FineST: contrastive learning integrates histology and spatial transcriptomics for nuclei-resolved ligand-receptor analysis.

My talk will present three computational frameworks we developed to study cytokine signaling activities and cell-cell communications during the antitumor immune response, using tumor single-cell and spatial transcriptomics. The basic immunology tool to study cytokine signaling mostly measures cytokine release, which is transient and does not represent downstream target activities. Therefore, we first developed the CytoSig platform, providing a database of target genes modulated by cytokines and a predictive model of cytokine signaling cascades from transcriptomic profiles. We collected 20,591 transcriptome profiles for human cytokine, chemokine, and growth factor responses. This atlas of transcriptional patterns induced by cytokines enabled the reliable prediction of signaling activities in distinct cell populations in infectious diseases, chronic inflammation, and cancer using bulk and single-cell transcriptomic data. CytoSig revealed previously unidentified roles of many cytokines, such as BMP6 as an anti-inflammatory factor. Then, based on CytoSig, we developed Tres, a computational model utilizing single-cell transcriptomic data to identify signatures of T cells that are resilient to immunosuppressive signals, such as TGF-β1, TRAIL, and prostaglandin E2. Tres reliably predicts clinical responses to immunotherapy in multiple cancer types using bulk T cell transcriptomic data from pre-treatment patient tumors or infusion/pre-manufacture samples for cellular immunotherapies. Further, Tres identified FIBP as a candidate immunotherapy target to potentiate adoptive cell therapy efficacies. FIBP knockout in T cells enhanced adoptive cell therapy by down-regulating T cells' cholesterol metabolism. Last, I will briefly show our SpaCET framework for deconvolving cell fractions and identifying cell-cell interactions in tumor spatial transcriptomics data. SpaCET resolved several challenges in spatial transcriptomics analysis that previous methods did not address sufficiently. Through coupling cell fractions with ligand-receptor co-expression analysis, SpaCET reveals that intercellular interactions tend to be located at the tumor-immune boundaries. Citation Format: Peng Jiang. Inference of intercellular signaling activities in tumor spatial and single-cell transcriptomics, with applications in identifying cancer immunotherapy targets [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr IA002.

In recent years, spatial transcriptomics (ST) technologies have developed rapidly and have been widely used in constructing spatial tissue atlases and characterizing spatiotemporal heterogeneity of cancers. Currently, ST has been used to profile spatial heterogeneity in multiple cancer types. Besides, ST is a benefit for identifying and comprehensively understanding special spatial areas such as tumor interface and tertiary lymphoid structures (TLSs), which exhibit unique tumor microenvironments (TMEs). Therefore, ST has also shown great potential to improve pathological diagnosis and identify novel prognostic factors in cancer. This review presents recent advances and prospects of applications on cancer research based on ST technologies as well as the challenges.

BackgroundTertiary lymphoid structures (TLS) are lymphoid aggregates that often form locally in tissues with chronic infection, autoimmune disease, and cancer. As such, TLS correlate with favorable prognosis in patients with...

The prognosis for muscle-invasive bladder cancer (MIBC) remains poor, and reliable prognostic markers have yet to be identified. Tertiary lymphoid structures (TLS) have been associated with favorable outcomes in certain cancers. However, the relationship between TLS and MIBC remains unclear. A multi-omics approach is utilized, leveraging single-cell RNA sequencing, spatial transcriptomics, bulk RNA sequencing, and immunohistochemistry, to investigate the roles of B cells and TLS in MIBC. These findings indicate that elevated levels of B cells and TLS correlate with improved prognoses in patients with MIBC, aligning with the robust antitumor immune responses observed in the TLS region. From a mechanistic perspective, CXCL13 serves as a critical cytokine for TLS formation in MIBC, primarily secreted by clonally expanded CXCL13+ T cells. This cytokine interacts with the CXCR5 receptor on NR4A2+ B cells, promoting TLS development. Plasma cells arising within the TLS microenvironment predominantly produce the IGHG antibody, potentially enhancing the phagocytic capabilities of C1QC+ macrophages. From an application standpoint, a TLS-specific gene signature is developed that effectively predicts outcomes in MIBC and other cancers. This study highlights the prognostic potential of TLS in MIBC and reveals immune mechanisms, offering insights for personalized treatment strategies.

Tertiary lymphoid structures (TLS) play an important role in the tumor microenvironment (TME) of Head and Neck Cancer (HNC) and have been linked to improved response to immunotherapy. Moreover, HNC patients with human papillomavirus (HPV)+ tumors have better survival compared to those with HPV- tumors, although both groups have better clinical outcomes when the tumors are TLS-rich. How TLS composition, characteristics, and signatures differ between response to treatment in relation to HPV status is still unclear. To investigate this, whole-tissue samples from 55 HNC patients were collected across two separate sites in Brisbane, Australia (The Princess Alexandra Hospital and The Royal Brisbane and Women’s Hospital) prior to immune checkpoint therapy (ICI). Using a multi-pathway panel, covering the ‘hallmarks of cancer’ and ‘TLS-associated proteins,’ we profiled 53 spatially resolved biomarkers using both a PhenoCycler-Fusion panel and 7-plex PSP panel (Akoya Biosciences). Using spatial proteomics, the TLS were assessed for their composition, activity, maturity, and distance metrics from the tumor. Using spatial transcriptomics, we profiled 96 TLS using whole transcriptome profiling (Bruker Spatial Biology). In addition, in patient samples abundant with TLS, we profiled 50 serial sections to obtain and profile the volumetric 3D data. Our study identified various degrees of TLS maturity, proteomic, and transcriptomic profiles associated with TLS localisation within the TME and proximity to the tumor. In addition, we identified TLS signatures associated with clinical endpoints such as response and resistance to ICI therapy. Taken together, this research highlights the multifaceted role of TLS in modulating the immunogenic landscape of HNC, influencing immunotherapy efficacy, and potentially serving as a biomarker for patient stratification and therapeutic strategies. Citation Format: Meg L. Donovan, Habib Sadeghirad, Naomi Berrell, James Monkman, Vahid Yaghoubi Naei, Chin Wee Tan, Joseph Yunis, Zoe West, Majid E. Warkiani, Rahul Ladwa, Brett G. Hughes, Jessica Da Gama Duarte, Arutha Kulasinghe. 2D and 3D spatial characterisation of tertiary lymphoid structures in head and neck cancer patients receiving immune checkpoint blockade therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5252.

Spatial omics technologies offer unprecedented insights into the cellular organization of tissues; however, they are not yet scalable for routine clinical use. In contrast, images of histological staining remain the foundation of pathological diagnosis despite lacking molecular information. Bridging this gap requires computational methods that can accurately infer spatial molecular data from histology alone. Here, we introduce TissueCraftAI, a generative artificial intelligence framework that predicts multi-modal spatial omics maps directly from standard histology images using natural language prompts. To train and validate our model, we created PRISM-12M, a large-scale dataset comprising over twelve million spatially registered histology and spatial omics image patches across fourteen tissue types from humans and mice. TissueCraftAI significantly outperforms existing methods in generating realistic histology images and predicting spatial proteomics and transcriptomics data with high fidelity. We demonstrated its utility in various downstream applications, including improving cell type annotation and enhancing the accuracy of patient survival predictions across multiple cancer types. By enabling flexible, query-driven in silico spatial molecular analysis using routine histology images, TissueCraftAI opens up new research avenues in computational pathology.

The tertiary lymphoid structure (TLS) is recognized as a potential prognosis factor for breast cancer and is strongly associated with response to immunotherapy. Inducing TLS neogenesis can enhance the immunogenicity of tumors and improve the efficacy of immunotherapy. However, our understanding of TLS associated region at the single-cell level remains limited. Therefore, we employed high-resolution techniques, including single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST), and a TLS-specific signature to investigate TLS associated regions in breast cancer. We identified eighteen cell types within the TLS associated regions and calculated differential expression genes by comparing TLS associated regions with other areas. Notably, macrophages in the TLS associated regions exhibit lineage transformation, shifting from facilitators of immune activation to supporters of tumor cell growth. In terms of cell–cell communication within the TLS associated regions, KRT86+ CD8+ T cells, HISTIH4C+ cycling CD8+ T cells, IFNG+ CD8+ T cells, and IGKV3-20+ B cells demonstrate strong interactions with other cells. Additionally, we found that APOD+ fibroblast and CCL21+ fibroblast primarily recruit T and B cells through the CXCL12-CXCR4 ligand-receptor signaling pathway. We also validate these findings in four independent breast cancer datasets, which include one cell-level resolution dataset from the 10 × Xenium platform and three spot-level datasets from the 10 × Visium platform.

Background: Invasive lobular carcinoma (ILC) is the second most common histological breast cancer subtype; however, little is known about its tumor microenvironment (TME). Here, we aimed to identify and to characterise ILC subgroups based on TME heterogeneity by combining spatial transcriptomics (ST) and single cell RNA-sequencing (scRNA-seq). Methods: We performed ST (Visium 10x Genomics) on frozen tumor samples from 41 primary hormone receptor positive (HR+), HER2-negative (HER2-) ILCs. Information coming from the morphological annotation of ST slides and the gene expression-based clustering of ST spots was integrated and used as input for a patient level classification (using intNMF algorithm). Subgroups of patients were annotated using morphology, gene set enrichment analysis and ST deconvolution based on scRNA-seq data (CARD software). SCAN-B bulk RNA-seq dataset was used as validation set (HR+, HER2- ILC samples, n = 853). Results: Four subgroups of patients were identified: proliferative (P, n = 12, enriched in tumor cells and proliferation-related pathways), normal-stroma enriched (NSE, n = 10, enriched in fibroblasts, stroma-related pathways and showing an higher level of colocalization between invasive and in situ carcinoma), metabolic (M, n = 9, enriched in metabolic related-pathways) and metabolic-immune enriched (MIE, n = 10, enriched in adipocytes, metabolic and immune-related pathways). Deconvolution of ST spots with single cell data revealed matching results with morphology (in terms of cell types). We observed an enrichment of myofibroblasts in NSE, an enrichment of cancer epithelial in P and, interestingly, an enrichment of endothelial cells in M subgroup (fdr < 0.25). MIE was characterized by perivascular like-endothelial cells and myeloid cells (monocytes and macrophages, fdr < 0.25). Of note, at the level of the ST slide, myeloid cells in MIE subgroup were more present in the adipose tissue compartment (fdr < 0.25) compared to the rest of the slide. NSE subgroup showed a trend for association with better prognosis. Gene signature-based assignment identified the same four subgroups in SCAN-B: GSEA analysis and comparisons among the four subgroups showed matching results between our dataset and SCAN-B. Of note, in SCAN-B, we observed differences in prognosis among the subgroups, with NSE showing better, M and MIE intermediate and P worse prognosis for overall survival and relapse free interval (p < 0.01). Conclusions: Four subgroups of ILC based on TME heterogeneity and showing differences in prognosis were identified and validated in external cohort. Of note, two of these groups were related to metabolism, highlighting the value of such process in ILC biology. Importantly, myeloid cells were the predominant immune cell types in ILC, and they showed a specific compartmentalization inside the TME. Further validation is needed. Citation Format: Matteo Serra, Andreas Papagiannis, Mattia Rediti, Frederic Lifrange, Nicola Occelli, Laetitia Collet, Delphine Vincent, Ghizlane Rouas, Danai Fimereli, Ligia Craciun, Denis Larsimont, David Venet, Miikka Vikkula, Francois P. Duhoux, Françoise Rothé, Christos Sotiriou. Integrating spatial and single cell transcriptomics to identify and characterise biologically driven subgroups in invasive lobular carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5066.

Tertiary lymphoid structures (TLSs) associate with prognosis of many malignancies. However, the clinical significance of TLSs is not well-elucidated in nasopharyngeal carcinoma (NPC) patients. In this whole population-based multicenter study, a total of 115 patients treated for NPC were included. The patients were treated at the five Finnish university hospitals. TLSs were assessed in routine hematoxylin and eosin (HE)-stained sections. Presence of TLSs associates significantly with improved survival in NPC. Absence of TLSs had a significant association with a poor disease-specific survival of NPC with a hazard ratio (HR) of 1.96 (95 % CI 1.09-3.53, P = 0.025) in the multivariable analysis. Similarly, absence of TLSs associated with worse overall survival with a HR of 1.68 (95 % CI 1.02-2.75, P = 0.040). TLSs seem to be associated with prognosis of NPC patients. Having TLSs in NPC tumors correlates with good survival. The assessment of TLSs could aid in understanding the clinical behavior and in planning the treatment of NPC.

Simple SummaryImmunotherapies for breast cancer (BC) are among the most promising treatments for mammary gland malignancies, but their tissue and cellular targets are heterogeneous and controversial. Hence, the effectiveness of immunotherapy varies. Tertiary lymphoid structures (TLSs) are paid the most attention among these therapies due to the favorable prognostic function they have been shown to play for several malignancies, but this has less investigated for BC because they are not at all connected to some BC molecular subtypes and the stromal vascular network. Moreover, research on the TLS’s impact on lymphovascular, perineural, and BC recurrence is inconsistent. In the current investigation, significant variations between TLS positive and TLS negative subgroups within the same BC molecular subtype were observed and had a significant impact on BC recurrence, lymphovascular invasion, and perineural invasion. By promoting quick blood vessel maturation followed by lowering lymphovascular or perineural invasion, and recurrence, BC-associated TLSs seem to have a local protective role against tumor spread.Background: Tertiary lymphoid structures (TLSs) mediate local antitumor immunity, and interest in them significantly increased since cancer immunotherapy was implemented. We examined TLS− tumor stromal blood vessel interplay for each breast cancer (BC) molecular subtype related to recurrence, lymphovascular invasion (LVI), and perineural invasion (PnI). Methods: TLSs were quantified on hematoxylin and eosin stain specimens followed by CD34/smooth muscle actin (SMA) double immunostaining for stromal blood vessel maturation assessment. Statistical analysis linked microscopy to recurrence, LVI, and PnI. Results: TLS negative (TLS−) subgroups in each BC molecular subtype (except to Luminal A) have higher LVI, PnI, and recurrence. A significant rise in LVI and PnI were observed for the HER2+/TLS− subgroup (p < 0.001). The triple negative breast cancer (TNBC)/TLS− subgroup had the highest recurrence and invasion risk which was also significantly related to tumor grade. PnI but not LVI significantly influenced recurrence in the TNBC/TLS+ subgroup (p < 0.001). TLS−stromal blood vessel interrelation was different amongst BC molecular subtypes. Conclusion: BC invasion and recurrence are strongly influenced by TLS presence and stromal blood vessels, especially for HER2 and TNBC BC molecular subtypes.

Hepatocellular carcinoma (HCC) is one of the most common types of cancer globally. However, HCC features poor prognosis due to complex pathogenesis and limitations of therapeutic approaches. To improve the prognosis of HCC patients, we analyzed single-cell transcriptome and spatial transcriptome on liver tissues from HCC patients. We applied Non-negative Matrix Factorization (NMF) method on spatial transcriptome and found a critical pathway associated with HCC through GO over-representation analysis. According to the pathway activity score, the cells in single-cell transcriptome were divided into three groups. Then we conducted hdWGCNA and selected HCC-related co-expressed gene modules which showed significant intergroup differences. Integrative machine learning algorithms on bulk transcriptome were employed for core genes selection. We respectively evaluated their AUC values as independent diagnostic markers and retained a core gene. We conducted a survival analysis using this gene. Next, we performed immune infiltration analysis, tumor microenvironmental analysis and drug sensitivity analysis. Finally, pseudotime analysis, differentiation potential analysis and cell-cell communication analysis were applied to decipher the mechanisms underlying tumor initiation and progression. Single-cell transcriptome analysis revealed the high heterogeneity of cells in patients with HCC. The GO over-representation analysis based on NMF indicated that cytoplasmic translation path was enriched in most NMF components. The SSR2 gene passed the integrative machine learning algorithms and possessed excellent diagnosis (AUC > 0.8) and prognostic abilities (K-M curve, P = 0.007). Further analysis identified SSR2 as the top-ranked gene by average expression level in NK cells compared to all other immune cell clusters. Its expression showed a consistent downward trend during NK cell maturation.NK cells with high expression of SSR2 exhibited stronger cell-cell communication than those with low expression of SSR2. NK cells mainly communicated with other cells through MIF-mediated signaling pathway. In hepatocellular carcinoma (HCC), the high expression of the SSR2 gene in NK cells is accompanied by enhanced cytoplasmic translation pathway, which promotes MIF secretion and activates its downstream signaling pathways, thereby driving the disruption of the tumor immune microenvironment and the progression of the disease.

Recent advances in tumor immunology show an important link exists between tumor infiltrating lymphocytes (TIL) and patient outcome. In human breast cancer (BC) more extensive lymphocyte infiltration is associated with a better prognosis and can also predict responses to pre-operative chemotherapy. Tertiary lymphoid structures (TLS) detected at the tumor periphery have been correlated with a good prognosis in lung and colorectal cancer. Our recent work was the first to demonstrate that TLS are present in BC, located adjacent to the tumor bed in extensively infiltrated tumors. TLS organization is similar to a lymph node, with a CD3+ T-cell zone adjacent to a CD20+ B-cell follicle where germinal centers containing CD23+ follicular dendritic cells, Bcl6+ TFH cells and Ki67+ cells are found. Our laboratory recently discovered that TLS-associated CD4+ Tfh cells are present in extensively infiltrated tumors and showed they signal a good prognosis. This important presence of Tfh-containing TLS adjacent to the tumor bed suggests that B-cells may also play a role in generating effective anti-tumor immune responses. We therefore undertook to fully characterize the B-cells infiltrating human BC. Flow cytometric analysis of fresh breast tumor homogenates detected an increase in CD45+ leukocytes in all BC subtypes compared with normal and non-tumor non-adjacent (NANT) breast tissue irrespective of lymphocyte infiltration levels. The infiltrate was dominated by CD3+ T-cells (65-86% of CD45+) in normal and malignant tissues. In contrast, B-cells were elevated in tumors compared to normal and NANT tissue, particularly in extensively infiltrated high proliferative BC subtypes. This increase was paralleled by a relative decrease in CD8+ T-cells. CD45/CD19/CD38/IgD labeling revealed that approximately 50% of the infiltrating B-cells are memory cells in contrast to normal tissues, which contain less than 15%. Centroblasts and centrocytes, which are follicular B cells, were significantly increased in extensively infiltrated tumors in association with Tfh cells. We assessed immunoglobulin isotypes in primary supernatants from breast tissue homogenates, detecting decreased IgA and increased IgG and IgM per mm3 in the tumor. Patient sera, particularly from high proliferative subtypes, had elevated IgG4 compared with low proliferative subtypes and healthy donors. Immunofluorescent analysis of embedded tissues show that TLS contain a marginal zone region(CD20+CD27+IgD-), a follicular mantle zone (CD20+IgD+) and a germinal center zone (CD20+Ki67+CD35+CD21+PD-1+). Tumor-associated TLS are surrounded by T-cells (CD4+ and CD8+). These data reveal that when B-cells are present in breast tumors they are principally associated with organized TLS and may therefore play an important functional role in comprehensive anti-tumor immune responses, an aspect currently under further investigation. Citation Format: Soizic Garaud, Laurence Buisseret, Chunyan Gu, Edoardo Migliori, Jean-Nicolas Lodewyckx, Hugues Duvillier, Ligia Craciun, Denis Larsimont, Karen Willard-Gallo. Characterization of B-cells infiltrating human breast cancer and their presence in peritumoral tertiary lymphoid structures. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1669. doi:10.1158/1538-7445.AM2014-1669

Genomic and immune landscape of parthanatos in breast carcinoma: The central role of AIFM1.

Background: In pancreatic ductal adenocarcinoma (PDAC), rare long-term survivors correlate with high intratumoral tertiary lymphoid structure (TLS) density. This finding prompted our investigation of clinically viable strategies to induce TLS in patients with immune-excluded tumors. We previously reported the induction of intratumoral TLS following administration of a neoadjuvant GM-CSF-secreting allogeneic vaccine (GVAX) to PDAC patients (NCT00727441). However, no clinical benefit was observed, likely owing to immune tolerance mechanisms governing the PDAC tumor microenvironment (TME). We previously observed upregulation of both the PD-1 and 4-1BB pathways with GVAX, and thus in a subsequent neoadjuvant trial combined GVAX with PD-1 blockade and 4-1BB agonism (NCT02451982) which was associated with pathologic responses. We hypothesized this combination strategy induced TLS of higher maturity and anti-tumor activity compared to GVAX alone. Methods: To explore how this therapeutic strategy affected TLS morphology and intercellular crosstalk, we leveraged the Visium spatial transcriptomics platform and a 35-marker customized TLS panel for imaging mass cytometry. We generated cellular and molecular maps of the TME after neoadjuvant treatment in 26 PDAC patients (GVAX n=19, GVAX+aPD1 n=2, GVAX+aPD1+a41BB n=5). To compare TLS maturation in parallel with secondary lymphoid organ-mediated tumor immunity, we also profiled tumor-adjacent lymph nodes. We applied unsupervised learning with non-negative matrix factorization (NMF) and trained AI-enabled image classification models to characterize cellular states within tissue structures of interest. Results: We identified spatial gene expression NMF patterns in PDAC TLS spanning across distinct morphologies and neoadjuvant treatment arms. Intratumoral TLS after GVAX were found to propagate activated B cells expressing immunoglobulins that infiltrated into malignant cellular niches. TLS NMF patterns were also associated with autoimmune disease signatures, such as diabetes, in a subset of patients. We scored TLS using tumor-draining lymph nodes as a reference and found increased maturation of TLS after PD-1 blockade, while addition of 4-1BB agonism significantly boosted the cytotoxic NK/T cell compartment compared to GVAX alone. Conclusions: We present machine learning approaches for spatial multi-omics analysis to characterize the TLS-enriched TME. We mined genome-wide spatial TLS gene expression patterns elucidating the spatial dynamics of humoral immunity of rare immunotherapy pathologic responders in PDAC. Altogether our findings shed light on the plasticity of TLS in neoadjuvant immunotherapy and suggest future immunotherapy approaches should target both humoral and cytotoxic NK/T cell compartments to augment responses in solid tumors. Citation Format: Dimitrios N. Sidiropoulos, Sarah M. Shin, Alexander Girgis, Daniel H. Shu, Janelle Montagne, Atul Deshpande, Jeanette A. Johnson, Lucie Dequiedt, Victoria Jacobs, Aleksandra Ogurtsova, Guanglan Mo, Xuan Yuan, Genevieve Stein-O’Brien, Mark Yarchoan, Qingfeng Zhu, Ashley Kiemen, Elizabeth M. Jaffee, Lei Zheng, Won Jin Ho, Robert Anders, Elana J. Fertig, Luciane T. Kagohara. Machine learning integrating spatial omics uncovers humoral immunity patterns in intratumoral tertiary lymphoid structures in pancreatic cancer pathologic responders [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1159.

Tumor-infiltrating lymphocytes (TIL) have been associated with good clinical outcomes in numerous large clinical trials for HER2-positive (HER2+) and triple-negative (TN) breast cancer (BC). Our previous work in human demonstrated that TIL can organize in tertiary lymphoid structures (TLS) with the B-cell chemoattractant, CXCL13, playing a key role in their formation as well as having a strong association with positive clinical outcomes. The present study investigated how TLS functionally contribute to immune responses in human BC. We prospectively collected fresh primary human BC tissues and prepared enzyme-free homogenates to produce TIL suspensions and tumor supernatants for flow cytometry and cytokine/chemokine/immunoglobulin (Ig) quantification, respectively. Matching formalin-fixed, paraffin-embedded tumor tissues were used for spatial analysis by dual immunohistochemistry and immunofluorescent confocal microscopy. We show that CD3+CD4+, CD3+CD8+ and CD19+ TIL in human BC contain subpopulations expressing CXCR5 (the CXCL13 receptor) and are co-localized in TLS. An in vitro functional assay activating Tfh cells with allogeneic B cells from human spleen evaluated the functionality of human BC Tfh TIL (CD45+CD3+CD4+CXCR5+). These experiments reveal that ICOS+PD-1hi Tfh TIL from TN and HER2+, but not luminal, BC possess helper activities for B cell IgG production. This observation is supported by a correlation between ICOS+PD-1hi Tfh TIL densities and IgG concentrations in primary human BC supernatants. A comparison of ICOS+PD-1hi and ICOS-PD-1- Tfh TIL confirms the activated, functional nature of these specialized TIL, which are characterized by high IL-21, IL-10 and CXCL13 mRNA expression. High IFNγ mRNA expression was detected in ICOS+PD-1hi Tfh TIL, suggesting their functional Th1 orientation. We also identified follicular regulatory T cells (Tfr), located in TLS that express CXCR5, CD25, demethylated Foxp3 and GARP, a marker of TGFβ activity. Tfr regulation of Tfh functions were evaluated by determining the ratio between functional Tfh TIL and GARP+ Tfr TIL. This analysis reveals a strong correlation between the Tfh/Tfr ratio and IgG production in primary tumor supernatants from TN and HER2+ human BC. In addition, strong correlations were observed with IgA and IgM production in HER2+ human BC. Our data show that Tfh TIL in human BC are major contributors to TLS activity, with the ratio between functional Tfh TIL and activated Tfr TIL directly influencing Ig production by B cells. Effective antitumor immunity in BC is therefore not only characterized by TIL density and organization but also by the balance between effector and regulatory TIL. These findings constitute important elements to consider when choosing patients for immunotherapy. Citation Format: Grégory Noël, Mireille Langouo, Soizic Garaud, Anaïs Boisson, Hugues Duvillier, Gert Van den Eynden, Denis Larsimont, Karen Willard-Gallo. The balance between activated follicular helper T cells and follicular regulatory T cells within tertiary lymphoid structures guides antitumor immune responses in human breast cancer [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2018 Nov 27-30; Miami Beach, FL. Philadelphia (PA): AACR; Cancer Immunol Res 2020;8(4 Suppl):Abstract nr A40.