Jia‐Ren Lin

This study identifies genomic subtypes and immune features of mucosal melanoma, linking CD163+ macrophages to immune resistance and suggesting TIM-3 blockade as a therapeutic target.

The paper analyzes HER2+ breast cancer using multi-platform data to identify molecular predictors of response to neoadjuvant therapy and highlights intra-tumoral heterogeneity and immune exclusion mechanisms.

This study shows CD40 agonist therapy reduces tumor growth in antigen presentation-deficient tumors by reprogramming monocytes and requiring IFN-gamma and CD8+ T cells for efficacy.

This study identifies epigenetic dysregulation of metabolic programs in liposarcoma, linking IGF1 loss and PPARG2 deficiency to dedifferentiation and proposing IGF1R-targeted therapy.

The paper maps oxidative stress response in TNBC using single-cell and spatial data, identifying GCLC+ mesenchymal tumor cells linked to better patient outcomes.

The paper introduces statistical tools to analyze immune cluster patterns in prostate cancer and finds high-grade tumors show more immune infiltration and active immune features.

This study uses spatial profiling to show immune suppression and microenvironment changes in fallopian tube precursors of high-grade serous ovarian cancer.

This paper introduces CyLinter, a quality control tool that removes imaging artefacts from high-plex spatial profiling data, improving single-cell analysis of archival tumor specimens.

This paper introduces a MALDI MSI method to spatially profile metals in tissues, applying it to study embryogenesis, genetic disorders, and chemotherapy delivery.

The paper proposes deep learning methods to reconstruct 3D CyCIF images and select optimal ROIs from histology and MTI data for tumor representation.

The paper develops computational methods to reduce multiplex imaging panels while retaining maximum information in breast cancer tissue microarrays.

Galaxy-ME is a web-based software hub for analyzing and visualizing multiplex tissue imaging datasets, demonstrating its utility on normal and cancerous tissue data.

This study quantifies cell proliferation in tumors using multiplexed imaging and identifies spatial and temporal patterns of cell cycle regulation.

MCMICRO processes multiplexed tissue images into single-cell data, demonstrating its versatility across different tissues and imaging platforms.

The paper introduces effective stoichiometric space (ESS) to infer biochemical reaction network structure from single-cell multiplex data using toric systems theory, identifying differences in drug-treated cells.