Abstract Single-cell technologies have enabled increasingly detailed reconstruction of developmental trajectories, yet a fundamental question remains unresolved: when does future cellular identity become predictable from a cell’s current molecular state? Existing approaches infer lineage relationships, transition probabilities or future transcriptional dynamics, but do not directly quantify the emergence of fate predictability during cellular state transitions. Here we present FateLimit, an information-theoretic framework for measuring the temporal dynamics of cell-fate predictability from single-cell omics data. FateLimit combines probabilistic fate assignment, fate entropy and mutual information to quantify how information about future cellular outcomes is encoded in present molecular states. We introduce two quantitative descriptors: the Fate Information Half-Life (FIHL), which measures the characteristic timescale of fate-information dynamics, and the Prediction Horizon (PH), defined as the earliest developmental stage at which observed fate predictability exceeds the 95th percentile of a permutation-derived null distribution. We applied FateLimit across developmental, lineage-tracing and reprogramming systems, including pancreatic endocrinogenesis, CellTag reprogramming, human hematopoiesis and zebrafish embryogenesis. Across all datasets, FateLimit identified significant fate information and reproducible prediction horizons that were robust to cell-state representation, lineage structure and biological context. Comparative analysis revealed that prediction horizons differ substantially among cellular lineages, indicating that distinct developmental programs acquire predictive information at different rates. FateLimit establishes a general framework for quantifying the predictability of future cellular identity from present molecular states. By transforming developmental trajectories into predictability landscapes, FateLimit enables systematic comparison of commitment dynamics across biological systems and establishes prediction horizons as a quantitative measure of cell-fate determination.

Cancer-associated fibroblasts are transcriptionally heterogeneous, yet how their reprogramming shapes gastric cancer progression remains unclear. Integrating single-cell and spatial transcriptomics, patient-derived fibroblast co-culture, and clinical cohorts, we identified a spatially organized continuum of extracellular matrix-producing fibroblasts. An inferred trajectory connected homeostatic ECMh through inflammatory-chemoattractive ECMi to tissue-remodeling ECMr, with increasing GLIS2 regulon activity and ECMr enrichment near the tumorstroma interface. ECMr co-culture induced a nonEMT epithelial program characterized by coordinated laminin332 subunit expression, hemidesmosome-associated genes, a matrix remodeling protease profile, and reduced proliferative activity. Longitudinal imaging showed progressive cancer-cell elongation and positional displacement over the fibroblast layer. ECMr-associated GLIS2 regulon activity in resected primary tumors was associated with shorter peritoneal metastasis-free survival across two gastric cancer cohorts, with a similar association in colorectal cancer. A peritoneal metastasis recapitulated the corresponding stromal and epithelial organization. Together, these findings define an ECMr centered stromal epithelial wound repair circuit linked to subsequent peritoneal dissemination.

Tumour infiltrating lymphocytes (TILs) are a key component of the tumour microenvironment. To establish a clinically relevant TILs cut-off for patients with oesophago-gastric (OG) cancer, it is essential to know whether TILs density varies by patient and/or disease characteristics. TILs were quantified as TILs/mm2 (TILs density) by a deep-learning algorithm applied to digitised Haematoxylin/Eosin (H E)-stained biopsies and resection specimens from 4628 patients from nine phase III trials. 4533 patients with TILs density and matched clinicopathological data were included in the final analyses. Associations between TILs density, disease stage, geographical region (UK versus Asia), sex, age, and treatment were analysed. Median TILs density was higher in pre-treatment biopsies from patients with early-stage versus late-stage disease (962 vs 479 TILs/mm2, p < 0.001). Within the same geographical region and disease stage, TILs density was similar across different chemotherapy regimens. In UK-led trials of early-stage disease, post-chemotherapy resections showed higher TILs density than chemotherapy-naïve resections (618 vs 571 TILs/mm2, p = 0.003). TILs density was higher in Asian tumours compared to UK tumours (1419 vs 571 TILs/mm2, p < 0.001). No significant associations were observed with age or sex. This is the largest study to date evaluating TILs density in OG cancer. TILs density varied with stage and geographical region but not by age or sex. These findings may explain enhanced response to immunotherapy observed in published studies of patients with early-stage disease and highlight the need to account for baseline TILs heterogeneity when interpreting TILs as a possible biomarker in future studies.

Abstract Introduction: Spatial omics experiments profile only a limited number of regions of interest (ROIs) per section, making ROI selection critical. However, manual selection from tumor annotations may miss critical subregion due to the complexity of tumor structures and the limited capability of human visual processing. We recently reported S2Omics, an AI framework that selects ROIs to maximize cell-type diversity and molecular information in an outcome-agnostic manner. Here, we extend this concept to develop an image-based ROI selection method that directly incorporates immune checkpoint inhibitor (ICI) treatment outcome in gastric cancer (GC), enabling outcome-aware spatial transcriptomic experiments. Methods: We assembled 157 H&E whole slide images (WSIs) from GC patients treated with ICIs at three centers in Korea and Japan (26 responders, 131 non-responders). WSIs were tiled into 256 µm × 256 µm patches. Tumor tiles were identified using an LG AI Research’s EXAONE Path-based cell-type classifier plus a ResNet18 tumor classifier. A weakly supervised model, developed in our previous work, was trained on the tumor tiles to predict responder versus non-responder status, achieving a slide-level area under the curve (AUC) exceeding 0.7 on an independent test set. Results: Tile-level prediction scores were aggregated into heatmaps representing predicted ICI responsiveness. By applying a sliding window (6.5 mm × 6.5 mm) with rotational adjustments to the prediction heatmap, we identified candidate regions of interest (ROIs) that (i) maximized predicted responsiveness, (ii) maximized predicted non-responsiveness, or (iii) captured heterogeneous (“mixed”) patterns. The multiprocessing pipeline efficiently generated ROI suggestions for each slide within seconds. This approach can provide a systematic framework for identifying optimal ROIs for spatial molecular profiling, directly linked to immune responses in gastric cancer. Conclusion: We developed an image-based approach that selects ROIs according to predicted ICI outcome in GC. By prioritizing regions enriched for predicted response, non-response, or mixed patterns, this strategy samples spatial niches more closely linked to outcome than conventional tumor-enriched or marker-based selection. The framework is adaptable to other spatial platforms by adjusting ROI size and applying user-defined weighting criteria based on predicted outcome, cell composition, or other image-derived features. Ongoing work will validate the method in larger cohorts and profile these ROIs with spatial transcriptomics and multimodal assays to define molecular programs underlying differential ICI response and support biomarker discovery, therapeutic development, and patient selection. *AI was used for language editing only; authors are responsible for all content and approved the final version. Citation Format: Sunho Park, Minji Kim, Jean R. Clemenceau, Seock-Jin Chung, Eric F. Sha, Changjin Hong, Soyoung Im, Hwanil Choi, Soonyoung Lee, Jongseong Jang, Kohei Shitara, Sung Hak Lee, Jae-Ho Cheong, Tae Hyun Hwang. Image-based ROI selection for spatial transcriptomic experiments using immune checkpoint inhibitor treatment outcome prediction in gastric cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 1420.

Background Large-scale genome projects have advanced the characterization of human genetic diversity; however, the lack of deeply sequenced, multiomic resources representing the Korean population has limited systematic evaluation of population-specific variation and its functional and translational impact. Results We present Korea10K, a population-scale genomic and multiomic resource comprising 10,239 high-depth whole genomes (mean coverage 30×) with integrated molecular and phenotypic data. Analysis of 9,000 unrelated individuals enabled near-complete discovery of rare and ultra-rare variants and supported the construction of a high-resolution, population-specific imputation panel. Koreans exhibit pronounced autosomal genetic homogeneity despite substantial diversity in Y-chromosomal, mitochondrial, and HLA lineages, reflecting long-term demographic continuity. We further identified 16.4 million variants that alter CpG dinucleotide context, revealing widespread sequence-driven modulation of the genomic CG landscape. Notably, population-specific CG-eliminating variants disrupt CpG probe targets in widely used methylation arrays, introducing a systematic source of bias in epigenome-wide association studies and epigenetic clock estimation. Conclusion Korea10K establishes a high-resolution genomic and multiomic reference for the Korean population and reveals a previously unrecognized interaction between genetic variation and epigenomic measurement. This resource provides a foundation for precision medicine and highlights the need for ancestry-aware interpretation of molecular data.

Abstract Understanding why specific metabolic states become stable in cancer has remained a fundamental challenge, as current pathway-centric frameworks lack a unifying physical principle governing global metabolic organization. We introduce the Metabolic Spin-Glass (MSG) model, which represents cellular metabolism using a thermodynamically informed effective Hamiltonian that integrates reference reaction free energies, cofactor-mediated network couplings, and patient-specific transcriptomic fields within a frustrated many-body optimization framework. The Hamiltonian is formulated as a binary optimization problem and solved using hybrid quantum annealing. Embedding gastric cancer transcriptomes (n = 497) reveals that malignant phenotypes occupy distinct low-energy configurations within the effective metabolic landscape rather than representing isolated pathway perturbations. A thermodynamic order parameter stratifies patients into prognostically distinct subtypes independently of transcriptomic classification, suggesting clinically applicable non-redundant biomarkers. This work establishes a thermodynamically informed spin-glass energy-landscape framework for patient-specific characterization and stratification of cancer metabolic organization.

Abstract Background Quantum biology explores how quantum mechanical phenomena—including coherence, tunneling, superposition, and spin dynamics—contribute to biological function. Although once considered negligible in warm and noisy biological environments, increasing evidence suggests that quantum effects play important roles in diverse living systems. Objective This review aims to summarize the current understanding of quantum biological mechanisms, highlight their relevance to physiology and disease, and discuss emerging biomedical and technological applications. Methods We reviewed recent experimental, computational, and theoretical advances in quantum biology, including studies employing ultrafast spectroscopy, quantum sensing, cryo‐electron microscopy, and quantum simulation approaches. Key biological systems examined include photosynthetic complexes, enzymatic reactions, DNA base pairing, sensory systems, and mitochondrial electron transport. Results Accumulating evidence indicates that quantum coherence, tunneling, and spin‐dependent processes contribute to photosynthetic energy transfer, enzymatic catalysis, proton transfer in DNA, magnetoreception, olfaction, and mitochondrial bioenergetics. Advances in quantum sensing and computational modeling have further enabled direct investigation of coherence dynamics and electron transfer mechanisms in biological systems. These findings suggest that quantum effects may influence aging, cancer, neurodegeneration, and metabolic dysfunction through mechanisms involving reactive oxygen species production, mutagenesis, and altered redox signaling. Conclusion Quantum biology is evolving from a speculative concept into an experimentally accessible and translationally relevant discipline. Integrating quantum principles with systems biology, multi‐omics, and precision medicine may provide new opportunities for diagnostics, biomarker discovery, and therapeutic development. Continued advances in spectroscopy, quantum sensing, and quantum computing are expected to further establish the role of quantum phenomena in health and disease.

Although gastric cancer remains a significant global health burden, its treatment strategies vary across different geographical regions, leading to distinct guidelines. In Asia, particularly in Korea, D2 gastrectomy followed by adjuvant chemotherapy has been established as the standard treatment for stage II/III gastric cancer based on landmark clinical trials. However, this "one-size-fits-all" approach requires refinement as emerging evidence suggests heterogeneous outcomes even within the same stage. This review discusses the evolving landscape of adjuvant treatment in gastric cancer, emphasizing the transition towards precision medicine. Recent molecular characterization of gastric cancer has revealed distinct subtypes with varying prognoses and chemotherapy responses, exemplified by the favorable outcomes of microsatellite instability-high tumors without adjuvant chemotherapy. Additionally, clinical factors including sub-stages within stage II/III, patient performance status, comorbidities, and personal preferences should be considered in treatment decisions. The integration of these molecular and clinical factors, along with shared decision-making between physicians and patients, represents a crucial step toward personalized treatment approaches. Looking ahead, the field is poised for further evolution with the emergence of immune checkpoint inhibitors, growing evidence for neoadjuvant chemotherapy in selected cases, and the potential of circulating tumor DNA as a biomarker for minimal residual disease. This comprehensive approach to treatment decision-making, considering both tumor biology and patient factors, will be essential for realizing precision medicine in gastric cancer care.

Determining tumor microsatellite status has significant clinical value because tumors that are microsatellite instability-high (MSI-H) or mismatch repair deficient (dMMR) respond well to immune checkpoint inhibitors (ICIs) and oftentimes not to chemotherapeutics. We propose MSI-SEER, a deep Gaussian process-based Bayesian model that analyzes H&E whole-slide images in weakly-supervised-learning to predict microsatellite status in gastric and colorectal cancers. We performed extensive validation using multiple large datasets comprised of patients from diverse racial backgrounds. MSI-SEER achieved state-of-the-art performance with MSI prediction by integrating uncertainty prediction. We achieved high accuracy for predicting ICI responsiveness by combining tumor MSI status with stroma-to-tumor ratio. Finally, MSI-SEER's tile-level predictions revealed novel insights into the role of spatial distribution of MSI-H regions in the tumor microenvironment and ICI response.

BACKGROUND:Stem-like gastric cancer (GC) is an aggressive molecular subtype marked by poor prognosis and limited response to immune checkpoint blockade (ICB). The spatial mechanisms driving this resistance remain unclear. METHODS:We conducted spatially resolved single-cell transcriptomic profiling of diffuse-type GC tissues to uncover the spatial architecture and functional diversity of tumor and stromal populations. Cellular heterogeneity and region-specific signaling pathways were characterized using integrative bioinformatics analyses. RESULTS:We identified transcriptionally diverse, high-entropy cell populations predominantly localized in the deep tumor regions. These included unique endothelial and fibroblast subsets enriched for pro-tumorigenic and immune-regulatory signaling. A notable finding was the engagement of deep-region endothelial cells in VISFATIN (extracellular NAMPT) signaling through the ITGA5-ITGB1 integrin axis, associated with immune evasion and poor prognosis. This endothelial signaling program is distinct from and functionally independent of cancer-associated fibroblast (CAF)-mediated pathways. Elevated expression of the NAMPT-ITGA5-ITGB1 axis was observed in ICB non-responders and correlated with reduced overall survival. CONCLUSIONS:Our study delineates spatially defined cellular programs that contribute to immune escape in stem-like GC, highlighting a novel VISFATIN-integrin signaling axis as a potential biomarker and therapeutic target in immunotherapy-resistant tumors.

PURPOSE:Patients with deficient mismatch repair (dMMR)/microsatellite instability-high (MSI-H) resectable gastroesophageal adenocarcinoma (GEA) have better survival after surgery and scant/no benefit from chemotherapy. Preoperative immune checkpoint inhibitors (ICIs) demonstrated a high proportion of major complete pathologic response, possibly allowing chemotherapy/surgery-free approaches. METHODS:Individual patient data pooled analysis was performed to determine an optimal strategy for resectable dMMR/MSI-H GEA. Patients were stratified across four groups: neoadjuvant dual CTLA-4/PD-(L)1 ICIs with or without surgery, perioperative fluorouracil, leucovorin, oxaliplatin, and docetaxel (FLOT) and surgery, and surgery alone or with older perioperative/adjuvant chemotherapy regimens. Primary end points were pathologic complete and major complete pathologic response proportion (pathologic complete response [pCR], tumor regression grade [TRG]1a, major pathologic response [MPR], TRG1a/b Becker criteria) in resected patients. Secondary end points were event-free survival (EFS) and overall survival (OS) in the overall population. RESULTS:Among 197 patients, 49 received ICIs, 27 FLOT, 33 surgery alone, and 88 older chemotherapy regimens. Among 69 patients who underwent surgery after ICIs or FLOT, ICIs demonstrated significantly higher pathologic response versus FLOT (pCR, 61.9% v 3.7%; odds ratio [OR], 54.8; P = .002; MPR, 78.6% v 10%; OR, 39.3; P < .001) and lower ypN+ (14.3% v 37%; OR, 4.2; P = .015) and ypT (OR, 16.4; P < .001) stage. No significant differences in EFS/OS were observed (the 36-month EFS and OS were 70.4% v 80.6% and 72.7% v 90.4% with ICI v surgery alone). Residual nodal disease (ypN+) or ypT4 status after neoadjuvant ICIs or FLOT and nonpathologic response status were associated with inferior progression-free survival/OS. CONCLUSION:In resectable dMMR/MSI-H GEA, neoadjuvant ICIs significantly increase pathologic response and downstaging versus FLOT, with comparable EFS/OS with surgery with or without chemotherapy. The higher proportion of ypN0 and lack of ypT4 after neoadjuvant ICIs versus FLOT should drive preoperative treatment choices in clinical high-risk disease. The high proportion of pCR/MPR with ICIs provides rationale for exploring organ-sparing surgery or nonoperative management.

WNT signaling plays a key role in maintaining the gastric epithelium and promoting tumorigenesis. However, how gastric tumors achieve WNT niche independence remains unclear, as mutations on APC or CTNNB1—common mechanisms of ligand-independent WNT activation in colorectal cancer—are infrequent in gastric cancer. Understanding how WNT self-sufficiency is acquired in the stomach is therefore critical. We analyzed mouse gastric organoids harboring oncogenic KRASG12D with or without RNF43/ZNRF3 (RZ) or CDH1/TP53 (CP) mutations, along with corresponding in vivo mouse models. Niche independence was assessed through growth factor withdrawal, Porcupine and pathway-specific inhibitor treatments, and WNT rescue assays. We performed single-nucleus multiome sequencing (RNA + ATAC) to investigate transcriptional and chromatin dynamics. Findings from mouse models were validated using patient-derived gastric cancer organoids, and pan-cancer cell line datasets were analyzed to evaluate clinical and cross-tissue relevance. Gastric fibroblasts secreted canonical WNT2B to maintain the homeostatic gastric epithelium. Upon KRAS activation, epithelial cells were reprogrammed to secrete WNT ligands independently of additional mutations. Single-nucleus multiome analysis revealed that KRAS-driven MAPK signaling opened SMAD2/3-bound enhancers at the WNT7B locus, leading to the emergence of WNT7B-expressing subpopulations. Inhibition of SMAD2/3 phosphorylation suppressed both organoid growth and WNT7B transcription, whereas exogenous WNT restored organoid proliferation. Patient-derived organoids with HER2 amplification, KRAS amplification, or WNT2 copy-number gain exhibited Porcupine inhibitor-sensitive growth, indicating dependence on WNT secretion from the organoids. Analysis of public transcriptomic datasets further demonstrated that the KRAS–MAPK–WNT7B axis is conserved across other cancer types, including lung cancer. Gastric tumors can bypass niche dependence by acquiring KRAS–MAPK–SMAD2/3-driven epithelial WNT secretion. Targeting this axis—through MAPK inhibition, SMAD2/3 blockade, or suppression of WNT secretion—may represent a therapeutic vulnerability in gastric cancer and other KRAS-high malignancies.

Secreted Frizzled-related protein 4 (SFRP4) has been identified as a patient-level biomarker of the stem-like subtype of gastric cancer (GC), which is associated with poor prognosis and resistance to chemotherapy. Although multiple studies have documented the clinical significance of SFRP4 in GC, its mechanistic role in the stem-like subtype remains incompletely understood. In this study, we elucidate how phosphorylation of SFRP4 by protein kinase A (PKA) converts it into a Wnt signaling agonist. We began with a phosphoproteomic database search to identify candidate kinases that phosphorylate SFRP4. Co-immunoprecipitation assays revealed a direct interaction between PKA and SFRP4, and in vitro kinase assays confirmed that PKA phosphorylates SFRP4 at key threonine residues. Phosphorylated SFRP4 then associates with β-catenin, augmenting Wnt-driven transcriptional activity. Importantly, pharmacological inhibition of PKA significantly reduced SFRP4 phosphorylation and suppressed stemness-associated phenotypes, such as sphere formation, migratory capacity, and chemoresistance, in gastric cancer cells. Collectively, our data demonstrate that PKA-mediated phosphorylation of SFRP4 enhances cancer stemness-related properties in GC through Wnt signaling. Furthermore, these results highlight the PKA-SFRP4 axis as a promising therapeutic target in the stem-like subtype of GC.

Refractory hepatocellular carcinoma (HCC) perpetuates metastasis or recurrence through anti-cancer drug resistance, necessitating more effective and reliable therapeutic strategies. We propose a new therapeutic approach involving the discovery of novel small molecules through target identification and validation in a patient-derived metastatic HCC model. We showed that calcium/calmodulin-dependent protein kinase 2 alpha (CaMK2α)-mediated enhancement of sarco/endoplasmic reticulum (ER) calcium ATPase 1 (SERCA1) expression level was pivotal events under anti-cancer drug treated conditions in patient-derived metastatic HCC cells. Increased SERCA1 was regulates to overloaded free calcium. SERCA is widely recognized as a key regulator of cytosolic free calcium under severe ER stress conditions. Though a cardiac dysfunction was unavoidable in vivo because of non-specific inhibition of SERCA isoforms by standard SERCA inhibitors. Based on the molecular structure of SERCA1, we discovered and synthesized two SERCA1-specific inhibitors, candidate 56 and 62. These compounds significantly reduced tumor size in the metastatic HCC xenograft tumor model without cardiac contractile dysfunction. This study first showed survival mechanism of patient-derived metastatic HCC cell, and propose a new therapeutic approach by the new small molecules, candidate 56 and 62, which are SERCA1 isoform-specific inhibitors without cardiac dysfunction by SERCA1 selectively inhibition.

455 Background: Patients with resectable MSI/dMMR GEA showed improved survival and modest if any benefit from chemotherapy. Preoperative treatment with immune checkpoint inhibition (ICI) showed high rate of major-complete pathologic response in single arm trials possibly allowing the design of chemotherapy/surgery-free approaches. Methods: This was a multinational IPD analysis including patients with resectable GEA with MSI/dMMR status enrolled in INFINITY and NEONIPIGA phase II trials, with dual CTLA-4/PD-(L)1 ICI followed by surgery +/- adjuvant ICI; PROSECCO retrospective study, with perioperative FLOT chemotherapy and surgery, and the dataset of our previous IPD analysis on MAGIC, CLASSIC, ARTIST and ITACA-S randomized trials of patients treated with surgery alone or plus older perioperative/adjuvant chemo(radio)therapy regimen. Primary endpoint was the evaluation of rates of pathologic complete response (pCR) defined as TRG1a Becker and major-complete pathologic response (pCR/MPR) defined as TRG1a/b Becker according to preoperative treatment schedule in patients who underwent surgery. Univariable and multivariable analyses were conducted using a random effects logistic model adjusted with propensity score. Secondary endpoints were event-free survival (EFS) and overall survival (OS) according to the therapeutic strategy in the overall study population. Multivariable mixed-effects Cox models weighted with propensity score were performed. Results: The IPD included 197 patients. Of these, 49 received ICI +/- surgery, 27 FLOT chemotherapy plus surgery, 33 surgery alone and 88 older chemo(radio)therapy regimens plus surgery. In the 69 patients resected after neoadjuvant ICI or FLOT standard of care treatment, ICI demonstrated a higher rate of pathologic response compared to chemotherapy (pCR 61.9% vs 3.7%, OR 54.8 p=0.002; pCR/MPR 78.6% vs 10%, OR 39.3 p<0.001). In ITT population, no significant difference in OS and EFS was shown in patients treated with ICI, FLOT plus surgery, old chemo(radio)therapy plus surgery or surgery alone. Conclusions: In resectable MSI/dMMR GEA, upfront ICI showed comparable survival outcomes to surgery alone, with limitations of study design and sample size. The impact on survival of ICI versus surgery alone should be investigated prospectively to avoid overtreatment or identify specific risk categories with benefit. The high rate of major-complete pathologic response may allow to study or perform organ sparing surgery procedures or non-operative management to reduce surgical morbidity/mortality and improve quality of life. OS EFS HR 2.5-97.5% CI p HR 2.5-97.5% CI p Ref: Surgery only - - - - - - Chemo+surgery 1.16 0.27-4.98 0.84 1.10 0.39-3.07 0.85 FLOT+surgery 1.10 0.19-6.22 0.92 2.38 0.90-6.27 0.08 ICI +/- surgery 1.97 0.43-8.96 0.38 1.39 0.51-3.77 0.52

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer with poor prognosis, largely due to the rapid development of chemoresistance in patients. Mitochondrial dynamics play a crucial role in cancer cell survival. Currently, the specific mechanisms underlying gemcitabine resistance in PDAC remain unknown. In this study, we identified the sodium/myo-inositol co-transporter solute carrier family 5 member 3 (SLC5A3) as a key modulator promoting chemoresistance in PDAC. SLC5A3 levels were significantly upregulated in gemcitabine-resistant PDAC cells, enhancing their cell survival by stabilizing the mitochondrial functions and inhibiting apoptosis. Mitochondrial analysis showed that SLC5A3 inhibition disrupted the mitochondrial dynamics, leading to increased reactive oxygen species production, mitochondrial fission, and impaired oxidative phosphorylation. Moreover, SLC5A3 inhibition activated the PTEN-induced kinase 1/Parkin-mediated mitophagy pathway, resulting in the excessive removal of damaged and healthy mitochondria, thereby depleting the mitochondrial reserves and sensitizing the cells to apoptosis. In vivo studies revealed that targeting SLC5A3 enhanced the efficacy of gemcitabine and significantly reduced the tumor growth. Collectively, these results suggest SLC5A3-mediated mitochondrial regulation as a promising therapeutic strategy to overcome gemcitabine resistance in PDAC.

Cancer, driven by mitochondrial and nuclear DNA mutations, presents opportunities for targeted therapies. Gastric cancer (GC), the 4th leading cause of cancer-related deaths, has poor prognosis due to cancer stem cells (CSCs), which depend on mitochondrial complex II (CII) respiration. Among CSC-enriched subtypes, the aggressive stem-like/EMT/Mesenchymal (SEM) GC subtype exhibits high plasticity, chemotherapy resistance, and metabolic adaptations that promote tumor survival. This study explores α-d-tocopherol derivatives targeting GC cells with enriched cancer stemness (S-cells) by inhibiting succinate dehydrogenase (SDH), also known as the CII complex. Malonate (10) and primary amide (17) derivatives of α-D-tocopherol showed potent anti-proliferative activities in S-cells, with GI50 values of 0.203 μM (SSNU638) and 0.156 μM (SSK4), respectively, over 10-fold more potent than α-TOS (6). Mechanistic studies showed that both 10 and 17 inhibit SDHC activity, reduce CII-specific oxygen consumption rates (OCR), and induce increased ROS production, leading to apoptosis. Furthermore, in patient-derived organoid (PDO) models, derivative 10 (GA265T GI50 = 5.623 μM) and 17 (GA265T GI50 = 6.347 μM) exhibited enhanced anti-proliferative activity in SEM-type GC PDOs (SDHC-high) compared to non-SEM-type PDOs (SDHC-low), with over a 2-fold increase in anti-proliferative activity against the GA265T SEM-type PDO model compared to α-TOS (6; GA265T GI50 = 12.660 μM). In vivo studies further demonstrated that compound markedly inhibited tumor growth in SSK4 xenograft models with miniaml systemic toxicity, outperforming the reference compound α-TOS. These results support that selective targeting of SDHC by α-TOS derivatives 10 and 17 disrupts mitochondrial complex II function and redox homeostasis, thereby inducing apoptosis in SEM-type gastric cancer both in vitro and in vivo.

The spatial patterns of tumor, stroma, and tumor-infiltrating lymphocytes (TILs) within the tumor microenvironment significantly affect cancer progression and are associated with clinical outcomes. Understanding the exact significance and statistical implications of these spatial patterns is, however, challenging due to the complexity of spatial interactions. In this paper, we investigate the spatial patterns related to patient survival in gastric and colorectal cancer using four classifiers to predict tumor, stroma, TILs, and Microsatellite Instability (MSI) status, along with the Getic-Ord-Gi* statistic as the spatial image analysis, analyzing four large patient cohorts. U-Net, a deep learning model for semantic image segmentation, was used to predict tumor, stroma, and TILs in digitized Hematoxylin and Eosin-stained formalin-fixed paraffin-embedded (FFPE) sections, and ResNet-18 was employed to predict the MSI status. The Getis-Ord-Gi* statistic was applied to determine statistically significant tumor hotspot regions by examining their relationship to surrounding areas. Kaplan-Meier analyses and log-rank tests were performed to assess the association between the spatial patterns of tumor and stroma and overall survival in the patient cohorts. Results indicate that the stroma composition around tumor hotspot regions, identified by the Getis-Ord-Gi* statistic, shows significant differences in overall survival among patients with gastric and colorectal cancer. The log-rank test was included to examine the relationship between stroma composition and MSI and ACTA2 expression levels.

CD39+CD8+ T cells are known as tumor-antigen-specific cells among CD8+ tumor-infiltrating lymphocytes (TILs). However, CD39+CD8+ T cells also reportedly exhibit immunosuppressive activity in hypoxic tumor models. Here, we investigate CD39+CD8+ TILs in clear cell renal cell carcinoma (ccRCC), a Von Hippel-Lindau (VHL) mutation-associated hypoxic tumor. Single-cell analyses confirm that CD39+CD8+ cells are a terminally exhausted subset of tumor-specific CD8+ TILs. CD39+CD8+ T cell development is directly induced by cAMP and T cell receptor (TCR) signaling. Analysis of a renal cell carcinoma (RCC) cohort reveals that the proportion of CD39+CD8+ TILs is associated with a high tumor mutational burden and hypoxic features. Ex vivo functional assays reveal that CD39+CD8+ TILs exert immunosuppressive activity via ectonucleotidase activity- and adenosine-dependent mechanisms. CD39+CD8+ TIL enrichment predicts poor prognosis in patients with ccRCC yet also predicts favorable treatment responses to anti-programmed cell death protein 1 (PD-1) therapy. This paradoxical prognostic significance in ccRCC is explained by the dual properties of CD39+CD8+ TILs: tumor antigen specificity and immunosuppressive activity.

Background The number of cancer survivors who develop subsequent primary cancers (SPCs) is expected to increase. Objective We evaluated the overall and cancer type–specific risks of SPCs among adult-onset cancer survivors by first primary cancer (FPC) types considering sex and age. Methods We conducted a retrospective cohort study using the Health Insurance Review and Assessment database of South Korea including 5-year cancer survivors diagnosed with an FPC in 2009 to 2010 and followed them until December 31, 2019. We measured the SPC incidence per 10,000 person-years and the standardized incidence ratio (SIR) compared with the incidence expected in the general population. Results Among 266,241 survivors (mean age at FPC: 55.7 years; 149,352/266,241, 56.1% women), 7348 SPCs occurred during 1,003,008 person-years of follow-up (median 4.3 years), representing a 26% lower risk of developing SPCs (SIR 0.74, 95% CI 0.72-0.76). Overall, men with 14 of the 20 FPC types had a significantly lower risk of developing any SPCs; women with 7 of the 21 FPC types had a significantly lower risk of developing any SPCs. The risk of developing any SPC type differed by age; the risk was 28% higher in young (<40 years) cancer survivors (SIR 1.28, 95% CI 1.16-1.42; incidence: 30 per 10,000 person-years) and 27% lower in middle-aged and older (≥40 years) cancer survivors (SIR 0.73, 95% CI 0.71-0.74; incidence: 80 per 10,000 person-years) compared with the age-corresponding general population. The most common types of FPCs were mainly observed as SPCs in cancer survivors, with lung (21.6%) and prostate (15.2%) cancers in men and breast (18.9%) and lung (12.2%) cancers in women. The risks of brain cancer in colorectal cancer survivors, lung cancer in laryngeal cancer survivors, and both kidney cancer and leukemia in thyroid cancer survivors were significantly higher for both sexes. Other high-risk SPCs varied by FPC type and sex. Strong positive associations among smoking-related cancers, such as laryngeal, head and neck, lung, and esophageal cancers, were observed. Substantial variation existed in the associations between specific types of FPC and specific types of SPC risk, which may be linked to hereditary cancer syndrome: for women, the risks of ovarian cancer for breast cancer survivors and uterus cancers for colorectal cancer survivors, and for men, the risk of pancreas cancer for kidney cancer survivors. Conclusions The varying risk for SPCs by age, sex, and FPC types in cancer survivors implies the necessity for tailored prevention and screening programs targeting cancer survivors. Lifestyle modifications, such as smoking cessation, are essential to reduce the risk of SPCs in cancer survivors. In addition, genetic testing, along with proactive cancer screening and prevention strategies, should be implemented for young cancer survivors because of their elevated risk of developing SPCs.