Stage I epithelial ovarian cancer (EOC) represents about 10% of all EOCs and is characterized by good prognosis with fewer than 20% of patients relapsing. As it occurs less frequently than ...advanced-stage EOC, its molecular features have not been thoroughly investigated. We have demonstrated that in stage I EOC
can predict patients' outcome. In the present study, we analyzed the expression of long non-coding RNAs (lncRNA) to enable potential definition of a non-coding transcriptional signature with prognostic relevance for stage I EOC.
202 snap-frozen stage I EOC tumor biopsies, 47 of which relapsed, were gathered together from three independent tumor tissue collections and subdivided into a training set (
= 73) and a validation set (
= 129). Median follow up was 9 years. LncRNAs' expression profiles were correlated in univariate and multivariate analysis with overall survival (OS) and progression-free survival (PFS).
The expression of
-
, and
was associated in univariate and multivariate analyses with relapse and poor outcome in both training and validation sets (
< 0.001). Using the expression profiles of
-
, and
simultaneously, it was possible to stratify patients into high and low risk. The OS for high- and low-risk individuals are 36 and 123 months, respectively (OR, 15.55; 95% confidence interval, 3.81-63.36).
We have identified a non-coding transcriptional signature predictor of survival and biomarker of relapse for stage I EOC.
.
In vivo use of monoclonal antibodies (mAbs) has become a mainstay of routine clinical practice in the treatment of various human diseases. A number of molecules can serve as targets, according to the ...condition being treated. Now entering human clinical trials, CD38 molecule is a particularly attractive target because of its peculiar pattern of expression and its twin role as receptor and ectoenzyme. This review provides a range of analytical perspectives on the current progress in and challenges to anti-CD38 mAb therapy. We present a synopsis of the evidence available on CD38, particularly in myeloma and chronic lymphocytic leukemia (CLL). Our aim is to make the data from basic science helpful and accessible to a diverse clinical audience and, at the same time, to improve its potential for in vivo use. The topics covered include tissue distribution and signal implementation by mAb ligation and the possibility of increasing cell density on target cells by exploiting information about the molecule's regulation in combination with drugs approved for in vivo use. Also analyzed is the behavior of CD38 as an enzyme: CD38 is a component of a pathway leading to the production of adenosine in the tumor microenvironment, thus inducing local anergy. Consequently, not only might CD38 be a prime target for mAb-mediated therapy, but its functional block may contribute to general improvement in cancer immunotherapy and outcomes.
iASPP, an inhibitory member of the ASPP (apoptosis stimulating protein of p53) family, is an evolutionarily conserved inhibitor of p53 which is frequently upregulated in human cancers. However, ...little is known about the role of iASPP under physiological conditions. Here, we report that iASPP is a critical regulator of epithelial development. We demonstrate a novel autoregulatory feedback loop which controls crucial physiological activities by linking iASPP to p63, via two previously unreported microRNAs, miR‐574‐3p and miR‐720. By investigating its function in stratified epithelia, we show that iASPP participates in the p63‐mediated epithelial integrity program by regulating the expression of genes essential for cell adhesion. Silencing of iASPP in keratinocytes by RNA interference promotes and accelerates a differentiation pathway, which also affects and slowdown cellular proliferation. Taken together, these data reveal iASPP as a key regulator of epithelial homeostasis.
This manuscript identifies an essential role for the p53 inhibitor iASPP in keratinocyte biology. By regulating two new microRNAs, iASPP controls p63, a key transcriptional regulator for the formation of stratified epithelia.
In meningioma recurrences a tumor progression has been proposed on a molecular genetic basis. From the histological point of view the problem has not been sufficiently investigated. Recurrences ...mainly depend on tumor location, histology, resection type and on the tumor growth in the adjacent nervous tissue. Seventy-six completely resected recurrent meningiomas have been studied. Most tumors were convexity or parasagittal meningiomas. The number of recurrences studied per tumor varied from 1 to 5. Besides histological methods, immunohistochemistry for Ki-67 MIB-1, TUNEL for apoptosis, counts of mitoses and molecular genetics for CDKN2A were performed. No variation of the mitotic index (MI) or MIB-1 labeling index (LI) was observed in recurrences. Histological features, the number of mitoses and the MIB-1 LI showed a great regional variability. Loss of heterozygosity (LOH) of CDKN2A was found to be slightly more frequent in the first recurrence than in the initial tumor, but it was lower in the following recurrences. The nervous tissue adjacent to the tumor could contain meningothelial cells and be responsible for recurrences. The number of mitoses appeared to be the most important criterion for establishing the tumor grade. The histological aspect does not change in recurrences and there is no progression. The greater number of recurrences in atypical and anaplastic tumors depends on their initial higher proliferation capacity. The occurrence of tumor meningothelial cells in the adjacent nervous tissue or in the thickened arachnoidal membrane can be responsible for recurrence.
Background: PIP3, generated by PI3-K, activates Akt which inactivates AFX/FKHR, with the consequent decrease in p27/Kip.1
expression and enhancement of cyclin D1 expression through FRAP/mTOR. PTEN ...lipid phosphatase degrades PIP3 and negatively
regulates Akt, whereas this is activated by EGFR through PI3. In glioblastomas, PTEN is mutated in 27%-40% and EGFR amplified
in 60%-65% of cases. Materials and Methods: PTEN mutation and EGFR amplification by PCR, Akt, p27/Kip.1 and cyclin D1 by immunohistochemistry,
apoptosis by TUNEL and MIB.1 LI were studied in a series of 65 operated glioblastomas. Results: EGFR amplification and PTEN
mutation were present in 50% and 30% of glioblastomas, respectively. No relationship between EGFR amplification and PTEN mutation,
and p27/Kip.1 and cyclin D1 was found. However, cyclin D1 was positive in 69% of Akt-expressing areas, whereas p27 was positive
in 30% only. Conclusion: A direct relationship is more evident between cyclin D1 and p27/Kip.1 and Akt than with PTEN and
EGFR.
Proteasomes are multisubunit proteases involved in many cellular processes, including tumorigenesis and immune surveillance.
In their catalytic core, the 20S proteasome, the β1, β2 and β5 subunits ...show peptidyl-glutamyl peptide hydrolyzing (PGPH),
trypsin-like and chymotrypsin-like activities, respectively. By IFN-γ and TNFα stimulus, these subunits are replaced by their
counterparts LMP2, MECL-1 and LMP7, defined inducible subunits, thus originating the immunoproteasome, and expression of the
proteasome activator PA28 is enhanced. These modifications strengthen MHC-class I restricted peptide generation. The 20S proteasome
has been detected immunohistochemically in formalin-fixed samples purified from fresh surgical specimens of 18 tumors (G20S)
and from 8 samples of normal peritumoral tissue. The G20S, LMP2, MECL-1 and LMP7 increased in only 12 cases, along with unvaried
trypsin-like and decreased PGPH and chymotrypsin-like activities; PA28 was unvaried in all 18 samples. The immunoproteasome
alterations may represent an anomalous immunological attitude of glioblastomas.
MicroRNAs have been found to be deregulated in several diseases and, due to their high stability in body fluids, represent promising noninvasively detectable biomarkers. However, numerous technical ...variables can affect accurate measurement of circulating miRNAs. Using a microarray-based method we assessed the: (i) adequate intra- and inter-array reproducibility of miRNA profiling; (ii) feasibility of using archival plasma samples stored for an extended period of time and available in limited amounts; (iii) good correlation between different batches; and (iv) time-dependent increase of background signals close to the chip expiration date.
Aromatase inhibitors (AIs), such as anastrozole, are established in the treatment of hormone-dependent breast cancer. However, ∼20% of patients with hormone receptor-positive breast tumors treated ...with anastrozole do not respond and it remains impossible to accurately predict sensitivity. Since polymorphisms in the aromatase gene may influence the response to inhibitory drugs, we evaluated the presence of rs6493497 and rs7176005 polymorphisms (mapping in the 5′-flanking region of the CYP19A1 gene coding for the aromatase protein) in a cohort of 37 patients with postmenopausal breast cancer who received three-month neoadjuvant treatment with anastrozole. We then investigated any association of the polymorphisms with changes in aromatase mRNA expression change and/or response to treatment. We also analyzed five miRNAs computationally predicted to target aromatase, to observe any association between their expression and sensitivity to anastrozole. Three samples carried the two polymorphisms and the remaining samples were wild-type for both, however, no association with response or with aromatase mRNA basal expression level or expression difference after therapy was observed. Polymorphic samples that were resistant to anastrozole showed no change or decrease in aromatase expression following AI treatment, whereas an increase in expression was observed for the polymorphic responsive samples. No statistically significant correlation was observed between miRNA and aromatase mRNA expression, or with response to anastrozole neoadjuvant treatment. These data indicate that the polymorphisms analyzed are not involved in aromatase activity and that other epigenetic mechanisms may regulate aromatase protein expression.
Aromatase inhibition (AI) is the most effective endocrine treatment for breast cancer in post-menopausal patients, but a percentage of hormone receptor-positive cancers do not benefit from such ...therapy: for example, about 20% of patients treated with anastrozole do not respond and it is still impossible to accurately predict sensitivity. Our main goal was to identify a robust expression signature predictive of response to neoadjuvant treatment with anastrozole in patients with ER+ breast cancer. At the same time, we addressed the question of delineating treatment effects and possible mechanisms of intrinsic resistance occurring in non-responder patients. We analyzed the transcriptome of 17 tru-cut biopsies before treatment and 13 matched surgical samples after 3 months treatment with anastrozole taken from ER+ breast tumors. Molecular profiles were related to clinical response data. Treatment with anastrozole was associated with a decreased expression of genes relating to cell proliferation and an increased expression of genes relating to inflammatory processes. There was also an enrichment of induction of T-cell anergy, positive regulation of androgen signalling, synaptic transmission and vesicle trafficking in non-responders, and of cell cycle inhibition and induction of immune response in responders. We identified an expression signature of 77 probes (54 genes) that predicted response in 100% of our cases. Five of them were able to accurately predict response on an independent dataset (P = 0.0056) of 52 ER+ breast cancers treated with letrozole. Ten fixed independent samples from the anastrozole study were also used for RT-qPCR validations. This study suggests that a relative small number of genes analysed in a pre-treatment biopsy may identify patients likely to respond to AI neoadjuvant treatment. This may have practical utility translatable to the clinics. Furthermore, it delineates novel mechanisms of intrinsic resistance to AI therapy that could be further investigated in order to explore circumventing treatments.
Abstract
Prostate cancer (PCa) shows tremendous heterogeneity which makes it difficult to identify patients with an increased risk of disease recurrence. A better understanding of the biological ...mechanism of prostate cancer formation and progression is crucial for the discovery of new markers for this disease. In recent years it has become apparent that different non-coding RNAs are also implicated in prostate cancer. Several microRNAs are now associated with progression and classification of prostate cancer and other malignancies. The role played in progression and differentiation of distinct PCa subtypes by a recently discovered class of non-coding RNAs, called large intergenic non-coding RNAs (lincRNAs), has remained unexplored. LincRNAs are believed to have major consequences on gene expression patterns through epigenetic mechanisms. Thousands of lincRNAs have been identified in human tissues, but only few have been functionally characterized. To assess the role of lincRNAs in PCa, we analysed the expression pattern of nearly 28000 Entrez genes and 7500 unique lincRNAs in 56 primary PCas and 5 normal prostate tissues, using Agilent 8x60k arrays. Unsupervised clustering over 1610 lincRNAs, selected after filtering out non informative probes, classified 61 samples into 5 distinct classes. Anova analysis was done to identify genes specifically over or under expressed in each cluster and was followed by functional annotation analysis. Normal samples were separated into a cluster characterized by the down regulation of genes involved in chemotaxis and intracellular signaling cascade. The four tumor clusters showed up regulation of distinct biological processes, like cell cycle, chromatin organization and immune response, together with deregulation of MAP-kinase signaling through EGFR and members of the RAS family oncogene. These results show that sample classification based on lincRNA profiling is able to separate tumors into subgroups with distinct biological processes.
Citation Format: Maurizia Mello-Grand, Vijay K. Singh, Chiara Ghimenti, Maria Scatolini, Nicole Longoni, Laura Curti, Andrea Zitella, Paolo Gontero, Carlo V. Catapano, Giuseppina M. Carbone, Giovanna Chiorino. LincRNA expression data analysis identifies prostate tumor subtypes with distinct biological processes abstract. In: Proceedings of the AACR Special Conference on Advances in Prostate Cancer Research; 2012 Feb 6-9; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2012;72(4 Suppl):Abstract nr C21.
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