Spatial predictors of immunotherapy response in triple-negative breast cancer

The XCL1-XCR1 axis supports intestinal tissue residency and antitumor immunity

Tissue-resident memory T cells (TRM) provide frontline protection against pathogens and emerging malignancies. Tumor-infiltrating lymphocytes (TIL) with TRM features are associated with improved clinical outcomes. However, the cellular interactions that program TRM differentiation and function are not well understood. Using murine genetic models and targeted spatial transcriptomics, we found that the CD8+ T cell-derived chemokine XCL1 is critical for TRM formation and conventional DC1 (cDC1) supported the positioning of intestinal CD8+ T cells during acute viral infection. In tumors, enforced Xcl1 expression by antigen-specific CD8+ T cells promoted intratumoral cDC1 accumulation and T cell persistence, leading to improved overall survival. Notably, analysis of human TIL and TRM revealed conserved expression of XCL1 and XCL2. Thus, we have shown that the XCL1-XCR1 axis plays a non-cell autonomous role in guiding intestinal CD8+ TRM spatial differentiation and tumor control.

A smart responsive NIR-operated chitosan-based nanoswitch to induce cascade immunogenic tumor ferroptosis via cytokine storm

In this work we present a near-infrared (NIR)-operated nanoswitch based on chitosan nanoparticles (EpCAM-CS-co-PNVCL@IR780/IMQ NPs) that induces cascade immunogenic tumor ferroptosis via cytokine storm. The formulation was prepared by loading a photosensitiser (IR780) and an immunotherapeutic drug (imiquimod; IMQ) into temperature- and pH-responsive chitosan-based NPs functionalized with tumor-targeting aptamers. The EpCAM aptamer can chaperone the NPs selectively into cancer cells, and allow them to enter the cell nucleus. In vitro and in vivo assays revelaed that the NPs were able to effectively induce the immunogenic ferroptosis of cancer cells. Under NIR irradiation, EpCAM-CS-co-PNVCL@IR780/IMQ cause cell death in tumors via photothermal therapy. Moreover, IMQ promotes the maturation of dendritic cells (DCs), which then activate cytotoxic T-lymphocytes (CTLs); these T-cells go on to provide immunotherapy of metastatic tumor cells. The metastatic tumor cells can be induced to undergo ferroptosis by the addition of arachidonic acid (AA), which interacts with interferon cytokines (IFN-γ) released from CTLs.

Profiling immune cell tissue niches in the spatial -omics era

Immune responses require complex, spatially coordinated interactions between immune cells and their tissue environment. For decades, we have imaged tissue sections to visualize a limited number of immune-related macromolecules in situ, functioning as surrogates for cell types or processes of interest. However, this inevitably provides a limited snapshot of the tissue's immune landscape. Recent developments in high-throughput spatial -omics technologies, particularly spatial transcriptomics, and its application to human samples has facilitated a more comprehensive understanding of tissue immunity by mapping fine-grained immune cell states to their precise tissue location while providing contextual information about their immediate cellular and tissue environment. These data provide opportunities to investigate mechanisms underlying the spatial distribution of immune cells and its functional implications, including the identification of immune niches, although the criteria used to define this term have been inconsistent. Here, we review recent technological and analytic advances in multiparameter spatial profiling, focusing on how these methods have generated new insights in translational immunology. We propose a 3-step framework for the definition and characterization of immune niches, which is powerfully facilitated by new spatial profiling methodologies. Finally, we summarize current approaches to analyze adaptive immune repertoires and lymphocyte clonal expansion in a spatially resolved manner.

Tumor cell-derived EMP1 is essential for cancer-associated fibroblast infiltration in tumor microenvironment of triple-negative breast cancer

The role of epithelial membrane protein 1 (EMP1) in tumor microenvironment (TME) remodeling has not yet been elucidated. In addition, the biological function of EMP1 in triple-negative breast cancer (TNBC) is largely unclear. In this study, we examined the infiltration landscape of cell types in the TME of breast cancer, and found that EMP1 expression was positively correlated with stromal and microenvironmental scores. Infiltration analysis and immunohistochemical (IHC) staining of serial sections confirmed the critical role of EMP1 in cancer-associated fibroblast (CAF) infiltration. Cell co-culture assays, xenograft tumor experiments, loss-of-function, gain-of-function, RNA sequencing studies, and rescue assays were performed to confirm the role of EMP1 in CAF infiltration in vitro and in vivo. These findings revealed that EMP1 depletion in TNBC cells resulted in considerable inhibition of CAF infiltration in vivo and in vitro. Mechanistically, EMP1 knockdown induced a substantial decrease in IL6 secretion from TNBC through the NF-κB signaling pathway, hindering CAF proliferation and subsequently inhibiting TNBC progression and metastasis. These cumulative results indicate that EMP1 functions as an oncogene in TNBC by mediating the cell communication of TNBC and CAFs. Targeted inhibition of EMP1 by suppressing CAF infiltration is a promising strategy for TNBC treatment.

Decomposable STING nanoagonist-amplified oncolytic virotherapy through remodeling the immunosuppressive microenvironment of triple-negative breast cancer

Oncolytic viruses (OVs) are promising for cancer treatment as they specifically replicate in tumor cells. However, the systemic delivery of OVs still faces the challenges of poor tumor targeting, short circulation periods, and limited lytic efficacy. Herein, an OV-concealed targeting nanoagonist (OV-MnO2/HE) was prepared to enhance the delivery of OVs to triple-negative breast cancer (TNBC) via intravenous administration. Decomposable MnO2 biomineral shells covered the surface antigens of OVs to prevent their clearance after systemic administration. The targeting materials of HA-EGCG (HE) enhanced intratumoral accumulation via active targeting. After entering tumors, OV-MnO2/HE readily released Mn2+ and OVs, which could enhance the number of CD4+/CD8+ T cells and maturation dendritic cells (DCs) due to the synergetic effect of the STING pathway and OVs, thereby activating the immune response, resulting in the significant inhibition of TNBC growth. This work highlights the potential of the STING agonist in enhancing the antitumor efficacy of OVs and provides a potent platform for TNBC therapy.

A tumor cornification and immune-infiltration-based scheme for anti-PD-1 plus chemotherapy response in advanced squamous cell lung carcinoma

BACKGROUND

Anti-PD-1 immunotherapy plus chemotherapy (combo) exhibits significantly prolonged survival for squamous cell lung cancer (LUSC). An exploration of predictive biomarkers is still needed.

METHODS

High-throughput RNA sequencing (RNA-seq) of 349 LUSC samples from the randomized, multi-center, phase 3 trial ORIENT-12 (ClinicalTrials.gov: NCT03629925) was conducted for biomarker discovery, followed by flow cytometry and multiplex immunohistochemistry (mIHC) in additional clinical cohorts, and in vitro experiments were performed for verification.

RESULTS

A high abundance of activated CD8+ T and CD56bright natural killer (NK) cells benefited patients' outcomes (progression-free survival [PFS]; overall survival [OS]) with combo treatment. Tumor cornification level remarkably affected the infiltration of the two crucial immune cells. Thus, a novel scheme of LUSC immune infiltration and cornification characterization-based classification (LICC) was established for combo efficacy prediction. Patients who received combo treatment achieved significant PFS improvements in LICC1 (hazard ratio [HR] = 0.43, 95% confidence interval [CI]: 0.25-0.75, p = 0.0029) and LICC2 (HR = 0.32, 95% CI: 0.17-0.58, p = 0.0002) subtypes but not in the LICC3 subtype (HR = 0.86, 95% CI: 0.60-1.23, p = 0.4053). Via single-cell RNA-seq analysis, the tumor cornification signal was mainly mapped to SPRR3+ tumor cells, whose relationships with activated CD8+ T or CD56bright NK cells were verified using flow cytometry and mIHC. Our data suggest that SPRR3+ tumor cells might evade immune surveillance via the CD24-SIGLEC10 (M2 macrophage) axis to maintain a suppressive tumor microenvironment.

CONCLUSIONS

Tumor cornification greatly impacts immune infiltration, and the LICC scheme may guide clinical medication of anti-PD-1+chemo treatment in patients with LUSC.

FUNDING

The study was funded by the National Key R&D Program of China, the National Natural Science Foundation of China, Shanghia Multidisplinary Cooperation Building Project for Diagnosis and Treatment of Major Disease, and Innovent Biologics, Inc.

Spatially distinct cellular and molecular landscapes define prognosis in triple negative breast cancer

Background-

Triple-negative breast cancer is a prevalent breast cancer subtype with the lowest 5-year survival. Several factors contribute to its treatment response, but the inherent molecular and cellular tumor heterogeneity are increasingly acknowledged as crucial determinants.

Methods-

Spatial transcriptomic profiling was performed on FFPE tissues from a retrospective, treatment-naive group of women with differential prognoses (17 with >15 years survival- good prognosis (GPx) and 15 with <3 years survival-poor prognosis (PPx)) using GeoMX® Digital Spatial Profiler. Regions of interest were segmented on pan-cytokeratin and analyzed for tumor and stromal components, probed using GeoMx human whole transcriptome atlas (WTA) panel. Data quality control, normalization, and differential analysis was performed in R using GeomxTools and linear mixed models. Additional analyses including cell-type deconvolution, spatial entropy, functional enrichment, TF-target / ligand-receptor analysis and convolution neural networks were employed to identify significant gene signatures contributing to differential prognosis.

Results-

Here we report on the spatial and molecular heterogeneity underlying differential prognosis. We observe that the state of the epithelia and its microenvironment (TME) are transcriptionally distinct between the two groups. Invasive epithelia in GPx show a significant increase in immune transcripts with the TME exhibiting increased immune cell presence (via IF), while in PPx they are more metabolically and translationally active, with the TME being more mesenchymal/fibrotic. Specifically, pre-cancerous epithelia in PPx display a prescience of aggressiveness as evidenced by increased EMT-signaling. We identify distinct epithelial gene signatures for PPx and GPx, that can, with high accuracy, classify samples at the time of diagnosis and likely inform therapy.

Conclusions-

To the best of our knowledge, this is the first study to leverage spatial transcriptomics for an in-depth delineation of the cellular and molecular underpinnings of differential prognosis in TNBC. Our study highlights the potential of spatial transcriptomics to not only uncover the molecular drivers of differential prognosis in TNBC but also to pave the way for precision diagnostics and tailored therapeutic strategies, transforming the clinical landscape for this aggressive breast cancer subtype.

Single-cell spatial immune profiling for precision immunotherapy in Lynch syndrome

Lynch syndrome (LS) is the most common hereditary colorectal cancer (CRC) predisposition syndrome, characterized by a high mutational burden and microsatellite instability-high (MSI-H) tumors. Immunology of LS-associated CRC (LS-CRC) is unique, with significant implications for treatment. Despite well-established knowledge of LS immunology, immunotherapy dose and treatment response can vary significantly based on local tumor immunity and specific germline pathogenic variant of LS genes. This variability necessitates tailored surveillance strategies and new personalised immunotherapy approaches for LS patients. LS-CRC often benefits from immunotherapy due to the distinct tumor microenvironment (TME) and the variety of tumor infiltrating lymphocytes (TILs). This perspective discusses a novel approach of analysing spatial TILs at a single-cell level using tumor whole slide images (WSIs) that accounts for the distinct TME of LS-CRC. By emphasizing the necessity of personalized medicine in hereditary cancer syndromes, the future research and clinical practices that enhance patient outcomes through precision oncology is inspired.

TNBC-DX genomic test in early-stage triple-negative breast cancer treated with neoadjuvant taxane-based therapy

BACKGROUND

Identification of biomarkers to optimize treatment strategies for early-stage triple-negative breast cancer (TNBC) is crucial. This study presents the development and validation of TNBC-DX, a novel test aimed at predicting both short- and long-term outcomes in early-stage TNBC. The objective of this study was to evaluate the association between TNBC-DX and efficacy outcomes [pathologic complete response (pCR), distant disease-free survival (DDFS) or event-free survival (EFS), and overall survival (OS)] in the validation cohorts.

METHODS

Information from 1259 patients with early-stage TNBC (SCAN-B, CALGB-40603, and BrighTNess) was used to establish the TNBC-DX scores. Independent validation of TNBC-DX was carried out in three studies: (i) WSG-ADAPT-TN; (ii) MMJ-CAR-2014-01; and (iii) NeoPACT, including 527 patients with stage I-III TNBC undergoing neoadjuvant chemotherapy. In WSG-ADAPT-TN, patients were randomized to receive nab-paclitaxel plus gemcitabine or carboplatin. In MMJ-CAR-2014-01, patients received carboplatin plus docetaxel. In NeoPACT, patients received carboplatin plus docetaxel and pembrolizumab.

RESULTS

TNBC-DX test was created incorporating the 10-gene Core Immune Gene module, the 4-gene tumor cell proliferation signature, tumor size, and nodal staging. In the two independent validation cohorts without pembrolizumab, the TNBC-DX pCR score was significantly associated with pCR after adjustment for clinicopathological variables and treatment regimen [odds ratio per 10-unit increment 1.34, 95% confidence interval (CI) 1.20-1.52, P < 0.001]. pCR rates for the TNBC-DX pCR-high, pCR-medium, and pCR-low categories were 56.3%, 53.6%, and 22.5% respectively (odds ratio for pCR-high versus pCR-low 3.48, 95% CI 1.72-7.15, P < 0.001). In addition, the TNBC-DX risk score was significantly associated with DDFS [hazard ratio (HR) high-risk versus low-risk 0.24, 95% CI 0.15-0.41, P < 0.001] and OS (HR 0.19, 95% CI 0.11-0.35, P < 0.001). In the validation cohort with pembrolizumab, the TNBC-DX scores were significantly associated with pCR, EFS, and OS.

CONCLUSIONS

TNBC-DX predicts pCR to neoadjuvant taxane-carboplatin in stage I-III TNBC and helps to forecast the patient's long-term survival in the absence of neoadjuvant anthracycline-cyclophosphamide, and independent of pembrolizumab use.

The characterization of tumor immune microenvironment after neoadjuvant immunotherapy in head and neck squamous cell cancer using multiplex immunohistochemistry

OBJECTIVE

Optimizing clinical decision-making in head and neck squamous cell carcinoma (HNSCC) is challenging due to the ambiguous understanding of the immune cell dynamics and immune checkpoints regulation in the disease after the administration of neoadjuvant immunotherapy (NIT).

METHODS

HNSCC biopsy samples collected before and after the neoadjuvant treatment are classified into the pathologic response (PR) and the non-pathologic response (NPR) groups according to treatment responses and the expression of immune cells and checkpoints was labeled using multiplex immunohistochemistry (m-IHC).

RESULTS

The populations of CD4+ T cells, CD8+ T cells, regulatory T cells (Treg), PD-1, and PD-L1 were particularly higher in the PR group than the NPR group in pre-treatment tissues, with the p-values of log-transformed positive cell density <0.05. Almost all markers showed a lower expression in the PR patients after treatment, resulting lower post/pre-treatment ratios of positive cell densities in the PR patients relative to the NPR patients. Following treatment, TIM3+ T cells and LAG3+ T cells exhibited significantly diminished levels in the PR cohort relative to the NPR cohort, with post/pre-treatment expression ratios showing significant differences (P < 0.05). Tumor infiltration lymphocyte analysis revealed that the PR group exhibited a considerably higher average density of CD8+ T cells infiltrating in the tumor marginal zone.

CONCLUSION

The presence of T cells demonstrated significant predictive capability for responses to neoadjuvant immunotherapy in HNSCC patients. Furthermore, TIM3+ T cells and LAG3+ T cells were found to be remarkably lower in the partial response (PR) cohort than in the non-partial response (NPR) cohort post-treatment. This research contributes critical understanding of the physiological changes occurring in immune cell responses.

Activatable Sulfur Dioxide Nanosonosensitizer Enables Precisely Controllable Sono-Gaseous Checkpoint Trimodal Therapy for Orthotopic Hepatocellular Carcinoma

Immune checkpoint blockade (ICB) is combined with sonodynamic therapy (SDT) to increase response rates and enhance anticancer efficacy. However, the "always on" property of most sonosensitizers in reducing tumor microenvironment (TME) compromises the therapeutic outcome of sonoimmunotherapy and exacerbates adverse side effects. Precisely controllable strategies combining sulfur dioxide (SO2) gas therapy with cancer immunotherapy can address these issues but remain lacking. Herein an "activatable SO2 nanosonosensitizer" for precise sono-gaseous checkpoint trimodal therapy of orthotopic hepatocellular carcinoma (HCC) is reported, whose full activity is initiated by ultrasound (US) irradiation in the reducing TME. This "activatable SO2 nanosonosensitizer," Aza-DNBS nanoparticles (NPs), are established by self-assembling Aza-boron-dipyrromethene based sonosensitizer molecules and 2,4-dinitrobenzenesulfonate (DNBS)-caged SO2 prodrug. The activity of Aza-DNBS NPs is initially silenced, and the sonodynamic, gaseous, and immunosuppressive TME reprogramming activities are precisely awakened under US irradiation. Due to the glutathione-responsiveness of Aza-DNBS NPs, Aza-DNBS NPs can generate large amounts of SO2 for gas therapy-enhanced SDT, which triggers robust immunogenic cell death activation and reprogramming of the immunosuppressive TME, thereby significantly suppressing orthotopic tumor growth and delaying lung metastasis. Thus, this study represents a strategy for designing a generic nanoplatform for precisely combined immunotherapy of orthotopic HCC.

Tumor-infiltrating lymphocytes in HER2-positive breast cancer: potential impact and challenges

INTRODUCTION

In this review, we evaluate the role of stromal tumor-infiltrating lymphocytes (sTILs) as a biomarker in human epidermal growth factor receptor 2 (HER2)-positive breast cancer, exploring the prognostic and predictive potential in various treatment settings.

METHODS

Data from multiple clinical trials in the early and metastatic settings, focusing on TILs' correlation with pathologic complete response (pCR), progression-free survival (PFS), and overall survival across early and metastatic HER2-positive breast cancer were summarized. This review also discusses TILs' assessment methods, interobserver variability, and emerging technologies to assess TILs.

RESULTS

TILs have been identified as a highly reproducible biomarker that predicts pCR in patients receiving neoadjuvant therapy and serves as a prognostic indicator for long-term outcomes in several breast cancer subtypes, including HER2-positive. Studies indicate that higher TIL levels correlate with better recurrence-free survival rates. Despite these findings, there is no consensus on the optimal TIL threshold for clinical decision making, and further research is required on how to incorporate TILs into routine clinical practice.

CONCLUSIONS

TILs represent a promising biomarker in HER2-positive breast cancer, particularly in early disease settings. This assessment could guide treatment de-escalation or intensification, tailoring therapies to individual patient profiles. Due to their prognostic importance, TILs can be added to pathology reports. However, further validation in clinical trials is essential for the widespread adoption of TILs in clinical practice.

Spatial Architecture of Single-Cell and Vasculature in Tumor Microenvironment Predicts Clinical Outcomes in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with limited treatment options, which warrants the identification of novel therapeutic targets. Deciphering nuances in the tumor microenvironment (TME) may unveil insightful links between antitumor immunity and clinical outcomes; however, such connections remain underexplored. Here, we employed a data set derived from imaging mass cytometry of 71 TNBC patient specimens at single-cell resolution and performed in-depth quantifications with a suite of multiscale computational algorithms. The TNBC TME reflected a heterogeneous ecosystem with high spatial and compositional heterogeneity. Spatial analysis identified 10 recurrent cellular neighborhoods-a collection of local TME characteristics with unique cell components. The prevalence of cellular neighborhoods enriched with B cells, fibroblasts, and tumor cells, in conjunction with vascular density and perivasculature immune profiles, could significantly enrich long-term survivors. Furthermore, relative spatial colocalization of SMAhi fibroblasts and tumor cells compared with B cells correlated significantly with favorable clinical outcomes. Using a deep learning model trained on engineered spatial data, we can predict with high accuracy (mean area under the receiver operating characteristic curve of 5-fold cross-validation = 0.71) how a separate cohort of patients in the NeoTRIP clinical trial will respond to treatment based on baseline TME features. These data reinforce that the TME architecture is structured in cellular compositions, spatial organizations, vasculature biology, and molecular profiles and suggest novel imaging-based biomarkers for the treatment development in the context of TNBC.

Distinct cellular mechanisms underlie chemotherapies and PD-L1 blockade combinations in triple-negative breast cancer

Combining immune checkpoint blockade (ICB) with chemotherapy shows promise for treating triple-negative breast cancer (TNBC), though the mechanisms remain incompletely understood. Here, we integrate published and new single-cell RNA sequencing (scRNA-seq) data to investigate the tumor immune microenvironment (TIME) in TNBC patients treated with paclitaxel (PTX), nab-paclitaxel (Nab-PTX), and their combinations with the anti-PD-L1 antibody atezolizumab (ATZ). Compared to ATZ plus PTX, ATZ plus Nab-PTX rewires TCF7+ stem-like effector memory CD8+ T cells (Tsem) and CD4+ T follicular helper (Tfh) cells. Nab-paclitaxel, unlike PTX, also reshapes the myeloid compartment, expanding mast cells and pro-inflammatory macrophages. Our analyses in human TNBC and murine models underscore the crucial role of mast cells in orchestrating anti-tumor immune responses, likely by promoting the recruitment and activation of T and B cells. In vivo experiments demonstrate that activating mast cells alongside PD-L1 blockade attenuates TNBC progression, suggesting mast cells as a promising adjunct for enhancing ICB therapy efficacy.

Temporal and spatial composition of the tumor microenvironment predicts response to immune checkpoint inhibition

Immune checkpoint inhibition (ICI) has fundamentally changed cancer treatment. However, only a minority of patients with metastatic triple negative breast cancer (TNBC) benefit from ICI, and the determinants of response remain largely unknown. To better understand the factors influencing patient outcome, we assembled a longitudinal cohort with tissue from multiple timepoints, including primary tumor, pre-treatment metastatic tumor, and on-treatment metastatic tumor from 117 patients treated with ICI (nivolumab) in the phase II TONIC trial. We used highly multiplexed imaging to quantify the subcellular localization of 37 proteins in each tumor. To extract meaningful information from the imaging data, we developed SpaceCat, a computational pipeline that quantifies features from imaging data such as cell density, cell diversity, spatial structure, and functional marker expression. We applied SpaceCat to 678 images from 294 tumors, generating more than 800 distinct features per tumor. Spatial features were more predictive of patient outcome, including features like the degree of mixing between cancer and immune cells, the diversity of the neighboring immune cells surrounding cancer cells, and the degree of T cell infiltration at the tumor border. Non-spatial features, including the ratio between T cell subsets and cancer cells and PD-L1 levels on myeloid cells, were also associated with patient outcome. Surprisingly, we did not identify robust predictors of response in the primary tumors. In contrast, the metastatic tumors had numerous features which predicted response. Some of these features, such as the cellular diversity at the tumor border, were shared across timepoints, but many of the features, such as T cell infiltration at the tumor border, were predictive of response at only a single timepoint. We trained multivariate models on all of the features in the dataset, finding that we could accurately predict patient outcome from the pre-treatment metastatic tumors, with improved performance using the on-treatment tumors. We validated our findings in matched bulk RNA-seq data, finding the most informative features from the on-treatment samples. Our study highlights the importance of profiling sequential tumor biopsies to understand the evolution of the tumor microenvironment, elucidating the temporal and spatial dynamics underlying patient responses and underscoring the need for further research on the prognostic role of metastatic tissue and its utility in stratifying patients for ICI.

TNIP1 Impacts Prognosis by Modulating the Immune Microenvironment in BRCA

Breast invasive carcinoma (BRCA) affects women worldwide, and despite advancements in diagnosis, prevention, and treatment, outcomes remain suboptimal. TNIP1, a novel target involved in multiple immune signaling pathways, influences tumor development and survival. However, the connection between BRCA and TNIP1 remains unclear. Analysis of data from the TCGA, GEO, Sangerbox, and Ualcan databases revealed that TNIP1 is underexpressed in BRCA tissues. This finding was corroborated by RT-PCR and immunohistochemistry. Furthermore, data from the TCGA and GEPIA2 databases, along with Sangerbox, identified TNIP1 as a marker of poor prognosis in BRCA patients. TNIP1 expression shows significant positive correlations with the BRCA Tumor Microenvironment (TME) StromalScore (R = 0.22), ImmuneScore (R = 0.25), and ESTIMATEScore (R = 0.27). Various algorithms have demonstrated a strong association between TNIP1 expression and BRCA tumor-infiltrating immune cells (TIICs). Further analysis using EPIC, TIMER, MCPCounter, QUANTISEQ, xCell, and other computational tools revealed that elevated TNIP1 expression is significantly associated with increased immune cell scores. TNIP1 expression in BRCA tumor tissues also shows a strong correlation with immune checkpoint markers. Data from the HAP database indicate that TNIP1 expression is predominantly involved in the normal skin microenvironment. Subsequent analysis using the TISCH platform with the BRCA single-cell dataset demonstrated that TNIP1 exhibits higher expression levels in immune cells compared to non-immune cells in BRCA patients. This expression is significantly positively correlated with inflammation (R = 0.25) and differentiation (R = 0.28) within the TME, while showing negative correlations with BRCA stemness (R = - 0.34) and invasion (R = - 0.22). Consequently, TNIP1 is proposed as a potential prognostic marker and therapeutic target for BRCA.

Injectable supramolecular hydrogel co-loading abemaciclib/NLG919 for neoadjuvant immunotherapy of triple-negative breast cancer

The efficacy of cancer immunotherapy relies on a sufficient amount of functional immune cells. Triple-negative breast cancer lacks enough immune cell infiltration, and adjuvant therapy is necessary to prime anti-tumor immunity. However, the improvement in efficacy is unsatisfactory with concern about inducing systemic immunotoxicity. Herein, we create an abemaciclib-loaded supramolecular peptide hydrogel formed by peptide-drug amphiphiles for neoadjuvant immunotherapy of triple-negative breast cancer, where the amphiphile is a conjugate of a β-sheet-forming peptide with 1-cyclohexyl-2-(5H-imidazo[5,1-a]isoindol-5-yl)ethanol (NLG919), an inhibitor of indoleamine 2,3-dioxygenase 1. The hydrogel can be injected into the tumor site and retained for at least one week for the sustained release of both abemaciclib and NLG919. The abemaciclib is able to induce immunogenic cell death of cancer cells and increase interleukin-2 secretion by cytotoxic T lymphocytes. Abemaciclib adversely upregulates indoleamine 2,3-dioxygenase 1, whose kynurenine production activity is inhibited by NLG919. The neoadjuvant immunotherapy reduces tumor recurrence and pulmonary metastasis and prolongs the survival of animals. This hydrogel provides a potential platform for neoadjuvant immunotherapy of triple-negative breast cancer with reduced toxicity compared with free abemaciclib.

Lovastatin-mediated pharmacological inhibition of Formin protein DIAPH1 suppresses tumor immune escape and boosts immunotherapy response

BACKGROUND

The immunosuppressive tumor microenvironment (TME) is a key characteristic of human cancer. Immunotherapy has emerged as a promising treatment strategy to overcome immune escape and has gained widespread use in recent years. In particular, the blockade of PD-1/PD-L1 interaction holds significant importance in oncotherapy. Combining anti-PD-1/PD-L1 with small molecule inhibitors targeting key pathways represents an emerging trend in therapeutic development.

METHODS

To validate our findings biologically, we employed qRT-PCR or Western blotting and immunofluorescence staining techniques to assess the expression levels of DIAPH1 and PD-L1 in cells. Additionally, CCK8 and clone formation assays were utilized to evaluate cell proliferation ability, while flow assays were conducted to detect apoptosis in T cells.

RESULTS

Knockdown of DIAPH1 restored the tumor-killing capacity of T cells, effectively suppressing tumor immune escape. We observed a highly positive correlation between the expression levels of DIAPH1 and 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR), which can be competitively inhibited by lovastatin. Through Sybyl analysis followed by confirmation via micro scale thermophoresis, we identified lovastatin as a potential inhibitor targeting DIAPH1. Lovastatin downregulated DIAPH1 expression both in tumor cell lines and xenograft lung cancer tissues within a mouse lung cancer model. Furthermore, we found that lovastatin degraded DIAPH1 through lysosomal degradation pathway. Treatment with lovastatin was strongly associated with improved response rates and prolonged overall survival among patients with lung adenocarcinoma. Finally, overexpression of DIAPH1 reversed the inhibitory effects mediated by lovastatin on tumor development.

CONCLUSIONS

Lovastatin downregulates PD-L1 expression by targeting DIAPH1 and restores the tumor-killing ability of T cells to block tumor immune escape. Lovastatin may become a potential drug for cancer patients to enhance immunotherapy response in the clinic.

Deciphering normal and cancer stem cell niches by spatial transcriptomics: opportunities and challenges

Cancer stem cells (CSCs) often exhibit stem-like attributes that depend on an intricate stemness-promoting cellular ecosystem within their niche. The interplay between CSCs and their niche has been implicated in tumor heterogeneity and therapeutic resistance. Normal stem cells (NSCs) and CSCs share stemness features and common microenvironmental components, displaying significant phenotypic and functional plasticity. Investigating these properties across diverse organs during normal development and tumorigenesis is of paramount research interest and translational potential. Advancements in next-generation sequencing (NGS), single-cell transcriptomics, and spatial transcriptomics have ushered in a new era in cancer research, providing high-resolution and comprehensive molecular maps of diseased tissues. Various spatial technologies, with their unique ability to measure the location and molecular profile of a cell within tissue, have enabled studies on intratumoral architecture and cellular cross-talk within the specific niches. Moreover, delineation of spatial patterns for niche-specific properties such as hypoxia, glucose deprivation, and other microenvironmental remodeling are revealed through multilevel spatial sequencing. This tremendous progress in technology has also been paired with the advent of computational tools to mitigate technology-specific bottlenecks. Here we discuss how different spatial technologies are used to identify NSCs and CSCs, as well as their associated niches. Additionally, by exploring related public data sets, we review the current challenges in characterizing such niches, which are often hindered by technological limitations, and the computational solutions used to address them.

The analysis of gene co-expression network and immune infiltration revealed biomarkers between triple-negative and non-triple negative breast cancer

Background

Triple-negative breast cancer (TNBC) is a heterogeneous disease with a worse prognosis. Despite ongoing efforts, existing therapeutic approaches show limited success in improving early recurrence and survival outcomes for TNBC patients. Therefore, there is an urgent need to discover novel and targeted therapeutic strategies, particularly those focusing on the immune infiltrate in TNBC, to enhance diagnosis and prognosis for affected individuals.

Methods

The gene co-expression network and gene ontology analyses were used to identify the differential modules and their functions based on the GEO dataset of GSE76275. The Weighted Gene Co-Expression Network Analysis (WGCNA) was used to describe the correlation patterns among genes across multiple samples. Subsequently, we identified key genes in TNBC by assessing genes with an absolute correlation coefficient greater than 0.80 within the eigengene of the enriched module that were significantly associated with breast cancer subtypes. The diagnostic potential of these key genes was evaluated using receiver operating characteristic (ROC) curve analysis with three-fold cross-validation. Furthermore, to gain insights into the prognostic implications of these key genes, we performed relapse-free survival (RFS) analysis using the Kaplan-Meier plotter online tool. CIBERSORT analysis was used to characterize the composition of immune cells within complex tissues based on gene expression data, typically derived from bulk RNA sequencing or microarray datasets. Therefore, we explored the immune microenvironment differences between TNBC and non-TNBC by leveraging the CIBERSORT algorithm. This enabled us to estimate the immune cell compositions in the breast cancer tissue of the two subtypes. Lastly, we identified key transcription factors involved in macrophage infiltration and polarization in breast cancer using transcription factor enrichment analysis integrated with orthogonal omics.

Results

The gene co-expression network and gene ontology analyses revealed 19 modules identified using the dataset GSE76275. Of these, modules 5, 11, and 12 showed significant differences between in breast cancer tissue between TNBC and non-TNBC. Notably, module 11 showed significant enrichment in the WNT signaling pathway, while module 12 demonstrated enrichment in lipid/fatty acid metabolism pathways. Subsequently, we identified SHC4/KCNK5 and ABCC11/ABCA12 as key genes in module 11 and module 12, respectively. These key genes proved to be crucial in accurately distinguishing between TNBC and non-TNBC, as evidenced by the promising average AUC value of 0.963 obtained from the logistic regression model based on their combinations. Furthermore, we found compelling evidence indicating the prognostic significance of three key genes, KCNK5, ABCC11, and ABCA12, in TNBC. Finally, we also identified the immune cell compositions in breast cancer tissue between TNBC and non-TNBC. Our findings revealed a notable increase in M0 and M1 macrophages in TNBC compared to non-TNBC, while M2 macrophages exhibited a significant reduction in TNBC. Particularly intriguing discovery emerged with respect to the transcription factor FOXM1, which demonstrated a significant regulatory role in genes positively correlated with the proportions of M0 and M1 macrophages, while displaying a negative correlation with the proportion of M2 macrophages in breast cancer tissue.

Conclusion

Our research provides new insight into the biomarkers and immune infiltration of TNBC, which could be useful for clinical diagnosis of TNBC.

B cells and tertiary lymphoid structures in tumors: immunity cycle, clinical impact, and therapeutic applications

Tumorigenesis involves a multifaceted and heterogeneous interplay characterized by perturbations in individual immune surveillance. Tumor-infiltrating lymphocytes, as orchestrators of adaptive immune responses, constitute the principal component of tumor immunity. Over the past decade, the functions of tumor-specific T cells have been extensively elucidated, whereas current understanding and research regarding intratumoral B cells remain inadequate and underexplored. The delineation of B cell subsets is contingent upon distinct surface proteins and the specific transcription factors that define these subsets have yet to be fully described. Consequently, there is a pressing need for extensive and comprehensive exploration into tumor-infiltrating B cells and their cancer biology. Notably, B cells and other cellular entities assemble within the tumor milieu to establish tertiary lymphoid structures that facilitate localized immune activation and furnish novel insights for tumor research. It is of great significance to develop therapeutic strategies based on B cells, antibodies, and tertiary lymphoid structures. In this review, we address the role of B cells and tertiary lymphoid structures in tumor microenvironment, with the highlight on their spatiotemporal effect, prognostic value and therapeutic applications in tumor immunity.

Estrogen Signaling in Early-Stage Breast Cancer: Impact on Neoadjuvant Chemotherapy and Immunotherapy

Neoadjuvant chemoimmunotherapy (NACIT) has been shown to improve pathologic complete response (pCR) rates and survival outcomes in stage II-III triple-negative breast cancer (TNBC). Promising pCR rate improvements have also been documented for selected patients with estrogen receptor-positive (ER+) human epidermal growth factor receptor 2-negative (HER2-) breast cancer (BC). However, one size does not fit all and predicting which patients will benefit from NACIT remains challenging. Accurate predictions would be useful to minimize immune-related toxicity, which can be severe, irreversible, and potentially impact fertility and quality of life, and to identify patients in need of alternative treatments. This review aims to capitalize on the existing translational and clinical evidence on predictors of treatment response in patients with early-stage BC treated with neoadjuvant chemotherapy (NACT) and NACIT. It summarizes evidence suggesting that NACT/NACIT effectiveness may correlate with pre-treatment tumor characteristics, including mutational profiles, ER expression and signaling, immune cell presence and spatial organization, specific gene signatures, and the levels of proliferating versus quiescent cancer cells. However, the predominantly qualitative and descriptive nature of many studies highlights the challenges in integrating various potential response determinants into a validated, comprehensive, and multimodal predictive model. The potential of novel multi-modal approaches, such as those based on artificial intelligence, to overcome current challenges remains unclear, as these tools are not free from bias and shortcut learning. Despite these limitations, the rapid evolution of these technologies, coupled with further efforts in basic and translational research, holds promise for improving treatment outcome predictions in early HER2- BC.

Spatial Cancer-Immune Phenotypes Predict Shorter Recurrence-Free Survival in the No Specific Molecular Profile Molecular Subtype of Endometrial Carcinoma

Compartmentation of the immune response into 3 main spatial cancer-immune phenotypes (SCIs) - inflamed, excluded, and desert - has been proposed as the main predictor of response to immune checkpoint inhibitors in solid tumors. The objective of the study was to define and characterize the SCI in a consecutive series of 213 endometrial carcinomas (ECs) by correlating it with molecular subtypes, clinicopathologic features, and prognosis. Immunohistochemistry (IHC) and next-generation sequencing were used to assign surrogate molecular EC subtypes: POLE mutant (POLE), mismatch repair deficient (MMRd), TP53 mutant (p53abn), and no specific molecular profile (NSMP). Immune cell markers (CD20, CD3, CD8, CD68, PD-L1) were assessed by IHC on whole sections and quantified by digital image analysis to define the 3 SCIs. ECs were stratified into 4 molecular subtypes: 17 (8.0%) POLE, 68 (31.9%) MMRd, 42 (19.7%) p53abn, and 86 (40.4%) NSMP. SCI determination showed 105 (49.3%) inflamed, 62 (29.1%) desert, and 46 (25.6%) excluded tumors. The inflamed phenotype was more prevalent in MMRd (64.7%) and POLE (76.5%) subtypes compared with NSMP (45.3%) and p53abn (21.4%). SCI revealed a strong correlation with disease-free survival in NSMP tumors: inflamed 96.2%, desert 83.2%, and excluded 40.5%. The SCI prognostic impact was also maintained in NSMP cases treated with adjuvant therapy resulting in a significant difference in recurrence between the inflamed and excluded phenotypes. To simplify SCI determination, a subset of immune cell markers was selected as appropriate to define the 3 SCI patterns: high intraepithelial CD8 for the inflamed phenotype; CD68, CD20, and PD-L1 to discriminate between desert and excluded tumors. The integration of SCI into molecular classification could be a promising opportunity to improve the prognostic risk stratification of patients and may guide the therapeutic approach, particularly in the NSMP subtype. Thus, the different patterns of immune response are a new prognostic parameter in the NSMP subtype.

Combining methylated RNF180 and SFRP2 plasma biomarkers for noninvasive diagnosis of gastric cancer

INTRODUCTION

Gastric cancer (GC) is a common malignant tumor, and early diagnosis significantly improves patient survival rates. This study aimed to investigate the diagnostic value of ring finger protein 180 (RNF180) and secreted frizzled protein 2 (SFRP2) in GC.

MATERIALS & METHODS

A total of 165 healthy individuals, 34 patients with precancerous gastric lesions, and 104 patients with confirmed GC were divided into training and validation sets; methylated RNF180 and SFRP2 were detected in circulating DNA from blood samples. Six models, including those based on logistic regression, Naive Bayes, K-nearest neighbor algorithm, glmnet, neural network, and random forest (RF) were built and validated. Area under the curve (AUC), sensitivity, specificity, positive predictive value, and negative predictive value were determined.

RESULTS

In the training set, the RF model with RNF180 and SFRP2 (R + S) had an AUC of 0.839 (95 % CI: 0.727-0.951), sensitivity of 60.3 %, and specificity of 85.5 % for diagnosing GC. The RF model with R + S+ Tumor markers had an AUC of 0.849 (95 % CI: 0.717-0.981), sensitivity of 62.8 %, and specificity of 87.1 %. In the validation set, the RF model with R + S had an AUC of 0.844 (95 % CI: 0.774-0.923), sensitivity of 87.8 %, and specificity of 69.2 %. The RF model with R + S + Tumor markers had an AUC of 0.858 (95 % CI: 0.781-0.939), sensitivity of 85.4 %, and specificity of 76.9 %.

CONCLUSION

Our results suggest that RNF180 and SFRP2 could serve as diagnostic biomarkers for GC when using the RF model.

Profiling cell identity and tissue architecture with single-cell and spatial transcriptomics

Single-cell transcriptomics has broadened our understanding of cellular diversity and gene expression dynamics in healthy and diseased tissues. Recently, spatial transcriptomics has emerged as a tool to contextualize single cells in multicellular neighbourhoods and to identify spatially recurrent phenotypes, or ecotypes. These technologies have generated vast datasets with targeted-transcriptome and whole-transcriptome profiles of hundreds to millions of cells. Such data have provided new insights into developmental hierarchies, cellular plasticity and diverse tissue microenvironments, and spurred a burst of innovation in computational methods for single-cell analysis. In this Review, we discuss recent advancements, ongoing challenges and prospects in identifying and characterizing cell states and multicellular neighbourhoods. We discuss recent progress in sample processing, data integration, identification of subtle cell states, trajectory modelling, deconvolution and spatial analysis. Furthermore, we discuss the increasing application of deep learning, including foundation models, in analysing single-cell and spatial transcriptomics data. Finally, we discuss recent applications of these tools in the fields of stem cell biology, immunology, and tumour biology, and the future of single-cell and spatial transcriptomics in biological research and its translation to the clinic.

Sonoactivated Z-Scheme Heterojunction for Enhanced Sonodynamic Mitophagy Inhibition and Triple Negative Breast Cancer Treatment

Sonodynamic therapy (SDT) has emerged as a potent therapeutic modality to generate intratumoral toxic reactive oxygen species (ROS) in combating refractory triple-negative breast cancer (TNBC). However, its therapeutic efficacy is compromised due to pro-survival cancer-cell mitophagy to mitigate mitochondrial oxidative damage. Here, an "all-in-one" tumor-therapeutic strategy that integrates nanosonosensitizer-augmented noninvasive SDT with mitophagy inhibition is reported. This is achieved using a rationally constructed sonoactivated liquid Z-scheme heterojunction that connects sonosensitizer PtCu3 nanocages and mitophagy-blocking sonosensitizer BP nanosheets via an amphipathic organic linker (PEI-PEG5000-C18). The conjugated electron mediator (M, Cp*Rh(phen)Cl) is strategically positioned between the 2 sonosensitizers to facilitate electron transfer. This M-based Z-scheme configuration prolongs the separation of sonoactivated electron-hole pairs, leading to efficient ROS generation upon ultrasound stimulation. Importantly, Cu2+ released from PtCu3 expedites BP degradation by reducing phosphorus vacancy formation energy, improving the overall biodegradability of BP-M-PtCu3 and favoring phosphate ions production. These ions elevate lysosomal pH, inhibiting the hydrolysis of damaged mitochondria within autophagic lysosomes, thus preventing cancer cell self-preservation under oxidative stress and effectively eliminating TNBC. It is believe that the M-based sonoactivated Z-scheme heterojunction will be a promising sonosensitizer structure, and the sonodynamic mitophagy inhibition strategy offers valuable prospects for cancer treatment.

In Situ Detection of Programmed Cell Death Protein 1 and Programmed Death Ligand 1 Interactions as a Functional Predictor for Response to Immune Checkpoint Inhibition in NSCLC

INTRODUCTION

Immune checkpoint inhibitors (ICIs) have transformed lung cancer treatment, yet their effectiveness seem restricted to certain patient subsets. Current clinical stratification on the basis of programmed death ligand 1 (PD-L1) expression offers limited predictive value. Given the mechanism of action, directly detecting spatial programmed cell death protein 1 (PD1)-PD-L1 interactions might yield more precise insights into immune responses and treatment outcomes.

METHODS

We applied a second-generation in situ proximity ligation assay to detect PD1-PD-L1 interactions in diagnostic tissue samples from 16 different cancer types, a tissue microarray with surgically resected early-stage NSCLC, and finally diagnostic biopsies from 140 patients with advanced NSCLC with and without ICI treatment. RNA sequencing analysis was used to identify potential resistance mechanisms.

RESULTS

In the early-stage NSCLC, only approximately half of the cases with detectable PD-L1 and PD1 expression exhibited PD1-PD-L1 interactions, with significantly lower levels in EGFR-mutated tumors. Interaction levels varied across cancer types, aligning with reported ICI response rates. In ICI-treated patients with NSCLC, higher PD1-PD-L1 interactions were linked to complete responses and longer survival, outperforming standard PD-L1 expression assays. Patients who did not respond to ICIs despite high PD1-PD-L1 interactions exhibited additional expression of stromal immune mediators (EOMES, HAVCR1/TIM-1, JAML, FCRL1).

CONCLUSION

Our study proposes a diagnostic shift from static biomarker quantification to assessing active immune pathways, providing more precise ICI treatment. This functional concept applies to tiny lung biopsies and can be extended to further immune checkpoints. Accordingly, our results indicate concerted ICI resistance mechanisms, highlighting the need for combination diagnostics and therapies.

Detecting Clinically Relevant Topological Structures in Multiplexed Spatial Proteomics Imaging Using TopKAT

Novel multiplexed spatial proteomics imaging platforms expose the spatial architecture of cells in the tumor microenvironment (TME). The diverse cell population in the TME, including its spatial context, has been shown to have important clinical implications, correlating with disease prognosis and treatment response. The accelerating implementation of spatial proteomic technologies motivates new statistical models to test if cell-level images associate with patient-level endpoints. Few existing methods can robustly characterize the geometry of the spatial arrangement of cells and also yield both a valid and powerful test for association with patient-level outcomes. We propose a topology-based approach that combines persistent homology with kernel testing to determine if topological structures created by cells predict continuous, binary, or survival clinical endpoints. We term our method TopKAT (Topological Kernel Association Test) and show that it can be more powerful than statistical tests grounded in the spatial point process model, particularly when cells arise along the boundary of a ring. We demonstrate the properties of TopKAT through simulation studies and apply it to two studies of triple negative breast cancer where we show that TopKAT recovers clinically relevant topological structures in the spatial distribution of immune and tumor cells.

Spatially-resolved analyses of muscle invasive bladder cancer microenvironment unveil a distinct fibroblast cluster associated with prognosis

Background

Muscle-invasive bladder cancer (MIBC) is a prevalent cancer characterized by molecular and clinical heterogeneity. Assessing the spatial heterogeneity of the MIBC microenvironment is crucial to understand its clinical significance.

Methods

In this study, we used imaging mass cytometry (IMC) to assess the spatial heterogeneity of MIBC microenvironment across 185 regions of interest in 40 tissue samples. We focused on three primary parameters: tumor (T), leading-edge (L), and nontumor (N). Cell gating was performed using the Cytobank platform. We calculated the Euclidean distances between cells to determine cellular interactions and performed single-cell RNA sequencing (scRNA-seq) to explore the molecular characteristics and mechanisms underlying specific fibroblast (FB) clusters. scRNA-seq combined with spatial transcriptomics (ST) facilitated the identification of ligand-receptor (L-R) pairs that mediate interactions between specific FB clusters and endothelial cells. Machine learning algorithms were used to construct a prognostic gene signature.

Results

The microenvironments in the N, L, and T regions of MIBC exhibited spatial heterogeneity and regional diversity in their components. A distinct FB cluster located in the L region-identified as S3-is strongly associated with poor prognosis. IMC analyses demonstrated a close spatial association between S3 and endothelial cells, with S3-positive tumors exhibiting increased blood vessel density and altered vascular morphology. The expression of vascular endothelial growth factor receptor and active vascular sprouting were significant in S3-positive tumors. scRNA-seq and ST analyses indicated that the genes upregulated in S3 were associated with angiogenesis. NOTCH1-JAG2 signaling pathway was identified as a significant L-R pair specific to S3 and endothelial cell interactions. Further analysis indicated that YAP1 was a potential regulator of S3. Machine learning algorithms and Gene Set Variation Analysis were used to establish an S3-related gene signature that was associated with the poor prognosis of tumors including MIBC, mesothelioma, glioblastoma multiforme, lower-grade glioma, stomach adenocarcinoma, uveal melanoma, kidney renal clear cell carcinoma, kidney renal papillary cell carcinoma, and lung squamous cell carcinoma.

Conclusions

We assessed the spatial landscape of the MIBC microenvironment and revealed a specific FB cluster with prognostic potential. These findings offer novel insights into the spatial heterogeneity of the MIBC microenvironment and highlight its clinical significance.

Chemotherapy induces myeloid-driven spatially confined T cell exhaustion in ovarian cancer

Anti-tumor immunity is crucial for high-grade serous ovarian cancer (HGSC) prognosis, yet its adaptation upon standard chemotherapy remains poorly understood. Here, we conduct spatial and molecular characterization of 117 HGSC samples collected before and after chemotherapy. Our single-cell and spatial analyses reveal increasingly versatile immune cell states forming spatiotemporally dynamic microcommunities. We describe Myelonets, networks of interconnected myeloid cells that contribute to CD8+ T cell exhaustion post-chemotherapy and show that M1/M2 polarization at the tumor-stroma interface is associated with CD8+ T cell exhaustion and exclusion, correlating with poor chemoresponse. Single-cell and spatial transcriptomics reveal prominent myeloid-T cell interactions via NECTIN2-TIGIT induced by chemotherapy. Targeting these interactions using a functional patient-derived immuno-oncology platform demonstrates that high NECTIN2-TIGIT signaling in matched tumors predicts responses to immune checkpoint blockade. Our discovery of clinically relevant myeloid-driven spatial T cell exhaustion unlocks immunotherapeutic strategies to unleash CD8+ T cell-mediated anti-tumor immunity in HGSC.

A High-Throughput Immune-Oncology Screen Identifies Immunostimulatory Properties of Cytotoxic Chemotherapy Agents in TNBC

Background: Triple-negative breast cancers (TNBCs) typically have a greater immune cell infiltrate and are more likely to respond to immune checkpoint inhibition (ICI) than ER+ or HER2+ breast cancers. However, there is a crucial need to optimize combining chemotherapy strategies with ICI to enhance overall survival in TNBC. Methods: Therefore, we developed a high-throughput co-culture screening assay to identify compounds that enhance CD8+ T-cell-mediated tumor cell cytotoxicity. Over 400 FDA-approved compounds or agents under investigation for oncology indications were included in the screening library. Results: Four chemotherapy agents were chosen as priority hits for mechanistic follow-up due to their ability to enhance T-cell-mediated cytotoxicity at multiple doses and multiple time points: paclitaxel, bleomycin sulfate, ispinesib, and etoposide. Lead compounds affected the expression of MHCI, MHCII, and PD-L1 and induced markers of immunogenic cell death (extracellular ATP or HMGB1). Conclusions: Based on the ability to increase tumor cell susceptibility to T-cell-mediated cytotoxicity while minimizing T-cell toxicity, bleomycin was identified as the most promising lead candidate. Overall, the results of these studies provide mechanistic insight into potential new chemotherapy partners to enhance anti-PD-1 efficacy in TNBC patients.

Early Alpha-Fetoprotein Response Predicts Sustained Tumor Response Following Immune Checkpoint Inhibitors Combined with Targeted Therapy in Liver Cancer

Background: Although immune checkpoint inhibitors (ICI) have revolutionized liver cancer treatment, some patients experience early tumor progression after therapy, missing the window for other potential treatments, such as neoadjuvant therapy. Therefore, identifying the predictive factors for early progression is critical for timely therapeutic adjustment and the optimization of patient outcomes. Methods: This retrospective study enrolled patients with liver cancer who received their first ICI combined with targeted therapy at the Fifth Medical Center of the PLA General Hospital between June 2022 and December 2023. Early tumor progression was defined as tumor progression within 6 months of therapy initiation. Multivariate logistic regression analysis was used to identify independent risk factors for early tumor progression, and overall survival (OS) curves were generated using the Kaplan-Meier method. Results: A total of 159 patients were enrolled. Multivariate logistic regression analysis indicated that patients with an early alpha-fetoprotein (AFP) response had a significantly reduced risk of early tumor progression (OR = 0.34, 95% CI: 0.13-0.84, p = 0.019), suggesting that an early AFP response is a protective factor against early progression. The area under curve (AUC) for the predictive model was 0.73 (95% CI: 0.63-0.83, p < 0.001). Stratified survival analysis showed that the median overall survival (mOS) in the early AFP response group was significantly longer than that in the poor response group (17.3 months vs. 6.1 months, HR = 2.11, 95% CI: 1.19-2.74, p = 0.009). Conclusions: Early AFP response is not only an effective biomarker for identifying high-risk patients prone to early tumor progression but is also significantly associated with long-term survival in liver cancer patients treated with ICI combined with targeted therapy. This finding will enable clinicians to make timely therapeutic adjustments and optimize treatment outcomes, thereby improving both progression-free survival and overall survival.

Powerful microscopy technologies decode spatially organized cellular networks that drive response to immunotherapy in humans

In tumors, immune cells organize into networks of different sizes and composition, including complex tertiary lymphoid structures and recently identified networks centered around the chemokines CXCL9/10/11 and CCL19. New commercially available highly multiplexed microscopy using cyclical RNA in situ hybridization and antibody-based approaches have the potential to establish the organization of the immune response in human tissue and serve as a foundation for future immunology research.

Spatial organization and stochastic fluctuations of immune cells impact clinical responsiveness to immunotherapy in melanoma patients

High-dimensional, spatial single-cell technologies, such as CyTOF imaging mass cytometry (IMC), provide detailed information regarding locations of a large variety of cancer and immune cells in microscopic scales in tumor microarray slides obtained from patients prior to immune checkpoint inhibitor (ICI) therapy. An important question is how the initial spatial organization of these cells in the tumor microenvironment (TME) changes with time and regulates tumor growth and eventually outcomes as patients undergo ICI therapy. Utilizing IMC data of melanomas of patients who later underwent ICI therapy, we develop a spatially resolved interacting cell system model that is calibrated against patient response data to address the above question. We find that the tumor fate in these patients is determined by the spatial organization of activated CD8+ T cells, macrophages, and melanoma cells and the interplay between these cells that regulate exhaustion of CD8+ T cells. We find that fencing of tumor cell boundaries by exhausted CD8+ T cells is dynamically generated from the initial conditions that can play a protumor role. Furthermore, we find that specific spatial features such as co-clustering of activated CD8+ T cells and macrophages in the pretreatment samples determine the fate of the tumor progression, despite stochastic fluctuations and changes over the treatment course. Our framework enables the determination of mechanisms of interplay between a key subset of tumor and immune cells in the TME that regulate clinical response to ICIs.

PD-1/PD-L1 immune checkpoint blockade in breast cancer: research insights and sensitization strategies

Immunotherapy targeting programmed cell death-1 (PD-1) and PD-L1 immune checkpoints has reshaped treatment paradigms across several cancers, including breast cancer. Combining PD-1/PD-L1 immune checkpoint blockade (ICB) with chemotherapy has shown promising efficacy in both early and metastatic triple-negative breast cancer, although only a subset of patients experiences durable responses. Identifying responders and optimizing immune drug selection are therefore critical. The effectiveness of PD-1/PD-L1 immunotherapy depends on both tumor-intrinsic factors and the extrinsic cell-cell interactions within the tumor microenvironment (TME). This review systematically summarizes the key findings from clinical trials of ICBs in breast cancer and examines the mechanisms underlying PD-L1 expression regulation. We also highlight recent advances in identifying potential biomarkers for PD-1/PD-L1 therapy and emerging evidence of TME alterations following treatment. Among these, the quantity, immunophenotype, and spatial distribution of tumor-infiltrating lymphocytes stand out as promising biomarkers. Additionally, we explore strategies to enhance the effectiveness of ICBs in breast cancer, aiming to support the development of personalized treatment approaches tailored to the unique characteristics of each patient's tumor.

Spatial transcriptomics reveals substantial heterogeneity in triple-negative breast cancer with potential clinical implications

While triple-negative breast cancer (TNBC) is known to be heterogeneous at the genomic and transcriptomic levels, spatial information on tumor organization and cell composition is still lacking. Here, we investigate TNBC tumor architecture including its microenvironment using spatial transcriptomics on a series of 92 patients. We perform an in-depth characterization of tumor and stroma organization and composition using an integrative approach combining histomorphological and spatial transcriptomics. Furthermore, a detailed molecular characterization of tertiary lymphoid structures leads to identify a gene signature strongly associated to disease outcome and response to immunotherapy in several tumor types beyond TNBC. A stepwise clustering analysis identifies nine TNBC spatial archetypes, further validated in external datasets. Several spatial archetypes are associated with disease outcome and characterized by potentially actionable features. In this work, we provide a comprehensive insight into the complexity of TNBC ecosystem with potential clinical relevance, opening avenues for treatment tailoring including immunotherapy.

Spatial interactions of immune cells as potential predictors to efficacy of toripalimab plus chemotherapy in locally advanced or metastatic pancreatic ductal adenocarcinoma: a phase Ib/II trial

Advanced pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis. Immunotherapy alone offers limited efficacy, but it is still unknown whether its combination with chemotherapy could offer synergistic anti-tumor effects. This phase Ib/II study evaluated the safety and efficacy of combining toripalimab with the gemcitabine plus nab-paclitaxel (GnP) regimen as first-line treatment for locally advanced or metastatic PDAC and explored predictive biomarkers (ChiCTR2000032293). The primary endpoints were safety and overall survival (OS). The secondary outcomes were objective response rate (ORR), disease control rate (DCR), and progression-free survival (PFS). Immune-related biomarkers including programmed death-ligand 1 (PD-L1) expression, genetic status, cytokine levels, and spatial features of the tumor immune microenviroment (TIME) were investigated. Neither serious treatment-related adverse events nor grade 4 immune-related adverse events were reported. Among the 72 patients, the median OS was 8.9 months, 12-month OS rate was 31.9%, with median PFS of 5.6 months, ORR of 33.3%, and DCR of 90.3%. Higher PD-L1 expression, without liver metastases were associated with higher ORR, however these factors could not effectively distinguish responders and non-responders. Importantly, dendritic cells - T helper cells - cytotoxic T lymphocytes (DC-Th-CTL) enriched immune niche and their spatial interactions were dominant predictors of response based on TIME analysis using a cyclic multiplex tissue staining assay, with an area under the curve value of 0.8. Overall, GnP plus toripalimab exhibited good safety and differentiated efficacy in selected population, and the spatial interactions of DC-Th-CTL represent promising predictors to efficacy of immunochemotherapy in locally advanced or metastatic PDAC.

Effects of virus-induced immunogenic cues on oncolytic virotherapy

Oncolytic virotherapy is a promising form of cancer treatment that uses viruses to infect and kill cancer cells. In addition to their direct effects on cancer cells, the viruses stimulate various immune responses partly directed against the tumour. Efforts are made to genetically engineer oncolytic viruses to enhance their immunogenic potential. However, the interplay between tumour growth, viral infection, and immune responses is complex and not fully understood, leading to variable and sometimes counterintuitive therapeutic outcomes. Here, we employ a spatio-temporal model to shed more light on this interplay. We investigate systematically how the properties of virus-induced immunogenic signals (their half-life, rate of spread, and potential to promote T-cell-mediated cytotoxicity) affect the therapeutic outcome. Our simulations reveal that strong immunogenic signals, combined with faster diffusion rates, improve the spread of immune activation, leading to better tumour eradication. However, replicate simulations suggest that the outcome of virotherapy is more stochastic than generally appreciated. Our model shows that virus-induced immune responses can interfere with virotherapy, by targeting virus-infected cancer cells and/or by impeding viral spread. In the presence of immune responses, the mode of virus introduction is important, with systemic viral delivery throughout the tumour yielding the most favourable outcomes. The timing of virus introduction also plays a critical role; depending on the efficacy of the immune response, a later start of virotherapy can be advantageous. Overall, our results emphasise that the rational design of oncolytic viruses requires optimising virus-induced immunogenic signals and strategies that balance viral spread with immune activity for improved therapeutic success.

CD19+CD73+ B cells infiltration indicates poor prognosis and unfavorable responses to immunotherapy in gastric cancer

OBJECTIVES

Cluster of Differentiation 73 (CD73) is expressed on immune cells and plays a significant role in tumor inhibition by suppressing antitumor immunity. The objectives of this study were to explore the expression and functional mechanisms of CD73 on B cells in patients with gastric cancer (GC).

METHODS

The prognostic significance of CD19+CD73+ B cells was evaluated in 390 GC patients through dual immunohistochemistry staining. Flow cytometry was employed to analyze the phenotype of the CD19 subpopulation using fresh tumor and non-tumor tissue samples from 8 GC patients. A bioinformatics analysis of CD19+CD73+ B cells was also performed within the scRNA-seq cohort, and the CD19+ B cell subtype was assessed using multiple immunofluorescence staining.

RESULTS

The infiltration of CD19+CD73+ B cells was observed to be elevated in gastric cancer (GC) tissue compared to normal tissues. A strong correlation was observed between high CD19+CD73+ B cell infiltration, poor overall survival, and diminished responsiveness to neoadjuvant immunotherapy in GC. These cells emerged as a novel subset of regulatory B cells (Bregs) linked to adenosine metabolism and the exhaustion of CD8+ T cells. The CD19+CD73+ B cells also correlated with the production of immunosuppressive cytokines IL-10 and TGFB1. Further analysis indicated an association between CD19+CD73+ B cells and advanced-stage GC.

CONCLUSIONS

The presence of CD19+CD73+ B cells in GC may serve as a prognostic indicator for clinical outcomes and a predictive marker for poor responsiveness to neoadjuvant immunotherapy. The correlation between the presence of CD19+CD73+ B cells and CD8+ T cell exhaustion, along with immunosuppression, highlights the tumor-promoting function of these cells.

The single-cell spatial landscape of stage III colorectal cancers

We conducted a spatial analysis using imaging mass cytometry applied to stage III colorectal adenocarcinomas. This study used multiplexed markers to distinguish individual cells and their spatial organization from 52 colorectal cancers. We determined the landscape features of cellular spatial features in the CRC tumor microenvironment. This spatial single-cell analysis identified 10 unique cell phenotypes in the tumor microenvironment that included stromal and immune cells with a subset which had a proliferative phenotype. These special features included spatial neighborhood interactions between single cells as well as different tissue niches, especially the tumor infiltrating lymphocyte regions. We applied a robust statistical analysis to identify significant correlations of cell features with phenotypes such as microsatellite instability or recurrence. We determined that microsatellite stable (MSS) colorectal cancers had an increased risk of recurrence if they had the following features: 1) a low level of stromal tumor-infiltrating lymphocytes, and 2) low interactions between CD4+ T cells and stromal cells. Our results point to the utility of spatial single-cell interaction analysis in defining novel features of the tumor immune microenvironments and providing useful clinical cell-related spatial biomarkers.

The Immune-Related 27-Gene Signature DetermaIO Predicts Response to Neoadjuvant Atezolizumab plus Chemotherapy in Triple-Negative Breast Cancer

PURPOSE

We assessed the 27-gene RT-qPCR-based DetermaIO assay and the same score calculated from RNA sequencing (RNA-seq) data as predictors of sensitivity to immune checkpoint therapy in the neoTRIPaPDL1 randomized trial that compared neoadjuvant carboplatin/nab-paclitaxel chemotherapy (CT) plus atezolizumab with CT alone in stage II/III triple-negative breast cancer. We also assessed the predictive function of the immuno-oncology (IO) score in expression data of patients treated with pembrolizumab plus paclitaxel (N = 29) or CT alone (N = 56) in the I-SPY2 trial.

EXPERIMENTAL DESIGN

RNA-seq data were obtained from pretreatment core biopsies from 242 (93.8%) of the 258 patients in the per-protocol-population. The DetermaIO RT-qPCR test, performed in the CAP/CLIA-accredited laboratory of Oncocyte Corp., was available for 220 patients (85.3%). A previously established threshold was used to assign DetermaIO-positive versus DetermaIO-negative status. Publicly available microarray data were used from I-SPY2.

RESULTS

IO scores calculated from RNA-seq and RT-qPCR data were highly concordant. In neoTRIPaPDL1, DetermaIO-positive cancers (N = 92, 41.8%) had pathologic complete response (pCR) rates of 69.8% and 46.9% in the CT + atezolizumab and CT arms, respectively. In DetermaIO-negative cases, pCR rates were similar in both arms (44.6% vs. 49.2%; interaction test P = 0.04). PDL1 protein expression and stromal tumor-infiltrating lymphocyte count were not predictive of differential benefit from atezolizumab. In I-SPY2, IO-positive cancers (45.9%) had pCR rates of 85.7% and 16%, with and without immunotherapy, respectively. In IO-negative cancers, pCR rates were 46.7% versus 16.1%.

CONCLUSIONS

DetermaIO identified patients who benefited from neoadjuvant immunotherapy resulting in improved pCR rate, independently of PDL1.

Inhibition of Notch enhances efficacy of immune checkpoint blockade in triple-negative breast cancer

Aberrant Notch, which is a defining feature of triple-negative breast cancer (TNBC) cells, regulates intercellular communication in the tumor immune microenvironment (TIME). This includes tumor-associated macrophage (TAM) recruitment through Notch-dependent cytokine secretion, contributing to an immunosuppressive TIME. Despite the low response rate of TNBC to immune checkpoint blockade (ICB), here, we report that inhibition of Notch-driven cytokine-mediated programs reduces TAMs and induces responsiveness to sequentially delivered ICB. This is characterized by the emergence of GrB+ cytotoxic T lymphocytes (CTLs) in the primary tumor. A more impressive effect of sequential treatment is observed in the lung where TAM depletion and increased CTLs are accompanied by near-complete abolition of metastases. This is due to (i) therapeutic reduction in Notch-dependent, prometastatic circulating factors released by the primary tumor, and (ii) elevated PD ligand 1 (PD-L1) in lung metastases, rendering them profoundly sensitive to ICB. These findings highlight the potential of combination cytokine inhibition and ICB as an immunotherapeutic strategy in TNBC.

Highly Multiplexed Tissue Imaging in Precision Oncology and Translational Cancer Research

Precision oncology tailors treatment strategies to a patient's molecular and health data. Despite the essential clinical value of current diagnostic methods, hematoxylin and eosin morphology, immunohistochemistry, and gene panel sequencing offer an incomplete characterization. In contrast, highly multiplexed tissue imaging allows spatial analysis of dozens of markers at single-cell resolution enabling analysis of complex tumor ecosystems; thereby it has the potential to advance our understanding of cancer biology and supports drug development, biomarker discovery, and patient stratification. We describe available highly multiplexed imaging modalities, discuss their advantages and disadvantages for clinical use, and potential paths to implement these into clinical practice. Significance: This review provides guidance on how high-resolution, multiplexed tissue imaging of patient samples can be integrated into clinical workflows. It systematically compares existing and emerging technologies and outlines potential applications in the field of precision oncology, thereby bridging the ever-evolving landscape of cancer research with practical implementation possibilities of highly multiplexed tissue imaging into routine clinical practice.

Spatial dynamics of CD39+CD8+ exhausted T cell reveal tertiary lymphoid structures-mediated response to PD-1 blockade in esophageal cancer

Despite the success of immune checkpoint blockade (ICB) therapy for esophageal squamous cell cancer, the key immune cell populations that affect ICB efficacy remain unclear. Here, imaging mass cytometry of tumor tissues from ICB-treated patients identifies a distinct cell population of CD39+PD-1+CD8+ T cells, specifically the TCF1+ subset, precursor exhausted T (CD39+ Tpex) cells, which positively correlate with ICB benefit. CD39+ Tpex cells are predominantly in the stroma, while differentiated CD39+ exhausted T cells are abundantly and proximally within the parenchyma. Notably, CD39+ Tpex cells are concentrated within and around tertiary lymphoid structure (TLS). Accordingly, tumors harboring TLSs have more of these cells in tumor areas than tumors lacking TLSs, suggesting Tpex cell recruitment from TLSs to tumors. In addition, circulating CD39+ Tpex cells are also increased in responders following ICB therapy. Our findings show that this unique subpopulation of CD39+PD-1+CD8+ T cells is crucial for ICB benefit, and suggest a key role in TLS-mediated immune responses against tumors.

Spatial oncology: Translating contextual biology to the clinic

Microscopic examination of cells in their tissue context has been the driving force behind diagnostic histopathology over the past two centuries. Recently, the rise of advanced molecular biomarkers identified through single cell profiling has increased our understanding of cellular heterogeneity in cancer but have yet to significantly impact clinical care. Spatial technologies integrating molecular profiling with microenvironmental features are poised to bridge this translational gap by providing critical in situ context for understanding cellular interactions and organization. Here, we review how spatial tools have been used to study tumor ecosystems and their clinical applications. We detail findings in cell-cell interactions, microenvironment composition, and tissue remodeling for immune evasion and therapeutic resistance. Additionally, we highlight the emerging role of multi-omic spatial profiling for characterizing clinically relevant features including perineural invasion, tertiary lymphoid structures, and the tumor-stroma interface. Finally, we explore strategies for clinical integration and their augmentation of therapeutic and diagnostic approaches.

Caspase-1-dependent spatiality in triple-negative breast cancer and response to immunotherapy

Tumor immune microenvironment (TIME) spatial organization predicts outcome and therapy response in triple-negative breast cancer (TNBC). An immunosuppressive TIME containing elevated tumor-associated macrophages (TAM) and scarce CD8+ T cells is associated with poor outcome, but the regulatory mechanisms are poorly understood. Here we show that ETS1-driven caspase-1 expression, required for IL1β processing and TAM recruitment, is negatively regulated by estrogen receptors alpha (ERα) and a defining feature of TNBC. Elevated tumoral caspase-1 is associated with a distinct TIME characterized by increased pro-tumoral TAMs and CD8+ T cell exclusion from tumor nests. Mouse models prove the functional importance of ERα, ETS1, caspase-1 and IL1β in TIME conformation. Caspase-1 inhibition induces an immunoreactive TIME and reverses resistance to immune checkpoint blockade, identifying a therapeutically targetable mechanism that governs TNBC spatial organization.

Spatial effects of infiltrating T cells on neighbouring cancer cells and prognosis in stage III CRC patients

Colorectal cancer (CRC) is one of the most frequently occurring cancers, but prognostic biomarkers identifying patients at risk of recurrence are still lacking. In this study, we aimed to investigate in more detail the spatial relationship between intratumoural T cells, cancer cells, and cancer cell hallmarks as prognostic biomarkers in stage III colorectal cancer patients. We conducted multiplexed imaging of 56 protein markers at single-cell resolution on resected fixed tissue from stage III CRC patients who received adjuvant 5-fluorouracil (5FU)-based chemotherapy. Images underwent segmentation for tumour, stroma, and immune cells, and cancer cell 'state' protein marker expression was quantified at a cellular level. We developed a Python package for estimation of spatial proximity, nearest neighbour analysis focusing on cancer cell-T-cell interactions at single-cell level. In our discovery cohort (Memorial Sloan Kettering samples), we processed 462 core samples (total number of cells: 1,669,228) from 221 adjuvant 5FU-treated stage III patients. The validation cohort (Huntsville Clearview Cancer Center samples) consisted of 272 samples (total number of cells: 853,398) from 98 stage III CRC patients. While there were trends for an association between the percentage of cytotoxic T cells (across the whole cancer core), it did not reach significance (discovery cohort: p = 0.07; validation cohort: p = 0.19). We next utilised our region-based nearest neighbour approach to determine the spatial relationships between cytotoxic T cells, helper T cells, and cancer cell clusters. In both cohorts, we found that shorter distance between cytotoxic T cells, T helper cells, and cancer cells was significantly associated with increased disease-free survival. An unsupervised trained model that clustered patients based on the median distance between immune cells and cancer cells, as well as protein expression profiles, successfully classified patients into low-risk and high-risk groups (discovery cohort: p = 0.01; validation cohort: p = 0.003). © 2024 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Next-generation spatial transcriptomics: unleashing the power to gear up translational oncology

The growing advances in spatial transcriptomics (ST) stand as the new frontier bringing unprecedented influences in the realm of translational oncology. This has triggered systemic experimental design, analytical scope, and depth alongside with thorough bioinformatics approaches being constantly developed in the last few years. However, harnessing the power of spatial biology and streamlining an array of ST tools to achieve designated research goals are fundamental and require real-world experiences. We present a systemic review by updating the technical scope of ST across different principal basis in a timeline manner hinting on the generally adopted ST techniques used within the community. We also review the current progress of bioinformatic tools and propose in a pipelined workflow with a toolbox available for ST data exploration. With particular interests in tumor microenvironment where ST is being broadly utilized, we summarize the up-to-date progress made via ST-based technologies by narrating studies categorized into either mechanistic elucidation or biomarker profiling (translational oncology) across multiple cancer types and their ways of deploying the research through ST. This updated review offers as a guidance with forward-looking viewpoints endorsed by many high-resolution ST tools being utilized to disentangle biological questions that may lead to clinical significance in the future.