Piero Dalerba

Bio: Piero Dalerba is an academic researcher from Columbia University. The author has contributed to research in topics: Stem cell & Cancer stem cell. The author has an hindex of 30, co-authored 54 publications receiving 15541 citations. Previous affiliations of Piero Dalerba include Istituto Superiore di Sanità & Stanford University.

Identification of Pancreatic Cancer Stem Cells

Abstract: Emerging evidence has suggested that the capability of a tumor to grow and propagate is dependent on a small subset of cells within a tumor, termed cancer stem cells. Although data have been provided to support this theory in human blood, brain, and breast cancers, the identity of pancreatic cancer stem cells has not been determined. Using a xenograft model in which primary human pancreatic adenocarcinomas were grown in immunocompromised mice, we identified a highly tumorigenic subpopulation of pancreatic cancer cells expressing the cell surface markers CD44, CD24, and epithelial-specific antigen (ESA). Pancreatic cancer cells with the CD44+CD24+ESA+ phenotype (0.2–0.8% of pancreatic cancer cells) had a 100-fold increased tumorigenic potential compared with nontumorigenic cancer cells, with 50% of animals injected with as few as 100 CD44+CD24+ESA+ cells forming tumors that were histologically indistinguishable from the human tumors from which they originated. The enhanced ability of CD44+CD24+ESA+ pancreatic cancer cells to form tumors was confirmed in an orthotopic pancreatic tail injection model. The CD44+CD24+ESA+ pancreatic cancer cells showed the stem cell properties of self-renewal, the ability to produce differentiated progeny, and increased expression of the developmental signaling molecule sonic hedgehog. Identification of pancreatic cancer stem cells and further elucidation of the signaling pathways that regulate their growth and survival may provide novel therapeutic approaches to treat pancreatic cancer, which is notoriously resistant to standard chemotherapy and radiation. [Cancer Res 2007;67(3):1030–7]

Identification of a subpopulation of cells with cancer stem cell properties in head and neck squamous cell carcinoma

Abstract: Like many epithelial tumors, head and neck squamous cell carcinoma (HNSCC) contains a heterogeneous population of cancer cells. We developed an immunodeficient mouse model to test the tumorigenic potential of different populations of cancer cells derived from primary, unmanipulated human HNSCC samples. We show that a minority population of CD44(+) cancer cells, which typically comprise <10% of the cells in a HNSCC tumor, but not the CD44(-) cancer cells, gave rise to new tumors in vivo. Immunohistochemistry revealed that the CD44(+) cancer cells have a primitive cellular morphology and costain with the basal cell marker Cytokeratin 5/14, whereas the CD44(-) cancer cells resemble differentiated squamous epithelium and express the differentiation marker Involucrin. The tumors that arose from purified CD44(+) cells reproduced the original tumor heterogeneity and could be serially passaged, thus demonstrating the two defining properties of stem cells: ability to self-renew and to differentiate. Furthermore, the tumorigenic CD44(+) cells differentially express the BMI1 gene, at both the RNA and protein levels. By immunohistochemical analysis, the CD44(+) cells in the tumor express high levels of nuclear BMI1, and are arrayed in characteristic tumor microdomains. BMI1 has been demonstrated to play a role in self-renewal in other stem cell types and to be involved in tumorigenesis. Taken together, these data demonstrate that cells within the CD44(+) population of human HNSCC possess the unique properties of cancer stem cells in functional assays for cancer stem cell self-renewal and differentiation and form unique histological microdomains that may aid in cancer diagnosis.

Phenotypic characterization of human colorectal cancer stem cells

Abstract: Recent observations indicate that, in several types of human cancer, only a phenotypic subset of cancer cells within each tumor is capable of initiating tumor growth. This functional subset of cancer cells is operationally defined as the “cancer stem cell” (CSC) subset. Here we developed a CSC model for the study of human colorectal cancer (CRC). Solid CRC tissues, either primary tissues collected from surgical specimens or xenografts established in nonobese diabetic/severe combined immunodeficient (NOD/SCID) mice, were disaggregated into single-cell suspensions and analyzed by flow cytometry. Surface markers that displayed intratumor heterogeneous expression among epithelial cancer cells were selected for cell sorting and tumorigenicity experiments. Individual phenotypic cancer cell subsets were purified, and their tumor-initiating properties were investigated by injection in NOD/SCID mice. Our observations indicate that, in six of six human CRC tested, the ability to engraft in vivo in immunodeficient mice was restricted to a minority subpopulation of epithelial cell adhesion molecule (EpCAM)high/CD44+ epithelial cells. Tumors originated from EpCAMhigh/CD44+ cells maintained a differentiated phenotype and reproduced the full morphologic and phenotypic heterogeneity of their parental lesions. Analysis of the surface molecule repertoire of EpCAMhigh/CD44+ cells led to the identification of CD166 as an additional differentially expressed marker, useful for CSC isolation in three of three CRC tested. These results validate the stem cell working model in human CRC and provide a highly robust surface marker profile for CRC stem cell isolation.

Cancer Stem Cells: Models and Concepts

Abstract: Although monoclonal in origin, most tumors appear to contain a heterogeneous population of cancer cells. This observation is traditionally explained by postulating variations in tumor microenvironment and coexistence of multiple genetic subclones, created by progressive and divergent accumulation of independent somatic mutations. An additional explanation, however, envisages human tumors not as mere monoclonal expansions of transformed cells, but rather as complex tridimensional tissues where cancer cells become functionally heterogeneous as a result of differentiation. According to this second scenario, tumors act as caricatures of their corresponding normal tissues and are sustained in their growth by a pathological counterpart of normal adult stem cells, cancer stem cells. This model, first developed in human myeloid leukemias, is today being extended to solid tumors, such as breast and brain cancer. We review the biological basis and the therapeutic implications of the stem cell model of cancer.

The CD47-signal regulatory protein alpha (SIRPa) interaction is a therapeutic target for human solid tumors

Abstract: CD47, a "don't eat me" signal for phagocytic cells, is expressed on the surface of all human solid tumor cells Analysis of patient tumor and matched adjacent normal (nontumor) tissue revealed that CD47 is overexpressed on cancer cells CD47 mRNA expression levels correlated with a decreased probability of survival for multiple types of cancer CD47 is a ligand for SIRPα, a protein expressed on macrophages and dendritic cells In vitro, blockade of CD47 signaling using targeted monoclonal antibodies enabled macrophage phagocytosis of tumor cells that were otherwise protected Administration of anti-CD47 antibodies inhibited tumor growth in orthotopic immunodeficient mouse xenotransplantation models established with patient tumor cells and increased the survival of the mice over time Anti-CD47 antibody therapy initiated on larger tumors inhibited tumor growth and prevented or treated metastasis, but initiation of the therapy on smaller tumors was potentially curative The safety and efficacy of targeting CD47 was further tested and validated in immune competent hosts using an orthotopic mouse breast cancer model These results suggest all human solid tumor cells require CD47 expression to suppress phagocytic innate immune surveillance and elimination These data, taken together with similar findings with other human neoplasms, show that CD47 is a commonly expressed molecule on all cancers, its function to block phagocytosis is known, and blockade of its function leads to tumor cell phagocytosis and elimination CD47 is therefore a validated target for cancer therapies

SPAdes: A New Genome Assembly Algorithm and Its Applications to Single-Cell Sequencing

Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V−SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online (http://bioinf.spbau.ru/spades). It is distributed as open source software.

SPAdes, a new genome assembly algorithm and its applications to single-cell sequencing ( 7th Annual SFAF Meeting, 2012)

Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

Myeloid-derived suppressor cells as regulators of the immune system.

Abstract: Myeloid-derived suppressor cells (MDSCs) are a heterogeneous population of cells that expand during cancer, inflammation and infection, and that have a remarkable ability to suppress T-cell responses. These cells constitute a unique component of the immune system that regulates immune responses in healthy individuals and in the context of various diseases. In this Review, we discuss the origin, mechanisms of expansion and suppressive functions of MDSCs, as well as the potential to target these cells for therapeutic benefit.

Supervised Risk Predictor of Breast Cancer Based on Intrinsic Subtypes

Abstract: Purpose To improve on current standards for breast cancer prognosis and prediction of chemotherapy benefit by developing a risk model that incorporates the gene expression–based “intrinsic” subtypes luminal A, luminal B, HER2-enriched, and basal-like. Methods A 50-gene subtype predictor was developed using microarray and quantitative reverse transcriptase polymerase chain reaction data from 189 prototype samples. Test sets from 761 patients (no systemic therapy) were evaluated for prognosis, and 133 patients were evaluated for prediction of pathologic complete response (pCR) to a taxane and anthracycline regimen. Results The intrinsic subtypes as discrete entities showed prognostic significance (P = 2.26E-12) and remained significant in multivariable analyses that incorporated standard parameters (estrogen receptor status, histologic grade, tumor size, and node status). A prognostic model for node-negative breast cancer was built using intrinsic subtype and clinical information. The C-index estimate for t...