Genomics England’s Post

Our team of researchers has conducted the first comprehensive review of the DNA landscape of male breast cancer. Through the whole genome sequencing analysis of tumor samples from ten patients, researchers at Weill Cornell Medicine identified gene mutations and molecular profiles that could be targets for diagnosis and treatment. Though breast cancer in men accounts for less than 1 percent of all breast cancer cases each year, the incidence in men has increased at a much faster rate than in women over the last 40 years. Also, most men are unaware of their risk, so they tend to be diagnosed at more advanced stages and have poorer treatment outcomes. Learn more: https://bit.ly/49FHUeu

Genome Doubling in Cancer Cells Involves Cell Division Glitch P.S. If you like this post please 1) Like it (so I know it's useful) and 2) Repost and share it (so others can see it too)

Genome Doubling in Cancer Cells Involves Cell Division Glitch P.S. If you like this post please 1) Like it (so I know it's useful) and 2) Repost and share it (so others can see it too)

Unlocking Cancer's Genetic Code: MaCroDNA, a groundbreaking platform developed by Rice University researchers, redefines the landscape of single-cell sequencing data integration. By meticulously mapping DNA-RNA dynamics with unprecedented precision and speed, this innovative tool sets a new benchmark in cancer research. Dive deeper into the complexities of cellular evolution and early disease detection with MaCroDNA 🔬 Check out their research findings through the following link: https://lnkd.in/dTWATN5T.

Just discovered a fascinating study highlighting AI's role in cancer research. ARTEMIS, a groundbreaking approach, identifies tumor-specific genetic changes, offering new paths for early cancer detection. A remarkable example of AI's impact in advancing cancer diagnostics!#AI #CancerResearch #Innovation https://lnkd.in/eMmRmzvS.

In addition to the paper mentioned in the previous post, Daniel Castillo-Secilla, Ph. D., Luis Javier Herrera, Jesús González Peñalver, and I have published a second paper at the same conference (IWANN 2023). This paper is aimed at identifying a set of genes able to distinguish between the following types of lung cancer: Adenocarcinoma (ACC), Squamous Cell Carcinoma (SCC), and healthy lung. The Differentially Expressed Genes (DEGs) analysis was carried out through RNA-seq data coming from The Cancer Genome Atlas (TCGA). An optimized evolutionary procedure has been developed with the purpose of finding the optimal combinations among the hundreds of candidate DEGs. Our custom method can maximize multiclass lung cancer recognition while minimizing the number of selected DEGs. The results show an outstanding classification rate with a significantly reduced number of DEGs biologically related to lung cancer. https://lnkd.in/dnsFxuV7

🔬 Exciting Breakthrough in Cancer Detection! 🔬 Researchers at Johns Hopkins Kimmel Cancer Center have developed ARTEMIS, a powerful machine learning strategy that detects early-stage lung and liver cancers by analyzing repetitive genetic sequences in the genome. This noninvasive method has the potential to revolutionize cancer detection and monitoring of treatment response. Read more about this groundbreaking discovery in this new article! #CancerDetection #MachineLearning #PrecisionMedicine #ARTEMIS #MedicalResearch

Could anti-estrogenic therapy be a potential treatment for all cancer types? 💡 Anti-estrogenic therapies have been successful in targeting ERα-positive breast cancer—a type of breast cancer triggered by estrogen, a naturally occurring female sex hormone. The cancer cells carry estrogen receptor alpha (ERα), allowing them to bind to estrogen which then causes tumor growth. However, in a recent study, a team of scientists from the Institute for Genetic Medicine (IGM) at Hokkaido University discovered that even cancers which did not express estrogen receptors also responded to the hormone. 🔬 Analyzing patient data from The Cancer Genome Atlas (TCGA) and conducting additional experiments using cell culture and mouse models, here's what the researchers found: 🔍 Estrogen accelerated the progression of ERα-negative cancers by influencing immune cells and creating an immunosuppressive environment to shield the tumors. “We have demonstrated that anti-estrogenic therapies can potentially maximize therapeutic efficacy of cancer immunotherapy regardless of tumor cells’ ERα expression. However, this is only the first step; future clinical research is required to develop cancer therapies that utilize this approach,” said Professor Seino Ken-ichiro, the corresponding author of the paper. Learn more via the link in our comments section. ⬇️ --- #AsianScientist #scicomm #research #cancer #cancertherapy

* CRISPR Deciphers lncRNA Role in Breast Cancer * A recent study provides significant insights into how certain long noncoding RNAs (lncRNAs) influence breast cancer risk by affecting cell proliferation. Utilizing CRISPR-Cas13d technology, researchers have identified and characterised the impact of the lncRNA KILR, which plays a role in controlling DNA replication and repair processes. The investigation began with a CRISPR-Cas13d-based screening of 844 breast cancer-associated lncRNAs to identify those impacting cell proliferation in breast cells. KILR was singled out due to its role in modulating cell proliferation, and the researchers conducted KILR pull-down assays followed by mass spectrometry to discern binding proteins. Further knockdown and overexpression studies were performed to unveil the mechanisms through which KILR regulates cell proliferation. Read on at https://lnkd.in/dtJfyGT9 #crispr #geneediting #genomeediting #crisprmedicine #crisprmedicinenews #breastcancer #cancer #lncrna #cas13 The University of Queensland