Spatial architecture of regulatory T-cells correlates with disease progression in patients with nasopharyngeal cancer

Prognosis and immune infiltration prediction in neuroblastoma based on neutrophil extracellular traps-related gene signature

Neuroblastoma (NB) is a malignant tumor originating from the peripheral sympathetic nervous system and high-risk NB patients have a dismal prognosis. Recent studies have underscored the pivotal role of neutrophil extracellular traps (NETs) in the proliferation, metastasis and immune evasion of cancer. To explore the effect of NETs on NB, we have carried out a systematic analysis and showed several findings in the present work. First, expression profiles along with clinical data were analyzed using the training dataset GSE62564 and 36 NETs-related genes were identified to be significantly associated with overall survival. Following LASSO regression analysis, 11 genes were enrolled to construct the NETs signature, which exhibited a robust predictive capability for overall survival with exhibiting high AUC values within the training set. Validation cohorts confirmed a similar predictive efficacy. Next, NB patients were classified into subgroups based on median risk scores and differentially expressed genes were analyzed. Furthermore, the study performed comprehensive analyses encompassing functional enrichment, immune infiltration and drug sensitivity. Enrichment analysis revealed that the high-risk NBs with high-risk score displayed characteristics of oncogenic malignancy, poor prognosis and immunosuppression. Notably, the risk score exhibited a strong correlation with infiltration levels of various immune cells and the sensitivity to anti-cancer drugs, and was further recognized as an independent prognostic factor for NB patients. In summary, our study elucidates a novel NETs-related gene signature comprising 11 genes, which serves a reliable predictor for NB prognosis.

Significance of longitudinal Epstein-Barr virus DNA combined with multipoint tumor response for dynamic risk stratification and treatment adaptation in nasopharyngeal carcinoma

Dynamic therapy response is strongly associated with cancer outcomes. This study aimed to evaluate the significance of longitudinal Epstein-Barr virus (EBV) DNA and radiological tumor regression in risk stratification and response-adaptive treatment in locally-advanced nasopharyngeal carcinoma (LA-NPC). In total, 1312 patients from two centers were assigned to the training and validation cohorts. Based on the multipoint examination of EBV-DNA and tumor response, four post-induction chemotherapy, four mid-radiotherapy, and four post-radiotherapy subgroups were established. Then seven phenotypes were further generated according to different permutations and combinations. These phenotypes were subsequently congregated into four response clusters, which reflect distinct biological treatment responses. The four response clusters correlated with an evident 5-year progression-free survival in both the training and external validation cohorts (5-year: training cohort 91.1 %, 82.8 %, 30.6 %, and 10.0 %; external validation 94.4 %, 55.6 %, 40.0 %, and 12.7 %) had superior prognostic performance compared to TNM staging and nomogram model (concordance index: training cohort-0.825 vs. 0.603 vs. 0.756 and external validation-0.834 vs. 0.606 vs. 0.789). Importantly, the response clusters exhibited an excellent capability in selecting candidates who can benefit from adjuvant chemotherapy. In conclusion, risk stratification based on the dynamic assessment of both radiological and biological responses can significantly enhance prognostic insights and shed light on individualized treatment modifications in LA-NPCs.

Examining the spatial distribution of tumor-infiltrating immune cells in patients with stage I to IIIA LUAD

This study aimed to examine the spatial distribution of immune cells by application of Gcross function in 170 patients with stage I to IIIA lung adenocarcinoma (LUAD) and explore its prognostic value. A total of 170 stage I to IIIA LUAD patients who underwent radical surgery were enrolled. Paraffinized tumor sections were collected for 2 panels of multicolor immunofluorescence staining (panel 1: CD4, CD8, FOXP3, CD69, CD39, CD73, and DAPI; panel 2: CD68, CD163, CD20, CD11c, PDL1, IDO, and DAPI). The immune cells were categorized as CD8+, CD4+ T helper cell (CD4Th), regulatory T cell, macrophage type 1 (M1), M2, dendritic cell (DC), and B cell. The immune cell numbers were enumerated, and the immune cell proximity score was calculated employing the Gcross function. The correlation between immune cell variables and disease-free survival (DFS) was explored through univariate Cox regression analyses. Factors with P < 0.05 were subjected to multivariate analyses. According to univariate Cox regression analyses, total PDL1+ and PDL1+ DC counts were negative factors (P = 0.003 and 0.031, respectively). CD4Th and IDO-DC counts were positive factors (P = 0.022 and 0.024, respectively). The proximity score (M1 to M2) was a positive factor for DFS (P = 0.032), and the proximity score (PDL1 + DC to M1) was a negative factor (P = 0.009) according to univariate Cox analyses. In multivariate analyses, stage (IIIA vs I + II) (hazard ratio [HR]: 1.77 [95% confidence interval (CI): 1.18-2.64], P = 0.006) and proximity score (PDL1 + DC to M1) (HR: 1.60 [95% CI: 1.07-2.37], P = 0.021) were independent negative factors and CD4Th counts (HR: 0.60 [95% CI: 0.40-0.90], P = 0.013) was an independent positive factor. Our study indicated that a higher level of tumor-infiltrating CD4Th cells predicted longer DFS, and a closer proximity of PDL1+ DCs to M1 cells was associated with dismal DFS in stage I to IIIA LUAD patients.

Computational methods and biomarker discovery strategies for spatial proteomics: a review in immuno-oncology

Advancements in imaging technologies have revolutionized our ability to deeply profile pathological tissue architectures, generating large volumes of imaging data with unparalleled spatial resolution. This type of data collection, namely, spatial proteomics, offers invaluable insights into various human diseases. Simultaneously, computational algorithms have evolved to manage the increasing dimensionality of spatial proteomics inherent in this progress. Numerous imaging-based computational frameworks, such as computational pathology, have been proposed for research and clinical applications. However, the development of these fields demands diverse domain expertise, creating barriers to their integration and further application. This review seeks to bridge this divide by presenting a comprehensive guideline. We consolidate prevailing computational methods and outline a roadmap from image processing to data-driven, statistics-informed biomarker discovery. Additionally, we explore future perspectives as the field moves toward interfacing with other quantitative domains, holding significant promise for precision care in immuno-oncology.

Spatial distance between tumor and lymphocyte can predict the survival of patients with resectable lung adenocarcinoma

Background and objective

Spatial interaction between tumor-infiltrating lymphocytes (TILs) and tumor cells is valuable in predicting the effectiveness of immune response and prognosis amongst patients with lung adenocarcinoma (LUAD). Recent evidence suggests that the spatial distance between tumor cells and lymphocytes also influences the immune responses, but the distance analysis based on Hematoxylin and Eosin (H&E) -stained whole-slide images (WSIs) remains insufficient. To address this issue, we aim to explore the relationship between distance and prognosis prediction of patients with LUAD in this study.

Methods

We recruited patients with resectable LUAD from three independent cohorts in this multi-center study. We proposed a simple but effective deep learning-driven workflow to automatically segment different cell types in the tumor region using the HoVer-Net model, and quantified the spatial distance (DIST) between tumor cells and lymphocytes based on H&E-stained WSIs. The association of DIST with disease-free survival (DFS) was explored in the discovery set (D1, n = 276) and the two validation sets (V1, n = 139; V2, n = 115).

Results

In multivariable analysis, the low DIST group was associated with significantly better DFS in the discovery set (D1, HR, 0.61; 95 % CI, 0.40-0.94; p = 0.027) and the two validation sets (V1, HR, 0.54; 95 % CI, 0.32-0.91; p = 0.022; V2, HR, 0.44; 95 % CI, 0.24-0.81; p = 0.009). By integrating the DIST with clinicopathological factors, the integrated model (full model) had better discrimination for DFS in the discovery set (C-index, D1, 0.745 vs. 0.723) and the two validation sets (V1, 0.621 vs. 0.596; V2, 0.671 vs. 0.650). Furthermore, the computerized DIST was associated with immune phenotypes such as immune-desert and inflamed phenotypes.

Conclusions

The integration of DIST with clinicopathological factors could improve the stratification performance of patients with resectable LUAD, was beneficial for the prognosis prediction of LUAD patients, and was also expected to assist physicians in individualized treatment.

Regulatory T cell-mediated immunosuppression orchestrated by cancer: towards an immuno-genomic paradigm for precision medicine

Accumulating evidence indicates that aberrant signalling stemming from genetic abnormalities in cancer cells has a fundamental role in their evasion of antitumour immunity. Immune escape mechanisms include enhanced expression of immunosuppressive molecules, such as immune-checkpoint proteins, and the accumulation of immunosuppressive cells, including regulatory T (Treg) cells, in the tumour microenvironment. Therefore, Treg cells are key targets for cancer immunotherapy. Given that therapies targeting molecules predominantly expressed by Treg cells, such as CD25 or GITR, have thus far had limited antitumour efficacy, elucidating how certain characteristics of cancer, particularly genetic abnormalities, influence Treg cells is necessary to develop novel immunotherapeutic strategies. Hence, Treg cell-targeted strategies based on the particular characteristics of cancer in each patient, such as the combination of immune-checkpoint inhibitors with molecularly targeted agents that disrupt the immunosuppressive networks mediating Treg cell recruitment and/or activation, could become a new paradigm of cancer therapy. In this Review, we discuss new insights on the mechanisms by which cancers generate immunosuppressive networks that attenuate antitumour immunity and how these networks confer resistance to cancer immunotherapy, with a focus on Treg cells. These insights lead us to propose the concept of 'immuno-genomic precision medicine' based on specific characteristics of cancer, especially genetic profiles, that correlate with particular mechanisms of tumour immune escape and might, therefore, inform the optimal choice of immunotherapy for individual patients.

Spatiotemporal architecture of immune cells and cancer-associated fibroblasts in high-grade serous ovarian carcinoma

High-grade serous ovarian carcinoma (HGSOC), the deadliest form of ovarian cancer, is typically diagnosed after it has metastasized and often relapses after standard-of-care platinum-based chemotherapy, likely due to advanced tumor stage, heterogeneity, and immune evasion and tumor-promoting signaling from the tumor microenvironment. To understand how spatial heterogeneity contributes to HGSOC progression and early relapse, we profiled an HGSOC tissue microarray of patient-matched longitudinal samples from 42 patients. We found spatial patterns associated with early relapse, including changes in T cell localization, malformed tertiary lymphoid structure (TLS)-like aggregates, and increased podoplanin-positive cancer-associated fibroblasts (CAFs). Using spatial features to compartmentalize the tissue, we found that plasma cells distribute in two different compartments associated with TLS-like aggregates and CAFs, and these distinct microenvironments may account for the conflicting reports about the role of plasma cells in HGSOC prognosis.

The impact of Foxp3+ regulatory T-cells on CD8+ T-cell dysfunction in tumour microenvironments and responses to immune checkpoint inhibitors

Immune checkpoint inhibitors (ICIs) have been a breakthrough in cancer therapy, inducing durable remissions in responding patients. However, they are associated with variable outcomes, spanning from disease hyperprogression to complete responses with the onset of immune-related adverse events. The consequences of checkpoint inhibition on Foxp3+ regulatory T (Treg ) cells remain unclear but could provide key insights into these variable outcomes. In this review, we first cover the mechanisms that underlie the development of hot and cold tumour microenvironments, which determine the efficacy of immunotherapy. We then outline how differences in tumour-intrinsic immunogenicity, T-cell trafficking, local metabolic environments and inhibitory checkpoint signalling differentially impair CD8+ T-cell function in tumour microenvironments, all the while promoting Treg -cell suppressive activity. Finally, we focus on the mechanisms that enable the induction of polyfunctional CD8+ T-cells upon checkpoint blockade and discuss the role of ICI-induced Treg -cell reactivation in acquired resistance to treatment.

Development and validation of neutrophil extracellular traps-derived signature to predict the prognosis for osteosarcoma patients

Neutrophil extracellular traps (NETs) have been reported to be crucial in tumorigenesis and malignant progression. However, their prognostic significance, association with tumor immune microenvironment (TIME), and therapeutic response in osteosarcoma (OS) stills remain unclear. Hence, TARGET and GSE21257 cohorts were included for analysis. Single-sample gene set enrichment analysis (ssGSEA) and weighted gene co-expression network analysis (WGCNA) were conducted to extract NETs-derived genes. Subsequently, the NETs score (NETScore) model, consisting of 4 signature genes, was established and validated with the least absolute shrinkage and selection operator (LASSO) and Cox regression analysis. Our results indicated that NETScore has satisfactory predictability of the patient's overall survival, with AUC values at 1-, 3- and 5-year in the training cohort of 0.798, 0.792 and 0.804, respectively; similar prominent prediction performance was obtained in three validation cohorts. Further, real-time quantitative PCR (RT-qPCR) assay was conducted to determine the expression of signature genes in human osteoblasts and OS cells. Besides, NETScore and clinical factors (age, gender, metastatic status) were integrated to construct a nomogram. C-index and AUC values at 1-, 3-, and 5-year were above 0.800, displaying robust predictive performance. Patients with high and low NETScore had different immune statuses and drug sensitivity. Meanwhile, several positive regulatory immune function pathways, including T cell proliferation, activation and migration, were significantly suppressed among patients with high NETScore. Summarily, we established a novel NETScore that can accurately predict OS patients' prognosis, which correlated closely with the immune landscape and therapeutic response and might help to guide clinical decision-making.

Neoadjuvant chemotherapy is linked to an amended anti-tumorigenic microenvironment in gastric cancer

BACKGROUND

Neoadjuvant chemotherapy (NAC) is a frequently intervention for patients with locally advanced gastric cancer (GC). Nevertheless, its impact on the tumor immune microenvironment remains unclear.

METHODS

We used immunohistochemistry to identify T-cell subpopulations, tumor-associated neutrophils (TANs), and tumor-associated macrophages (TAMs) in the GC microenvironment (GCME) among paired samples (pre-chemotherapy and post-chemotherapy) from 48 NAC-treated patients. Multiplex immunofluorescence (mIF) was performed to assess immune biomarkers, including CK, CD4, CD8, FOXP3, PD1, PD-L1, CD163, CD86, myeloperoxidase and Arginase-1 in paired samples from 6 GC patients whose response to NAC were rigorously defined.

RESULTS

NAC was intricately linked to enhanced CD8+:CD4+ ratio, reduced CD163+ M2-like macrophages, augmented CD86+ M1: CD163+ M2-like macrophage ratio, and diminished FOXP3+ regulatory T cells (T-regs) and TANs density. Based on mIF, PD1+CD8+T-cells, FOXP3+T-regs, PD-L1+ TANs, and CD163+ M2-like macrophages exhibited marked reduction and greater co-localization with tumor cells following NAC. The pre-NAC FOXP3+ T-regs and CD163+ M2-like macrophages content was substantially elevated in the response cohort, whereas, the post-NAC CD8+:CD4+ and CD86+ M1: CD163+ M2-like macrophage ratios were intricately linked to the tumor pathologic response. We observed greater CD163+ M2-like macrophages and tumor cells co-localization following NAC, which was correlated with tumor pathologic response. Lastly, multivariate analysis revealed that post-NAC CD8+:CD4+ and CD86+ M1: CD163+ M2-like macrophage ratios were stand-alone indicators of positive patient prognosis.

CONCLUSIONS

NAC converts the GCME to an anti-tumorigenic state that is conducive to enhanced patient outcome. These finding can significantly benefit the future planning of highly efficacious and personalized GC immunotherapy.

The molecular mechanism of actions and clinical utilities of tumor infiltrating lymphocytes in gastrointestinal cancers: a comprehensive review and future prospects toward personalized medicine

Gastrointestinal (GI) cancers remain a significant global health burden, accounting for a substantial number of cases and deaths. Regrettably, the inadequacy of dependable biomarkers hinders the precise forecasting of patient prognosis and the selection of appropriate therapeutic sequencing for individuals with GI cancers, leading to suboptimal outcomes for numerous patients. The intricate interplay between tumor-infiltrating lymphocytes (TILs) and the tumor immune microenvironment (TIME) has been shown to be a pivotal determinant of response to anti-cancer therapy and consequential clinical outcomes across a multitude of cancer types. Therefore, the assessment of TILs has garnered global interest as a promising prognostic biomarker in oncology, with the potential to improve clinical decision-making substantially. Moreover, recent discoveries in immunotherapy have progressively changed the landscape of cancer treatment and significantly prolonged the survival of patients with advanced cancers. Nonetheless, the response rate remains constrained within solid tumor sufferers, even when TIL landscapes appear comparable, which calls for the development of our understanding of cellular and molecular cross-talk between TIME and tumor. Hence, this comprehensive review encapsulates the extant literature elucidating the TILs' underlying molecular pathogenesis, prognostic significance, and their relevance in the realm of immunotherapy for patients afflicted by GI tract cancers. Within this review, we demonstrate that the type, density, and spatial distribution of distinct TIL subpopulations carries pivotal implications for the prediction of anti-cancer treatment responses and patient survival. Furthermore, this review underscores the indispensable role of TILs in modulating therapeutic responses within distinct molecular subtypes, such as those characterized by microsatellite stability or programmed cell death ligand-1 expression in GI tract cancers. The review concludes by outlining future directions in TIL-based personalized medicine, including integrating TIL-based approaches into existing treatment regimens and developing novel therapeutic strategies that exploit the unique properties of TILs and their potential as a promising avenue for personalized cancer treatment.

Multi-omics analysis reveals the association between elevated KIF18B expression and unfavorable prognosis, immune evasion, and regulatory T cell activation in nasopharyngeal carcinoma

Background

Nasopharyngeal carcinoma (NPC) is prevalent in Southern China. The expression profile and functions of kinesin family member 18B (KIF18B) remain unclear in NPC.

Methods

Bulk and single-cell transcriptome data for NPC were downloaded. KIF18B expression differences in NPC and normal tissues and its prognostic value were validated by immunohistochemistry and Cox model. We performed multi-faceted functional enrichment analysis on KIF18B. Immune infiltration was analyzed comprehensively by the CIBERSORT, EPIC, and quanTIseq algorithms and the BisqueRNA package and confirmed by immunofluorescence assay. The intercellular communication were investigated by the CellChat package. We explored the dynamics of KIF18B expression by pseudotime trajectory. M6A modification analysis rely on SRAMP platform. The treatment response were evaluated by Tumor Immune Dysfunction and Exclusion (TIDE) score, immunophenoscore and IC50 value.

Results

KIF18B overexpression in NPC led to unfavorable prognosis, and significantly associated with advanced T, N, and stage classifications. Functional analysis demonstrated that KIF18B was involved in immune suppression, epithelial-mesenchymal transition (EMT), N6-methyladenosine (m6A) modification and therapeutic responses. The deconvolution algorithm indicated that activated regulatory T cells (Tregs) had the strongest positive correlation with KIF18B among immune cells (R = 0.631). Validated by immunofluorescence assay, the high KIF18B expression group displayed a notable rise in Tregs infiltration, accompanied by a substantial decrease in the infiltration of CD8+ T cells and macrophages. In the intercellular communication network, malignant cells with high KIF18B expression implicated in more interactions, and activated and recruited Tregs by modulating cytokines, chemokines, and immune checkpoints. KIF18B was upregulated in more advanced malignant cells and influenced EMT by regulating ITGA6, VIM, and ZEB1/2. KIF18B expression was positively related to m6A "writer" and "reader" genes, and negatively related to "eraser" genes. The KIF18B high expression group exhibited a higher TIDE score and elevated IC50 values for the commonly used chemotherapy drugs, gemcitabine, oxaliplatin, and 5-fluorouracil.

Conclusion

KIF18B is a significant prognostic marker in NPC, and may modulate immune evasion and EMT. M6A modification may account for the aberrant overexpression of KIF18B in NPC. Furthermore, KIF18B may predict response to immunotherapy and chemotherapy.