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Triple-negative breast cancer is a heterogeneous disease and specific therapies have not been available for a long time. Therefore, conventional chemotherapy is still considered the clinical state of the art. Different subgroups of triple-negative breast cancer have been identified on the basis of protein expression, mRNA signatures, and genomic alterations. Important elements of triple-negative breast cancer biology include high proliferative activity, an increased immunological infiltrate, a basal-like and a mesenchymal phenotype, and deficiency in homologous recombination, which is in part associated with loss of BRCA1 or BRCA2 function. A minority of triple-negative tumours express luminal markers, such as androgen receptors, and have a lower proliferative activity. These biological subgroups are overlapping and currently cannot be combined into a unified model of triple-negative breast cancer biology. Nevertheless, the molecular analysis of this disease has identified potential options for targeted therapeutic intervention. This has led to promising clinical strategies, including modified chemotherapy approaches targeting the DNA damage response, angiogenesis inhibitors, immune checkpoint inhibitors, or even anti-androgens, all of which are being evaluated in phase 1–3 clinical studies. This Series paper focuses on the most relevant clinical questions, summarises the results of recent clinical trials, and gives an overview of ongoing studies and trial concepts that will lead to a more refined therapy for this tumour type.

The addition of pembrolizumab to platinum-based neoadjuvant chemotherapy significantly increased the percentage of patients with a pathological complete response among patients with locally advanced triple-negative breast cancer. Side effects of the immunotherapy were added to the usual toxic effects of chemotherapy, but most patients completed planned treatment.

Altered expression and function of the transcription factor cyclic AMP response-binding protein (CREB) has been identified to play an important role in cancer and is associated with the overall survival and therapy response of tumor patients. This review focuses on the expression and activation of CREB under physiologic conditions and in tumors of distinct origin as well as the underlying mechanisms of CREB regulation by diverse stimuli and inhibitors. In addition, the clinical relevance of CREB is summarized, including its use as a prognostic and/or predictive marker as well as a therapeutic target.

Key Points The detection of tumour-infiltrating lymphocytes (TILs) on routine histology constitutes a robust prognostic and predictive biomarker in patients with early stage breast cancer, despite the complexity of host antitumour immunity Ongoing efforts to ensure reliable and reproducible reporting of TILs will facilitate their use in the routine management of breast cancer Exploiting the antitumour immune response in breast cancer for therapeutic benefit is currently an area of active research Early phase trials of antibodies that target programmed cell-death protein 1 (PD-1) and PD1 ligand 1 in patients with metastatic triple-negative breast cancer have shown promising and durable responses Useful biomarkers to predict benefit from immunotherapy are urgently needed — TILs might fulfil this role The presence of tumour-infiltrating lymphocytes (TILs) in breast tumours is related to a better prognosis in patients with early stage breast cancer, but the immunobiology of breast cancer remains to be well-characterized. In this Review, the authors discuss how to measure TIL-related parameters in the clinic, as well as their value as a prognostic and predictive biomarker in breast cancer. The rationale for enhancing immunity in breast cancer is also examined. The clinical relevance of the host immune system in breast cancer has long been unexplored. Studies developed over the past decade have highlighted the biological heterogeneity of breast cancer, prompting researchers to investigate whether the role of the immune system in this malignancy is similar across different molecular subtypes of the disease. The presence of high levels of lymphocytic infiltration has been consistently associated with a more-favourable prognosis in patients with early stage triple-negative and HER2-positive breast cancer. These infiltrates seem to reflect favourable host antitumour immune responses, suggesting that immune activation is important for improving survival outcomes. In this Review, we discuss the composition of the immune infiltrates observed in breast cancers, as well as data supporting the clinical relevance of host antitumour immunity, as represented by lymphocytic infiltration, and how this biomarker could be used in the clinical setting. We also discuss the rationale for enhancing immunity in breast cancer, including early data on the efficacy of T-cell checkpoint inhibition in this setting.

Increased stiffness of solid tissues has long been recognized as a diagnostic feature of several pathologies, most notably malignant diseases. In fact, it is now well established that elevated tissue rigidity enhances disease progression and aggressiveness and is associated with a poor prognosis in patients as documented, for instance, for lung fibrosis or the highly desmoplastic cancer of the pancreas. The underlying mechanisms of the interplay between physical properties and cellular behavior are, however, not very well understood. Here, we have found that switching culture conditions from soft to stiff substrates is sufficient to evoke (macro) autophagy in various fibroblast types. Mechanistically, this is brought about by stiffness-sensing through an Integrin αV–focal adhesion kinase module resulting in sequestration and posttranslational stabilization of the metabolic master regulator AMPKα at focal adhesions, leading to the subsequent induction of autophagy. Importantly, stiffness-induced autophagy in stromal cells such as fibroblasts and stellate cells critically supports growth of adjacent cancer cells in vitro and in vivo. This process is Integrin αV dependent, opening possibilities for targeting tumor-stroma crosstalk. Our data thus reveal that the mere change in mechanical tissue properties is sufficient to metabolically reprogram stromal cell populations, generating a tumor-supportive metabolic niche.

Recent advances in cancer research and diagnostics largely rely on new developments in microscopic or molecular profiling techniques, offering high levels of detail with respect to either spatial or molecular features, but usually not both. Here, we present an explainable machine-learning approach for the integrated profiling of morphological, molecular and clinical features from breast cancer histology. First, our approach allows for the robust detection of cancer cells and tumour-infiltrating lymphocytes in histological images, providing precise heatmap visualizations explaining the classifier decisions. Second, molecular features, including DNA methylation, gene expression, copy number variations, somatic mutations and proteins are predicted from histology. Molecular predictions reach balanced accuracies up to 78%, whereas accuracies of over 95% can be achieved for subgroups of patients. Finally, our explainable AI approach allows assessment of the link between morphological and molecular cancer properties. The resulting computational multiplex-histology analysis can help promote basic cancer research and precision medicine through an integrated diagnostic scoring of histological, clinical and molecular features. Cancers are complex diseases that are increasingly studied using a diverse set of omics data. At the same time, histological images show the interaction of cells, which is not visible with bulk omics methods. Binder and colleagues present a method to learn from both kinds of data, such that molecular markers can be associated with visible patterns in the tissue samples and be used for more accurate breast cancer diagnosis.

Validating prognostic or predictive candidate genes in appropriately powered breast cancer cohorts are of utmost interest. Our aim was to develop an online tool to draw survival plots, which can be used to assess the relevance of the expression levels of various genes on the clinical outcome both in untreated and treated breast cancer patients. A background database was established using gene expression data and survival information of 1,809 patients downloaded from GEO (Affymetrix HGU133A and HGU133+2 microarrays). The median relapse free survival is 6.43 years, 968/1,231 patients are estrogen-receptor (ER) positive, and 190/1,369 are lymph-node positive. After quality control and normalization only probes present on both Affymetrix platforms were retained ( n  = 22,277). In order to analyze the prognostic value of a particular gene, the cohorts are divided into two groups according to the median (or upper/lower quartile) expression of the gene. The two groups can be compared in terms of relapse free survival, overall survival, and distant metastasis free survival. A survival curve is displayed, and the hazard ratio with 95% confidence intervals and logrank P value are calculated and displayed. Additionally, three subgroups of patients can be assessed: systematically untreated patients, endocrine-treated ER positive patients, and patients with a distribution of clinical characteristics representative of those seen in general clinical practice in the US. Web address: www.kmplot.com . We used this integrative data analysis tool to confirm the prognostic power of the proliferation-related genes TOP2A and TOP2B , MKI67 , CCND2 , CCND3 , CCNDE2 , as well as CDKN1A , and TK2 . We also validated the capability of microarrays to determine estrogen receptor status in 1,231 patients. The tool is highly valuable for the preliminary assessment of biomarkers, especially for research groups with limited bioinformatic resources.

Gene or protein expression data are usually represented by metric or at least ordinal variables. In order to translate a continuous variable into a clinical decision, it is necessary to determine a cutoff point and to stratify patients into two groups each requiring a different kind of treatment. Currently, there is no standard method or standard software for biomarker cutoff determination. Therefore, we developed Cutoff Finder, a bundle of optimization and visualization methods for cutoff determination that is accessible online. While one of the methods for cutoff optimization is based solely on the distribution of the marker under investigation, other methods optimize the correlation of the dichotomization with respect to an outcome or survival variable. We illustrate the functionality of Cutoff Finder by the analysis of the gene expression of estrogen receptor (ER) and progesterone receptor (PgR) in breast cancer tissues. This distribution of these important markers is analyzed and correlated with immunohistologically determined ER status and distant metastasis free survival. Cutoff Finder is expected to fill a relevant gap in the available biometric software repertoire and will enable faster optimization of new diagnostic biomarkers. The tool can be accessed at http://molpath.charite.de/cutoff.

Bevacizumab added to neoadjuvant combination chemotherapy increased the rate of pathological complete response among patients with HER-2-negative early-stage breast cancer. The effect was greatest in patients with the poorest prognosis, those with so-called triple-negative tumors. The efficacy of neoadjuvant chemotherapy, as measured by the rate of pathological complete response (the absence of invasive and intraductal disease in the breast and the axillary lymph nodes), varies according to breast-cancer subtype. 1 When anthracyclines, taxanes, and agents directed against anti–human epidermal growth factor receptor 2 (HER2) (if indicated) are used, approximately 30 to 40% of all breast cancers that are HER2-positive or triple-negative (estrogen-receptor–negative, progesterone-receptor–negative, and no overexpression of HER2) are completely eradicated locally at the time of surgery. 2 – 6 Long-term follow-up studies have shown a consistent correlation between pathological complete response and low rates of relapse and . . .

Tumour-infiltrating lymphocytes (TILs) are predictive for response to neoadjuvant chemotherapy in triple-negative breast cancer (TNBC) and HER2-positive breast cancer, but their role in luminal breast cancer and the effect of TILs on prognosis in all subtypes is less clear. Here, we assessed the relevance of TILs for chemotherapy response and prognosis in patients with TNBC, HER2-positive breast cancer, and luminal–HER2-negative breast cancer. Patients with primary breast cancer who were treated with neoadjuvant combination chemotherapy were included from six randomised trials done by the German Breast Cancer Group. Pretherapeutic core biopsies from 3771 patients included in these studies were assessed for the number of stromal TILs by standardised methods according to the guidelines of the International TIL working group. TILs were analysed both as a continuous parameter and in three predefined groups of low (0–10% immune cells in stromal tissue within the tumour), intermediate (11–59%), and high TILs (≥60%). We used these data in univariable and multivariable statistical models to assess the association between TIL concentration and pathological complete response in all patients, and between the amount of TILs and disease-free survival and overall survival in 2560 patients from five of the six clinical trial cohorts. In the luminal–HER2-negative breast cancer subtype, a pathological complete response (pCR) was achieved in 45 (6%) of 759 patients with low TILs, 48 (11%) of 435 with intermediate TILs, and 49 (28%) of 172 with high TILs. In the HER2-positive subtype, pCR was observed in 194 (32%) of 605 patients with low TILs, 198 (39%) of 512 with intermediate TILs, and 127 (48%) of 262 with high TILs. Finally, in the TNBC subtype, pCR was achieved in 80 (31%) of 260 patients with low TILs, 117 (31%) of 373 with intermediate TILs, and 136 (50%) of 273 with high TILs (p<0·0001 for each subtype, χ2 test for trend). In the univariable analysis, a 10% increase in TILs was associated with longer disease-free survival in TNBC (hazard ratio [HR] 0·93 [95% CI 0·87–0·98], p=0·011) and HER2-positive breast cancer (0·94 [0·89–0·99], p=0·017), but not in luminal–HER2-negative tumours (1·02 [0·96–1·09], p=0·46). The increase in TILs was also associated with longer overall survival in TNBC (0·92 [0·86–0·99], p=0·032), but had no association in HER2-positive breast cancer (0·94 [0·86–1·02], p=0·11), and was associated with shorter overall survival in luminal–HER2-negative tumours (1·10 [1·02–1·19], p=0·011). Increased TIL concentration predicted response to neoadjuvant chemotherapy in all molecular subtypes assessed, and was also associated with a survival benefit in HER2-positive breast cancer and TNBC. By contrast, increased TILs were an adverse prognostic factor for survival in luminal–HER2-negative breast cancer, suggesting a different biology of the immunological infiltrate in this subtype. Our data support the hypothesis that breast cancer is immunogenic and might be targetable by immune-modulating therapies. In light of the results in luminal breast cancer, further research investigating the interaction of the immune system with different types of endocrine therapy is warranted. Deutsche Krebshilfe and European Commission.