RNA Interference and cyclooxygenase-2 (COX-2) regulation in colon cancer cells

Despite new methods and combined strategies, conventional cancer chemotherapy still lacks specificity and induces drug resistance. Gene therapy can offer the potential to obtain the success in the clinical treatment of cancer and this can be achieved by replacing mutated tumour suppressor genes, inhibiting gene transcription, introducing new genes encoding for therapeutic products, or specifically silencing any given target gene. Concerning gene silencing, attention has recently shifted onto the RNA interference (RNAi) phenomenon. Gene silencing mediated by RNAi machinery is based on short RNA molecules, small interfering RNAs (siRNAs) and microRNAs (miRNAs), that are fully o partially homologous to the mRNA of the genes being silenced, respectively. On one hand, synthetic siRNAs appear as an important research tool to understand the function of a gene and the prospect of using siRNAs as potent and specific inhibitors of any target gene provides a new therapeutical approach for many untreatable diseases, particularly cancer. On the other hand, the discovery of the gene regulatory pathways mediated by miRNAs, offered to the research community new important perspectives for the comprehension of the physiological and, above all, the pathological mechanisms underlying the gene regulation. Indeed, changes in miRNAs expression have been identified in several types of neoplasia and it has also been proposed that the overexpression of genes in cancer cells may be due to the disruption of a control network in which relevant miRNA are implicated. For these reasons, I focused my research on a possible link between RNAi and the enzyme cyclooxygenase-2 (COX-2) in the field of colorectal cancer (CRC), since it has been established that the transition adenoma-adenocarcinoma and the progression of CRC depend on aberrant constitutive expression of COX-2 gene. In fact, overexpressed COX-2 is involved in the block of apoptosis, the stimulation of tumor-angiogenesis and promotes cell invasion, tumour growth and metastatization. On the basis of data reported in the literature, the first aim of my research was to develop an innovative and effective tool, based on the RNAi mechanism, able to silence strongly and specifically COX-2 expression in human colorectal cancer cell lines. In this study, I firstly show that an siRNA sequence directed against COX-2 mRNA (siCOX-2), potently downregulated COX-2 gene expression in human umbilical vein endothelial cells (HUVEC) and inhibited PMA-induced angiogenesis in vitro in a specific, non-toxic manner. Moreover, I found that the insertion of a specific cassette carrying anti-COX-2 shRNA sequence (shCOX-2, the precursor of siCOX-2 previously tested) into a viral vector (pSUPER.retro) greatly increased silencing potency in a colon cancer cell line (HT-29) without activating any interferon response. Phenotypically, COX-2 deficient HT-29 cells showed a significant impairment of their in vitro malignant behaviour. Thus, results reported here indicate an easy-to-use, powerful and high selective virus-based method to knockdown COX-2 gene in a stable and long-lasting manner, in colon cancer cells. Furthermore, they open up the possibility of an in vivo application of this anti-COX-2 retroviral vector, as therapeutic agent for human cancers overexpressing COX-2. In order to improve the tumour selectivity, pSUPER.retro vector was modified for the shCOX-2 expression cassette. The aim was to obtain a strong, specific transcription of shCOX-2 followed by COX-2 silencing mediated by siCOX-2 only in cancer cells. For this reason, H1 promoter in basic pSUPER.retro vector [pS(H1)] was substituted with the human Cox-2 promoter [pS(COX2)] and with a promoter containing repeated copies of the TCF binding element (TBE) [pS(TBE)]. These promoters were choosen because they are partculary activated in colon cancer cells. COX-2 was effectively silenced in HT-29 and HCA-7 colon cancer cells by using enhanced pS(COX2) and pS(TBE) vectors. In particular, an higher siCOX-2 production followed by a stronger inhibition of Cox-2 gene were achieved by using pS(TBE) vector, that represents not only the most effective, but also the most specific system to downregulate COX-2 in colon cancer cells. Because of the many limits that a retroviral therapy could have in a possible in vivo treatment of CRC, the next goal was to render the enhanced RNAi-mediate COX-2 silencing more suitable for this kind of application. Xiang and et al. (2006) demonstrated that it is possible to induce RNAi in mammalian cells after infection with engineered E. Coli strains expressing Inv and HlyA genes, which encode for two bacterial factors needed for successful transfer of shRNA in mammalian cells. This system, called “trans-kingdom” RNAi (tkRNAi) could represent an optimal approach for the treatment of colorectal cancer, since E. Coli in normally resident in human intestinal flora and could easily vehicled to the tumor tissue. For this reason, I tested the improved COX-2 silencing mediated by pS(COX2) and pS(TBE) vectors by using tkRNAi system. Results obtained in HT-29 and HCA-7 cell lines were in high agreement with data previously collected after the transfection of pS(COX2) and pS(TBE) vectors in the same cell lines. These findings suggest that tkRNAi system for COX-2 silencing, in particular mediated by pS(TBE) vector, could represent a promising tool for the treatment of colorectal cancer. Flanking the studies addressed to the setting-up of a RNAi-mediated therapeutical strategy, I proposed to get ahead with the comprehension of new molecular basis of human colorectal cancer. In particular, it is known that components of the miRNA/RNAi pathway may be altered during the progressive development of colorectal cancer (CRC), and it has been already demonstrated that some miRNAs work as tumor suppressors or oncomiRs in colon cancer. Thus, my hypothesis was that overexpressed COX-2 protein in colon cancer could be the result of decreased levels of one or more tumor suppressor miRNAs. In this thesis, I clearly show an inverse correlation between COX-2 expression and the human miR- 101(1) levels in colon cancer cell lines, tissues and metastases. I also demonstrate that the in vitro modulating of miR-101(1) expression in colon cancer cell lines leads to significant variations in COX-2 expression, and this phenomenon is based on a direct interaction between miR-101(1) and COX-2 mRNA. Moreover, I started to investigate miR-101(1) regulation in the hypoxic environment since adaptation to hypoxia is critical for tumor cell growth and survival and it is known that COX-2 can be induced directly by hypoxia-inducible factor 1 (HIF-1). Surprisingly, I observed that COX-2 overexpression induced by hypoxia is always coupled to a significant decrease of miR-101(1) levels in colon cancer cell lines, suggesting that miR-101(1) regulation could be involved in the adaption of cancer cells to the hypoxic environment that strongly characterize CRC tissues.

New approaches to open problems in gene expression microarray data

In the past decade, the advent of efficient genome sequencing tools and high-throughput experimental biotechnology has lead to enormous progress in the life science. Among the most important innovations is the microarray tecnology. It allows to quantify the expression for thousands of genes simultaneously by measurin the hybridization from a tissue of interest to probes on a small glass or plastic slide. The characteristics of these data include a fair amount of random noise, a predictor dimension in the thousand, and a sample noise in the dozens. One of the most exciting areas to which microarray technology has been applied is the challenge of deciphering complex disease such as cancer. In these studies, samples are taken from two or more groups of individuals with heterogeneous phenotypes, pathologies, or clinical outcomes. these samples are hybridized to microarrays in an effort to find a small number of genes which are strongly correlated with the group of individuals. Eventhough today methods to analyse the data are welle developed and close to reach a standard organization (through the effort of preposed International project like Microarray Gene Expression Data -MGED- Society [1]) it is not unfrequant to stumble in a clinician's question that do not have a compelling statistical method that could permit to answer it.The contribution of this dissertation in deciphering disease regards the development of new approaches aiming at handle open problems posed by clinicians in handle specific experimental designs. In Chapter 1 starting from a biological necessary introduction, we revise the microarray tecnologies and all the important steps that involve an experiment from the production of the array, to the quality controls ending with preprocessing steps that will be used into the data analysis in the rest of the dissertation. While in Chapter 2 a critical review of standard analysis methods are provided stressing most of problems that In Chapter 3 is introduced a method to adress the issue of unbalanced design of miacroarray experiments. In microarray experiments, experimental design is a crucial starting-point for obtaining reasonable results. In a two-class problem, an equal or similar number of samples it should be collected between the two classes. However in some cases, e.g. rare pathologies, the approach to be taken is less evident. We propose to address this issue by applying a modified version of SAM [2]. MultiSAM consists in a reiterated application of a SAM analysis, comparing the less populated class (LPC) with 1,000 random samplings of the same size from the more populated class (MPC) A list of the differentially expressed genes is generated for each SAM application. After 1,000 reiterations, each single probe given a "score" ranging from 0 to 1,000 based on its recurrence in the 1,000 lists as differentially expressed. The performance of MultiSAM was compared to the performance of SAM and LIMMA [3] over two simulated data sets via beta and exponential distribution. The results of all three algorithms over low- noise data sets seems acceptable However, on a real unbalanced two-channel data set reagardin Chronic Lymphocitic Leukemia, LIMMA finds no significant probe, SAM finds 23 significantly changed probes but cannot separate the two classes, while MultiSAM finds 122 probes with score >300 and separates the data into two clusters by hierarchical clustering. We also report extra-assay validation in terms of differentially expressed genes Although standard algorithms perform well over low-noise simulated data sets, multi-SAM seems to be the only one able to reveal subtle differences in gene expression profiles on real unbalanced data. In Chapter 4 a method to adress similarities evaluation in a three-class prblem by means of Relevance Vector Machine [4] is described. In fact, looking at microarray data in a prognostic and diagnostic clinical framework, not only differences could have a crucial role. In some cases similarities can give useful and, sometimes even more, important information. The goal, given three classes, could be to establish, with a certain level of confidence, if the third one is similar to the first or the second one. In this work we show that Relevance Vector Machine (RVM) [2] could be a possible solutions to the limitation of standard supervised classification. In fact, RVM offers many advantages compared, for example, with his well-known precursor (Support Vector Machine - SVM [3]). Among these advantages, the estimate of posterior probability of class membership represents a key feature to address the similarity issue. This is a highly important, but often overlooked, option of any practical pattern recognition system. We focused on Tumor-Grade-three-class problem, so we have 67 samples of grade I (G1), 54 samples of grade 3 (G3) and 100 samples of grade 2 (G2). The goal is to find a model able to separate G1 from G3, then evaluate the third class G2 as test-set to obtain the probability for samples of G2 to be member of class G1 or class G3. The analysis showed that breast cancer samples of grade II have a molecular profile more similar to breast cancer samples of grade I. Looking at the literature this result have been guessed, but no measure of significance was gived before.

Preclinical development of cancer vaccines

Triplex cell vaccine is a cancer immunopreventive cell vaccine that can prevent almost completely mammary tumor onset in HER-2/neu transgenic mice. A future translation of cancer immunoprevention from preclinical to clinical studies should take into account several aspects. The work reported in this thesis deals with the study of three of these aspects: vaccine schedule, activity in a therapeutic set-up and second-generation DNA vaccines. An important element in determining human acceptance and compliance of a treatment protocol is the number of vaccinations. In order to improve the vaccination schedule a minimal protocol was searched, i.e. a schedule consisting of a lower number of administrations than standard protocol but with a similar efficacy. A candidate optimal protocol was identified by the use of an in silico model, SimTriplex simulator. The in vivo test of this schedule in HER-2/neu transgenic mice only partially confirmed in silico predictions. This result shows that in silico models have the potential ability to aid in searching of optimal treatment protocols, provided that they will be further tuned on experimental data. As a further result this preclinical study highlighted that kinetic of antibody response plays a major role in determining cancer prevention, leading to the hypothesis of a threshold that must be reached rapidly and maintained lifetime. Early clinical trials would be performed in a therapeutic, rather than preventive, setting. Thus, the activity of Triplex vaccine was investigated against experimental lung metastases in HER-2/neu transgenic mice in order to evaluate if the immunopreventive Triplex vaccine could be effective also against a pre-existing tumor mass. This preclinical model of aggressive metastatic development showed that the vaccine was an efficient treatment also 4 for the cure of micrometastases. However the immune mechanisms activated against tumor mass were not antibody dependent, i.e. different from those preventing the onset of primary mammary carcinoma. DNA vaccines could be more easily used than cellular ones. A second generation of Triplex vaccine based on DNA plasmids was evaluated in an aggressive preclinical model (BALBp53neu female mice) and compared with the preventive ability of cellular Triplex vaccine. It was observed that Triplex DNA vaccine was as effective as Triplex cell vaccine, exploiting a more restricted immune stimulation.

The role of interleuchin 6 (IL-6) in the promotion of an aggressive and stem cell-like phenotype in human breast cancer cells and in stem/progenitor cells expanded in vitro as mammospheres

High serum levels of Interleukin-6 (IL-6) correlate with poor outcome in breast cancer patients. However no data are available on the relationship between IL-6 and stem/progenitor cells which may fuel the genesis of breast cancer in vivo. Herein, we address this issue in mammospheres (MS), multi-cellular structures enriched in stem/progenitor cells of the mammary gland, and also in MCF-7 breast cancer cells. We show that MS from node invasive breast carcinoma tissues express IL-6 mRNA at higher levels than MS from matched non-neoplastic mammary glands. We find that IL-6 mRNA is detectable only in basal-like breast carcinoma tissues, an aggressive variant showing stem cell features. Our results reveal that IL-6 triggers a Notch-3-dependent up-regulation of the Notch ligand Jagged-1, whose interaction with Notch-3 promotes the growth of MS and MCF-7 derived spheroids. Moreover, IL-6 induces a Notch-3-dependent up-regulation of the carbonic anhydrase IX gene, which promotes a hypoxia-resistant/invasive phenotype in MCF-7 cells and MS. Finally, an autocrine IL-6 loop relies upon Notch-3 activity to sustain the aggressive features of MCF-7-derived hypoxia-selected cells. In conclusion, our data support the hypothesis that IL-6 induces malignant features in Notch-3 expressing, stem/progenitor cells from human ductal breast carcinoma and normal mammary gland.

Lesion detection and classification in breast cancer: evaluation of approaches based on morphological features, tracer kinetic modelling and semi-quantitative parameters in MR functional imaging (DCE-MRI)

The diagnosis, grading and classification of tumours has benefited considerably from the development of DCE-MRI which is now essential to the adequate clinical management of many tumour types due to its capability in detecting active angiogenesis. Several strategies have been proposed for DCE-MRI evaluation. Visual inspection of contrast agent concentration curves vs time is a very simple yet operator dependent procedure, therefore more objective approaches have been developed in order to facilitate comparison between studies. In so called model free approaches, descriptive or heuristic information extracted from time series raw data have been used for tissue classification. The main issue concerning these schemes is that they have not a direct interpretation in terms of physiological properties of the tissues. On the other hand, model based investigations typically involve compartmental tracer kinetic modelling and pixel-by-pixel estimation of kinetic parameters via non-linear regression applied on region of interests opportunely selected by the physician. This approach has the advantage to provide parameters directly related to the pathophysiological properties of the tissue such as vessel permeability, local regional blood flow, extraction fraction, concentration gradient between plasma and extravascular-extracellular space. Anyway, nonlinear modelling is computational demanding and the accuracy of the estimates can be affected by the signal-to-noise ratio and by the initial solutions. The principal aim of this thesis is investigate the use of semi-quantitative and quantitative parameters for segmentation and classification of breast lesion. The objectives can be subdivided as follow: describe the principal techniques to evaluate time intensity curve in DCE-MRI with focus on kinetic model proposed in literature; to evaluate the influence in parametrization choice for a classic bi-compartmental kinetic models; to evaluate the performance of a method for simultaneous tracer kinetic modelling and pixel classification; to evaluate performance of machine learning techniques training for segmentation and classification of breast lesion.

Generation and characterization of mouse models of Small cell lung cancer and Basal cell carcinoma for the preclinical evaluation of new therapies

Background. Human small cell lung cancer (SCLC) accounting for approximately 15-20% of all lung cancers, is an aggressive tumor with high propensity for early regional and distant metastases. Although the initial tumor rate response to chemotherapy is very high, SCLC relapses after approximately 4 months in ED and 12 months in LD. Basal cell carcinoma (BCC) is the most prevalent cancer in the western world, and its incidence is increasing worldwide. This type of cancer rarely metastasizes and the death rate is extraordinary low. Surgery is curative for most of the patients, but for those that develop locally advanced or metastatic BCC there is currently no effective treatment. Both types of cancer have been deeply investigated and genetic alterations, MYCN amplification (MA) among the most interesting, have been found. These could become targets of new pharmacological therapies. Procedures. We created and characterized novel BLI xenograft orthotopic mouse models of SCLC to evaluate the tumor onset and progression and the efficacy of new pharmacological strategies. We compared an in vitro model with a transgenic mouse model of BCC, to investigate and delineate the canonical HH signalling pathway and its connections with other molecular pathways. Results and conclusions. The orthotopic models showed latency and progression patterns similar to human disease. Chemotherapy treatments improved survival rates and validated the in vivo model. The presence of MA and overexpression were confirmed in each model and we tested the efficacy of a new MYCN inhibitor in vitro. Preliminar data of BCC models highlighted Hedgehog pathway role and underlined the importance of both in vitro and in vivo strategies to achieve a better understanding of the pathology and to evaluate the applicability of new therapeutic compounds

Differential expression analysis for sequence count data via mixtures of negative binomials

The recent advent of Next-generation sequencing technologies has revolutionized the way of analyzing the genome. This innovation allows to get deeper information at a lower cost and in less time, and provides data that are discrete measurements. One of the most important applications with these data is the differential analysis, that is investigating if one gene exhibit a different expression level in correspondence of two (or more) biological conditions (such as disease states, treatments received and so on). As for the statistical analysis, the final aim will be statistical testing and for modeling these data the Negative Binomial distribution is considered the most adequate one especially because it allows for "over dispersion". However, the estimation of the dispersion parameter is a very delicate issue because few information are usually available for estimating it. Many strategies have been proposed, but they often result in procedures based on plug-in estimates, and in this thesis we show that this discrepancy between the estimation and the testing framework can lead to uncontrolled first-type errors. We propose a mixture model that allows each gene to share information with other genes that exhibit similar variability. Afterwards, three consistent statistical tests are developed for differential expression analysis. We show that the proposed method improves the sensitivity of detecting differentially expressed genes with respect to the common procedures, since it is the best one in reaching the nominal value for the first-type error, while keeping elevate power. The method is finally illustrated on prostate cancer RNA-seq data.

Preclinical development of anti-cancer strategies against human HER-2

HER-2 is a 185 kDa transmembrane receptor tyrosine kinase that belongs to the EGFR family. HER-2 is overexpressed in nearly 25% of human breast cancers and women with this subtype of breast cancer have a worse prognosis and frequently develop metastases. The progressive high number of HER-2-positive breast cancer patients with metastatic spread in the brain (up to half of women) has been attributed to the reduction in mortality, the effectiveness of Trastuzumab in killing metastatic cells in other organs and to its incapability to cross the blood-brain barrier. Apart from full-length-HER-2, a splice variant of HER-2 lacking exon 16 (here referred to as D16) was identified in human HER-2-positive breast cancers. Here, the contribution of HER-2 and D16 to mammary carcinogenesis was investigated in a model transgenic for both genes (F1 model). A dominant role of D16, especially in early stages of tumorigenesis, was suggested and the coexistence of heterogeneous levels of HER-2 and D16 in F1 tumors revealed the undeniable value of F1 strain as preclinical model of HER-2-positive breast cancer, closer resembling the human situation in respect to previous models. The therapeutical efficacy of anti-HER-2 agents, targeting HER-2 receptor (Trastuzumab, Lapatinib, R-LM249) or signaling effectors (Dasatinib, UO126, NVP-BKM120), was investigated in models of local or advanced HER-2-positive breast cancer. In contrast with early studies, data herein collected suggested that the presence of D16 can predict a better response to Trastuzumab and other agents targeting HER-2 receptor or Src activity. Using a multiorgan HER-2-positive metastatic model, the efficacy of NVP-BKM120 (PI3K inhibitor) in blocking the growth of brain metastases and the oncolytic ability of R-LM249 (HER-2-retargeted HSV) to reach and destroy metastatic HER-2-positive cancer cells were shown. Finally, exploiting the definition of “oncoantigen” given to HER-2, the immunopreventive activity of two vaccines on HER-2-positive mammary tumorigenesis was demonstrated.

Chemopreventive effects of eicosapentaenoic acid free fatty acid in a murine model of colitis-associated colorectal cancer

Inflammatory bowel diseases are associated with increased risk of developing colitis-associated colorectal cancer (CAC). Epidemiological data show that the consumption of ω-3 polyunsaturated fatty acids (ω-3 PUFAs) decreases the risk of sporadic colorectal cancer (CRC). Importantly, recent data have shown that eicosapentaenoic acid-free fatty acid (EPA-FFA) reduces polyps formation and growth in models of familial adenomatous polyposis. However, the effects of dietary EPA-FFA are unknown in CAC. We tested the effectiveness of substituting EPA-FFA, for other dietary fats, in preventing inflammation and cancer in the AOM-DSS model of CAC. The AOM-DSS protocols were designed to evaluate the effect of EPA-FFA on both initiation and promotion of carcinogenesis. We found that EPA-FFA diet strongly decreased tumor multiplicity, incidence and maximum tumor size in the promotion and initiation arms. Moreover EPA-FFA, in particular in the initiation arm, led to reduced cell proliferation and nuclear β-catenin expression, whilst it increased apoptosis. In both arms, EPA-FFA treatment led to increased membrane switch from ω-6 to ω-3 PUFAs and a concomitant reduction in PGE2 production. We observed no significant changes in intestinal inflammation between EPA-FFA treated arms and AOM-DSS controls. Importantly, we found that EPA-FFA treatment restored the loss of Notch signaling found in the AOM-DSS control, resulted in the enrichment of Lactobacillus species in the gut microbiota and led to tumor suppressor miR34-a induction. In conclusion, our data suggest that EPA-FFA is an effective chemopreventive agent in CAC.

Functional characterization of the placenta specific protein PLAC1 and its use for cancer immunotherapy

Summary Antibody-based cancer therapies have been successfully introduced into the clinic and have emerged as the most promising therapeutics in oncology. The limiting factor regarding the development of therapeutical antibody vaccines is the identification of tumor-associated antigens. PLAC1, the placenta-specific protein 1, was categorized for the first time by the group of Prof. Sahin as such a tumor-specific antigen. Within this work PLAC1 was characterized using a variety of biochemical methods. The protein expression profile, the cellular localization, the conformational state and especially the interacting partners of PLAC1 and its functionality in cancer were analyzed. Analysis of the protein expression profile of PLAC1 in normal human tissue confirms the published RT-PCR data. Except for placenta no PLAC1 expression was detectable in any other normal human tissue. Beyond, an increased PLAC1 expression was detected in several cancer cell lines derived of trophoblastic, breast and pancreatic lineage emphasizing its properties as tumor-specific antigen. rnThe cellular localization of PLAC1 revealed that PLAC1 contains a functional signal peptide which conducts the propeptide to the endoplasmic reticulum (ER) and results in the secretion of PLAC1 by the secretory pathway. Although PLAC1 did not exhibit a distinct transmembrane domain, no unbound protein was detectable in the cell culture supernatant of overexpressing cells. But by selective isolation of different cellular compartments PLAC1 was clearly enriched within the membrane fraction. Using size exclusion chromatography PLAC1 was characterized as a highly aggregating protein that forms a network of high molecular multimers, consisting of a mixture of non-covalent as well as covalent interactions. Those interactions were formed by PLAC1 with itself and probably other cellular components and proteins. Consequently, PLAC1 localize outside the cell, where it is associated to the membrane forming a stable extracellular coat-like structure.rnThe first mechanistic hint how PLAC1 promote cancer cell proliferation was achieved identifying the fibroblast growth factor FGF7 as a specific interacting partner of PLAC1. Moreover, it was clearly shown that PLAC1 as well as FGF7 bind to heparin, a glycosaminoglycan of the ECM that is also involved in FGF-signaling. The participation of PLAC1 within this pathway was approved after co-localizing PLAC1, FGF7 and the FGF7 specific receptor (FGFR2IIIb) and identifying the formation of a trimeric complex (PLAC1, FGF7 and the specific receptor FGFR2IIIb). Especially this trimeric complex revealed the role of PLAC1. Binding of PLAC1 together with FGF7 leads to the activation of the intracellular tyrosine kinase of the FGFR2IIIb-receptor and mediate the direct phosphorylation of the AKT-kinase. In the absence of PLAC1, no FGF7 mediated phosphorylation of AKT was observed. Consequently the function of PLAC1 was clarified: PLAC1 acts as a co-factor by stimulating proliferation by of the FGF7-FGFR2 signaling pathway.rnAll together, these novel biochemical findings underline that the placenta specific protein PLAC1 could be a new target for cancer immunotherapy, especially considering its potential applicability for antibody therapy in tumor patients.

Older Breast Cancer Survivors: Geriatric Assessment Domains Are Associated With Poor Tolerance of Treatment Adverse Effects and Predict Mortality Over 7 Years of Follow-Up

Purpose To evaluate geriatric assessment (GA) domains in relation to clinically important outcomes in older breast cancer survivors. Methods Six hundred sixty women diagnosed with primary breast cancer in four US geographic regions (Los Angeles, CA; Minnesota; North Carolina; and Rhode Island) were selected with disease stage I to IIIA, age ≥ 65 years at date of diagnosis, and permission from attending physician to contact. Data were collected over 7 years of follow-up from consenting patients' medical records, telephone interviews, physician questionnaires, and the National Death Index. Outcomes included self-reported treatment tolerance and all-cause mortality. Four GA domains were described by six individual measures, as follows: sociodemographic by adequate finances; clinical by Charlson comorbidity index (CCI) and body mass index; function by number of physical function limitations; and psychosocial by the five-item Mental Health Index (MHI5) and Medical Outcomes Study Social Support Survey (MOS-SSS). Associations were evaluated using t tests, χ2 tests, and regression analyses. Results In multivariable regression including age and stage, three measures from two domains (clinical and psychosocial) were associated with poor treatment tolerance; these were CCI ≥ 1 (odds ratio [OR] = 2.49; 95% CI, 1.18 to 5.25), MHI5 score less than 80 (OR = 2.36; 95% CI, 1.15 to 4.86), and MOS-SSS score less than 80 (OR = 3.32; 95% CI, 1.44 to 7.66). Four measures representing all four GA domains predicted mortality; these were inadequate finances (hazard ratio [HR] = 1.89; 95% CI, 1.24 to 2.88; CCI ≥ 1 (HR = 1.38; 95% CI, 1.01 to 1.88), functional limitation (HR = 1.40; 95% CI, 1.01 to 1.93), and MHI5 score less than 80 (HR = 1.34; 95% CI, 1.01 to 1.85). In addition, the proportion of women with these outcomes incrementally increased as the number of GA deficits increased. Conclusion This study provides longitudinal evidence that GA domains are associated with poor treatment tolerance and predict mortality at 7 years of follow-up, independent of age and stage of disease.

Hierarchical clustering of flow cytometry data for the study of conventional central chondrosarcoma

We have investigated the use of hierarchical clustering of flow cytometry data to classify samples of conventional central chondrosarcoma, a malignant cartilage forming tumor of uncertain cellular origin, according to similarities with surface marker profiles of several known cell types. Human primary chondrosarcoma cells, articular chondrocytes, mesenchymal stem cells, fibroblasts, and a panel of tumor cell lines from chondrocytic or epithelial origin were clustered based on the expression profile of eleven surface markers. For clustering, eight hierarchical clustering algorithms, three distance metrics, as well as several approaches for data preprocessing, including multivariate outlier detection, logarithmic transformation, and z-score normalization, were systematically evaluated. By selecting clustering approaches shown to give reproducible results for cluster recovery of known cell types, primary conventional central chondrosacoma cells could be grouped in two main clusters with distinctive marker expression signatures: one group clustering together with mesenchymal stem cells (CD49b-high/CD10-low/CD221-high) and a second group clustering close to fibroblasts (CD49b-low/CD10-high/CD221-low). Hierarchical clustering also revealed substantial differences between primary conventional central chondrosarcoma cells and established chondrosarcoma cell lines, with the latter not only segregating apart from primary tumor cells and normal tissue cells, but clustering together with cell lines from epithelial lineage. Our study provides a foundation for the use of hierarchical clustering applied to flow cytometry data as a powerful tool to classify samples according to marker expression patterns, which could lead to uncover new cancer subtypes.

Imetelstat (GRN163L)--telomerase-based cancer therapy

Telomeres and telomerase play essential roles in the regulation of the lifespan of human cells. While normal human somatic cells do not or only transiently express telomerase and therefore shorten their telomeres with each cell division, most human cancer cells typically express high levels of telomerase and show unlimited cell proliferation. High telomerase expression allows cells to proliferate and expand long-term and therefore supports tumor growth. Owing to the high expression and its role, telomerase has become an attractive diagnostic and therapeutic cancer target. Imetelstat (GRN163L) is a potent and specific telomerase inhibitor and so far the only drug of its class in clinical trials. Here, we report on the structure and the mechanism of action of imetelstat as well as about the preclinical and clinical data and future prospects using imetelstat in cancer therapy.

American Society of Clinical Oncology/American Society of Hematology clinical practice guideline update on the use of epoetin and darbepoetin in adult patients with cancer

Purpose To update American Society of Clinical Oncology/American Society of Hematology recommendations for use of erythropoiesis-stimulating agents (ESAs) in patients with cancer. Methods An Update Committee reviewed data published between January 2007 and January 2010. MEDLINE and the Cochrane Library were searched. Results The literature search yielded one new individual patient data analysis and four literature-based meta-analyses, two systematic reviews, and 13 publications reporting new results from randomized controlled trials not included in prior or new reviews. Recommendations For patients undergoing myelosuppressive chemotherapy who have a hemoglobin (Hb) level less than 10 g/dL, the Update Committee recommends that clinicians discuss potential harms (eg, thromboembolism, shorter survival) and benefits (eg, decreased transfusions) of ESAs and compare these with potential harms (eg, serious infections, immune-mediated adverse reactions) and benefits (eg, rapid Hb improvement) of RBC transfusions. Individual preferences for assumed risk should contribute to shared decisions on managing chemotherapy-induced anemia. The Committee cautions against ESA use under other circumstances. If used, ESAs should be administered at the lowest dose possible and should increase Hb to the lowest concentration possible to avoid transfusions. Available evidence does not identify Hb levels � 10 g/dL either as thresholds for initiating treatment or as targets for ESA therapy. Starting doses and dose modifications after response or nonresponse should follow US Food and Drug Administration–approved labeling. ESAs should be discontinued after 6 to 8 weeks in nonresponders. ESAs should be avoided in patients with cancer not receiving concurrent chemotherapy, except for those with lower risk myelodysplastic syndromes. Caution should be exercised when using ESAs with chemotherapeutic agents in diseases associated with increased risk of thromboembolic complications. Table 1 lists detailed recommendations. This guideline was developed through a collaboration between the American Society of Clinical Oncology and the American Society of Hematology and has been published jointly by invitation and consent in both Journal of Clinical Oncology and Blood.

American Society of Hematology/American Society of Clinical Oncology clinical practice guideline update on the use of epoetin and darbepoetin in adult patients with cancer

Purpose: To update American Society of Hematology/American Society of Clinical Oncology recommendations for use of erythropoiesis-stimulating agents (ESAs) in patients with cancer. Methods: An Update Committee reviewed data published between January 2007 and January 2010. MEDLINE and the Cochrane Library were searched. Results: The literature search yielded one new individual patient data analysis and four literature-based meta-analyses, two systematic reviews, and 13 publications reporting new results from randomized controlled trials not included in prior or new reviews. Recommendations: For patients undergoing myelosuppressive chemotherapy who have a hemoglobin (Hb) level less than 10 g/dL, the Update Committee recommends that clinicians discuss potential harms (eg, thromboembolism, shorter survival) and benefits (eg, decreased transfusions) of ESAs and compare these with potential harms (eg, serious infections, immune-mediated adverse reactions) and benefits (eg, rapid Hb improvement) of RBC transfusions. Individual preferences for assumed risk should contribute to shared decisions on managing chemotherapy-induced anemia. The Committee cautions against ESA use under other circumstances. If used, ESAs should be administered at the lowest dose possible and should increase Hb to the lowest concentration possible to avoid transfusions. Available evidence does not identify Hb levels 10 g/dL either as thresholds for initiating treatment or as targets for ESA therapy. Starting doses and dose modifications after response or nonresponse should follow US Food and Drug Administration-approved labeling. ESAs should be discontinued after 6 to 8 weeks in nonresponders. ESAs should be avoided in patients with cancer not receiving concurrent chemotherapy, except for those with lower risk myelodysplastic syndromes. Caution should be exercised when using ESAs with chemotherapeutic agents in diseases associated with increased risk of thromboembolic complications. Table 1 lists detailed recommendations.