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    BioLake: an RNA expression analysis framework for prostate cancer biomarker powered by data lakehouse
    (2025) Li, Qiaowang; Gamallat, Yaser; Rokne, Jon George; Bismar, Tarek; Alhajj, Reda
    Biomedical researchers must often deal with large amounts of raw data, and analysis of this data might provide significant insights. However, if the raw data size is large, it might be difficult to uncover these insights. In this paper, a data framework named BioLake is presented that provides minimalist interactive methods to help researchers conduct bioinformatics data analysis. Unlike some existing analytical tools on the market, BioLake supports a wide range of web-based bioinformatics data analysis for public datasets, while allowing researchers to analyze their private datasets instantly. The tool also significantly enhances result interpretability by providing the source code and detailed instructions. In terms of data storage design, BioLake adopts the data lakehouse architecture to provide storage scalability and analysis flexibility. To further enhance the analysis efficiency, BioLake supports online analysis for custom data, allowing researchers to upload their own data via a designed procedure without waiting for server-side approval. BioLake allows a one-time upload of custom data of up to 500 MB to ensure that researchers avoid issues with data being too large for upload. In terms of the built-in dataset, BioLake applies reactive continuous data integration, helping the analysis pipeline to get rid of most preprocessing steps. The only pre-built-in dataset of BioLake in the first public version is TCGA-PRAD mRNA expression data for prostate cancer research, which is the primary focus of the development team of BioLake. In summary, BioLake offers a lightweight online tool to facilitate bioinformatic mRNA data analysis with the support of custom online data processing.
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    Exploring the prognostic significance of set-domain containing 2 (setd2) expression in advanced and castrate-resistant prostate cancer
    (2024) Gamallat, Yaser; Felipe Lima, Joema; Seyedi, Sima; Li, Qiaowang; Rokne, Jon George; Alhajj, Reda; Ghosh, Sunita; Bismar, Tarek A.
    SET-domain containing 2 (SETD2) is a histone methyltransferase and an epigenetic modifier with oncogenic functionality. In the current study, we investigated the potential prognostic role of SETD2 in prostate cancer. A cohort of 202 patients’ samples was assembled on tissue microarrays (TMAs) containing incidental, advanced, and castrate-resistant CRPCa cases. Our data showed significant elevated SETD2 expression in advanced and castrate-resistant disease (CRPCa) compared to incidental cases (2.53 ± 0.58 and 2.21 ± 0.63 vs. 1.9 ± 0.68; p < 0.001, respectively). Interestingly, the mean intensity of SETD2 expression in deceased vs. alive patients was also significantly different (2.31 ± 0.66 vs. 2 ± 0.68; p = 0.003, respectively). Overall, high SETD2 expression was found to be considered high risk and was significantly associated with poor prognosis and worse overall survival (OS) (HR 1.80; 95% CI: 1.28–2.53, p = 0.001) and lower cause specific survival (CSS) (HR 3.14; 95% CI: 1.94–5.08, p < 0.0001). Moreover, combining high-intensity SETD2 with PTEN loss resulted in lower OS (HR 2.12; 95% CI: 1.22–3.69, p = 0.008) and unfavorable CSS (HR 3.74; 95% CI: 1.67–8.34, p = 0.001). Additionally, high SETD2 intensity with ERG positive expression showed worse prognosis for both OS (HR 1.99, 95% CI 0.87–4.59; p = 0.015) and CSS (HR 2.14, 95% CI 0.98–4.68, p = 0.058). We also investigated the protein expression database TCPA, and our results showed that high SETD2 expression is associated with a poor prognosis. Finally, we performed TCGA PRAD gene set enrichment analysis (GSEA) data for SETD2 overexpression, and our data revealed a potential association with pathways involved in tumor progression such as the AMPK signaling pathway, the cAMP signaling pathway, and the PI3K-Akt signaling pathway, which are potentially associated with tumor progression, chemoresistance, and a poor prognosis.
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    Serrate RNA effector molecule (SRRT) is associated with prostate cancer progression and is a predictor of poor prognosis in lethal prostate cancer
    (MDPI, 2023) Gamallat, Yaser; Choudhry, Muhammad; Li, Qiaowang; Rokne, Jon George; Alhajj, Reda; Abdelsalam, Ramy; Ghosh, Sunita; Arbet, Jaron; Boutros, Paul C.; Bismar, Tarek A.
    Arsenite-resistance protein 2, also known as serrate RNA effector molecule (ARS2/SRRT), is known to be involved in cellular proliferation and tumorigenicity. However, its role in prostate cancer (PCa) has not yet been established. We investigated the potential role of SRRT in 496 prostate samples including benign, incidental, advanced, and castrate-resistant patients treated by androgen deprivation therapy (ADT). We also explored the association of SRRT with common genetic aberrations in lethal PCa using immunohistochemistry (IHC) and performed a detailed analysis of SRRT expression using The Cancer Genome Atlas (TCGA PRAD) by utilizing RNA-seq, clinical information (pathological T category and pathological Gleason score). Our findings indicated that high SRRT expression was significantly associated with poor overall survival (OS) and cause-specific survival (CSS). SRRT expression was also significantly associated with common genomic aberrations in lethal PCa such as PTEN loss, ERG gain, mutant TP53, or ATM. Furthermore, TCGA PRAD data revealed that high SRRT mRNA expression was significantly associated with higher Gleason scores, PSA levels, and T pathological categories. Gene set enrichment analysis (GSEA) of RNAseq data from the TCGA PRAD cohort indicated that SRRT may play a potential role in regulating the expression of genes involved in prostate cancer aggressiveness. Conclusion: The current data identify the SRRT's potential role as a prognostic for lethal PCa, and further research is required to investigate its potential as a therapeutic target.