ArchiveIn the past decade, cancer immunotherapy has emerged as a transformative treatment modality for diverse malignancies. Although impressive clinical efficacy has been demonstrated in some cancer patients, most patients respond poorly to immunotherapies. The complicated architecture and cellular composition of the tumor immune microenvironment (TIME) have substantial roles in the clinical outcomes of immunotherapies. Therefore, employing optimal in vitro models recapitulating the in vivo TIME characteristics is particularly important for interpreting the dynamic complexity of the TIME, evaluating drug efficacy, and developing novel immunotherapeutics. In recent years, microfluidic technology has been shown to be a valuable tool for mimicking dynamic crosstalk among the TIME in vitro through the manipulation of microscale fluids in an integrated device. Cellular behaviors, function and signal transduction, and tumor–immune interactions can be monitored in real time and analyzed in microfluidic chips by combining visualization technologies. Numerous recent studies have shown how to design and fabricate microfluidic chips for reproducing the complex three-dimensional architecture and dynamic changes in the TIME. This review comprehensively examines the application of innovative microfluidic technology in the field of cancer immunology research, focusing on interpreting dynamic crosstalk inside the TIME from bulk-cell to single-cell analyses, evaluating the efficacy of novel immunotherapies and preparing immunotherapeutic agents, and analyzes current limitations. This work aimed to propose a translational roadmap for leveraging microfluidics in elucidating mechanisms, biomarker discovery, high-throughput drug screening, and personalized immunotherapy development.
The immune checkpoint blockade (ICB) approach in cancer therapy involves the disruption of immune checkpoint inhibitory signals on tumor-specific CD8+ T cells, thereby reinstating the immune activity of CD8+ T cells and yielding therapeutic efficacy. However, due to the co-expression of immune checkpoint molecules, such as CTLA-4 and PD-1 on tumor-infiltrating Tregs (TI-Tregs) and conventional T cells (Tconvs), immune checkpoint inhibitors (ICIs) inadvertently amplify the immunosuppressive activity of Tregs while targeting CD8+ T cells, which contributes to the failure of immune therapy. Conventional strategies targeting Tregs, including ICI/conventional kinase and chemokine/chemokine receptor blockade, generally induce systemic Treg depletion, which triggers autoimmune diseases. Thus, achieving high selectivity and specificity in targeting TI-Tregs is of paramount importance in mitigating adverse immunologic reactions. Targeting metabolism-based TI-Tregs has been shown to enhance target precision, providing potential for the development of adjunctive immunotherapeutic strategies. This article explores the reciprocal interaction between TI-Tregs and the tumor microenvironment (TME), elucidating metabolic reprogramming, while envisioning plausible high-selectivity targets for TI-Tregs without compromising systemic immune homeostasis and immune reactivity of effector T cells.
Emerging evidence suggests that the efficacy of immunotherapy in patients with advanced HER2-negative gastric cancer differs between Asian and non-Asian populations. This review examines potential factors contributing to these disparities, including differences in demographic and clinicopathologic characteristics, somatic mutations, molecular subtypes, tumor immunity, Helicobacter pylori (H. pylori) infection, dietary habits, and gut microbiome composition. These factors may serve as predictors of immunotherapy response in gastric cancer patients. For example, the prevalence of molecular subtypes and somatic mutations have been linked to variations in immunotherapy efficacy between Asian and non-Asian populations. In addition, differences in H. pylori infection rates, dietary habits, and gut microbiota composition may influence systemic immune responses, and consequently, immunotherapy outcomes. Understanding the factors contributing to these disparities in immunotherapy response is crucial for optimizing treatment strategies and improving outcomes for patients with gastric cancer. Further research into the mechanisms underlying racial and ethnic disparities in immunotherapy response is needed to identify potential biomarkers predictive of immunotherapy response in diverse patient populations.
As an emerging biomarker, tumor mutational burden (TMB) has attracted increasing attention from clinicians in predicting the efficacy of tumor immunotherapy. Currently, TMB is detected primarily by whole-exome sequencing or targeted panel sequencing on high-throughput sequencing platforms. However, the lack of uniformity in detection methods, threshold settings, and reporting formats, as well as the significant differences in TMB values among different cancer types, have hindered the standardized application of this biomarker in clinical practice. This consensus focuses on the definition, standardization of detection, clinical significance, and limitations of TMB, and provides consensus recommendations for the clinical application of TMB in real-world practice in China. This consensus is aimed at helping clinicians and laboratory personnel understand the clinical significance and testing standards of TMB, promoting more accurate interpretation of test results, and improving patient care.
Paclitaxel (PTX), a conventional second-line therapeutic agent for advanced gastric cancer (GC), exhibits compromised clinical efficacy due to acquired chemoresistance in patients, the molecular mechanisms of which remain poorly elucidated. This study aimed to investigate the therapeutic potential of targeting extracellular vesicle (EV) protein in reversing PTX resistance in GC cells and to delineate the underlying molecular pathways involved.
Proteomic profiling was used to identify differentially expressed EV proteins in PTX-resistant GC cells. EVs were isolated via size exclusion chromatography (SEC) and characterized using transmission electron microscopy (TEM), nano-flow cytometry (nano-FCM), and western blot analysis. In vivo functional validation was performed in xenograft tumor models by injecting EV proteins into nude mice via the tail vein (6 groups, n = 4). EVs derived from 4,4′-diisothiocyanatostilbene-2,2′-disulfonic acid (DIDS)-treated cells were administered to tumor-bearing nude mouse model (4 groups, n = 5) to determine the impact of EV-derived voltage-dependent anion channel protein 1 (VDAC1) on PTX resistance. In addition, VDAC1 protein expression was evaluated using immunohistochemical (IHC) assays in 34 clinical specimens from PTX-resistant patients.
Proteomic analyses demonstrated a marked upregulation of VDAC1 in EVs secreted by PTX-resistant GC cells. Functional studies revealed that intercellular transfer of EV-derived VDAC1 directly conferred PTX resistance to drug-sensitive cancer cells. Gene set enrichment analysis (GSEA) and adenosine triphosphate (ATP) functional assay further elucidated that VDAC1-mediated chemoresistance was mechanistically linked to the activation of adenosine 5′-monophosphate (AMP)-activated protein kinase (AMPK) signaling and concomitant suppression of the mammalian target of rapamycin – p70 ribosomal protein S6 kinase (mTOR-p70S6K) pathway. In vivo validation confirmed that systemic delivery of EV-derived VDAC1 significantly reduced PTX sensitivity in GC tumors. Furthermore, DIDS inhibited the expression of the VDAC1 protein in EVs, thereby reducing PTX resistance in vivo and in vitro. IHC analysis revealed that VDAC1 expression was significantly higher in GC patients with PTX resistance compared to PTX-sensitive patients.
The findings herein underscore the pivotal role of EV-derived VDAC1 in driving PTX resistance in GC through dual modulation of autophagy and mitophagy, mediated by the AMPK/mTOR signaling axis. Targeting EV-derived VDAC1 has emerged as a promising therapeutic strategy to counteract chemoresistance, providing a novel avenue for improving GC treatment outcomes.
Colorectal cancer (CRC) progression is driven by cancer stem cells (CSCs) that evade treatment through dynamic phenotype modulation. Our previous research identified BEX2 as a significant regulator of CRC malignancy involving the Hedgehog (Hh) pathway. This study aimed to elucidate the influence of BEX2 on CRC stemness and the interaction with the Hh signaling pathway, potentially uncovering innovative therapeutic strategies for combating CRC.
TCGA and GEO data were analyzed to correlate BEX2 expression with clinical outcomes and stemness markers in CRC. Functional assays, including spheroid formation, flow cytometry, extreme limiting dilution assay (ELDA), Transwell, wound healing, and cell viability assay, were performed in DLD1 and HCT116 cell lines. Immunoblotting and qRT-PCR assessed BEX2 expression with in vivo validation in NOD/SCID mice.
The findings revealed a negative correlation between BEX2 expression and the levels of stemness-associated genes with a significant association with CRC patient’ prognosis. Overexpression of BEX2 diminished CRC stemness potential, whereas BEX2 knockdown led to a pronounced enhancement of these stem-like characteristics. Further investigation revealed that BEX2 inhibited the Hh pathway. BEX2 interacted with MCL1, promoting ubiquitination and degradation, thereby decreasing MCL1 stability. Low BEX2 expression stabilized MCL1, which enhanced stemness potential. These results suggested BEX2 modulates CRC stemness via MCL1 downregulation.
Taken together, the current study findings highlight BEX2 and MCL1 as potential therapeutic targets in CRC with BEX2 emerging as a key regulator of stemness, chemoresistance, and invasiveness. These findings advance our understanding of CRC and pave the way for more effective therapies.
This study aimed to develop and validate a temporal radiomics model based on pre- and post-treatment CT scans for the preoperative prediction of pathologic complete response (pCR) in patients with resectable non-small cell lung cancer (NSCLC) undergoing neoadjuvant chemoimmunotherapy (NCI).
Data from 263 patients with resectable NSCLC who underwent NCI followed by curative surgery and had both pre- and post-treatment CT scans were retrospectively collected. Patients from one hospital were randomly divided into training and internal test sets at a 7:3 ratio, while patients from two other hospitals served as the external test set. Radiomics features were extracted from the CT scans at both timepoints and delta features capturing the temporal changes were calculated. Radiomics models based on different features were developed using the least absolute shrinkage and selection operator for feature selection, followed by logistic regression. Model performance was evaluated using the area under the curve (AUC).
The radiomics model based on delta features yielded AUCs of 0.85, 0.76, and 0.72 in the training, internal test, and external test sets, respectively, which were superior to the radiomics models based on pre-treatment features (0.74, 0.66, and 0.62, respectively) and post-treatment features (0.80, 0.76, and 0.65, respectively). By integrating the optimal features from all three feature sources, the combined model achieved further improvements in performance, with AUCs of 0.89, 0.85, and 0.78, respectively, across the three sets.
A CT-based radiomics model incorporating temporal features from pre- and post-treatment scans shows favorable performance for the non-invasive preoperative estimation of pCR to NCI in patients with NSCLC.
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