Immune complexity status in the TME has been linked to clinical outcomes in pancreatic ductal adenocarcinoma (PDAC) patients. TME assessments with current cell marker and cell density-based analyses do not identify the original phenotypes of single cells with multilineage selectivity, the functional status of the cells, or cellular spatial information in the tissues. Here, we describe a method that circumvents these problems. The combined strategy of multiplexed IHC with computational image cytometry and multiparameter cytometric quantification allows us to assess multiple lineage-selective and functional phenotypic biomarkers in the TME. Our study revealed that the percentage of CD8⁺ T lymphoid cells expressing the T cell exhaustion marker PD-1 and the high expression of the checkpoint PD-L1 in CD68⁺ cells are associated with a poor prognosis. The prognostic value of this combined approach is more significant than that of lymphoid and myeloid cell density analyses. In addition, a spatial analysis revealed a correlation between the abundance of PD-L1⁺CD68⁺ tumor-associated macrophages and PD-1⁺CD8⁺T cell infiltration, indicating pro-tumor immunity associated with a poor prognosis. These data highlight the implications of practical monitoring for understanding the complexity of immune cells in situ. Digital imaging and multiparameter cytometric processing of cell phenotypes in the TME and tissue architecture can reveal biomarkers and assessment parameters for patient stratification.

The anti-tumor function of CD8⁺ T cells is dependent on their proximity to tumor cells. Current studies have focused on the infiltration level of CD8⁺ T cells in the tumor microenvironment, while further spatial information, such as spatial localization and inter-cellular communication, have not been defined. In this study, co-detection by indexing (CODEX) was designed to characterize PDAC tissue regions with seven protein markers in order to identify the spatial architecture that regulates CD8⁺ T cells in human pancreatic ductal adenocarcinoma (PDAC). The cellular neighborhood algorithm was used to identify a total of six conserved and distinct cellular neighborhoods. Among these, one unique spatial architecture of CD8⁺ T and CD4⁺ T cell-enriched neighborhoods enriched the majority of CD8⁺ T cells, but heralded a poor prognosis. The proximity analysis revealed that the CD8⁺ T cells in this spatial architecture were significantly closer to themselves and the CD4⁺ T cells than to the tumor cells. Collectively, we identified a unique spatial architecture that restricted the proximity of CD8⁺ T cells to tumor cells in the tumor microenvironment, indicating a novel immune evasion mechanism of pancreatic ductal adenocarcinoma in a topologically regulated manner and providing new insights into the biology of PDAC.

Tumor-derived circulating cell-free DNA (ctDNA) has emerged as a pivotal biomarker for non-invasive cancer diagnosis, treatment monitoring, and prognostic evaluation. However, its inherently low abundance, high fragmentation, and rapid degradation impose stringent requirements on assay sensitivity, specificity, and analytical robustness. Rapid advances in nanotechnology have significantly accelerated progress in ctDNA detection. This review summarizes recent nanotechnology-assisted strategies for ctDNA analysis, including surface-engineered nanomaterials for selective enrichment, nano-enabled signal amplification modalities, and integrated platforms such as CRISPR-based detection, microfluidics and nanopore technologies. We further highlight nanostructure-based approaches for decoding methylation, fragmentation profiles, and multi-omics signatures, focusing on their potential to enhance early cancer detection and real-time therapeutic assessment. Moreover, increasing incorporation of artificial intelligence (AI) which spans nanostructure characterization, aptamer and probe design, multi-omics data integration, and algorithm development is reshaping the landscape of nano-assisted liquid biopsy. Finally, current challenges and future perspectives concerning the clinical translation of nanotechnology-assisted ctDNA detection are presented, emphasizing standardization, biocompatibility, automation, and regulatory readiness. Overall, this review provides a comprehensive outlook on how converging nanotechnology and AI innovations are advancing ctDNA-based precision oncology.

Introduction: Clostridioides difficile Infection (CDI) is more prevalent in people with hematologic diseases. However, epidemiological characteristics are poorly understood. Methods: From July 2016 to November 2021, we studied the epidemiology of CDI in patients with hematological diseases at a tertiary teaching hospital in Shanghai, China. Results: In hematological patients, the prevalence of CDI was 21.6%, with 89.8% hospital-acquired infections. C. difficile ST81, which is a multidrug-resistant strain carrying only the toxin B, is the most common strain (38.1%), followed by ST3 (16.7%) and ST2 (9.5%). Clindamycin and moxifloxacin resistance rates of all C. difficile species were 64.3% and 31%, respectively, and no isolate was resistant to vancomycin, linezolid, metronidazole, teicoplanin, or daptomycin. Discussion: This study provides a comprehensive characterization of CDI in hematological patients, highlighting the urgent need for enhanced surveillance and preventive strategies against this emerging nosocomial threat.

Clostridium difficile infection (CDI) is a leading cause of antibiotic-associated diarrhea and pseudomembranous colitis, and there remains a significant unmet need for therapies specifically targeting C. difficile. The Pyrin inflammasome, activated by bacterial toxins, plays a critical role in driving macrophage-mediated intestinal inflammation during CDI. In this study, we report that myeloid-specific deficiency of Zbtb16 protects mice from C. difficile-induced colitis by attenuating IL-1β-dependent inflammatory signaling. Mechanistic studies revealed that Zbtb16 deletion disrupts ASC oligomerization and speck formation, thereby selectively inhibiting inflammasome assembly and reducing mature IL-1β production in macrophages stimulated with C. difficile culture supernatant or purified TcdB toxin. Importantly, pharmacological degradation of ZBTB16 using the cereblon E3 ligase modulating drug CC-3060 significantly ameliorated colitis severity in a murine model of CDI. Our findings establish ZBTB16 as a key regulator of Pyrin inflammasome activation in macrophages, highlighting the therapeutic promise of ZBTB16 degradation as a novel strategy for treating CDI.

Background/Objectives: Cholangiocarcinoma (CCA) is characterized by a heterogeneous immune microenvironment, where the prognostic significance of CD8⁺ tissue-resident memory T (T_RM) cell activation and spatial positioning remains to be fully elucidated. This study investigated how the activation phenotypes and their spatial distribution relative to tumor cells influence anti-tumor immunosurveillance and predict clinical outcomes in CCA. Methods: Multiplex immunohistochemistry (mIHC) and single-cell RNA sequencing (scRNA-seq) were employed to characterize naïve (PD-1⁻CD103⁺CD8⁺) and exhausted (PD-1⁺CD103⁺CD8⁺) subsets. G-cross function analysis was utilized to quantify the spatial proximity between these specific T_RM subsets and tumor cells, correlating the spatial interaction with patient overall survival. Results: scRNA-seq profiling revealed that PD-1⁻CD103⁺CD8⁺ T_RM cells were enriched in genes associated with lymphocyte activation and cytotoxicity, while PD-1⁺CD103⁺CD8⁺ T_RM cells exhibited an exhaustion signature. Spatially, PD-1⁻CD103⁺CD8⁺ T_RM cells exhibited increased interactions with tumor cells, whereas PD-1⁺CD103⁺CD8⁺ T_RM cells showed reduced engagement. Therefore, the close proximity of PD-1⁻CD103⁺CD8⁺ T_RM cells to tumor cells was identified as a significant predictor of favorable clinical outcomes. Conclusions: The activation state of CD8⁺ T_RM cells combined with their spatial localization constitutes a critical prognostic factor in CCA. Effective anti-tumor immunosurveillance relies on the direct engagement of naïve T_RM cells with tumor cells. These findings highlight the potential of PD-1-targeted immunotherapies to remodel the spatial proximity of the tumor microenvironment, potentially promoting the redistribution of effector cells into tumor-proximal regions.