Purpose Stimulator of Interferon Genes (STING) is a key inducer of type I interferon signalling that promotes immune cell activation and antitumour immune responses. Reduced STING expression has been reported in multiple tumour types, and STING agonists for their purpose of eliciting an anti-tumour immune response, have emerged as a promising strategy in cancer immunotherapy, including in triple-negative breast cancer. However, the role of STING activation within the tumour cells remains largely unexplored. As STING agonists are increasingly being considered for TNBC clinical trials, defining how tumour-intrinsic STING activation influences breast cancer progression and metastasis is critical for the effective therapeutic exploitation of this pathway. Methods We investigated tumour-intrinsic STING expression in breast cancer using phosphorylated STING (pSTING) as a marker of pathway activation. pSTING expression was assessed by immunohistochemistry in two independent cohorts: a breast cancer clinical cohort consisting of 546 BC tumours with > 25 years of clinical follow-up, and a BrM cohort consisting of 81 BrM tumours including 50 matched BC-BrM pairs. To define tumour-intrinsic biological programs associated with STING activation, quantitative proteomic profiling was performed following STING overexpression and knockdown in TNBC cells. Results Low or absent pSTING expression in primary tumours was significantly associated with poorer breast cancer–specific survival at both 5 years and 30 years (P = 0.0009, P < 0.001). While pSTING expression was not associated with survival following brain metastasis surgery, patients with pSTING-high primary tumours exhibited a significantly longer time to brain metastasis development (P = 0.0112). Integrative network and pathway analyses revealed coordinated proteomic reprogramming, including upregulation of ribosomal and translational machinery and suppression of metabolic and epithelial–mesenchymal transition–associated programs. Conclusion Collectively, our findings demonstrate that tumour-intrinsic STING activation is associated with favourable prognosis, delayed brain metastasis development, and coordinated proteomic reprogramming, highlighting a tumour-intrinsic dimension of STING biology beyond immune activation alone.

Background Pathogenic germline variants in certain genes are associated with somatic tumour mutation signatures. The use of somatic tumour mutation data has the potential to improve the identification of true pathogenic variants but remains underexplored. We investigated the integration of tumour homologous recombination (HR) deficiency status as a predictor of pathogenicity for germline BRCA1 and BRCA2 variants, building on the established link between HR deficiency and germline pathogenic variants in these genes. Methods We analysed breast tumour whole-genome sequence and matching germline data from 350 patients across four datasets: Familial Breast Cancer (N = 77), The Cancer Genome Atlas (TCGA-BRCA, N = 96), the MAGIC study (N = 136), and Q-IMPROvE (N = 41). A total of 15,156 germline variants (including structural variations) in BRCA1, BRCA2, and other cancer genes (ATM, BARD1, BRIP1, CHEK2, PALB2, PTEN, RAD51C, RAD51D, TP53) underwent variant curation. Patients were categorised based on germline classification as BRCA1 positive (N = 27), BRCA2 positive (N = 21), and BRCA1/2 negative (N = 232), excluding those with BRCA1/2 variants of uncertain significance (N = 8) and pathogenic or only uncertain variants in other cancer genes (N = 62). Somatic HR status (deficient or proficient) was predicted using three algorithms: HRDetect, CHORD, and HRDsum. HR-deficient and HR-proficient status were significant predictors of germline BRCA1/2 pathogenic variant status (positive and negative directions). Findings The CHORD algorithm, which estimates BRCA1 and BRCA2 subtype specifically, added precision contributing evidence towards pathogenicity for the corresponding gene, reaching pathogenic moderate strength for the relevant gene-subtype. Finally, we assessed CHORD HR predictions for variants of uncertain significance in BRCA1 and BRCA2, and reported their tumour HR status for potential use as additional evidence in variant curation. Interpretation Analysis across multiple tumour whole-genome sequencing datasets has shown that HR status prediction algorithms can separate profiles for BRCA1 and BRCA2 pathogenic variants and provide further evidence at increased weight to aid in the classification of germline BRCA1 and BRCA2 variants. Tumour sequencing offers a promising strategy for reducing the uncertainty in germline variant interpretation. Funding This work was funded by the National Breast Cancer Foundation.

Small cell lung cancer (SCLC) is an aggressive disease that is often diagnosed at an advanced stage when surgery is no longer feasible. The lack of tumor tissue and rapid clinical decline of patients have hindered the feasibility of large omics studies. However, with advances in omics technologies recent studies have started to unravel the molecular heterogeneity of SCLCs. Here, 82 fresh EBUS-TBNA aspirates underwent methylation profiling (EPIC arrays), with subsets of those subjected to whole-genome sequencing (n = 76), RNA-seq (n = 48) and blood cfDNA sequencing (n = 69) to characterize the molecular features of SCLCs. Methylation profiling revealed four sub-groups associated with distinct survival and extrinsic/intrinsic tumor features. Groups 1 and 2 presented increased expression of ASCL1. Group 1 tumors had a greater proportion of CD8 + T cells (immune enriched-NE) and patients with better survival. Group 2 (SCLC-A) harbored the largest number of cases, and high expression of SLFN11 and DLL3, as potential therapeutic options. Group 3 tumors presented increased expression and hypomethylation of NEUROD1 (SCLC-N), with a greater proportion of fibroblasts. Group 4 tumors expressed POU2F3 and/or YAP1, had increased expression of non-neuroendocrine genes (non-NE) and had the worst survival. TACSTD2 expression was higher in Group 4, suggesting a potential therapeutic option for this group. SEZ6, another potential therapeutic option, was highly expressed in most SCLCs. These results highlight that novel therapeutic options may need to be considered in the context of SCLC heterogeneity. We showed that methylation of the most common source of tumor tissue in the clinical setting can stratify SCLCs with distinct clinical outcomes and potentially tailored therapeutic options. Methylation can characterize the intrinsic and extrinsic heterogeneity of SCLCs and fuel the discovery of novel therapeutic vulnerabilities to help bridge the gap between research and clinical application to improve care for SCLC patients.

Spatial transcriptomics (ST) links tissue morphology with gene expression values, opening new avenues for digital pathology. Deep learning models are used to predict gene expression or classify cell types directly from images, offering significant clinical potential but still requiring improvements in interpretability and robustness. We present STimage as a comprehensive suite of models to predict spatial gene expression and classify cell types directly from standard H&E images. STimage enhances robustness by estimating gene expression distributions and quantifying both data-driven (aleatoric) and model-based (epistemic) uncertainty using an ensemble approach with foundation models. Interpretability is achieved through attribution analysis at single-cell resolution integrated with histopathological annotations, functional genes, and latent representations. We validated STimage across diverse datasets, demonstrating its performance across various platforms. STimage-predicted gene expression can stratify patient survival and predict drug response. By enabling molecular and cellular prediction from routine histology, STimage offers a powerful tool to advance digital pathology.

The estrogen receptor (ER) drives growth in most breast cancers. Endocrine therapy reduces recurrence, however around 30% of cancers relapse. Many recurrences occur years later, with slowly proliferating, hard-to-treat disease. To study this, we generate slow-growing resistant cells that form small primary tumours but readily metastasise. Single-cell RNA sequencing (scRNAseq) reveals that endocrine therapy reprograms these cells, notably upregulating the Rac1 signalling component P-Rex1. We find in clinical cohorts that P-Rex1 is high in ER+ breast cancer, including in late recurrent disease. Intravital imaging demonstrates that Rac1 signalling is active in ER+ cells following endocrine therapy. Targeting the Rac1 pathway with small molecule inhibitors (NSC23766, R-ketorolac) reduces survival and motility in resistant cells, inhibits in vivo Rac1 activity, and reduces tumour burden when combined with tamoxifen in a drug-refractory patient derived xenograft model. This work identifies the P-Rex1/Rac1 axis as a potential therapeutic target for late recurring ER+ breast cancer.

AIMS:Invasive lobular carcinoma (ILC) may show targetable vulnerabilities secondary to the characteristic loss of the cell adhesion protein E-cadherin. Specifically, a synthetic lethal interaction was identified between E-cadherin loss and ROS1 inhibition. Several clinical trials are currently under way to assess the efficacy of ROS1 inhibitors in ILC; however, ROS1 expression has not been confirmed in ILC tumours and ROS1 has not been validated as a biomarker in the breast cancer setting. This study aimed to (i) examine ROS1 expression in a large cohort of breast cancer cases and (ii) investigate the biology and clinical significance of ROS1 positivity in breast cancer. METHODS AND RESULTS:ROS1 immunohistochemistry was performed on a large cohort of ILC (n = 274) and invasive carcinoma of no special type (NST; n = 431) cases with extensive clinicopathological data. The staining performance of four ROS1 antibody clones was compared. There was marked variation in ROS1 status according to antibody clone. D4D6 and SP384 were negative in almost all breast cancer cases, whereas EP282 and EPMGHR2 were positive in 37 and 47% of ILC cases, and 49 and 74% of NST cases, respectively. Only data from clones D4D6 and SP384 were highly concordant, while EP282 and EPMGHR2 were positive in distinct breast cancer subtypes. CONCLUSIONS:Assessment of ROS1 status in breast cancer appears to be highly antibody clone-dependent. ROS1 antibody clone selection will be an important consideration in the design of clinical trials investigating the clinical validity of ROS1 as a predictive biomarker in breast cancer.

Metaplastic breast cancer (MpBC) is defined by the presence of various morphological elements, typically biphasic, with epithelial (e.g. no-special type (NST), squamous) and mesenchymal (e.g. spindle, chondroid, osteoid) components. The established clonality of the different components favours an evolution model encompassing either a multipotent progenitor, or a linear metaplastic conversion. We used methylation profiling and showed that different morphologies have specific methylation profiles. Furthermore, our spatial transcriptomic approach, using 10× Genomics Visium and trajectory analysis, evidenced that spindle cells form a transition between the originating carcinoma of no-special type (NST) and pleomorphic regions, with osteoid differentiation likely to be an end-stage fate of the chondroid growth pattern, supporting the conversion model of lineage differentiation. We have also identified a series of master transcription factors likely to regulate these processes, and are significantly associated with metaplastic-like clinical features. This data further supports the conversion model of metaplasia and warrants functional analysis.

The aim of this study was to test the hypothesis that the diagnostic performance (as defined by the classification accuracy, sensitivity and specificity) of CA15-3 to detect breast cancer is increased by detection of the cancer-associated Neu5Gc sialic acids on the mucin MUC1 using the novel lectin, SubB2M. A genetically engineered lectin (SubB2M) that binds Neu5Gc was used as a detection reagent in a sandwich ELISA format CA15-3 assay. In a case : control cohort equivalence study the classification accuracy for the SubB2M-based CA15-3 assay (neuCA15-3) was determined and compared to an FDA-approved CA15-3 IVD test (Elecsys CA15-3 II, Roche Diagnostics). Classification accuracy and AUC for neuCA15-3 were 81% and 0.886 ± 0.015 (standard error, n=567) and for Elecsys Ca15-3 II, 55% and 0.642 ± 0.023 (n=558), respectively. At a threshold cut-off serum concentration of 23.6 Units/ml, overall breast cancer classification accuracy of the neuCA15-3 was 81% (compared to 55% for the comparator assay, p < 0.001). At 95% specificity, the sensitivity of the NeuCA15-3 assay was 69.5%, significantly greater than the competitor assay (11.9%, p<0.001). NeuCA15-3 concentrations did not vary significantly with breast cancer receptor subtype. The diagnostic performance of the neuCA15-3 assay was substantially improved over the classical CA15-3 sandwich assay that detects all forms of MUC1. The reporter signal generated for the neuCA15-3 assay depends on capture of the MUC1 protein and the presence of the aberrant Neu5Gc sialic acid residues on the MUC1 protein, thus increasing the assay specificity. The presence of multiple Neu5Gc lectin binding sites per glycoprotein molecule increases signal generation and assay sensitivity. The inclusion of additional cancer biomarkers in a multivariate index assay format may further increase diagnostic performance for breast cancer. Sara Nikseresht, Ramin Khanabdali, Lucy Shewell, Christopher Day, Amy McCart Reed, Michael Jennings, Haarika Haarika, Sunil Sunil, Peter Simpson, Romina Nabiee, Mathew Moore, Leearne Hinch, Gregory Rice. Enhancing sensitivity and specificity of the CA15-3 (MUC1) breast cancer assay by detection of N-glycolylneuraminic acid (Neu5Gc) using the lectin SubB2M [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_2):Abstract nr LB407.

The use of nanomaterials is an exciting prospect to facilitate radiotherapy delivery based on molecular targeting of tumors. This molecular targeted radiotherapy approach involves the use of radioligands-radioactive isotopes that are chemically linked to tumor-binding ligands–to ensure that radiation damage is delivered accurately and efficiently to tumor cells while sparing normal tissues. Although the use of nanomaterials has been well summarized for passive cancer radiotherapy, a clinical take on modern molecular targeted radioligand applications is yet to be reviewed. In this review, we will firstly discuss the innovative design of nanomaterials in relation to pre-clinical molecular targeted radioligand therapy. As we identify a current lack of clinical nanomaterial-based radiotherapy across various tumor types, we then provide our insights on related challenges and strategies to clinically translate innovative nanomaterial technologies to aid in driving molecular targeted radioligand therapies.

Background The nucleocytoplasmic shuttling of ERK5 has gained recent attention as a regulator of its diverse roles in cancer progression but the exact mechanisms for this shuttling are still under investigation. Methods Using in vitro, in vivo and in silico studies, we investigated the roles of shorter ERK5 isoforms in regulating the nucleocytoplasmic shuttling of active phosphorylated-ERK5 (pERK5). Retrospective cohorts of primary and metastatic breast cancer cases were used to evaluate the association of the subcellular localization of pERK5 with clinicopathological features. Results Extranuclear localization of pERK5 was observed during cell migration in vitro and at the invasive fronts of metastatic tumors in vivo . The nuclear and extranuclear cell fractions contained different isoforms of pERK5, which are encoded by splice variants expressed in breast and other cancers in the TCGA data. One isoform, isoform-3, lacks the C-terminal transcriptional domain and the nuclear localization signal. The co-expression of isoform-3 and full-length ERK5 associated with high epithelial-to-mesenchymal transition (EMT) and poor patient survival. Experimentally, expressing isoform-3 with full-length ERK5 in breast cancer cells increased cell migration, drove EMT and led to tamoxifen resistance. In breast cancer patient samples, pERK5 showed variable subcellular localizations where its extranuclear localization associated with aggressive clinicopathological features, metastasis, and poor survival. Conclusion Our studies support a model of ERK5 nucleocytoplasmic shuttling driven by splice variants in an interplay between mesenchymal and epithelial states during metastasis. Using ERK5 as a biomarker and a therapeutic target should account for its splicing and context-dependent biological functions. Graphical Abstract ERK5 isoform-3 expression deploys active ERK5 (pERK5) outside the nucleus to facilitate EMT and cell migration. In cells dominantly expressing isoform-1, pERK5 shuttles to the nucleus to drive cell expansion.

BACKGROUND:Lung cancer is a heterogeneous disease and the primary cause of cancer-related mortality worldwide. Somatic mutations, including large structural variants, are important biomarkers in lung cancer for selecting targeted therapy. Genomic studies in lung cancer have been conducted using short-read sequencing. Emerging long-read sequencing technologies are a promising alternative to study somatic structural variants, however there is no current consensus on how to process data and call somatic events. In this study, we preformed whole genome sequencing of lung cancer and matched non-tumour samples using long and short read sequencing to comprehensively benchmark three sequence aligners and seven structural variant callers comprised of generic callers (SVIM, Sniffles2, DELLY in generic mode and cuteSV) and somatic callers (Severus, SAVANA, nanomonsv and DELLY in somatic modes). RESULTS:Different combinations of aligners and variant callers influenced somatic structural variant detection. The choice of caller had a significant influence on somatic structural variant detection in terms of variant type, size, sensitivity, and accuracy. The performance of each variant caller was assessed by comparing to somatic structural variants identified by short-read sequencing. When compared to somatic structural variants detected with short-read sequencing, more events were detected with long-read sequencing. The mean recall of somatic variant events identified by long-read sequencing was higher for the somatic callers (72%) than generic callers (53%). Among the somatic callers when using the minimap2 aligner, SAVANA and Severus achieved the highest recall at 79.5% and 79.25% respectively, followed by nanomonsv with a recall of 72.5%. CONCLUSION:Long-read sequencing can identify somatic structural variants in clincal samples. The longer reads have the potential to improve our understanding of cancer development and inform personalized cancer treatment.

Brain metastases are secondary brain tumours characterised by their aggressive nature and poor prognosis. Breast cancer is one of the most common primary tumours in women to spread to the brain. A lack of biomarkers predicting likely spread to the brain and limited therapeutic interventions represents major areas of clinical unmet need. We investigated N-myc downregulated gene-1 (NDRG1) as a clinically relevant biomarker in breast cancer brain metastasis patients. NDRG1 expression was investigated using immunohistochemistry on tissue microarrays of two clinical cohorts: (i) brain metastatic breast cancers (n = 48) and brain metastases (n = 64; including a subset of 39 patient-matched breast and brain metastasis cases) and (ii) unselected primary breast cancers (n = 336). NDRG1 was highly expressed in breast-to-brain metastases, as well as in high-grade primary breast cancers. High NDRG1 expression and also an absence of expression were associated with worse survival outcomes in both breast cancer and breast cancer brain metastasis patients. This establishes NDRG1 as a 'Goldilocks' protein, where too much or too little has a negative effect on survival. We pose that this accounts for its previous categorisation as both tumour suppressor and oncoprotein. Additionally, a shift in NDRG1 localisation with a gain of nuclear expression was seen at the brain metastasis stage. Significant survival benefit in cases expressing cytoplasmic NDRG1 was observed, whereas NDRG1 localisation in the nucleus showed a clear association with poorer survival. In vitro analyses revealed that hypoxic stress significantly elevated NDRG1 expression and resulted in its nuclear localisation. Our findings suggest NDRG1 expression and subcellular localisation are clinically relevant biomarkers for poor prognosis in breast cancer and breast cancer brain metastasis.

Neutral Re(I) morpholine complexes exhibiting long emission lifetimes, high photo- and pH stability and low cytotoxicity for imaging endosome-lysosome compartments.

Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is often the only source of tumor tissue from patients with advanced, inoperable lung cancer. EBUS-TBNA aspirates are used for the diagnosis, staging, and genomic testing to inform therapy options. Here we extracted DNA and RNA from 220 EBUS-TBNA aspirates to evaluate their suitability for whole genome (WGS), whole exome (WES), and comprehensive panel sequencing. For a subset of 40 cases, the same nucleic acid extraction was sequenced using WGS, WES, and the TruSight Oncology 500 assay. Genomic features were compared between sequencing platforms and compared with those reported by clinical testing. A total of 204 aspirates (92.7%) had sufficient DNA (100 ng) for comprehensive panel sequencing, and 109 aspirates (49.5%) had sufficient material for WGS. Comprehensive sequencing platforms detected all seven clinically reported tier 1 actionable mutations, an additional three (7%) tier 1 mutations, six (15%) tier 2–3 mutations, and biomarkers of potential immunotherapy benefit (tumor mutation burden and microsatellite instability). As expected, WGS was more suited for the detection and discovery of emerging novel biomarkers of treatment response. WGS could be performed in half of all EBUS-TBNA aspirates, which points to the enormous potential of EBUS-TBNA as source material for large, well-curated discovery-based studies for novel and more effective predictors of treatment response. Comprehensive panel sequencing is possible in the vast majority of fresh EBUS-TBNA aspirates and enhances the detection of actionable mutations over current clinical testing.

Brain metastasis is a significant challenge for some breast cancer patients, marked by its aggressive nature, limited treatment options, and poor clinical outcomes. Immunotherapies have emerged as a promising avenue for brain metastasis treatment. B7-H3 (CD276) is an immune checkpoint molecule involved in T cell suppression, which is associated with poor survival in cancer patients. Given the increasing number of clinical trials using B7-H3 targeting CAR T cell therapies, we examined B7-H3 expression across breast cancer subtypes and in breast cancer brain metastases to assess its potential as an interventional target. B7-H3 expression was investigated using immunohistochemistry on tissue microarrays of three clinical cohorts: (i) unselected primary breast cancers (n = 347); (ii) brain metastatic breast cancers (n = 61) and breast cancer brain metastases (n = 80, including a subset of 53 patient-matched breast and brain metastasis cases); and (iii) mixed brain metastases from a range of primary tumours (n = 137). In primary breast cancers, B7-H3 expression significantly correlated with higher tumour grades and aggressive breast cancer subtypes, as well as poorer 5-year survival outcomes. Subcellular localisation of B7-H3 impacted breast cancer-specific survival, with cytoplasmic staining also correlating with a poorer outcome. Its expression was frequently detected in brain metastases from breast cancers, with up to 90% expressing B7-H3. However, not all brain metastases showed high levels of expression, with those from colorectal and renal tumours showing a low frequency of B7-H3 expression (0/14 and 2/16, respectively). The prevalence of B7-H3 expression in breast cancers and breast cancer brain metastases indicates potential opportunities for B7-H3 targeted therapies in breast cancer management.

Abstract Invasive Lobular Carcinoma (ILC) is the most common special histological subtype of breast cancer. ILC typically present as Oestrogen and Progesterone Receptor positive cancers, without over-expression of HER2 and are defined by their invasive pattern of growth. Despite clinical and biological differences, including diverse sites of metastasis, ILC are managed in the same way as the more commonly diagnosed, Invasive Carcinomas of no special type. Previously, we derived the LobSig lobular specific gene signature in an attempt to prognosticate within an otherwise homogeneous tumour category. We showed that this set of genes could stratify Grade 2 and Nottingham Prognostic Index moderate tumours into high and low risk groups. Herein, we use a nanoString nCounter custom codeset and immunohistochemistry to validate the LobSig signature. Using a CoxBoost analysis we further refined the geneset to 14 genes of interest which we examined using Immunohistochemistry on a large panel of ILC with clinical follow up data. Four targets showed a significant association with breast cancer specific survival, with high levels correlating with the poorest outcomes. Considering the expression data for these 4 candidates together, we performed a Cox Proportional Hazard Regression resulting in a combined prognostic power of (P=0.00034, HR=8.07 (CI 2.58-25.30)), which has superior prognostic power over variables including tumor size and patient age. ‘LobSig4’ represents a readily implementable and informative biomarker set for prognostication in Invasive Lobular Carcinoma. Citation Format: Lauren Kalinowski, Jamie Kutasovic, Sriganesh Srihari, Yufan Feng, Samir Lal, Kaltin Ferguson, Haarika Chittoory, Anna Sokolova, Malcolm Lim, Priyakshi Kalita De Croft, Sunil Lakhani, Peter Simpson, Amy McCart Reed. LobSig4 is a superior and readily implementable ILC-focussed prognostic biomarker set [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 PO3-15-09.