Biology subjects

Tatsuoka, C.

Publications and source records attributed to Tatsuoka, C..

6 recordsLinked to original sources

bioRxiv2026

Layer-Specific Source-Anchored Transfer Learning for Multi-Omics Survival Prediction in Younger Breast Cancer Patients

Background: Younger breast cancer patients (<50 years) often present with more aggressive disease and distinct molecular characteristics, yet predictive models for this group are underpowered due to small sample sizes. Most existing models are built on older populations and may not translate directly, particularly across multiple omics data types. To address this, we developed Layered Source-Anchored Transfer Elastic Net (LSAT-EN), which adaptively borrows from the older source cohort while allowing borrowing strength to vary across omics layers according to their similarity between source and target cohorts, while performing EN variable selection. Methods: Patients aged >=60, >=55, and >=50 years were used as the source to improve prediction in patients aged <50 years. LSAT-EN were evaluated in group-correlated simulations and in TCGA-BRCA integrating 6 omics layers. Binary survival at 2-4 years was assessed by AUC; censored survival by Harrell's C-index and 2-5-year inverse probability of censoring weighted (IPCW) AUC. Results: In simulation, LSAT-EN achieved the highest AUC under moderate source-target heterogeneity (sigma^2=0.25; 0.747- 0.802), outperforming GAS-EN (0.735-0.767), overall EN (0.683-0.710), individual EN (0.646-0.767), and glmtrans EN (0.640-0.733) across target training sample sizes (nT). Its advantage was greatest under higher source-target heterogeneity (sigma^2=4), particularly with small nT, where LSAT-EN achieved AUCs of 0.689- 0.789 compared with 0.590-0.771 across competing methods. In TCGA-BRCA data, LSAT-EN improved discrimination relative to overall and individual EN in all binary and Cox models across all time horizons and source age groups. The method also identified clinically/ biologically important mRNA and miRNA, as well as useful candidate miRNA-mRNA pairs, indicating powerful biomarker discovery capability. Conclusion: LSAT-EN is a powerful TL method for improving prediction for younger breast cancer patients; The framework may support prediction in other underrepresented populations with limited target-cohort data to advance cancer disparity ML research.

bioinformatics↗

bioRxiv2025

Cytosolic transport of citrate protects nutrient-austere pancreatic cancer from ferroptosis

Pancreatic cancer (PDAC) cells experience nutrient starvation in a poorly perfused tumor microenvironment. Metabolic dependencies that protect PDAC cells from detrimental oxidative stress in a nutrient-restricted niche represent as tumor-specific targets. While the role of mitochondria in supporting energy production and biosynthetic requirements of cells has been well investigated, their contribution to maintaining intracellular redox homeostasis when PDAC cells are exposed to nutrient deprivation is unknown. Our results demonstrate that cytosolic transport of citrate via SLC25A1 confers a survival advantage to PDAC cells by protecting them from ferroptosis, a well-established iron-dependent cell death mechanism, under nutrient-limited conditions. Employing selective SLC25A1 inhibitor or targeting mitochondrial OXPHOS dramatically reduced GPX4 expression and PDAC cell viability. Rescuing GPX4 expression with the products of both ACLY and ACO1-dependent pathways uncovered their critical role in conferring survival advantage under metabolic stress. Importantly, exogenous expression of GPX4 reversed redox imbalance and metabolic discordance resulting from the lack of SLC25A1 activity, indicating the requirement of citrate-induced GPX4 expression to support mitochondrial health and function. As observed with cultured cells under nutrient limitation, SLC25A1 function was revealed to be indispensable in pancreatic tumor microenvironment, and the reduced growth, due to the lack of SLC25A1 activity, was rescued with antioxidant NAC in preclinical models of PDAC. Lastly, SLC25A1 suppression was accompanied by elevated glutamine metabolism, and combination therapy with pharmacologic inhibitors of SLC25A1 and glutaminase inhibitor CB-839 dramatically suppressed tumor growth, highlighting this combinatorial approach as a potential therapeutic strategy in PDAC.

cancer biology↗

bioRxiv2024

Sliding window functional connectivity inference with nonstationary autocorrelations and cross-correlations

Functional connectivity (FC) is the degree of synchrony of time series between distinct, spatially separated brain regions. While traditional FC analysis assumes the temporal stationarity throughout a brain scan, there is growing recognition that connectivity can change over time and is not stationary, leading to the concept of dynamic FC (dFC). Resting-state functional magnetic resonance imaging (fMRI) can assess dFC using the sliding window method with the correlation analysis of fMRI signals. Accurate statistical inference of sliding window correlation must consider the autocorrelated nature of the time series. Currently, the dynamic consideration is mainly confined to the point estimation of sliding window correlations. Using in vivo resting-state fMRI data, we first demonstrate the non-stationarity in both the cross-correlation function (XCF) and the autocorrelation function (ACF). Then, we propose the variance estimation of the sliding window correlation considering the nonstationary of XCF and ACF. This approach provides a means to dynamically estimate confidence intervals in assessing dynamic connectivity. Using simulations, we compare the performance of the proposed method with other methods, showing the impact of dynamic ACF and XCF on connectivity inference. Accurate variance estimation can help in addressing the critical issue of false positivity and negativity. HighlightsO_LIWe study the impact of nonstationary covariance on inference in resting-state fMRI C_LIO_LIWe propose dual sliding window estimators for correlation and its variance C_LIO_LIDynamic Z scores and confidence intervals characterize fluctuations of connectivity C_LIO_LIA statistical manner to determine static vs. dynamic connectivity at the inter-regional level C_LIO_LIImproves statistical inference accuracy compared with stationary covariance model C_LI

neuroscience↗

bioRxiv2022

Fractions strategy differences in those born extremely preterm

IntroductionTo investigate the effects of different strategies and cognitive load we explored brain hemodynamic responses associated with the use of different strategies to solve subtraction of fractions. We focused on those born extremely preterm (EPT; <28 weeks gestation) as they are known to have cognitive challenges and struggle with mathematics. We also included a group of full-term (FT) peers for comparison. MethodsFunctional MRI was acquired while the participants mentally solved fraction equations using either a strategy based on improper or mixed fractions. Different fraction item types were given, which affected respective required cognitive loads per strategy. Diffusion and T1-weighted structural images were also acquired. ResultsThe EPT and FT groups differed in terms of task-related hemodynamic responses. Functional group differences were greatest when strategies were applied to item types that result in high cognitive load. Other findings showed reduced white and grey matter volume and reduced white matter connectivity in widespread areas in the EPT group compared to the FT group. ConclusionThe understanding of function and structure presented here may help inform pedagogical practices by allowing for tailoring of mathematical education through identifying suitable strategy adoption that depends on item type, to circumvent weaknesses in cognitive skills.

neuroscience↗

bioRxiv2022

Increased glucose availability sensitizes pancreatic cancer to chemotherapy

Pancreatic cancer (Pancreatic Ductal Adenocarcinoma; PDAC) is highly resistant to chemotherapy. Effective alternative therapies have yet to emerge, leaving chemotherapy as the best available systematic treatment. The discovery of safe and available adjuncts that improve chemotherapeutic efficacy would potentially improve survival outcomes. We show that a hyperglycemic state enhances the efficacy of conventional single- and multi-agent chemotherapies against PDAC. Molecular analyses of tumors exposed to relatively high glucose levels revealed that a key metabolic pathway, glutathione biosynthesis, is diminished and underlies chemo-sensitization by enhancing oxidative injury to cancer cells. Inhibition of this pathway under normal conditions phenocopied a hyperglycemic state by enhancing chemotherapeutic efficacy in mouse PDAC, while rescuing the pathway under high glucose abrogated the anti-tumor effects observed with chemotherapy.

cancer biology↗

bioRxiv2021

Fascicles split or merge every ~560 microns within the human cervical vagus nerve

1Vagus nerve stimulation (VNS) is FDA approved for stroke rehabilitation, epilepsy, and depression; however, the vagus functional anatomy underlying the implant is poorly understood. We used microCT to quantify fascicular structure and neuroanatomy within human cervical vagus nerves. Fascicles split or merged every ~560 m (17.8 {+/-} 6.1 events/cm). The high degree of fascicular splitting and merging in humans may explain the clinical heterogeneity in patient responses.

neuroscience↗