Publications by authors named "S Taavitsainen"
Article Synopsis
- Prostate cancer treatment resistance is a major challenge, with genomic studies revealing how cancer cells evade therapies, yet the tumor microenvironment's (TME) role remains unclear.
- A study using advanced techniques on samples from 120 patients offers a detailed transcriptomic profile of the prostate TME throughout the treatment process.
- The research highlights a unique cell type called club-like cells that interact with the immune system, suggesting their involvement in inflammation and resistance to androgen deprivation therapy, indicating they could be potential targets for new treatments.
Article Synopsis
- - Current strategies to predict outcomes in metastatic castration-resistant prostate cancer (mCRPC) are lacking, but circulating tumor DNA fraction (ctDNA%) may hold promise for assessing patient risk.
- - An analysis of 738 plasma samples from mCRPC patients shows that ctDNA% correlates with disease severity and is a strong predictor of overall and progression-free survival, outperforming traditional clinical factors.
- - To address challenges with low ctDNA%, researchers developed a machine-learning tool that indicates when ctDNA% is sufficient for detailed genetic testing, enhancing patient risk assessment and biomarker testing.
Prostate cancer is one of the leading causes of death among men worldwide, and thus, research on the genetic factors enabling the formation of treatment-resistant cancer cells is crucial for improving patient outcomes. Here, we report a cell line-specific dependence on and related signaling pathways to counteract the effects of DNA-damaging chemotherapy in prostate cancer. Our results reveal that depletion results in significant downregulation of Fanconi anemia (FA) pathway members in prostate cancer cells, indicating that is an important regulator of the FA pathway.
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- - The study examines the genomic heterogeneity of prostate cancer and its impact on treatment resistance, suggesting that incorporating evolutionary principles into clinical trials could provide valuable insights for therapy strategies.
- - Researchers analyzed whole genome data and 3D anatomical structures from two patients with high-risk prostate cancer, using advanced tools to map tumor origins, genetic mutations, and metastasis patterns.
- - Results indicate that specific mutations and evolutionary patterns significantly influence cancer progression and metastasis, highlighting the potential for evolutionary analysis to inform therapy choices in prostate cancer patients.
Single-cell RNA sequencing studies have suggested that total mRNA content correlates with tumor phenotypes. Technical and analytical challenges, however, have so far impeded at-scale pan-cancer examination of total mRNA content. Here we present a method to quantify tumor-specific total mRNA expression (TmS) from bulk sequencing data, taking into account tumor transcript proportion, purity and ploidy, which are estimated through transcriptomic/genomic deconvolution.
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