study. All newly diagnosed breast cancer cases were chosen from a group of patients with hypertension. Using multivariate conditional logistic regression models, the odds ratios of BCa among CCBs users were estimated. In addition, there was no correlation between long-term exposure to CCBs and elevated BCa risk. BCa risk was not elevated in CDCBs' cumulative doses, but not associated with an elevated risk of BCa.
Source link: https://doi.org/10.3390/cancers14092344
Breast cancer is a common form of cancer found in women and is a common research topic in medical science. Cancer spreads to other organs in patients who are not diagnosed and not treated early, making treatment difficult. The ability of the pathological diagnosis is of utmost importance in breast cancer diagnosis, helping to shorten the decision-making process, minimize unnoticed cancer cells, and obtain a faster diagnosis. However, the similarity of images in histopathological breast cancer image analysis is a delicate and difficult process that necessitates great skill for field experts. In this research, a hybrid DCNN + ReliefF method for the classification of breast cancer histopathological images is developed, utilizing the activation capabilities of pre-trained deep convolution neural network networks models, as well as the dimension-reduction-based ReliefF feature selective algorithm. In addition, the models were compared to the k-nearest neighbor, naive Bayes, and support vector machine learning techniques.
Source link: https://doi.org/10.18280/ts.390214
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