Broad Institute of MIT and Harvard’s Post

🔬 Delving into the intricate world of cancer transcriptomics: In my recent work, I unveiled fascinating insights into the molecular landscape of breast cancer metastasis. In my previous post, I generated a comprehensive heat map elucidating the differential expression of genes between primary and metastatic sites (lung) of breast cancer. To delve deeper into these findings, I conducted thorough Gene Ontology (#GO) and Kyoto Encyclopedia of Genes and Genomes (#KEGG) analyses. 🧬 The KEGG analysis showed an upregulation of CLOCK in the circadian rhythm pathway, which corroborated the results of the initial differential gene expression analysis: the significant upregulation of CLOCK in primary sites compared to metastatic sites. 🌟 But what's the significance of this finding? CLOCK is part of the circadian rhythm in mammals. Research shows that the likelihood of cancer increases when the circadian rhythm is disrupted. It is said to control the angiogenic factors and vascular endothelial growth factors in cancer cells. Tumour development and metastasis are promoted when there are increased expression levels of angiogenesis-promoting factors in the tumour microenvironment (TME) (Huang et al., 2023). In addition, Matsunaga et al. (2018) found that CLOCK genes upregulated the expression of downstream acetaldehyde dehydrogenase 3 (ALDH3A1). The enzyme is part of cancer stem cells (CSCs) and is correlated to the degree of tumour malignancy. While this pilot study provided a glimpse into the intricate world of cancer biology and genomics, it was also a great learning experience. From navigating bioinformatics analyses to unravelling the complexities of cancer biology, each step has been a lesson in growth and discovery. As I continue this journey, I'm fuelled by curiosity and driven by the prospect of uncovering further insights that may ultimately shape the future of cancer research and treatment. There's still much ground to cover, and I'm eager to see where this path leads next! 🧪 #KEGGanalysis #GOanalysis #cancergenomics #cancertranscriptomics #transcriptomics #bioinformatics #pathwayanalysis #genomics #research #breastcancer #rstudio #rprogramming #circadianrhythm

Current research shows that we can employ machine learning to analyse 3D topology of our genomes to predict different types of cancer. This promissing methodology can be potentially implemented in prsonalisation of cancer treamtent in the future. #Science #Biology #Cell #3D #Genome #Topology #CTCF #Cancerresearch #Cancerdiagnostic #AI #ML

Copy number alterations (CNAs) are critical genetic changes in cancer that affect the number of copies of genes or genomic regions in cancer cells. CNAqc is a bioinformatics R tool designed to accurately detect clonal and subclonal CNAs from bulk DNA sequencing data, addressing challenges such as unknown sample purity, tumor ploidy, and intra-tumor heterogeneity. Utilizing an evolution-inspired method and integrating somatic mutations, allele-specific CNAs, and tumor purity estimates, CNAqc significantly improves the accuracy of CNA detection. #CNA #bioinformatics #tools #R #cancer #oncology #cancerresearch #oncologyresearch https://lnkd.in/gkkJa9su

Lab automation can enhance cancer genomics sequencing by: ✅ Improving data quality and accessibility Tools like LINQ can collect and contextualise extensive data, facilitating reproducible experiments. ✅ Removing bottlenecks Automating labour-intensive steps like sample preparation reduces human error and frees up researchers for more valuable tasks. ✅ Facilitating scale Automation allows for large-scale experiments, increasing efficiency and throughput and reducing costs. Check out our article below to learn more about the impact of lab automation in cancer genomics ⬇️ #Cancer #Genomics #LabAutomation

“Cancer is a disease of disordered genomes.” This comprehensive genome sequencing of 13,880 tumors is the largest of its kind. Read up on how Genomics England, w/ the NHS analyzed WGS data from tumors spanning 33 cancer types, and it's exciting, actionable results. Read about it via The Scientist: https://lnkd.in/g2ZZDZM6 The original study can be read here: https://lnkd.in/gnKW7VBU 🧬 🧬 #genomics #cancergenomics #genomicsuk

Lab automation can enhance cancer genomics sequencing by: ✅ Improving data quality and accessibility Tools like LINQ can collect and contextualise extensive data, facilitating reproducible experiments. ✅ Removing bottlenecks Automating labour-intensive steps like sample preparation reduces human error and frees up researchers for more valuable tasks. ✅ Facilitating scale Automation allows for large-scale experiments, increasing efficiency and throughput and reducing costs. Check out Automata's article below to learn more about the impact of lab automation in cancer genomics ⬇️ #Cancer #Genomics #LabAutomation

Incredible Nature article discussing the significance of speed in genome diagnostics. It emphasizes the crucial role of mass-scale genome sequencing and the bottleneck in genome analysis and interpretation, highlighting their paramount importance for the implementation of clinical genomics. Horizon is built to breakthrough this bottleneck! Read more: https://lnkd.in/gwkrZMeU #genomics #rarediseases #cancer #precisionmedicine #genomesequencing

In a recent GEN interview, Dr. Christina Curtis, co-chair of AACR and a professor at Stanford University, highlights how the significant progress made in spatial profiling technology will be a major theme at this year's #AACR24 meeting. "Another theme is the huge advance in spatial profiling which allows us to look at human tissue at unprecedented resolution across different scales—from the subcellular, to cellular, and up to intercellular," says Dr. Curtis. If you're attending #AACR24, attend Dr. Arutha Kulasinghe's spatial profiling presentation on "Ultra high-plex profiling of the tumor microenvironment." He will discuss the development of ultrahigh-plex antibody panels to comprehensively characterize the tumor microenvironment on Saturday, April 6, from 12:36 PM to 12:54 PM PT in Session MW14—Choosing and Using Antibodies for Spatial Informed Protein Expression. Genetic Engineering & Biotechnology News American Association for Cancer Research #SpatialBiology #SpatialProfiling

Hematopoiesis—the production of blood cells that occurs throughout a person’s lifetime—is regulated by proteins called transcription factors that regulate the expression of hematopoietic genes. Germ-line mutations in RUNX1, the gene coding for the transcription factor RUNX1, causes a familial platelet disorder predisposes people to develop blood cancer. So far, however, scientists haven’t identified the specific genes that RUNX1 controls. Kristy Stengel, Ph.D., has received a four-year, $2.6 million grant from the National Heart, Lung, and Blood Institute to identify which genes are regulated by RUNX1 and how RUNX1 controls them. Dr. Stengel’s lab recently developed a novel technology that uses a small molecule to rapidly remove RUNX1 proteins from cells within one-to-two hours of treatment; use of that technology suggests that RUNX1 collaborates with several other transcription factors and co-regulatory proteins to regulate hematopoietic gene networks. By incorporating the technology in a mouse model, Dr. Stengel hopes to determine how RUNX1 controls gene expression to promote normal blood development as well as the molecular mechanisms by which defective RUNX1 results in blood cancer. Dr. Stengel is an assistant professor of cell biology at Einstein and a member of the Stem Cell & Cancer Biology Research (SCCB) Program at the National Cancer Institute-designated Montefiore Einstein Comprehensive Cancer Center. #bloodcancer #hematopoiesis #cancer #NCI #cellbiology #biomedicalresearch #science

Using whole genome sequencing and AI techniques, researchers have identified two different subtypes of prostate cancer among patients. The team then integrated all the information to generate an evolutionary tree, portraying how the two subtypes developed. This ground-breaking study provides new insight into the disease and could lead to more personalized treatments for patients. #ProstateCancerResearch #GenomeSequencing #AI #Genomics