Biology subjects

Stawiski, K.

Publications and source records attributed to Stawiski, K..

3 recordsLinked to original sources

bioRxiv2025

Tumor-myeloid crosstalk drives therapy resistance in localized bladder cancer

Neoadjuvant cisplatin-based chemotherapy results in pathologic complete response for only a minority of patients with muscle-invasive bladder cancer (MIBC), and mechanisms of resistance and the effects of chemotherapy on the MIBC microenvironment remain incompletely understood. Here, we defined the single-cell and spatial transcriptomes of cancer and immune cells from MIBC patients with resistance to cisplatin-based chemotherapy. Tumors with persistent MIBC after chemotherapy harbored cancer cells expressing epithelial-to-mesenchymal programs that were associated with worse overall survival in independent cisplatin-treated bladder cancer cohorts. These cisplatin-resistant tumor cells were infiltrated by macrophages that upregulated tumor permissive programs defined by increased PARP14 expression in spatially resolved multicellular niches. Macrophage reprogramming through PARP14 inhibition sensitized tumors to cisplatin via downregulation of tumor cell pathways implicated in resistance. Our results demonstrate that cancer cells and macrophages cooperate to promote cisplatin resistance and identify macrophage-directed PARP14 inhibition as a novel therapeutic strategy to sensitize MIBC to cisplatin.

cancer biology↗

bioRxiv2025

Tumor B cell infiltration in platinum-treated advanced urothelial carcinoma

Platinum-based chemotherapy combined with immunotherapy provides durable disease control in advanced urothelial cancer. However, cisplatin and carboplatin differently impact the tumor immune microenvironment, affecting chemo-immunotherapy response. Here, we evaluate immune cell populations and ecosystems associated with overall survival in patients treated with platinum-based chemotherapy. Our transcriptomic analysis of pretreatment tumor samples from three cohorts (189 patients) of advanced urothelial cancer showed that lymphoid cell infiltration was significantly associated with prolonged overall survival. In cisplatin-treated patients, high memory B cell infiltration provided a significant overall survival improvement, but no such association was found in carboplatin-treated patients. Additionally, gene expression signatures implicated in B cell memory lineage and associated cytokines were associated with better overall survival in independent cancer patient cohorts. Our findings highlight memory B cell infiltration as a potential prognostic biomarker in urothelial cancer and emphasize the role of the tumor immune microenvironment in chemotherapy response.

cancer biology↗

bioRxiv2022

OmicSelector: automatic feature selection and deep learning modeling for omic experiments.

A crucial phase of modern biomarker discovery studies is selecting the most promising features from high-throughput screening assays. Here, we present the OmicSelector - Docker-based web application and R package that facilitates the analysis of such experiments. OmicSelector provides a consistent and overfitting-resilient pipeline that integrates 94 feature selection approaches based on 25 distinct variable selection methods. It identifies and then ranks the best feature sets using 11 modeling techniques with hyperparameter optimization in hold-out or cross-validation. OmicSelector provides classification performance metrics for proposed feature sets, allowing researchers to choose the overfitting-resistant biomarker set with the highest diagnostic potential. Finally, it performs GPU-accelerated development, validation, and implementation of deep learning feedforward neural networks (up to 3 hidden layers, with or without autoencoders) on selected signatures. The application performs an extensive grid search of hyperparameters, including balancing and preprocessing of next-generation sequencing (e.g. RNA-seq, miRNA-seq) oraz qPCR data. The pipeline is applicable for determining candidate circulating or tissue miRNAs, gene expression data and methylomic, metabolomic or proteomic analyses. As a case study, we use OmicSelector to develop a diagnostic test for pancreatic and biliary tract cancer based on serum small RNA next-generation sequencing (miRNA-seq) data. The tool is open-source and available at https://biostat.umed.pl/OmicSelector/

bioinformatics↗