Cancer Metastasis Research
Ayass BioScience, LLC utilizes biomarkers that predict disease outcome
Cancer metastasis is a complex process in which cancer cells spread from the primary tumor to other parts of the body through the bloodstream or lymphatic system and invade the secondary tissues or organs. Understanding the mechanisms of cancer metastasis is crucial for developing effective treatments and improving patient outcomes. Ayass BioScience, LLC metastasis research covers both chronological progression and the adaptations of specific environments to predict early metastatic colonization. Spatial profiling (spatial transcriptomics), is a cutting-edge technique that enables the mapping of gene expression patterns within intact tissue sections. Traditional transcriptomic analysis provides information on gene expression levels but lacks spatial context. Spatial profiling overcomes this limitation by preserving the spatial information of gene expression, allowing us to understand the organization and distribution of different cell types and gene expression patterns within a tissue sample. READ MORE ABOUT SPATIAL PROFILING
Here are some ways in which transcriptomic analysis contributes to our understanding of cancer metastasis:
Identification of metastasis-associated genes: Transcriptomic studies can identify genes that are upregulated or downregulated during metastasis. By comparing the expression profiles of primary tumors and metastatic lesions, we can identify genes that play a role in promoting or inhibiting metastasis. These genes can serve as potential biomarkers for metastasis or as therapeutic targets.
Molecular pathways involved in metastasis: Transcriptomic analysis helps uncover the molecular pathways and signaling networks that are dysregulated during metastasis. By identifying the specific genes and pathways involved, we can gain insights into the underlying mechanisms driving metastasis and potentially develop targeted therapies to disrupt these processes.
Subtyping of metastatic tumors: Different types of cancer exhibit distinct metastatic patterns and characteristics. Transcriptomic analysis can aid in identifying molecular subtypes of metastatic tumors, providing insights into their origin, behavior, and potential vulnerabilities. This information can guide treatment decisions and personalized therapies.
Predicting prognosis and treatment response: Transcriptomic profiling of primary tumors or metastatic lesions can provide prognostic information and predict treatment response. By examining the expression levels of specific genes or gene signatures, we can stratify patients into different risk groups and tailor treatment plans accordingly.
Uncovering novel therapeutic targets: Transcriptomic analysis can reveal previously unknown genes or pathways associated with metastasis. These discoveries can lead to the identification of novel therapeutic targets that can be exploited to develop new treatment strategies for metastatic cancer.
Transcriptomic analysis is often integrated with other omics technologies, such as genomics, proteomics, and epigenomics, to gain a comprehensive understanding of cancer metastasis. Integrative analyses of multiple data types can provide a more comprehensive view of the molecular alterations and regulatory networks underlying metastasis.