How many etiological subtypes of breast cancer: two, three, four, or more?

Breast cancer is a heterogeneous disease, divisible into a variable number of clinical subtypes. A fundamental question is how many etiological classes underlie the clinical spectrum of breast cancer? An etiological subtype reflects a grouping with a common set of causes, whereas a clinical subtype represents a grouping with similar prognosis and/or prediction. Herein, we review the evidence for breast cancer etiological heterogeneity. We then evaluate the etiological evidence with mRNA profiling data. A bimodal age distribution at diagnosis with peak frequencies near ages 50 and 70 years is a fundamental characteristic of breast cancer for important tumor features, clinical characteristics, risk factor profiles, and molecular subtypes. The bimodal peak frequencies at diagnosis divide breast cancer overall into a 'mixture' of two main components in varying proportions in different cancer populations. The first breast cancer tends to arise early in life with modal age-at-diagnosis near 50 years and generally behaves aggressively. The second breast cancer occurs later in life with modal age near 70 years and usually portends a more indolent clinical course. These epidemiological and molecular data are consistent with a two-component mixture model and compatible with a hierarchal view of breast cancers arising from two main cell types of origin. Notwithstanding the potential added value of more detailed categorizations for personalized breast cancer treatment, we suggest that the development of better criteria to identify the two proposed etiologic classes would advance breast cancer research and prevention

The altered transcriptome and DNA methylation profiles of docetaxel resistance in breast cancer PDX models

Taxanes are standard therapy in clinical practice for metastatic breast cancer; however, primary or acquired chemoresistance are a common cause of mortality. Breast cancer patient-derived xenografts (PDX) are powerful tools for the study of cancer biology and drug treatment response. Specific DNA methylation patterns have been associated to different breast cancer subtypes but its association with chemoresistance remains unstudied. Aiming to elucidate docetaxel resistance mechanisms, we performed genome-wide DNA methylation in breast cancer PDX models, including luminal and triple-negative breast cancer (TNBC) models sensitive to docetaxel, their matched models after emergence of chemoresistance and residual disease after short-term docetaxel treatment. We found that DNA methylation profiles from breast cancer PDX models maintain the subtype-specific methylation patterns of clinical samples. Two main DNA methylation clusters were found in TNBC PDX and remain stable during the emergence of docetaxel resistance; however, some genes/pathways were differentially methylated according to docetaxel response. A DNA methylation signature of resistance able to segregate TNBC based on chemotherapy response was identified. Transcriptomic profiling of selected sensitive/resistant pairs and integrative analysis with methylation data demonstrated correlation between some differentially methylated and expressed genes in docetaxel-resistant TNBC PDX models. Multiple gene expression changes were found after the emergence of docetaxel resistance in TNBC. DNA methylation and transcriptional changes identified between docetaxel-sensitive and -resistant TNBC PDX models or residual disease may have predictive value for chemotherapy response in TNBC. IMPLICATIONS: Subtype-specific DNA methylation patterns are maintained in breast cancer PDX models. While no global methylation changes were found, we uncovered differentially DNA methylated and expressed genes/pathways associated with the emergence of docetaxel resistance in TNBC

Determinants of activity and efficacy of anti-PD1/PD-L1 therapy in patients with advanced solid tumors recruited in a clinical trials unit: a longitudinal prospective biomarker-based study

Immune-checkpoint inhibitors (ICI) have revolutionized the therapeutic landscape of cancer. However, optimal patient selection is still an unmet need. One-hundred-forty-six patients with metastatic cancer candidates to ICI at the Hospital Clinic of Barcelona Clinical Trials Unit were prospectively recruited in this observational study. Blood samples were collected at different timepoints, baseline LIPI score calculated and pre-ICI archived tissues retrieved to evaluate PD-L1, tumor-infiltrating lymphocytes (TILs) and PD1 mRNA levels. Tumor assessments were centrally reviewed by RECIST 1.1 criteria. Associations with overall response rates (ORR), durable clinical benefit (DCB), progression-free survival (PFS) and overall survival (OS) were performed with univariable/multivariable logistic and Cox regressions, where appropriate. At a median follow-up of 26.9 months, median PFS and OS were 2.7 and 12.9 months. Response rates were 17.8% with duration of response (DOR) of 4.4 months. LIPI score was independently associated with PFS (p = 0.025) and OS (p < 0.001). Immunotherapy-naïve status was independently associated with better PFS (p = 0.005). Time-to-best response (TTBR) and ORR (p < 0.001 both) were associated with better OS at univariate analysis. PFS and DOR were moderately correlated with OS (p < 0.001 both). A PD-L1 10% cut-off detected worse/best responders in terms of ORR (univariate p = 0.011, multivariate p = 0.028) and DCB (univariate p = 0.043). PD1 mRNA levels were strikingly associated to complete responses (p = 0.021). To resume, in our prospective observational pan-cancer study, baseline LIPI score, immunotherapy-naïve status, cancer type and RT before starting ICI were the most relevant clinical factors independently correlated with immunotherapy outcomes. Longer TTBR seemed to associate with better survival, while PD1 mRNA and PD-L1 protein levels might be tumor-agnostic predictive factors of response to ICI and should be furtherly explored

Immune microenvironment characterisation and dynamics during anti-HER2-based neoadjuvant treatment in HER2-positive breast cancer

Despite their recognised role in HER2-positive (HER2+) breast cancer (BC), the composition, localisation and functional orientation of immune cells within tumour microenvironment, as well as its dynamics during anti-HER2 treatment, is largely unknown. We here investigate changes in tumour-immune contexture, as assessed by stromal tumour-infiltrating lymphocytes (sTILs) and by multiplexed spatial cellular phenotyping, during treatment with lapatinib-trastuzumab in HER2+ BC patients (PAMELA trial). Moreover, we evaluate the relationship of tumour-immune contexture with hormone receptor status, intrinsic subtype and immune-related gene expression. sTIL levels increase after 2 weeks of HER2 blockade in HR-negative disease and HER2-enriched subtype. This is linked to a concomitant increase in cell density of all four immune subpopulations (CD3+, CD4+, CD8+, Foxp3+). Moreover, immune contexture analysis showed that immune cells spatially interacting with tumour cells have the strongest association with response to anti-HER2 treatment. Subsequently, sTILs consistently decrease at the surgery in patients achieving pathologic complete response, whereas most residual tumours at surgery remain inflamed, possibly reflecting a progressive loss of function of T cells. Understanding the features of the resulting tumour immunosuppressive microenvironment has crucial implications for the design of new strategies to de-escalate or escalate systemic therapy in early-stage HER2+ BC

Human selenoprotein P and S variant mRNAs with different numbers of SECIS elements and inferences from mutant mice of the roles of multiple SECIS elements

Dynamic redefinition of the 10 UGAs in human and mouse selenoprotein P (Sepp1) mRNAs to specify selenocysteine instead of termination involves two 3′ UTR structural elements (SECIS) and is regulated by selenium availability. In addition to the previously known human Sepp1 mRNA poly(A) addition site just 3′ of SECIS 2, two further sites were identified with one resulting in 10–25% of the mRNA lacking SECIS 2. To address function, mutant mice were generated with either SECIS 1 or SECIS 2 deleted or with the first UGA substituted with a serine codon. They were fed on either high or selenium-deficient diets. The mutants had very different effects on the proportions of shorter and longer product Sepp1 protein isoforms isolated from plasma, and on viability. Spatially and functionally distinctive effects of the two SECIS elements on UGA decoding were inferred. We also bioinformatically identify two selenoprotein S mRNAs with different 5′ sequences predicted to yield products with different N-termini. These results provide insights into SECIS function and mRNA processing in selenoprotein isoform diversity

Lunatic Fringe Deficiency Cooperates with the Met/Caveolin Gene Amplicon to Induce Basal-Like Breast Cancer

Basal-like breast cancers (BLBC) express a luminal progenitor gene signature. Notch receptor signaling promotes luminal cell fate specification in the mammary gland, while suppressing stem cell self-renewal. Here we show that deletion of Lfng, a sugar transferase that prevents Notch activation by Jagged ligands, enhances stem/progenitor cell proliferation. Mammary-specific deletion of Lfng induces basal-like and claudin-low tumors with accumulation of Notch intracellular domain fragments, increased expression of proliferation-associated Notch targets, amplification of the Met/Caveolin locus, and elevated Met and Igf-1R signaling. Human BL breast tumors, commonly associated with JAGGED expression, elevated MET signaling, and CAVEOLIN accumulation, express low levels of LFNG. Thus, reduced LFNG expression facilitates JAG/NOTCH luminal progenitor signaling and cooperates with MET/CAVEOLIN basal-type signaling to promote BLBC

Management and outcomes of gastrointestinal congenital anomalies in low, middle and high income countries: Protocol for a multicentre, international, prospective cohort study

Introduction Congenital anomalies are the fifth leading cause of death in children <5 years of age globally, contributing an estimated half a million deaths per year. Very limited literature exists from low and middle income countries (LMICs) where most of these deaths occur. The Global PaedSurg Research Collaboration aims to undertake the first multicentre, international, prospective cohort study of a selection of common congenital anomalies comparing management and outcomes between low, middle and high income countries (HICs) globally. Methods and analysis The Global PaedSurg Research Collaboration consists of surgeons, paediatricians, anaesthetists and allied healthcare professionals involved in the surgical care of children globally. Collaborators will prospectively collect observational data on consecutive patients presenting for the first time, with one of seven common congenital anomalies (oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation and Hirschsprung''s disease). Patient recruitment will be for a minimum of 1 month from October 2018 to April 2019 with a 30-day post-primary intervention follow-up period. Anonymous data will be collected on patient demographics, clinical status, interventions and outcomes using REDCap. Collaborators will complete a survey regarding the resources and facilities for neonatal and paediatric surgery at their centre. The primary outcome is all-cause in-hospital mortality. Secondary outcomes include the occurrence of postoperative complications. Chi-squared analysis will be used to compare mortality between LMICs and HICs. Multilevel, multivariate logistic regression analysis will be undertaken to identify patient-level and hospital-level factors affecting outcomes with adjustment for confounding factors. Ethics and dissemination At the host centre, this study is classified as an audit not requiring ethical approval. All participating collaborators have gained local approval in accordance with their institutional ethical regulations. Collaborators will be encouraged to present the results locally, nationally and internationally. The results will be submitted for open access publication in a peer reviewed journal

Patient-derived xenograft (PDX) models in basic and translational breast cancer research

Patient-derived xenograft (PDX) models of a growing spectrum of cancers are rapidly supplanting long-established traditional cell lines as preferred models for conducting basic and translational preclinical research. In breast cancer, to complement the now curated collection of approximately 45 long-established human breast cancer cell lines, a newly formed consortium of academic laboratories, currently from Europe, Australia, and North America, herein summarizes data on over 500 stably transplantable PDX models representing all three clinical subtypes of breast cancer (ER+, HER2+, and "Triple-negative" (TNBC)). Many of these models are well-characterized with respect to genomic, transcriptomic, and proteomic features, metastatic behavior, and treatment response to a variety of standard-of-care and experimental therapeutics. These stably transplantable PDX lines are generally available for dissemination to laboratories conducting translational research, and contact information for each collection is provided. This review summarizes current experiences related to PDX generation across participating groups, efforts to develop data standards for annotation and dissemination of patient clinical information that does not compromise patient privacy, efforts to develop complementary data standards for annotation of PDX characteristics and biology, and progress toward "credentialing" of PDX models as surrogates to represent individual patients for use in preclinical and co-clinical translational research. In addition, this review highlights important unresolved questions, as well as current limitations, that have hampered more efficient generation of PDX lines and more rapid adoption of PDX use in translational breast cancer research