Vessela Nedelcheva Kristensen

Introduction: Cytokines are signaling molecules produced by various cell types, including immune cells, and play important roles in tumor development and progression. Extracellular vesicles (EVs) are small membrane-bound particles secreted by all cell types, including cancer cells. EVs mediate intercellular communication through the transfer of proteins, lipids and nucleic acids, affecting many cellular processes. EV-associated cytokines may therefore represent a novel source of circulatory biomarkers in cancer. In this study, we investigated EV-associated cytokines obtained from estrogen receptor-positive (ER+) breast cancer (BC) patients and healthy individuals and evaluated treatment-associated changes during neoadjuvant endocrine therapy (NET). Materials and methods: EVs were isolated from plasma samples of BC patients, healthy individuals, and from breast cell lines through ultracentrifugation. EVs were characterized by transmission electron microscopy, flow cytometry, nanoparticle tracking analysis and western blotting. EV-associated cytokines were profiled using Luminex multiplex assay in plasma samples of ER + BC patients ( n = 46) enrolled in the Neoletexe clinical trial. EV-associated cytokine levels were analyzed at three timepoints, before (T0) and after NET (T1 and T2), and in healthy individuals ( n = 13). EV-associated cytokine levels were compared with free-circulating cytokines in blood and with cytokine gene expression in tumor tissue from a subset of the same patients from the Neoletexe cohort. Results: Three EV-associated cytokines, interleukin 10 (IL-10), interleukin 12 (IL-12) and interferon gamma inducible protein 10 (IP-10), were significantly elevated in ER + BC patients compared to healthy individuals. CXCL10 (IP-10) gene expression was also found to be overexpressed in breast cancer tissue relative to normal and benign tissue, supporting the EV-associated IP-10 findings. Levels of EV-associated IL-10 and IL-12 decreased significantly during NET, but only eotaxin was associated with Ki-67 treatment response. Treatment-associated changes were more pronounced in EV-associated cytokines than for corresponding free-circulating cytokines and tumor gene expression. Conclusion: EV-associated cytokines differ between ER + BC patients and healthy individuals and change during NET in ER+ LABC patients. These findings suggest that EV-associated cytokines may reflect disease and treatment related changes and provide complementary information to free-circulating cytokines and tumor gene expression. Further studies are required to determine their potential clinical relevance as biomarkers. Trial registration: The Neoletexe study was approved on March 19th, 2015, by the Regional Ethics Committee (REC) of Southeast Norway in Oslo (national registration number: 2015/84).

Transcription is regulated through the sequence-specific binding of transcription factors (TFs) to cis-regulatory regions (CRRs); DNA variants in CRRs can disrupt TF-DNA interactions and gene regulatory networks through a cascading effect. Despite a few cases of reported recurrent cis-regulatory variants (CRVs), another approach for detecting non-coding functional events relies on combining gene-CRR associations capturing the regulatory elements controlling gene transcription, and functional impact (FI) scores quantifying the deleterious effect of variants. While many methods exist for each, how much they agree and how strongly the choice of CRR-FI score combination impacts the prediction of cis-regulatory altered genes has not been systematically assessed. Here, we demonstrate that gene-CRR associations and FI scoring methods exhibit little consensus, highlighting the impact of the choice of a specific CRR-FI score combination in a given analysis. These observations point to the need for a systematic approach to evaluate several gene-CRR and FI scoring methods in a unified framework. To address this gap, we developed HiFIseek, a Snakemake pipeline of two enrichment detection methods exploring the enrichment of high FI variants in CRRs associated with a gene using all region-score combinations. We applied HiFIseek to detect genes exhibiting high functional impact CRVs in eight cancer cohorts and a set of breast cancer risk-associated single-nucleotide polymorphisms (SNPs). We demonstrate that cancer driver genes exhibit a higher frequency of FI CRVs compared to non-cancer genes. In the cancer cohorts, HiFIseek detected genes pointing to cancer-related pathways with enrichment for high FI CRVs despite a small degree of agreement across CRR-FI score combinations. In the SNP cohort, HiFIseek found again small consensus across CRR-score combinations, one of which returned 18 known cancer-related genes, including BRCA1 , showing an enrichment of high-impact CRVs.

Despite thorough characterizations of cellular compositions within the breast tumor microenvironment (TME), their implications for disease progression and patient prognosis remain poorly understood. Unraveling these effects is vital for identifying potential targets to improve treatment outcomes. In this study, we devise an explainable machine learning (XML) pipeline to scrutinize the associations between TME cellular constituents and relapse-free survival (RFS). By applying this pipeline to estimated cell fractions in the METABRIC and TCGA datasets and comparing these results with associations to pathological complete response (pCR) after neoadjuvant chemotherapy (NAC), we create a comprehensive catalog of the TME's role based on 5000 patient samples. Our findings reveal an unexpected dichotomy in which macrophages correlate positively with pCR but negatively with RFS, particularly within estrogen receptor-positive (ER+) and Luminal A and B (LumA/B) cancer subtypes. We show that this pattern is driven by heterogeneity in breast tumors characterized by increasing levels of macrophage infiltration. Through imaging mass cytometry (IMC) data analysis, we find that macrophages tend to accumulate in the vicinity of HLA-ABC^hi epithelial cells as their frequency increases in tumor tissues and that they also express elevated levels of HLA-ABC protein. In both IMC and single-cell RNA sequencing (scRNA-seq) data, we uncover a significant association between these HLA-ABC^hi macrophages and regulatory and exhausted T cells (TReg and TEx), suggesting their involvement in immune suppression, likely by creating a chronically activated immunosuppressive TME. Subsequent cell-cell communication analysis predicts interactions between HLA-ABC^hi macrophages and TEx cells via the ligands SIGLEC9, ALCAM, and CSF1, and with TReg cells through APP, ANGPTL4, and SIGLEC9 signaling. Considering the clinical relevance of macrophages in ER+ (LumA/B) subtypes, this work enhances the characterization of macrophage-associated immune suppression in these tumors and identifies potential targets for immunomodulatory strategies.

Background: Tumor immune cell infiltration is a favorable prognostic factor in triple-negative breast cancer. Most triple-negative tumors belong to the aggressive basal-like subtype. We hypothesized that immune gene expression may identify low-risk patients for whom adjuvant chemotherapy can be de-escalated. Methods: The expression of 753 immune-related genes was analyzed in tumor biopsies from 45 patients with basal-like disease and no lymph node metastases (Oslo1 cohort) and evaluated for prognostic value. Findings were validated in two independent cohorts. Oslo1 biopsies were also analyzed for tumor-infiltrating lymphocytes (TIL) and tertiary lymphoid structures (TLS). Results: Here we show that a high expression of CTLA4 (above 63^rd percentile) is associated with an excellent prognosis in the Oslo1 cohort. None of the patients in the CTLA4 ^high group suffered disease recurrence (median follow-up 7.4 years) or breast cancer-related death (median follow-up 17.7 years). Analysis of the SCAN-B (n = 233; 97% without distant recurrence in CTLA4^high group) and METABRIC cohorts (n = 155; 93% disease-specific survival in CTLA4^high group) validates this finding, which also applies to patients who did not receive chemotherapy. CTLA4 expression correlates with TIL score and TLS levels (Oslo1 cohort), but no TIL^low/CTLA4 ^high patients died from breast cancer, suggesting that the CTLA4 readout identifies low-risk patients not captured by TIL assessment. Conclusions: A high primary tumor expression of CTLA4 identifies patients with an excellent prognosis, for whom standard chemotherapy may be de-escalated or omitted.

Transcription is regulated through the sequence-specific binding of transcription factors (TFs) to cis-regulatory regions (CRRs). Although scattered along the genome, multiple CRRs are brought in close spatial proximity to the genes they regulate through the formation of DNA loops. The sequence component of transcriptional regulation suggests that DNA variants in CRRs could disrupt TF-DNA interactions and gene regulatory networks through a cascading effect. To date, only a few cases of recurrent cis-regulatory variants have been described. As an alternative to variant recurrence, some methods utilize genomic annotations that indicate the functional impact (FI) of a variant and the CRRs of each gene to detect the enrichment of high-impact cis-regulatory variants (CRVs). However, the agreement across the different associations and FI scoring methods remains unexplored. This work demonstrates that gene-CRR and FI scoring methods exhibit little consensus, highlighting the impact of the choice of a specific CRR-score combination in a given analysis. In addition, we demonstrate that cancer genes exhibit a higher frequency of FI variants compared to non-cancer genes. Based on this, we developed HiFIseek, a Snakemake pipeline exploring the enrichment of FI variants in associated genomic regions using all region-score combinations and two enrichment detection methods. We apply HiFIseek to detect genes exhibiting high FI CRVs in eight cancer cohorts and a set of breast cancer risk-associated single-nucleotide polymorphisms (SNPs). In the cancer cohorts, we observe a small degree of agreement across CRR-score combinations. Although HiFIseek detected known cancer-related genes with FI CRVs, most of them did not show significant changes in their expression. In the SNPs cohort, HiFIseek found small consensus across CRR-score combinations. However, one of the combinations returned 18 known cancer-related genes, including BRCA1 , showing an enrichment of high-impact CRVs.

Clinical genetic testing identifies variants causal for hereditary cancer, information that is used for risk assessment and clinical management. Unfortunately, some variants identified are of uncertain clinical significance (VUS), complicating patient management. Case-control data is one evidence type used to classify VUS. As an initiative of the Evidence-based Network for the Interpretation of Germline Mutant Alleles (ENIGMA) Analytical Working Group we analyze germline sequencing data of BRCA1 and BRCA2 from 96,691 female breast cancer cases and 302,116 controls from three studies: the BRIDGES study of the Breast Cancer Association Consortium, the Cancer Risk Estimates Related to Susceptibility consortium, and the UK Biobank. We observe 11,207 BRCA1 and BRCA2 variants, with 6909 being coding, covering 23.4% of BRCA1 and BRCA2 VUS in ClinVar and 19.2% of ClinVar curated (likely) benign or pathogenic variants. Case-control likelihood ratio (ccLR) evidence is highly consistent with ClinVar assertions for (likely) benign or pathogenic variants; exhibiting 99.1% sensitivity and 95.3% specificity for BRCA1 and 93.3% sensitivity and 86.6% specificity for BRCA2. This approach provides case-control evidence for 787 unclassified variants; these include 579 with strong or moderate benign evidence and 10 with strong pathogenic evidence for which ccLR evidence is sufficient to alter clinical classification.

The role of germline genetics in adjuvant aromatase inhibitor (AI) treatment efficacy in ER-positive breast cancer is poorly understood. We employed a two-stage candidate gene approach to examine associations between survival endpoints and common germline variants in 753 endocrine resistance-related genes. For a discovery cohort, we screened the Breast Cancer Association Consortium database (n ≥ 90,000 cases) and retrieved 2789 AI-treated patients. Cox model-based analysis revealed 125 variants associated with overall, distant relapse-free, and relapse-free survival (p-value ≤ 1E-04). In validation analysis using five independent cohorts (n = 8857), none of the six selected candidates representing major linkage blocks at CELA2B/CASP9, NR1I2/GSK3B, LRP1B, and MIR143HG (CARMN) were validated. We discuss potential reasons for the failed validation and replication of published findings, including study/treatment heterogeneity and other limitations inherent to genomic treatment outcome studies. For the future, we envision prospective longitudinal studies with sufficiently long follow-up and endpoints that reflect the dynamic nature of endocrine resistance.

Breast cancer (BCa) is a major global health challenge. The BCa genome often carries extensive somatic copy number alterations (CNAs), including gains/amplifications and losses/deletions. These CNAs significantly affect tumor development, drug response and patient survival. However, how individual CNAs contribute is mostly elusive. We identified loss of chromosome 13q14.2 as a key CNA in BCa, occurring in up to 63% of patients, depending on the subtype, and correlating with poor survival. Through multi-omics and in vitro analyses, we uncover a paradoxical role of 13q14.2 loss, promoting both cell cycle and pro-apoptotic pathways in cancer cells, while also associating with increased NK cell and macrophage populations in the tumor microenvironment. Notably, 13q14.2 loss increases BCa susceptibility to BCL2 inhibitors, both in vitro and in patient-derived xenografts. Thus, 13q14.2 loss could serve as a biomarker for BCa prognosis and treatment, potentially improving outcomes for BCa patients. Graphical abstract