Basal breast carcinomas triple negative for estrogen receptors, progesterone receptors and Her2/neu breast carcinomas are more aggressive than conventional neoplasms. We studied 64 cases with immunohistochemistry, using 23 antibodies, to characterize diverse pathological pathways. A basal cytokeratin was identified in 81% of tumors and vimentin was identified in 55%. The mean Ki67 index was 46% (range, 10-90%). Coincident expression of p50 and p65, which suggests an active nuclear factor-jB factor, was present in 13% of neoplasms. Epithelial growth factor receptor (EGFR), insulin-like growth factor-I receptor (IGF-IR) or c-kit (CD117) was identified in 77% of tumors. Loss of protein tyrosine phosphatase was found in 14%, whereas Akt activation was present in 28%. Several differences were identified between two subtypes of basal breast carcinomas: the pure variant (negative S-100 and actin) was more frequently associated with 'in situ carcinoma' (P ¼ 0.019) and pBad overexpression (P ¼ 0.098), whereas the myoepithelial variant (positive S-100 or actin) showed more frequent tumor necrosis (P ¼ 0.048), vimentin expression (P ¼ 0.0001), CD117 expression (P ¼ 0.001) and activated caspase-3 (P ¼ 0.089). IGF-IR could be as important as EGFR for the growth of these neoplasms. Basal cell carcinoma has at least two subtypes with distinct microscopic and immunohistochemical features.
Oncogene addiction postulates that the survival and growth of certain tumor cells is dependent upon the activity of one oncogene, despite their multiple genetic and epigenetic abnormalities. This phenomenon provides a foundation for molecular targeted therapy and a rationale for oncogene-based stratification. We have previously reported that the Promyelocytic Leukemia protein (PML) is upregulated in triple negative breast cancer (TNBC) and it regulates cancer-initiating cell function, thus suggesting that this protein can be therapeutically targeted in combination with PML-based stratification. However, the effects of PML perturbation on the bulk of tumor cells remained poorly understood. Here we demonstrate that TNBC cells are addicted to the expression of this nuclear protein. PML inhibition led to a remarkable growth arrest combined with features of senescence in vitro and in vivo. Mechanistically, the growth arrest and senescence were associated to a decrease in MYC and PIM1 kinase levels, with the subsequent accumulation of CDKN1B (p27), a trigger of senescence. In line with this notion, we found that PML is associated to the promoter regions of MYC and PIM1, consistent with their direct correlation in breast cancer specimens. Altogether, our results provide a feasible explanation for the functional similarities of MYC, PIM1, and PML in TNBC and encourage further study of PML targeting strategies for the treatment of this breast cancer subtype.
25The dysregulation of gene expression is an enabling hallmark of cancer. Computational analysis of 26 transcriptomics data from human cancer specimens, complemented with exhaustive clinical annotation, 27provides an opportunity to identify core regulators of the tumorigenic process. Here we exploit well-28 annotated clinical datasets of prostate cancer for the discovery of transcriptional regulators relevant to 29 prostate cancer. Following this rationale, we identify Microphthalmia-associated transcription factor 30 (MITF) as a prostate tumor suppressor among a subset of transcription factors. Importantly, we further 31 interrogate transcriptomics and clinical data to refine MITF perturbation-based empirical assays and 32 unveil Crystallin Alpha B (CRYAB) as an unprecedented direct target of the transcription factor that is, 33 at least in part, responsible for its tumor suppressive activity in prostate cancer. This evidence was 34 supported by the enhanced prognostic potential of a signature based on the concomitant alteration of 35 MITF and CRYAB in prostate cancer patients. In sum, our study provides proof-of-concept evidence of 36 the potential of the bioinformatics screen of publicly available cancer patient databases as discovery 37 platforms, and demonstrates that the MITF-CRYAB axis controls prostate cancer biology. 38 39 have demonstrated that deregulation of gene expression is a key node for cancer pathogenesis and 48 progression (2-6). Prostate cancer (PCa) research exemplifies the effort in deciphering the genomics 49 and transcriptomics landscape of tumors, and extremely valuable data has been generated (7-13). In 50 spite of the public availability of these relevant data, they are still underexploited by the scientific 51 community to understand PCa biology. In this regard, the computational tools and dataset selection 52 strategies to carry out these studies are a bottleneck for the cancer research field. 53By combining integrated-bioinformatics screening of clinically relevant PCa datasets with in vivo and in 54 vitro molecular biology assays, we have recently described the metastasis suppressor activity of 55 Peroxisome proliferator-activated receptor γ (PPARγ) coactivator alpha (PGC1α) (14, 15). This 56 transcriptional coactivator is a major regulator of mitochondrial biogenesis and function, and has an 57 inherent capacity to integrate environmental signals and cellular energetic demands. This ability 58 empowers PGC1α to be a driver in shaping responses to metabolic stress during different physiologic 59 and tumorigenic processes (16). As might be expected due to its fundamental role in normal and cancer 60 scenarios, the regulation of PGC1α expression, from the genomic to the protein level, is complex and 61 dynamic (17). At the level of mRNA expression, one of the well-defined direct regulators of PGC1αis 62 the Microphthalmia-associated transcription factor (MITF) (18). 63MITF is a basic helix-loop-helix leucine zipper (bHLHZIP) transcription factor that regulates the 64 expression of lin...
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