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Identifying molecular alterations in normal tissue adjacent to cancer is important for understanding cancer aetiology and designing preventive measures. Here we analyse the DNA methylome of 569 breast tissue samples, including 50 from cancer-free women and 84 from matched normal cancer pairs. We use statistical algorithms for dissecting intra- and inter-sample cellular heterogeneity and demonstrate that normal tissue adjacent to breast cancer is characterized by tens to thousands of epigenetic alterations. We show that their genomic distribution is non-random, being strongly enriched for binding sites of transcription factors specifying chromatin architecture. We validate the field defects in an independent cohort and demonstrate that over 30% of the alterations exhibit increased enrichment within matched cancer samples. Breast cancers highly enriched for epigenetic field defects, exhibit adverse clinical outcome. Our data support a model where clonal epigenetic reprogramming towards reduced differentiation in normal tissue is an important step in breast carcinogenesis. Altered epigenetics is a feature of cancer but whether these changes occur early in tumour development is unclear. Here, the authors analyse methylation events in breast cancer and adjacent normal pairs, and show that methylation changes in the normal tissue are also found in the tumour, suggesting that some of these events occur early in cancer.

HER2-targeted treatments have improved outcomes in patients with HER2-positive breast cancer in the neoadjuvant, adjuvant, and metastatic settings; however, some patients remain at risk of relapse or death for many years after treatment of early-stage disease. Therefore, new strategies are needed. We did a phase 3 trial to assess a neoadjuvant regimen for HER2-positive breast cancer that replaces traditional systemic chemotherapy with targeted treatment. We did a randomised, open-label phase 3 KRISTINE trial in 68 Translational Research In Oncology centres (hospitals and specialty cancer centres in Asia, Europe, USA, and Canada). Eligible participants were aged 18 years or older with centrally confirmed HER2-positive stage II–III operable breast cancer (>2 cm tumour size), an Eastern Cooperative Oncology Group performance status of 0–1, and a baseline left ventricular ejection fraction of at least 55% (by echocardiogram or multiple-gated acquisition scan). We randomly assigned participants (1:1) to receive either trastuzumab emtansine plus pertuzumab or docetaxel, carboplatin, and trastuzumab plus pertuzumab. We did the randomisation via an interactive response system under a permuted block randomisation scheme (block size of four), stratified by hormone receptor status, stage at diagnosis, and geographical location. Patients received six cycles (every 3 weeks) of neoadjuvant trastuzumab emtansine plus pertuzumab (trastuzumab emtansine 3·6 mg/kg; pertuzumab 840 mg loading dose, 420 mg maintenance doses) or docetaxel, carboplatin, and trastuzumab plus pertuzumab (docetaxel 75 mg/m2; carboplatin area under the concentration–time curve 6 mg/mL × min; trastuzumab 8 mg/kg loading dose, 6 mg/kg maintenance doses) plus pertuzumab [same dosing as in the other group]). All treatments were administered intravenously. The primary objective was to compare the number of patients who achieved a pathological complete response (ypT0/is, ypN0), between groups in the intention-to-treat population (two-sided assessment), based on local evaluation of tumour samples taken at breast cancer surgery done between 14 days and 6 weeks after completion of neoadjuvant therapy. Safety was analysed in patients who received at least one dose of study medication. This trial is registered with ClinicalTrials.gov, number NCT02131064, and follow-up of the adjuvant phase is ongoing. Between June 25, 2014, and June 15, 2015, we randomly assigned 444 patients to neoadjuvant treatment with trastuzumab emtansine plus pertuzumab (n=223) or docetaxel, carboplatin, and trastuzumab plus pertuzumab (n=221). A pathological complete response was achieved by 99 (44·4%) of 223 patients in the trastuzumab emtansine plus pertuzumab group and 123 (55·7%) of 221 patients in the docetaxel, carboplatin, and trastuzumab plus pertuzumab group (absolute difference −11·3 percentage points, 95% CI −20·5 to −2·0; p=0·016). During neoadjuvant treatment, compared with patients receiving docetaxel, carboplatin, and trastuzumab plus pertuzumab, fewer patients receiving trastuzumab emtansine plus pertuzumab had a grade 3–4 adverse event (29 [13%] of 223 vs 141 [64%] of 219) or a serious adverse event (11 [5%] of 223 vs 63 [29%] of 219). The most common grade 3–4 adverse events in the trastuzumab emtansine plus pertuzumab group were decreased platelet count (three [1%] of 223 patients vs 11 [5%] of 219 with docetaxel, carboplatin, and trastuzumab plus pertuzumab), fatigue (three [1%] vs seven [3%]), alanine aminotransferase increase (three [1%] vs four [2%]), and hypokalaemia (three [1%] vs five [2%]). The most common grade 3–4 adverse events in the docetaxel, carboplatin, and trastuzumab plus pertuzumab group were neutropenia (55 [25%] of 219 vs one [<1%] of 223 with trastuzumab emtansine plus pertuzumab), diarrhoea (33 [15%] vs 2 [<1%]), and febrile neutropenia (33 [15%] vs 0). No deaths were reported during neoadjuvant treatment. Traditional neoadjuvant systemic chemotherapy plus dual HER2-targeted blockade (docetaxel, carboplatin, and trastuzumab plus pertuzumab) resulted in significantly more patients achieving a pathological complete response than HER2-targeted chemotherapy plus HER2-targeted blockade (trastuzumab emtansine plus pertuzumab); however, numerically more grade 3–4 and serious adverse events occurred in the chemotherapy plus trastuzumab and pertuzumab group. Further efforts to improve the efficacy of chemotherapy without imparting more toxicity are warranted. F Hoffmann-La Roche and Genentech.

Intraamniotic administration of a recombinant portion of ectodysplasin A to three fetuses with X-linked hypohydrotic ectodermal dysplasia (caused by mutations in the gene encoding ectodysplasin A) was followed by the birth of healthy infants who could sweat normally.

Breast cancer is a heterogeneous disease with distinct molecular subtypes including the aggressive subtype triple-negative breast cancer (TNBC). We compared blood-borne miRNA signatures of early-stage basal-like (cytokeratin-CK5-positive) TNBC patients to age-matched controls. The miRNAs of TNBC patients were assessed prior to and following platinum-based neoadjuvant chemotherapy (NCT). After an exploratory genome-wide study on 21 cases and 21 controls using microarrays, the identified signatures were verified independently in two laboratories on the same and a new cohort by RT-qPCR. We differentiated the blood of TNBC patients before NCT from controls with 84% sensitivity. The most significant miRNA for this diagnostic classification was miR-126-5p (two tailed t-test p-value of 1.4 × 10 −5 ). Validation confirmed the microarray results for all tested miRNAs. Comparing cancer patients prior to and post NCT highlighted 321 significant miRNAs (among them miR-34a, p-value of 1.2 × 10 −23 ). Our results also suggest that changes in miRNA expression during NCT may have predictive potential to predict pathological complete response (pCR). In conclusion we report that miRNA expression measured from blood facilitates early and minimally-invasive diagnosis of basal-like TNBC. We also demonstrate that NCT has a significant influence on miRNA expression. Finally, we show that blood-borne miRNA profiles monitored over time have potential to predict pCR.

MicroRNAs (miRNAs, miRs) are a class of small, non-coding RNA molecules with relevance as regulators of gene expression thereby affecting crucial processes in cancer development. MiRNAs offer great potential as biomarkers for cancer detection due to their remarkable stability in blood and their characteristic expression in many different diseases. We investigated whether microarray-based miRNA profiling on whole blood could discriminate between early stage breast cancer patients and healthy controls. We performed microarray-based miRNA profiling on whole blood of 48 early stage breast cancer patients at diagnosis along with 57 healthy individuals as controls. This was followed by a real-time semi-quantitative Polymerase Chain Reaction (RT-qPCR) validation in a separate cohort of 24 early stage breast cancer patients from a breast cancer screening unit and 24 age matched controls using two differentially expressed miRNAs (miR-202, miR-718). Using the significance level of p<0.05, we found that 59 miRNAs were differentially expressed in whole blood of early stage breast cancer patients compared to healthy controls. 13 significantly up-regulated miRNAs and 46 significantly down-regulated miRNAs in our microarray panel of 1100 miRNAs and miRNA star sequences could be detected. A set of 240 miRNAs that was evaluated by radial basis function kernel support vector machines and 10-fold cross validation yielded a specificity of 78.8%, and a sensitivity of 92.5%, as well as an accuracy of 85.6%. Two miRNAs were validated by RT-qPCR in an independent cohort. The relative fold changes of the RT-qPCR validation were in line with the microarray data for both miRNAs, and statistically significant differences in miRNA-expression were found for miR-202. MiRNA profiling in whole blood has potential as a novel method for early stage breast cancer detection, but there are still challenges that need to be addressed to establish these new biomarkers in clinical use.

Background The pathological complete response (pCR) after neoadjuvant chemotherapy is a surrogate marker for a favorable prognosis in breast cancer patients. Factors capable of predicting a pCR, such as the proliferation marker Ki67, may therefore help improve our understanding of the drug response and its effect on the prognosis. This study investigated the predictive and prognostic value of Ki67 in patients with invasive breast cancer receiving neoadjuvant treatment for breast cancer. Methods Ki67 was stained routinely from core biopsies in 552 patients directly after the fixation and embedding process. HER2/neu, estrogen and progesterone receptors, and grading were also assessed before treatment. These data were used to construct univariate and multivariate models for predicting pCR and prognosis. The tumors were also classified by molecular phenotype to identify subgroups in which predicting pCR and prognosis with Ki67 might be feasible. Results Using a cut-off value of > 13% positively stained cancer cells, Ki67 was found to be an independent predictor for pCR (OR 3.5; 95% CI, 1.4, 10.1) and for overall survival (HR 8.1; 95% CI, 3.3 to 20.4) and distant disease-free survival (HR 3.2; 95% CI, 1.8 to 5.9). The mean Ki67 value was 50.6 ± 23.4% in patients with pCR. Patients without a pCR had an average of 26.7 ± 22.9% positively stained cancer cells. Conclusions Ki67 has predictive and prognostic value and is a feasible marker for clinical practice. It independently improved the prediction of treatment response and prognosis in a group of breast cancer patients receiving neoadjuvant treatment. As mean Ki67 values in patients with a pCR were very high, cut-off values in a high range above which the prognosis may be better than in patients with lower Ki67 values may be hypothesized. Larger studies will be needed in order to investigate these findings further.

We investigated whether the integration of machine learning (ML) into MRI interpretation can provide accurate decision rules for the management of suspicious breast masses. A total of 173 consecutive patients with suspicious breast masses upon complementary assessment (BI-RADS IV/V: n = 100/76) received standardized breast MRI prior to histological verification. MRI findings were independently assessed by two observers (R1/R2: 5 years of experience/no experience in breast MRI) using six (semi-)quantitative imaging parameters. Interobserver variability was studied by ICC (intraclass correlation coefficient). A polynomial kernel function support vector machine was trained to differentiate between benign and malignant lesions based on the six imaging parameters and patient age. Ten-fold cross-validation was applied to prevent overfitting. Overall diagnostic accuracy and decision rules (rule-out criteria) to accurately exclude malignancy were evaluated. Results were integrated into a web application and published online. Malignant lesions were present in 107 patients (60.8%). Imaging features showed excellent interobserver variability (ICC: 0.81-0.98) with variable diagnostic accuracy (AUC: 0.65-0.82). Overall performance of the ML algorithm was high (AUC = 90.1%; BI-RADS IV: AUC = 91.6%). The ML algorithm provided decision rules to accurately rule-out malignancy with a false negative rate <1% in 31.3% of the BI-RADS IV cases. Thus, integration of ML into MRI interpretation can provide objective and accurate decision rules for the management of suspicious breast masses, and could help to reduce the number of potentially unnecessary biopsies.

Analysis of circulating cell-free DNA (ccfDNA) is a suitable tool for detecting somatic mutations for the purpose of making decisions on treatment, monitoring treatment response, and predicting survival. High-throughput techniques for ccfDNA extraction are essential to implementing ccfDNA testing in the clinical setting. We set out to compare two automated techniques with regard to hands-on time, ccfDNA output and integrity, and circulating mitochondrial DNA (mtDNA). CcfDNA was isolated using the EZ1&2 ccfDNA field test kit (EZ2 kit, QIAGEN) and the Maxwell RSC ccfDNA plasma kit (Maxwell kit, Promega). DNA was extracted from plasma of 30 breast cancer patients enrolled in the iMODE-B (#325_19B; 12.10.2020) study. Real-time PCR, fluorescence-based detection and automated electrophoresis were used to assess ccfDNA concentrations. The ccfDNA yield was significantly higher when extracted with the EZ2 kit. The EZ2 kit enabled the isolation of a higher proportion of short fragments and a lower proportion of long fragments, resulting in lower DNA integrity. Significantly lower mtDNA quantities were detected in the Maxwell eluate than in the EZ2 eluate. Thus, decisions on which extraction method to use should proceed on the basis of the required input for downstream applications, the anticipated fragment size and minimum hands-on time.

High‐grade serous ovarian carcinoma (HGSOC) associates with the worst patient outcome. Understanding the tumor environment in terms of quantifying endogenous retroviruses (ERVs) and LINE‐1 expression and their correlations with inflammation genes, checkpoint inhibitors and patient survival is needed. Analysis of 102 treatment‐naïve HGSOC and control tissues for ERVs, LINE‐1, inflammation and immune checkpoints identified five clusters with diverse patient recurrence‐free survivals. One cluster termed Triple‐I with the best patient survival showed the highest number of tumor infiltrating lymphocytes along with 22 overexpressed genes, including CXCL9 and AIM2. However, Triple‐I associated with the lowest ERV/LINE‐1 expression. The tumor cluster with the second‐best patient survival had both high ERV/LINE‐1 expression and inflammation. Multiplex‐immunohistochemistry revealed CD28 protein solely on immune cells, without co‐expression of the inhibitory CTLA4 receptor. The largest tumor cluster with high ERV/LINE‐1 expression but low inflammation showed a significant low gene expression of the dsRNA sensors MDA5 and RIG‐I supporting an aberrant block in IFN signaling. Our study represents an intrinsic ‘molecular and immunological snapshot’ of the HGSOC tumor environment important for understanding retroelements and inflammation for clinical relevance. Analysis of treatment‐naïve high‐grade serous ovarian carcinoma (HGSOC) and control tissues for ERVs, LINE‐1 (L1), inflammation, and immune checkpoints identified five clusters with diverse patient recurrence‐free survivals. An inflammation score was calculated and correlated with retroelement expression, where one novel cluster (Triple‐I) with high inflammation and the lowest retroelement expression (no viral mimicry) showed the best survival.

Purpose In 2008, the first gynecological cancer centres were certified by the German Cancer Society (DKG). Guideline-based quality Indicators (QIs) are a core element of the certification process. These QI are defined to assess the quality of care within the centres and can serve to measure the implementation of guideline recommendation. This article aims to give an overview of the developing and updating process of guideline based-QIs for women with cervical cancer and presents the QI results from the certified gynaecological cancer centres. Methods The QIs are derived in a multiple step review process and then implemented in the certification data sheet of the certified centres. The first set of QIs created in 2014 was revised in the update process of the S3-Guideline in 2020. QIs are based on strong recommendations of the evidence-based “Guideline for patients with Cervical Carcinoma” (registry-number: 032/033OL). Results In total, there are nine guideline-based QIs for cervical cancer. Four QIs are part of the certification process. In the treatment year 2020, 3.522 cases of cervical cancer were treated in 169 centers. The target values for the four QIs were met in at least 95% of the certified centers. In the guideline update in 2020, a new QI was added to the set of QIs “Complete pathological report on conization findings” and the QI “Exenteration” was removed. Conclusions QIs derived from strong recommendations of a guideline are an important tool to make essential parts of patient’s care measurable and enable the centers to draw consequences in process optimization. Over the years, the number of certified centers has grown, and the quality was improved. The certification systems is under constant revision to further improve patient’s care in the future, based on the results of the QI re-evaluation.