correlating imaging parameters with molecular data an integrated approach to improve the management of breast cancer patients

The goal of this review is to provide an overview of the studies aimed at integrating imaging parameters with molecular biomarkers for improving breast cancer patient's diagnosis and prognosis. The use of diagnostic imaging to extract quantitative parameters related to the morphology, metabolism, and functionality of tumors, as well as their correlation with cancer tissue biomarkers is an emerging research topic. Thanks to the development of imaging biobanks and the technological tools required for extraction of imaging parameters including radiomic features, it is possible to integrate imaging markers with genetic data. This new field of study represents the evolution of radiology–pathology correlation from an anatomic–histologic level to a genetic level, which paves new interesting perspectives for breast cancer management

The new paradigm of Network Medicine to analyse breast cancer phenotypes

Breast cancer (BC) is a heterogeneous and complex disease as witnessed by the existence of different subtypes and clinical characteristics that poses significant challenges in disease management. The complexity of this tumor may rely on the highly interconnected nature of the various biological processes as stated by the new paradigm of Network Medicine. We explored The Cancer Genome Atlas (TCGA)-BRCA data set, by applying the network-based algorithm named SWItch Miner, and mapping the findings on the human interactome to capture the molecular interconnections associated with the disease modules. To characterize BC phenotypes, we constructed protein–protein interaction modules based on “hub genes”, called switch genes, both common and specific to the four tumor subtypes. Transcriptomic profiles of patients were stratified according to both clinical (immunohistochemistry) and genetic (PAM50) classifications. 266 and 372 switch genes were identified from immunohistochemistry and PAM50 classifications, respectively. Moreover, the identified switch genes were functionally characterized to select an interconnected pathway of disease genes. By intersecting the common switch genes of the two classifications, we selected a unique signature of 28 disease genes that were BC subtype-independent and classification subtype-independent. Data were validated both in vitro (10 BC cell lines) and ex vivo (66 BC tissues) experiments. Results showed that four of these hub proteins (AURKA, CDC45, ESPL1, and RAD54L) were over-expressed in all tumor subtypes. Moreover, the inhibition of one of the identified switch genes (AURKA) similarly affected all BC subtypes. In conclusion, using a network-based approach, we identified a common BC disease module which might reflect its pathological signature, suggesting a new vision to face with the disease heterogeneity

Extended flow cytometry characterization of normal bone marrow progenitor cells by simultaneous detection of aldehyde dehydrogenase and early hematopoietic antigens: implication for erythroid differentiation studies

<p>Abstract</p> <p>Background</p> <p>Aldehyde dehydrogenase (ALDH) is a cytosolic enzyme highly expressed in hematopoietic precursors from cord blood and granulocyte-colony stimulating factor mobilized peripheral blood, as well as in bone marrow from patients with acute myeloblastic leukemia. As regards human normal bone marrow, detailed characterization of ALDH⁺cells has been addressed by one single study (Gentry <it>et al</it>, 2007). The goal of our work was to provide new information about the dissection of normal bone marrow progenitor cells based upon the simultaneous detection by flow cytometry of ALDH and early hematopoietic antigens, with particular attention to the expression of ALDH on erythroid precursors. To this aim, we used three kinds of approach: i) multidimensional analytical flow cytometry, detecting ALDH and early hematopoietic antigens in normal bone marrow; ii) fluorescence activated cell sorting of distinct subpopulations of progenitor cells, followed by <it>in vitro </it>induction of erythroid differentiation; iii) detection of ALDH⁺cellular subsets in bone marrow from pure red cell aplasia patients.</p> <p>Results</p> <p>In normal bone marrow, we identified three populations of cells, namely ALDH⁺CD34⁺, ALDH^-CD34⁺and ALDH⁺CD34^-(median percentages were 0.52, 0.53 and 0.57, respectively). As compared to ALDH^-CD34⁺cells, ALDH⁺CD34⁺cells expressed the phenotypic profile of primitive hematopoietic progenitor cells, with brighter expression of CD117 and CD133, accompanied by lower display of CD38 and CD45RA. Of interest, ALDH⁺CD34^-population disclosed a straightforward erythroid commitment, on the basis of three orders of evidences. First of all, ALDH⁺CD34^-cells showed a CD71^bright, CD105⁺, CD45^-phenotype. Secondly, induction of differentiation experiments evidenced a clear-cut expression of glycophorin A (CD235a). Finally, ALDH⁺CD34^-precursors were not detectable in patients with pure red cell aplasia (PRCA).</p> <p>Conclusion</p> <p>Our study, comparing surface antigen expression of ALDH⁺/CD34⁺, ALDH^-/CD34⁺and ALDH⁺/CD34^-progenitor cell subsets in human bone marrow, clearly indicated that ALDH⁺CD34^-cells are mainly committed towards erythropoiesis. To the best of our knowledge this finding is new and could be useful for basic studies about normal erythropoietic differentiation as well as for enabling the employment of ALDH as a red cell marker in polychromatic flow cytometry characterization of bone marrow from patients with aplastic anemia and myelodysplasia.</p

LINC00958 as new diagnostic and prognostic biomarker of childhood acute lymphoblastic leukaemia of B cells

BackgroundPaediatric acute B-cell lymphoblastic leukaemia is the most common cancer of the paediatric age. Although the advancement of scientific and technological knowledge has ensured a huge step forward in the management of this disease, there are 15%–20% cases of recurrence leading to serious complications for the patient and sometimes even death. It is therefore necessary to identify new and increasingly personalised biomarkers capable of predicting the degree of risk of B-ALL in order to allow the correct management of paediatric leukaemia patients.MethodsStarting from our previously published results, we validate the expression level of LINC00958 in a cohort of 33 B-ALL and 9 T-ALL childhood patients, using in-silico public datasets as support. Expression levels of LINC00958 in B-ALL patients stratified by risk (high risk vs. standard/medium risk) and who relapsed 3 years after the first leukaemia diagnosis were also evaluated.ResultsWe identified the lncRNA LINC00958 as a biomarker of B-ALL, capable of discriminating B-ALL from T-ALL and healthy subjects. Furthermore, we associated LINC00958 expression levels with the disease risk classification (high risk and standard risk). Finally, we show that LINC00958 can be used as a predictor of relapses in patients who are usually stratified as standard risk and thus not always targeted for marrow transplantation.ConclusionsOur results open the way to new diagnostic perspectives that can be directly used in clinical practice for a better management of B-ALL paediatric patients

The percentage of CD133+ cells in human colorectal cancer cell lines is influenced by Mycoplasma hyorhinis infection

<p>Abstract</p> <p>Background</p> <p><it>Mollicutes </it>contamination is recognized to be a critical issue for the cultivation of continuous cell lines. In this work we characterized the effect of <it>Mycoplasma hyorhinis </it>contamination on CD133 expression in human colon cancer cell lines.</p> <p>Methods</p> <p>MycoAlert^®and mycoplasma agar culture were used to detect mycoplasma contamination on GEO, SW480 and HT-29 cell lines. Restriction fragment length polymorphism assay was used to determine mycoplasma species. All cellular models were decontaminated by the use of a specific antibiotic panel (Enrofloxacin, Ciprofloxacin, BM Cyclin 1 and 2, Mycoplasma Removal Agent and MycoZap^®). The percentage of CD133 positive cells was analyzed by flow cytometry on GEO, SW480 and HT-29 cell lines, before and after <it>Mycoplasma hyorhinis </it>eradication.</p> <p>Results</p> <p><it>Mycoplasma hyorhinis </it>infected colon cancer cell lines showed an increased percentage of CD133+ cells as compared to the same cell lines rendered mycoplasma-free by effective exposure to antibiotic treatment. The percentage of CD133 positive cells increased again when mycoplasma negative cells were re-infected by <it>Mycoplasma hyorhinis</it>.</p> <p>Conclusions</p> <p><it>Mycoplasma hyorhinis </it>infection has an important role on the quality of cultured human colon cancer cell lines giving a false positive increase of cancer stem cells fraction characterized by CD133 expression. Possible explanations are (i) the direct involvement of Mycoplasma on CD133 expression or (ii) the selective pressure on a subpopulation of cells characterized by constitutive CD133 expression.</p> <p>In keeping with United Kingdom Coordinating Committee on Cancer Research (UKCCCR) guidelines, the present data indicate the mandatory prerequisite, for investigators involved in human colon cancer research area, of employing mycoplasma-free cell lines in order to avoid the production of non-reproducible or even false data.</p

Cancer Cell Lines Are Useful Model Systems for Medical Research

Cell lines are in vitro model systems that are widely used in different fields of medical research, especially basic cancer research and drug discovery. Their usefulness is primarily linked to their ability to provide an indefinite source of biological material for experimental purposes. Under the right conditions and with appropriate controls, authenticated cancer cell lines retain most of the genetic properties of the cancer of origin. During the last few years, comparing genomic data of most cancer cell lines has corroborated this statement and those that were observed studying the tumoral tissue equivalents included in the The Cancer Genome Atlas (TCGA) database. We are at the disposal of comprehensive open access cell line datasets describing their molecular and cellular alterations at an unprecedented level of accuracy. This aspect, in association with the possibility of setting up accurate culture conditions that mimic the in vivo microenvironment (e.g., three-dimensional (3D) coculture), has strengthened the importance of cancer cell lines for continuing to sustain medical research fields. However, it is important to consider that the appropriate use of cell lines needs to follow established guidelines for guaranteed data reproducibility and quality, and to prevent the occurrence of detrimental events (i.e., those that are linked to cross-contamination and mycoplasma contamination)