Acquired drug resistance is an increasing challenge in treating cancer with chemotherapy. One mechanism
behind this resistance is the increased inflammation that supports the progression and development of
cancer that arises because of the drug’s presence. Integrative oncology is the field that focuses on including natural products alongside traditional therapy to create a treatment that focuses on holistic patient well-being.
In this study, the authors demonstrate that the use of an herbal formulation, consisting of turmeric and green tea, alongside a traditional chemotherapeutic drug, 5-fluorouracil (FU) significantly decreases the level of cytokines produced in breast cancer cells when compared to the levels produced when exposed solely to the chemo drug. The authors conclude that this combination of treatment, based on the principle of integrative oncology, shows potential for reducing the resistance against treatment conferred through increased inflammation. Consequently, this suggests a prospective way forward in improving the efficacy of cancer treatment.
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Using explainable artificial intelligence to identify patient-specific breast cancer subtypes
Breast cancer is the most common cancer in women, with approximately 300,000 diagnosed with breast cancer in 2023. It ranks second in cancer-related deaths for women, after lung cancer with nearly 50,000 deaths. Scientists have identified important genetic mutations in genes like BRCA1 and BRCA2 that lead to the development of breast cancer, but previous studies were limited as they focused on specific populations. To overcome limitations, diverse populations and powerful statistical methods like genome-wide association studies and whole-genome sequencing are needed. Explainable artificial intelligence (XAI) can be used in oncology and breast cancer research to overcome these limitations of specificity as it can analyze datasets of diagnosed patients by providing interpretable explanations for identified patterns and predictions. This project aims to achieve technological and medicinal goals by using advanced algorithms to identify breast cancer subtypes for faster diagnoses. Multiple methods were utilized to develop an efficient algorithm. We hypothesized that an XAI approach would be best as it can assign scores to genes, specifically with a 90% success rate. To test that, we ran multiple trials utilizing XAI methods through the identification of class-specific and patient-specific key genes. We found that the study demonstrated a pipeline that combines multiple XAI techniques to identify potential biomarker genes for breast cancer with a 95% success rate.
Read More...Cytotoxicity evaluation of Amaranthus extracts compared with AS20 on MCF-7 cancer cells
The authors test the antiproliferative and apoptosis-inducing properties of an extract created from a traditional Indian medicinal plant of the Amaranthus genus.
Read More...The anticancer and anti-inflammatory effects of polyherbal drug AS20 on HeLa cells resistant to 5-Fluorouracil
The authors looked at 5-FU resistant HeLa cells and the ability of an herbal extract to show anti-inflammatory properties.
Read More...DNA repair protein mutations alter blood cancer sensitivity to cisplatin or gemcitabine in vitro
The authors investigate whether human blood cancers carrying mutations in DNA repair genes possess increased sensitivity to common chemotherapy drugs cisplatin or gemcitabine.
Read More...Luteolin's positive inhibition of melanoma cell lines.
Luteolin (3′,4′,5,7-tetrahydroxyflavone) is a flavonoid that occurs in fruits, vegetables, and herbs. Research suggests that luteolin is effective against various forms of cancer by triggering apoptosis pathways. This experiment analyzes the effects of luteolin on the cell viability of malignant melanoma cells using an in vitro experiment to research alternative melanoma treatments and hopefully to help further cancer research as a whole.
Read More...Upregulation of the Ribosomal Pathway as a Potential Blood-Based Genetic Biomarker for Comorbid Major Depressive Disorder (MDD) and PTSD
Major Depressive Disorder (MDD), and Post-Traumatic Stress Disorder (PTSD) are two of the fastest growing comorbid diseases in the world. Using publicly available datasets from the National Institute for Biotechnology Information (NCBI), Ravi and Lee conducted a differential gene expression analysis using 184 blood samples from either control individuals or individuals with comorbid MDD and PTSD. As a result, the authors identified 253 highly differentially-expressed genes, with enrichment for proteins in the gene ontology group 'Ribosomal Pathway'. These genes may be used as blood-based biomarkers for susceptibility to MDD or PTSD, and to tailor treatments within a personalized medicine regime.
Read More...TNF signaling pathway upregulation as a potential pharmaceutical target for cocaine-addicted individuals
In this article, the authors investigate the RNA expression differences between groups of chronic cocaine abusers and drug-free subjects.
Read More...Distribution of prophages in the Streptococcus bacteria genus and their role in increasing host pathogenicity
The authors investigated prophages present in Streptococcus bacteria that may increase their survival in different environments.
Read More...Mendelian randomization reveals shared genetic landscape in autism spectrum disorder and Alzheimer's disease
Autism Spectrum Disorder (ASD) and Alzheimer's Disease (AD) are distinct conditions, but research suggests a link, as individuals with ASD are 2.5 times more likely to develop AD. A study employing genome-wide association studies and Mendelian randomization revealed shared genetic factors, particularly in synaptic regulation pathways, that may increase the risk of AD in those with ASD. These findings provide insights into the genetic underpinnings connecting the two disorders.
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