Breast cancer is a heterogeneous disease comprising a variety of entities with various genetic backgrounds. Estrogen receptor-positive, human epidermal growth factor receptor 2-negative tumors typically have a favorable outcome; however, some patients eventually relapse, which suggests some heterogeneity within this category. In the present study, we used proteomics and miRNA profiling techniques to characterize a set of 102 either estrogen receptor-positive (ER+)/progesterone receptor-positive (PR+) or triple-negative formalin-fixed, paraffin-embedded breast tumors. Protein expression-based probabilistic graphical models and flux balance analyses revealed that some ER+/PR+ samples had a protein expression profile similar to that of triple-negative samples and had a clinical outcome similar to those with triple-negative disease. This probabilistic graphical model-based classification had prognostic value in patients with luminal A breast cancer. This prognostic information was independent of that provided by standard genomic tests for breast cancer, such as MammaPrint, OncoType Dx and the 8-gene Score.

Heterotrimers composed of B cell CLL/lymphoma 10 (BCL10), mucosa-associated lymphoid tissue lymphoma translocation protein 1 (MALT1), and caspase recruitment domain-containing (CARD) family adaptors play a role in NF-κB activation and have been shown to be involved in both the innate and the adaptive arms of immunity in murine models. Moreover, individuals with inherited defects of MALT1, CARD9, and CARD11 present with immunological and clinical phenotypes. Here, we characterized a case of autosomal-recessive, complete BCL10 deficiency in a child with a broad immunodeficiency, including defects of both hematopoietic and nonhematopoietic immunity. The patient died at 3 years of age and was homozygous for a loss-of-expression, loss-of-function BCL10 mutation. The effect of BCL10 deficiency was dependent on the signaling pathway, and, for some pathways, the cell type affected. Despite the noted similarities to BCL10 deficiency in mice, including a deficient adaptive immune response, human BCL10 deficiency in this patient resulted in a number of specific features within cell populations. Treatment of the patient's myeloid cells with a variety of pathogen-associated molecular pattern molecules (PAMPs) elicited a normal response; however, NF-κB-mediated fibroblast functions were dramatically impaired. The results of this study indicate that inherited BCL10 deficiency should be considered in patients with combined immunodeficiency with B cell, T cell, and fibroblast defects.

Better knowledge of the biology of breast cancer has allowed the use of new targeted therapies, leading to improved outcome. High-throughput technologies allow deepening into the molecular architecture of breast cancer, integrating different levels of information, which is important if it helps in making clinical decisions. microRNA (miRNA) and protein expression profiles were obtained from 71 estrogen receptor-positive (ER þ ) and 25 triple-negative breast cancer (TNBC) samples. RNA and proteins obtained from formalin-fixed, paraffin-embedded tumors were analyzed by RT-qPCR and LC/MS-MS, respectively. We applied probabilistic graphical models representing complex biologic systems as networks, confirming that ER þ and TNBC subtypes are distinct biologic entities. The integration of miRNA and protein expression data unravels molecular processes that can be related to differences in the genesis and clinical evolution of these types of breast cancer. Our results confirm that TNBC has a unique metabolic profile that may be exploited for therapeutic intervention. Cancer Res; 75(11); 2243-53. Ó2015 AACR.

A total of 192 pediatric patients, median age 8.6 years, with high-risk hematological malignancies, underwent haploidentical stem cell transplantation (haplo-HSCT) using post-transplantation cyclophosphamide (PT-Cy), or ex vivo T cell-depleted (TCD) graft platforms, from January 1999 to December 2016 in 10 centers in Spain. Some 41 patients received an unmanipulated graft followed by PT-Cy for graft-vs-host disease (GvHD) prophylaxis. A total of 151 patients were transplanted with CD3-depleted peripheral blood stem cells (PBSCs) by either CD34 + selection, CD3 + CD19 + depletion, TCRαβ + CD19 + depletion or CD45RA + depletion, added to CD34 + selection for GvHD prophylaxis. The PBSCs were the only source in patients

As of today two types of cartilage tumors remain a challenge even for the orthopedic oncologist: enchondroma (E), a benign tumor, and chondrosarcoma (LGC), a malignant and low aggressiveness tumor. A prospective study of 133 patients with a cartilaginous tumor of low aggressiveness in the long bones of the appendicular skeleton was done to prove this difficult differential diagnosis. Parameters including medical history and radiological and nuclear imaging were collected and compared to the result of the biopsy. A scale of aggressiveness was applied to each patient according to the number of aggressiveness episodes present. A comparison of the results of the biopsy with the initial diagnosis made by the orthopedic oncologist based solely on clinical data and imaging tests was also made. Finally, a management algorithm for these cases was proposed. A statistical significance for LGC resulted from the parameter as follows: pain on palpation, involvement of cortical in either the CT or MRI, and Tc99 bone scan uptake equal or superior to anterosuperior iliac crest. In our series, a tumor scoring 5 points or higher in the scale of aggressiveness can have 50% more chance of being LGC. When compared with the gold standard (the biopsy), surgeon's initial judgement showed a sensitivity of 73.5% and a specificity of 94.1%.

BackgroundTriple-negative breast cancer (TNBC) accounts for 15–20% of all breast cancers and usually requires the administration of adjuvant chemotherapy after surgery but even with this treatment many patients still suffer from a relapse. The main objective of this study was to identify proteomics-based biomarkers that predict the response to standard adjuvant chemotherapy, so that patients at are not going to benefit from it can be offered therapeutic alternatives.MethodsWe analyzed the proteome of a retrospective series of formalin-fixed, paraffin-embedded TNBC tissue applying high-throughput label-free quantitative proteomics. We identified several protein signatures with predictive value, which were validated with quantitative targeted proteomics in an independent cohort of patients and further evaluated in publicly available transcriptomics data.ResultsUsing univariate Cox analysis, a panel of 18 proteins was significantly associated with distant metastasis-free survival of patients (p<0.01). A reduced 5-protein profile with prognostic value was identified and its prediction performance was assessed in an independent targeted proteomics experiment and a publicly available transcriptomics dataset. Predictor P5 including peptides from proteins RAC2, RAB6A, BIEA and IPYR was the best performance protein combination in predicting relapse after adjuvant chemotherapy in TNBC patients.ConclusionsThis study identified a protein combination signature that complements histopathological prognostic factors in TNBC treated with adjuvant chemotherapy. The protein signature can be used in paraffin-embedded samples, and after a prospective validation in independent series, it could be used as predictive clinical test in order to recommend participation in clinical trials or a more exhaustive follow-up.

Triple-negative breast cancer is a heterogeneous disease characterized by a lack of hormonal receptors and HER2 overexpression. It is the only breast cancer subgroup that does not benefit from targeted therapies, and its prognosis is poor. Several studies have developed specific molecular classifications for triple-negative breast cancer. However, these molecular subtypes have had little impact in the clinical setting. Gene expression data and clinical information from 494 triple-negative breast tumors were obtained from public databases. First, a probabilistic graphical model approach to associate gene expression profiles was performed. Then, sparse k-means was used to establish a new molecular classification. Results were then verified in a second database including 153 triple-negative breast tumors treated with neoadjuvant chemotherapy. Clinical and gene expression data from 494 triple-negative breast tumors were analyzed. Tumors in the dataset were divided into four subgroups (luminal-androgen receptor expressing, basal, claudin-low and claudin-high), using the cancer stem cell hypothesis as reference. These four subgroups were defined and characterized through hierarchical clustering and probabilistic graphical models and compared with previously defined classifications. In addition, two subgroups related to immune activity were defined. This immune activity showed prognostic value in the whole cohort and in the luminal subgroup. The claudin-high subgroup showed poor response to neoadjuvant chemotherapy. Through a novel analytical approach we proved that there are at least two independent sources of biological information: cellular and immune. Thus, we developed two different and overlapping triple-negative breast cancer classifications and showed that the luminal immune-positive subgroup had better prognoses than the luminal immune-negative. Finally, this work paves the way for using the defined classifications as predictive features in the neoadjuvant scenario.

Metabolic reprogramming is a hallmark of cancer. It has been described that breast cancer subtypes present metabolism differences and this fact enables the possibility of using metabolic inhibitors as targeted drugs in specific scenarios. In this study, breast cancer cell lines were treated with metformin and rapamycin, showing a heterogeneous response to treatment and leading to cell cycle disruption. The genetic causes and molecular effects of this differential response were characterized by means of SNP genotyping and mass spectrometry-based proteomics. Protein expression was analyzed using probabilistic graphical models, showing that treatments elicit various responses in some biological processes such as transcription. Moreover, flux balance analysis using protein expression values showed that predicted growth rates were comparable with cell viability measurements and suggesting an increase in reactive oxygen species response enzymes due to metformin treatment. In addition, a method to assess flux differences in whole pathways was proposed. Our results show that these diverse approaches provide complementary information and allow us to suggest hypotheses about the response to drugs that target metabolism and their mechanisms of action.