Invasive lobular carcinoma (ILC) is the second most common histological subtype of breast cancer and displays distinct clinical and biological behavior compared to breast cancer of no special type. However, current molecular classifications largely overlook its complex spatial organization and tumor microenvironment (TME). Here, we performed spatial transcriptomics on 43 hormone receptor-positive, HER2-negative (HR+/HER2-) ILC tumors with detailed morphological annotation and long-term clinical follow-up. By integrating spatial gene expression with histology and single-cell deconvolution, we characterized the composition and architecture of the TME and revealed high inter-and intratumor heterogeneity. Spatial clustering uncovered cell populations and pathways linked to clinical outcome. We then developed a multimodal classification of ILC by integrating gene expression, morphology, and spatial metrics, identifying four distinct subtypes: normal/stroma-enriched (NSE), proliferative (P), androgen receptor-enriched (ARE), and metabolic/immune-enriched (MIE). These subtypes, collectively termed ILC4TME, reflect the interplay between tumor and microenvironmental features. Gene signatures derived from the spatial data enabled subtype assignment in external bulk RNA-seq and microarray datasets (SCAN-B, METABRIC), revealing reproducible biology and significant associations with survival. In multivariable models, ILC4TME retained prognostic value beyond established gene signatures and clinicopathological variables. Notably, the P subtype was linked to poor prognosis, even in patients treated with endocrine therapy alone, while the NSE subtype was associated with favorable outcomes. Our findings uncover spatial and cellular heterogeneity in ILC that is not captured by existing classification approaches, offering a refined framework for risk stratification and therapeutic targeting based on tumor microenvironment architecture.

Bispecific antibody is a new treatment for hematological disease, especially for lymphoma, myeloma and acute lymphoblastic leukemia. This class of treatment presents the same kind of side effect as CAR-T cell which are immune-mediated. Nevertheless, infectious complication remains a major concerns with related mortality. Fungal infection are rarely reported in clinical trial but remains a major concern. We report a case of a co-infection of Aspergillus and Mucorales in a patient with diffuse large B-cell lymphoma (DLBCL) following treatment with the bispecific antibody epcoritamab. The patient developed severe cytokine release syndrome (CRS) and subsequent fungal infections, which were challenging to diagnose and treat due to the complexities of managing immunocompromised patients and co-infection. Advanced diagnostics, including PET-CT, and a combination of antifungal therapies were crucial in achieving remission. The case underscores the need for early diagnosis, multidisciplinary management, and innovative treatment strategies in similar high-risk patients.

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. Triple-negative breast cancer (TNBC) is a heterogenous disease with several molecular subtypes previously described. Here the authors perform a spatial transcriptomics analysis on a series of 92 patients, providing additional insights into the heterogeneity of TNBC, with implications for clinical outcomes and therapy.

Urine cytology is a long-used technique for the detection of high grade neoplastic urothelial lesions. Since 2016, «The Paris System» classification has revolutionized this field by introducing a standardized terminology widely adopted by cytopathologists and urologists. In this article, we explain this classification and discuss its impact on the clinical management of patients with urothelial lesions, as well as its role in the secondary prevention of these lesions.

e12576 Background: Triple-negative breast cancer’s (TNBC) dismal prognosis demands more effective therapy selection. Previously described molecular subtypes reveal its heterogeneity but lack spatial insight and are not currently used in clinical practice. Here, we aim to evaluate by immunohistochemistry (IHC) the expression of key biomarkers in TNBC and its correlation with spatial gene expression obtained by spatial transcriptomics (ST). Methods: We studied a retrospective cohort of 92 patients (pts) treated at the Institut Jules Bordet in Belgium with primary surgery for early TNBC. ST (Visium Spatial Gene Expression, 10X Genomics) was previously performed on fresh frozen surgical samples. Using serial sections of these samples, we performed duplex IHC staining for Trop-2/androgen receptor (AR) and HER2/Ki-67. IHC staining was scored using H-score (Trop-2), Allred score (AR), and current guidelines (Ki67/HER2), adding the ultra-low and null HER2 categories. Statistical analyses included descriptive statistics, Spearman correlation, Mann-Whitney test, and Kaplan-Meier with log-rank tests for estimating outcome distribution. Results: Of 92 pts included, 4 (4.3%), 25 (27.2%), 28 (30.4%), and 35 (38%) pts had HER2 2+, 1+, ultra-low, and null, respectively, tumors. Importantly, we observed a significant difference in tumor cell-derived ERBB2 gene expression of HER2 ultra-low versus HER2 null tumors ( p<0.0001), while there was no difference in ERBB2 expression between HER2 ultra-low and HER2 1+ tumors ( p=0.49). HER2 expression was not correlated with prognosis. Trop-2 expression by IHC was high, medium, and low in 67%, 23%, and 10% of pts, respectively. IHC expression correlated well with tumor-derived gene expression (r=0.54), with intrasample heterogeneity observed both in IHC and spatial gene expression. Trop-2 expression was prognostic, pts with high Trop-2 H-score tumors having significantly worse outcome ( p=0.021). In this cohort, 25%, 40.2%, and 34.8% of pts had AR Allred scores of 0-2, 3-5, and 6-8, respectively. Tumor AR gene expression was well correlated with IHC AR expression (67.7%). IHC AR expression was associated with the presence of adipose tissue in the stroma (r=0.23, p=0.025) but not with prognosis. Of note, we report for the first time, to our knowledge, for TNBC, AR expression both in tumor and stroma cells, both at the IHC and gene expression levels. Importantly, we could construct a classifier that identifies luminal androgen receptor tumors, using AR Allred score > 5 and Ki67 ≤ 40%, with a PPV of 93% and an NPV of 96%. Conclusions: ST data has the potential to improve easily accessible IHC classifiers, with the aim of refining patient selection for ADC and anti-AR therapies in TNBC.

Abstract Background Tertiary lymphoid structures (TLS) are ectopic lymphoid organs playing a role in adaptive antitumor immune response. They were shown to be associated with favorable outcome and appears to be a promising biomarker for response to immune checkpoint inhibitors (ICI). Yet, there is no consensus for their detection and quantification. Here we aimed to derive a specific TLS signature using high resolution spatial transcriptomics data from a large series of triple negative breast cancer (TNBC) samples and to assess its clinical relevance including response to ICI. Methods Spatial transcriptomics (ST) was performed on a series of 94 early-stage TNBC surgical samples with detailed clinicopathological and outcome data. TLS and tumor infiltrating lymphocytes (TILs) were scored using hematoxylin and eosin and double immunohistochemistry (CD3/CD20) stained slides by a dedicated breast pathologist. Regression based on morphological annotations and deconvolution methods estimated the fraction of gene expression related to TLS in each ST spot allowing to derive specific TLS signature. Its prognostic and predictive value of response to ICI was assessed using publicly available breast cancer (METABRIC, SCAN-B, and I-SPY2) and other tumor type datasets treated with ICI (Bareche et al. Ann Oncol, 2022) from bulk gene expression data. Results Deconvolution of the TLS compartments using the ST gene expression data showed that TLS are enriched in all B cell subsets, CD4+ (central) memory and naïve T cells, as well as mast cells. A functional analysis showed an enrichment of ‘vascular endothelial cell proliferation’, ‘mitotic G2/M transition checkpoint’, ‘V/D/J recombination’ and ‘regulation of cell chemotaxis to fibroblast growth factor’ suggesting that TLS aggregates are associated with angiogenesis, immune cell proliferation, adaptative humoral response and tissue remodeling. A comparison of gene expression data between TLS and non-aggregated TILs led to the development of a specific TLS gene signature comprising B and T cell-specific genes, immunoglobulin genes as well as genes associated with TLS initiation. Its projection on tumor slides overlapped with the regions annotated as TLS by the pathologist, demonstrating its specificity for TLS detection. As expected, the highest levels of the TLS signature were observed in the immunomodulatory TNBC molecular subtype and fully inflamed tumors, whereas the lowest levels were observed in the mesenchymal molecular subtype and immune desert tumors (p< 0.05). Of note, high levels of the TLS signature were associated with better prognosis in TNBC patients from METABRIC (p=6.5 10−5) and SCAN-B datasets (p=1.6 10−3) as well as with higher pathological complete response rates in all breast cancer patients treated with neoadjuvant pembrolizumab in the I-SPY2 study (p=0.026). Similar results were found in other tumor types treated with immunotherapy in the metastatic setting including metastatic melanoma, pancreatic and bladder cancers (PFS, p=6 10−6). Of interest, the TLS signature outperformed the predictive value of other immune-related signatures including TILs suggesting a key role of TLS in obtaining a sustainable, adaptive antitumor immune response in the vicinity of the tumor area. Conclusion By leveraging the potential of spatial transcriptomics, we have successfully developed a unique TLS gene signature that demonstrates a strong correlation with the response to ICI in breast cancer and various other tumor types. This TLS gene signature outperforms other immune biomarkers, underscoring the pivotal role of TLS in eliciting a robust antitumor immune response. The universality of this TLS signature makes it a potent biomarker capable of identifying patients who would benefit from immunotherapy, pending further validation. Citation Format: Xiaoxiao Wang, David Venet, Frédéric Lifrange, Denis Larsimont, Mattia Rediti, Linnea Stenbeck, Floriane Dupont, Ghizlane Rouas, Andrea Joaquin Garcia, David Gacquer, Ligia Craciun, Laurence Buisseret, Nayanika Bhalla, Yuvarani Masarapu, Kim Thrane, Eva Gracia Villacampa, Lovisa Franzén, Sami Saarenpää, Linda Kvastad, Joakim Lundeberg, Françoise Rothé, Christos Sotiriou. Characterization of tertiary lymphoid structures and its association with response to immune checkpoint inhibitors in triple negative breast cancer using spatial transcriptomics [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-25-07.

Abstract 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 study ILC TME using spatial transcriptomics (ST). Methods: We performed ST (Visium 10x Genomics) on frozen tumor samples from 43 primary hormone receptor positive (HR+), HER2-negative (HER2-) ILCs. Of note, 9 samples were coming from patients who experienced disease relapse. Relative hematoxylin/eosin (H&E) slides were morphologically annotated (QuPath software). xCell was used to perform cell type enrichment analysis on sample pseudo-bulks. After cross-samples integration, ST spots were clustered using hierarchical clustering (STutility R package). intNMF algorithm was used to perform clustering at the patient-level by combining: RNA sequencing information (relative percentage of spot-level clusters in each sample), morphology and level of colocalization between cancer cells and the other cell types of the tumor microenvironment. METABRIC (HR+, HER2- ILC samples, n = 122) was used as external validation cohort. Survival analyses (univariable and multivariable adjusting for clinicopathological features) were performed using Cox proportional hazard models. Results: The patient-level classification revealed four groups showing different biological characteristics. Differences in terms of morphology (annotation) and pathway enrichment analysis based on marker genes (GSEA) were observed between groups. This information allowed us to annotate our groups as: proliferative (P, n = 12, enriched in tumor cells and proliferation-related pathways), normal-stroma enriched (NSE, n = 10, enriched in fibroblasts and carcinoma in situ), metabolic (M, n = 9, enriched in metabolic-related pathways) and metabolic-immune enriched (MIE, n = 10, enriched in adipose tissue, metabolic and immune-related pathways). Interestingly, a significantly higher presence of macrophages M2 was found in MIE group. Using group-specific gene signatures, we were able to reproduce the same 4 groups in the METABRIC. Of note, we observed significant differences in relapse-free survival (RFS) in METABRIC (p = 0.03), with NSE presenting better outcome, while P, M and MIE presented worse prognosis. Analysing the area of contact between adipocytes and cancer cells typical of MIE group, we noticed an enrichment in metabolic and M2 macrophages-related pathways. In doing so, we derived a 28 gene signature relative to the tumor-adipocytes contact area. Importantly, our signature was highly expressed in M and MIE groups, and it was not correlated with proliferation-related signatures. Interestingly, the adipocytes-related signature was significantly associated with shorter RFS in ILC patients in METABRIC (univariable: HR 1.4, p = 0.023; multivariable: HR 1.6, p = 0.005). Since both proliferation and metabolism showed to be key processes in defining prognosis in ILC, we built a prognostic index by integrating our adipocytes-related signature with genomic grade index (GGI, a proliferation-related signature). Our index outperformed other existing prognostic signatures (e.g., Oncotype DX, MammaPrint, EndoPredict, LobSig) in assessing prognosis (RFS) in ILC in METABRIC (univariable: HR 1.7, p &lt; 0.001; multivariable: HR 1.7, p = 0.002). Conclusions: We identified 4 biologically driven HR+, HER2- ILC groups describing tumor microenvironment heterogeneity. Of note, two of the three groups associated to worse disease outcome were related to metabolism, highlighting the importance of such process in ILC biology and in the future development of new treatment strategies. Moreover, the prognostic power of our index has the potential to refine the assessment of the risk of relapse in ILC. Further validation is warranted. Citation Format: Matteo Serra, Mattia Rediti, Laetitia Collet, Frédéric Lifrange, David Venet, Nicola Occelli, Xiaoxiao Wang, Delphine Vincent, Ghizlane Rouas, Ligia Craciun, Denis Larsimont, Laurence Buisseret, Miikka Vikkula, François Duhoux, Françoise Rothé, Christos Sotiriou. Spatially resolved analysis of tumor microenvironment in invasive lobular carcinoma [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-15-03.

Introduction:Brain abscess is the most common focal infectious neurological injury. Until the nineteenth century this condition was fatal, however the development of neuroimaging for early diagnosis, neurosurgery and antibiotic therapy in the twentieth century has led to new therapeutic strategies decreasing mortality from 50 % in the 1970s to less than 10 % nowadays. In this context we report a case of brain abscess with a dental origin.Case report:A immunocompetent man without any addiction presented to the emergency department with dysarthria and frontal headache at home. The clinical examination was normal. Further investigations revealed a polymicrobial brain abscess as a consequence of an ear, nose or throat (ENT) infection with locoregional extension with a dental starting point involving Actinomyces israelii and Fusobacterium nucleatum . In spite of a rapid diagnosis and a neurosurgical management associated with an optimal treatment by a dual therapy made of ceftriaxone and metronidazole the patient unfortunately died.Conclusion:This case report shows that despite a low incidence and a good prognosis following the diagnosis, brain abscesses can lead to patient's death. Thereby, when the patient's condition and urgency allow, a thorough dental examination of patients with neurological signs following the recommendations would improve the diagnosis made by the clinician. The use of microbiological documentation, the respect of pre-analytical conditions, the interaction between the laboratory and the clinicians are indispensable for an optimal management of these pathologies.

Background: Invasive lobular breast carcinoma (ILC) represents 5 to 15% of all invasive breast cancers. Recent studies showed the importance of tumor microenvironment (TME) heterogeneity on patient outcome. Here, we aim to characterize TME spatial heterogeneity by performing clustering analysis on spatial transcriptomics (ST) data. Methods: Frozen tumor samples from 43 primary estrogen receptor positive, HER2-negative ILCs were characterized using ST (Visium, 10x Genomics), each ST slide containing 4992 spots. Hematoxylin/eosin (H&E) stained ST slides were annotated (QuPath software) reaching single cell resolution. After performing normalization, hierarchical clustering (STutility R package) across all samples was carried out on principal components computed using highly variable genes. Clusters were characterized using morphological annotation and gene set enrichment analysis for hallmark gene sets from MSigDB (FGSEA R package). A cluster of spots was defined as tumoral or stromal if the average proportion of pixels annotated as tumor or stroma across its constitutive spots was higher than the average proportion of tumor or stroma pixels across all spots of our cohort. Spatial heterogeneity was assessed by comparing the number of contacts between spots belonging to the same cluster (homo-contacts) and the number of contacts between spots belonging to different clusters (hetero-contacts). Comparisons between groups were assessed using Wilcoxon test. Results: Out of the 43 ILC samples, 19 were T2 or T3, 13 were node-positive and 34 were grade 2. Of note, 9 patients experienced disease relapse. Morphological annotation revealed that an average of 20.4%, 61.12%, 11.5%, 0.45%, 3% of the tissues in our dataset corresponded to tumor, stroma, adipose tissue, immune infiltrate and normal structures (vessels, normal breast), respectively. Bioinformatics analysis revealed 7 tumor, 11 stroma, and 6 normal structures clusters, as well as 8 mixed clusters with no predominant morphological structure, with a median of 22 clusters per sample. Tumor and stroma clusters were either shared across all samples or present only in specific samples. Overall, tumor clusters were characterized by an enrichment in estrogen and androgen response related pathways. Moreover, tumor clusters enriched in oxidative phosphorylation, G2M checkpoint and MYC targets were more present in samples with higher histopathological grade (p=0.016), whereas tumor clusters enriched in interferon alpha/gamma response related pathway were associated with a higher tumor stage (p=0.007). A higher number of hetero-contacts among tumor spots were associated with disease relapse (p=0.02). Similarly, a higher number of hetero-contacts among stroma spots including immune and adipose related clusters was also found in samples from patients who experienced disease relapse (p=0.01). Overall, these findings suggest a role of both tumor and stroma spatial disorganization and heterogeneity in tumor progression. Furthermore, clusters capturing the presence of normal breast and in situ carcinoma were enriched in samples from patients who did not relapse (p< 0.001). Conclusion: Our results revealed the substantial inter- and intra-patient heterogeneity of ILC both at the tumor and microenvironment levels. Different tumor and stroma clusters characterized by specific hallmarks were associated to specific clinical features and disease outcome, unraveling potential new targets for optimizing ILC care. Further validation is needed. Citation Format: Matteo Serra, Mattia Rediti, Frédéric Lifrange, David Venet, Nicola Occelli, Laetitia Collet, Delphine Vincent, Ghizlane Rouas, Ligia Craciun, Denis Larsimont, Miikka Vikkula, Francois P. Duhoux, Françoise Rothé, Christos Sotiriou. Decoding Inter- and Intra-Tumor Heterogeneity in Lobular Breast Cancer Using Spatial Transcriptomics and Clustering Analysis [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P2-21-01.

Introduction: Invasive lobular breast cancer (ILC) is the most frequent special type of breast cancer. Recent studies showed the impact of intratumor heterogeneity (ITH) on patient outcome. Here, we aimed to better characterize ITH in ILC using spatial transcriptomics (ST) together with high-resolution morphological annotation. Methods: Spatial transcriptomics (Visium 10x Genomics) was performed on frozen tumor samples from 15 primary estrogen receptor positive, HER2-negative ILCs with 4 patients developing disease relapse. For each sample, we annotated hematoxylin/eosin sections (QuPath software) in two steps: manual annotation of specific histomorphological structures (e.g. normal breast ducts, fat tissue, vessels) and machine learning annotation of stroma and tumor cells at the single cell level. Proportion of each specific tissue type per sample was defined by pixel percentage computed within each ST spot. For each sample, the proportion of a given tissue type was defined as the proportion of pixels annotated with this specific type averaged across all spots within the tissue section. Spatially variable genes were used as input for non-negative matrix factorization and the reduced expression matrix was clustered with the Louvain algorithm implemented in Seurat. A cluster of spots was defined as tumoral if the average proportion of pixels annotated as tumor across its constitutive spots was higher than the average proportion of tumor pixels across all spots from the tissue section. Cluster characterization was performed using gene set enrichment analysis based on hallmarks (Molecular Signature Database) with a false discovery rate < 0.05. Spatial heterogeneity and tumor organization within each sample were assessed according to the number and type of cluster interactions, homo-contacts being defined as interactions between spots belonging to the same cluster and hetero-contacts between spots from two different clusters. Comparisons between groups were assessed using Wilcoxon test. Results: A total of 45 tumor clusters were identified among the 15 patients, with a range of 2-4 tumor clusters per sample highlighting intra-tumor heterogeneity. Cluster characterization revealed the presence of clusters enriched in different biological pathways within a given sample. These analyses also showed inter-patient heterogeneity as witnessed by distinct tumor clusters only present in a subset of tissue samples. In particular, 66% (N=10/15) of the tissue samples harbored clusters enriched in oxidative phosphorylation, 53% (N=8/15) in epithelial-mesenchymal transition, 33% (N=5/15) in interferon gamma response, 27% (N=4/15) in TNF-alpha via NFkB, 27% (N=4/15) in androgen response and 13% (N=2/15) in protein secretion hallmarks. All samples shared at least one tumor cluster enriched in estrogen early and late response.Although the number of tumor clusters was similar between samples from patients with or without relapse (median of 3, range 2-4), the presence of clusters enriched in protein secretion was associated with disease recurrence (p = 0.02). Of note, higher number of hetero-contacts mirroring tumor disorganization was associated with poor outcome although not significant (p= 0.08). Conclusions: Here, we showed for the first time a substantial inter- and intra-tumor heterogeneity of ILC at an unprecedented level, characterized by the presence of specific tumor clusters and distinct tumor organization patterns associated with outcome. We also. uncovered potentially targetable clusters missed by bulk analysis, offering novel perspectives for optimized ILC care. Further validation is warranted. Citation Format: Laetitia Collet, Matteo Serra, Mattia Rediti, Frédéric Lifrange, David Venet, XiaoXiao Wang, Delphine Vincent, Ghizlane Rouas, Danai Fimereli, David Gacquer, Andrea Joaquin Garcia, Isabelle Veys, Ligia Craciun, Denis Larsimont, Miikka Vikkula, François Duhoux, Françoise Rothé, Christos Sotiriou. Unravelling spatial tumor organization and heterogeneity in lobular breast cancer using spatial transcriptomics [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr PD14-02.

Background: Invasive lobular breast carcinoma (ILC) represents 5 to 15% of all invasive breast cancers (BCs). Here, we aim to investigate inter- and intra-tumor heterogeneity in terms of microenvironment composition, PAM50 molecular classification and proliferation (genomic grade index [GGI]) by combining spatial transcriptomics (ST) and accurate morphological annotation. Methods: Spatial RNA sequencing (Visium - 10X Genomics) was performed on frozen tumor samples from 15 primary estrogen receptor positive, HER2-negative ILC patients with long-term follow up. Hematoxylin/eosin slides were morphologically annotated integrating manual and machine learning-based approaches reaching single-cell resolution (QuPath software). The relative histomorphological categories (HC) composition of each spot across the ST slide was computed as percentage of pixels, while the level of proximity of different HC was evaluated computing the proportion of co-occurring HC at each spot. The PAM50 subtypes (AIMS R package) and GGI were computed on spots containing at least 40% of tumor (merging all the spots belonging to each sample [pseudo-bulk] for PAM50, while calculating mean and standard deviation [SD] across spots for GGI). PAM50 was also computed on the pseudo-bulk of the whole set of spots per sample. Wilcoxon and Spearman rank tests were used to compare continuous variables and assess correlations. Results: Out of 15 tumors, 7 were T2 or T3, 6 were node positive at diagnosis and 14 were grade 2. Four patients experienced disease relapse. Morphological annotation revealed that an average (per patient) of 20.3% (5.6-46.7%), 65.9% (45.5-83.5%) and 6.5% (0.0-27.1%) of the spots corresponded to tumor, stroma and fat tissue respectively. Larger tumors (T2-3 vs T1) presented a higher proportion of fat tissue and tumor cells, although these differences did not reach statistical significance. The levels and spatial variability of proliferation, measured using GGI, were higher in T2-3 compared to T1 tumors (p = 0.072 and 0.040, respectively). Of note, higher spatial variability of proliferation was also associated with node-positive tumors (p = 0.066). By computing the PAM50 classification using the pseudo-bulk, 9 samples were classified as luminal A, 1 as luminal B and 5 as normal-like. Of interest, when focusing on the tumor enriched spots, 60% of the samples previously classified as normal-like were re-classified as luminal A. Samples from patients who relapsed showed a higher fraction of fat tissue at the level of the whole slide (14.4% vs 3.5%; p = 0.018), with an increased co-localization of fat tissue and tumor cells at the spot level as well as higher proliferation values, although not significant. Conclusions: High proportion of fat tissue together with higher co-localization of fat tissue with tumor cells are associated with poor outcome in ILC. Higher spatial variability of proliferation is associated with larger tumors, lymph node positivity and recurrence. The proportion of stroma and fat tissue affected substantially the PAM50 classification of the tumors. Further validation is needed. Citation Format: Matteo Serra, Laetitia Collet, Mattia Rediti, Frédéric Lifrange, David Venet, Xiaoxiao Wang, Delphine Vincent, Ghizlane Rouas, Danai Fimereli, David Gacquer, Andrea Joaquin Garcia, Isabelle Veys, Ligia Craciun, Denis Larsimont, Miikka Vikkula, François Duhoux, Françoise Rothé, Christos Sotiriou. Integrating spatial transcriptomics and high-resolution morphological annotation to investigate tumor heterogeneity and PAM50 molecular subtyping in lobular breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P1-05-03.