Biology subjects

Seoane, J. A.

Publications and source records attributed to Seoane, J. A..

4 recordsLinked to original sources

bioRxiv2025

Transcriptomic signature reveals sensitivity to tubulin inhibitors in colon cancer

Colon cancer is the second most common cause of cancer death worldwide. Despite advances in the development of new molecular strategies for stratifying patients with colon cancer, many of these patients do not respond adequately to the standard of care. While previous studies have focused on the development of prognostic gene expression signatures, the exploration of predictive signatures to inform treatment decisions remains incomplete. In this study, we leveraged public gene expression datasets to design and experimentally validate a 37-gene expression signature for prognosis in colon cancer patients. We obtained a C-index of 0.732 (0.610-0.853) in four independent studies. Specifically, we discovered that the signature is associated with the mitotic phase of the cell cycle. Furthermore, the signature identified a population of colon cancer patients sensitive to tubulin inhibitor drugs. In particular, we validated in vitro and in vivo the efficacy of paclitaxel, a commonly used tubulin inhibitor in breast cancer treatment, in patient-derived preclinical models. These results highlight the importance of incorporating gene expression signatures to identify new therapeutic options for colon cancer treatment. Furthermore, the identification of alternative treatment options with potentially improved efficacy holds promise for the development of new clinical trials, and reshapes the biomarker-based treatment strategy for second line and refractory colon cancer patients.

cancer biology↗

bioRxiv2021

The Mettl3 epitranscriptomic writer amplifies p53 stress responses

The p53 transcription factor, encoded by the most frequently mutated gene in human cancer, plays a critical role in tissue homeostasis in response to stress signals. The mechanisms through which p53 promotes downstream tumor suppressive gene expression programs remain, however, only superficially understood. Here, we used tandem affinity purification and mass spectrometry to reveal new components of the p53 response. This approach uncovered Mettl3, a component of the m6A RNA methyltransferase complex (MTC), as a p53-interacting protein. Analysis of Mettl3- deficient cells revealed that Mettl3 promotes p53 protein stabilization and target gene expression in response to DNA damage. Mettl3 acts in part by competing with the p53 negative regulator, Mdm2, for binding to the p53 transactivation domains to promote methyltransferase-independent stabilization of p53. In addition, Mettl3 relies on its catalytic activity to augment p53 responses, with p53 recruiting Mettl3 to p53 target genes to co-transcriptionally direct m6A modification of p53 pathway transcripts to enhance their expression. Mettl3 also promotes p53 activity downstream of oncogenic signals in vivo, in both allograft and autochthonous lung adenocarcinoma models, suggesting cooperative action of p53 and Mettl3 in tumor suppression. Accordingly, we found in diverse human cancers that mutations in MTC components perturb expression of p53 target genes and that MTC mutations are mutually exclusive with TP53 mutations, suggesting that the MTC enhances the p53 transcriptional program in human cancer. Together, these studies reveal a fundamental role for Mettl3 in amplifying p53 signaling through protein stabilization and epitranscriptome regulation.

cancer biology↗

bioRxiv2021

The Human Tumor Atlas Network (HTAN) Breast PreCancer Atlas: A multi-omic integrative analysis of ductal carcinoma in situ with clinical outcomes

Ductal carcinoma in situ (DCIS) is the most common precursor of invasive breast cancer (IBC), with variable propensity for progression. We have performed the first multiscale, integrated profiling of DCIS with clinical outcomes by analyzing 677 DCIS samples from 481 patients with 7.1 years median follow-up from the Translational Breast Cancer Research Consortium (TBCRC) 038 study and the Resource of Archival Breast Tissue (RAHBT) cohorts. We identified 812 genes associated with ipsilateral recurrence within 5 years from treatment and developed a classifier that was predictive of DCIS or IBC recurrence in both cohorts. Pathways associated with recurrence include proliferation, immune response, and metabolism. Distinct stromal expression patterns and immune cell compositions were identified. Our multiscale approach employed in situ methods to generate a spatially resolved atlas of breast precancers, where complementary modalities can be directly compared and correlated with conventional pathology findings, disease states, and clinical outcome. HIGHLIGHTS Development of a new classifier for DCIS recurrence or progression Outcome associated pathways identified across multiple data types and compartments Four stroma-specific signatures identified CNAs characterize DCIS subgroups associated with high risk invasive cancers

cancer biology↗

bioRxiv2020

Convergent mutations in tissue-specific regulatory regions reveal novel cancer drivers

Although much effort has been devoted to identifying coding mutations across cancer types, regulatory mutations remain poorly characterized. Here, we describe a framework to identify non-coding drivers by aggregating mutations in cell-type specific regulatory regions for each gene. Application of this approach to 2,634 patients across 11 human cancer types identified 60 pan-cancer, 22 pan-breast and 192 cancer specific candidate driver genes that were enriched for expression changes. Analysis of high-throughput CRISPR knockout screens revealed large, cancer specific growth effects for these genes, on par with coding mutations and exceeding that for promoter mutations. Amongst the five candidate drivers selected for further analysis, four (IPO9, MED8, PLEKHA6, and OXNAD1) were associated with survival across multiple cancer types. These studies demonstrate the power of our cell-type aware, convergent regulatory framework to define novel tissue specific cancer driver genes, considerably expanding evidence of functional non-coding mutations in cancer.

cancer biology↗