Introduction: Triple-negative breast cancers need to be refined in order to identify therapeutic subgroups of patients. Methods: We conducted an unsupervised analysis of microarray gene-expression profiles of 107 triple-negative breast cancer patients and undertook robust functional annotation of the molecular entities found by means of numerous approaches including immunohistochemistry and gene-expression signatures. A triple-negative external cohort (n = 87) was used for validation. Results: Fuzzy clustering separated triple-negative tumours into three clusters: C1 (22.4%), C2 (44.9%) and C3 (32.7%). C1 patients were older (mean = 64.6 years) than C2 (mean = 56.8 years; P = 0.03) and C3 patients (mean = 51.9 years; P = 0.0004). Histological grade and Nottingham prognostic index were higher in C2 and C3 than in C1 (P < 0.0001 for both comparisons). Significant event-free survival (P = 0.03) was found according to cluster membership: patients belonging to C3 had a better outcome than patients in C1 (P = 0.01) and C2 (P = 0.02). Event-free survival analysis results were confirmed when our cohort was pooled with the external cohort (n = 194; P = 0.01). Functional annotation showed that 22% of triple-negative patients were not basal-like (C1). C1 was enriched in luminal subtypes and positive androgen receptor (luminal androgen receptor). C2 could be considered as an almost pure basal-like cluster. C3, enriched in basal-like subtypes but to a lesser extent, included 26% of claudin-low subtypes. Dissection of immune response showed that high immune response and low M2-like macrophages were a hallmark of C3, and that these patients had a better event-free survival than C2 patients, characterized by low immune response and high M2-like macrophages: P = 0.02 for our cohort, and P = 0.03 for pooled cohorts. Conclusions: We identified three subtypes of triple-negative patients: luminal androgen receptor (22%), basal-like with low immune response and high M2-like macrophages (45%), and basal-enriched with high immune response and low M2-like macrophages (33%). We noted out that macrophages and other immune effectors offer a variety of therapeutic targets in breast cancer, and particularly in triple-negative basal-like tumours. Furthermore, we showed that CK5 antibody was better suited than CK5/6 antibody to subtype triple-negative patients.

Heterogeneity and lack of targeted therapies represent the two main impediments to precision treatment of triple-negative breast cancer (TNBC), and therefore, molecular subtyping and identification of therapeutic pathways are required to optimize medical care. The aim of the present study was to define robust TNBC subtypes with clinical relevance. Gene expression profiling by means of DNA chips was conducted in an internal TNBC cohort composed of 238 patients. In addition, external data (n = 257), obtained by using the same DNA chip, were used for validation. Fuzzy clustering was followed by functional annotation of the clusters. Immunohistochemistry was used to confirm transcriptomics results: CD138 and CD20 were used to test for plasma cell and B lymphocyte infiltrations, respectively; MECA79 and CD31 for tertiary lymphoid structures; and UCHL1/PGP9.5 and S100 for neurogenesis. We identified three molecular clusters within TNBC: one molecular apocrine (C1) and two basal-like-enriched (C2 and C3). C2 presented pro-tumorigenic immune response (immune suppressive), high neurogenesis (nerve infiltration), and high biological aggressiveness. In contrast, C3 exhibited adaptive immune response associated with complete B cell differentiation that occurs in tertiary lymphoid structures, and immune checkpoint upregulation. External cohort subtyping by means of the same approach proved the robustness of these results. Furthermore, plasma cell and B lymphocyte infiltrates, tertiary lymphoid structures, and neurogenesis were validated at the protein levels by means of histological evaluation and immunohistochemistry. Our work showed that TNBC can be subcategorized in three different subtypes characterized by marked biological features, some of which could be targeted by specific therapies.

Breast cancer biological characteristics change as age advances. Today, there is a lack of knowledge regarding age-specific molecular alterations that characterize breast tumours, notably in elderly patients. The vast majority of studies that aimed at exploring breast cancer in function of age are based on clinico-pathological data. Gene-expression signatures (GES), which in some ways capture biological information in a non-reductionist manner, represent powerful tools able to explore tumour heterogeneity. Twenty-five GES were used for functional annotation of breast tumours in function of age: five for molecular subtyping, seven for immune response, three for metabolism, seven for critical pathways in cancer and three for prognosis. Affymetrix® genomics datasets were exclusively used to avoid cross-platform normalization issues. Available corresponding clinico-pathological data were also retrieved and analysed. Fifteen publicly available datasets were pooled for a total of 2378 breast cancer patients (whole cohort), out of whom 1413 were of Caucasian origin. Three age groups were defined: ≤ 40 years (AG1), > 40 to < 70 years (AG2) and ≥ 70 years (AG3). We confirmed that age influenced the incidence of molecular subtypes. We found a significant growing incidence of luminal B and a decreasing kinetics for basal-like in function of age. We showed that AG3 luminal B tumours were less aggressive than AG1 luminal B tumours based on different GES (iron metabolism, mitochondrial oxidative phosphorylation and reactive stroma), recurrence score prognostic GES and histological grade (SBR). Contrary to tumours of young patients, tumours of elderly patients concentrated favourable GES scores: high oestrogen receptor and mitochondrial oxidative phosphorylation, low proliferation, basal-like, glycolysis, chromosomal instability and iron metabolism, and low GES prognostic scores (van’t Veer 70-GES, genomic grade index and recurrence score). Functional annotation of breast tumours by means of 25 GES demonstrated a decreasing aggressiveness of breast tumours in function of age. This strategy, which can be strengthened by increasing the number of representative GES to gain more insight into biological systems involved in this disease, provides a framework to develop rational therapeutic strategies in function of age.

Among glucocorticoids (GCs), dexamethasone (Dex) is widely used in treatment of multiple myelomas. However, despite a definite benefit, all patients relapse. Moreover, the molecular basis of glucocorticoid efficacy remains elusive. To determine genomic response to Dex in myeloma cells, we generated bulk and single-cell multi-omics data and high-resolution contact maps of active enhancers and target genes. We show that a minority of glucocorticoid receptor-binding sites are associated with enhancer activity gains, increased interaction loops, and transcriptional activity. We identified and characterized a predominant enhancer enriched in cohesin (RAD21) and more accessible upon Dex exposure. Analysis of four gene-specific networks revealed the importance of the CTCF–cohesin couple and the synchronization of regulatory sequence openings for efficient transcription in response to Dex. Notably, these epigenomic changes are associated with cell-to-cell transcriptional heterogeneity, in particular, lineage-specific genes. As consequences,BCL2L11-encoding BIM critical for Dex-induced apoptosis andCXCR4protective from chemotherapy-induced apoptosis are rather up-regulated in different cells. In summary, our work provides new insights into the molecular mechanisms involved in Dex escape.

Purpose: Neoadjuvant chemotherapy is now a common first line therapy for breast cancer. International guidelines recommend placement of a clip before commencement of therapy to assist with localizing the tumor bed in the event of excellent response—this takes up time and resources. The microcalcifications associated usually persist after chemotherapy and could serve as an alternative marker. We investigated to determine prognostic criteria to avoid the need for a marker clip before neoadjuvant chemotherapy for breast tumors associated with microcalcifications. Methods: We performed a 7 year single-center bi-site retrospective analytical observational study of 88 women with calcified breast carcinoma treated by neoadjuvant chemotherapy at our bi-site institution between September 2015 and September 2022. This study includied two groups (clip-free tumor localization vs. clip-free tumor non-localization), and investigating quantitative and qualitative predictive factors. The clip-free tumor localization after neoadjuvant chemotherapy was defined by the visibility of residual calcifications on both views of the pre-operative mammogram on the day of or the day prior to surgery. Results: The mean age of the 88 women included in our population was 52.8 years (± 12.7 years standard deviation). Of the 90 tumors with microcalcifications, 64 carcinomas (71.1%) were localizable with no marker clip after neoadjuvant chemotherapy. The main predictive factors significantly associated with clip-free tumor localization were number of calcifications > 10 (P < 0.0001), grade 2 tumor (P = 0.003) with a probability of locating tumor after neoadjuvant chemotherapy of 97.9%, 95% CI [95.6; 99.0]. Conclusion: More than 10 microcalcifications in a grade 2 breast tumor at the initial diagnosis may obviate the need for a marker clip.

Objectives This retrospective study aimed to assess the efficiency of consolidation chemotherapy after 6 cycles of neoadjuvant chemotherapy and delayed complete surgery on overall survival and progression-free survival among patients with advanced epithelial ovarian cancer. Methods This was a retrospective consecutive study with a propensity score to ensure balance for the baseline characteristics between the study groups. All patients treated for advanced ovarian cancer with 6 cycles of neoadjuvant chemotherapy followed by delayed complete surgery, without post-operative chemotherapy (group 1), or with post-operative chemotherapy (group 2), were included. We evaluated survival and the quality of cytoreductive surgery using the propensity score. Results From 2000 to 2017, 42 patients were included in group 1, and 59 in group 2. The median follow-up was 78 months (confidence interval (CI) 95% (60.1; not computable)). Neither progression-free survival nor overall survival were different between the two groups. The median progression-free survival was 10.2 months (CI 95% (8.8–17.0)) for group 1 and 10.4 months (CI 95% (7.9–12.8)) for group 2 (p=0.57). Five-year overall survival was 21.0% (CI 95% (10.4–42.3)) for group 1 and 26.1% (CI 95% (16.0–42.5)) for group 2 (p=0.73). Conclusions Adding cycles of consolidation chemotherapy after delayed surgery following 6 cycles of neoadjuvant chemotherapy did not demonstrate any survival improvement in patients treated for advanced ovarian cancer not amenable to primary or interval surgery.