FIELD OF THE INVENTION

The present invention relates to the field of medicine, in particular of oncology. It provides a new prognostic and/or diagnostic marker in human cancer.

BACKGROUND OF THE INVENTION

Cancer occurs when cell division gets out of control and results from impairment of a DNA repair pathway, the transformation of a normal gene into an oncogene or the malfunction of a tumor supressor gene. Many different forms of cancer exist. The incidence of these cancers varies but it represents the second highest cause of mortality, after heart disease, in most developed countries. While different forms of cancer have different properties, one factor which many cancers share is the ability to metastasize. Distant metastasis of all malignant tumors remains the primary cause of death in patients with the disease.

The therapeutic care of the patients having cancer is primarily based on surgery, radiotherapy and chemotherapy and the practitioner has to choose the most adapted therapeutic strategy for the patient. In the majority of the cases, the choice of the therapeutic protocol is based on the anatomo-pathological and clinical data. Currently, the methods to determine prognosis and select patients for adjuvant therapy rely mainly on pathological and clinical staging. However, it is very difficult to predict which localized tumor will eventuate in distant metastasis. Therefore, there is a great need for the identification of prognostic markers that can accurately distinguish tumors associated with poor prognosis including high probability of metastasis, early disease progression, increased disease recurrence or decreased patient survival, from the others. Using such markers, the practitioner can predict the patient's prognosis and can effectively target the individuals who would most likely benefit from adjuvant therapy.

SUMMARY OF THE INVENTION

The inventors demonstrate that HPlα is overexpressed in cancer cells in comparison with non-tumoral cells and that high HPlα expression levels in cancer cells are correlated with a poor prognosis including early disease progression, increased metastasis formation, increased disease recurrence and/or decreased patient survival. Accordingly, in a first aspect, the present invention concerns a method for predicting or monitoring clinical outcome of a subject affected with a cancer, wherein the method comprises the step of determining the expression level of HPl α in a cancer sample from said subject, a high expression level of HPlα being indicative of a poor prognosis. Preferably, a poor prognosis is a decreased patient survival and/or an early disease progression and/or an increased disease recurrence and/or an increase metastasis formation.

In a second aspect, the present invention concerns a method for diagnosing a cancer in a subject, wherein the method comprises the step of determining the expression level of HPlα in a sample from said subject, a high expression level of HPlα indicating that said subject suffers from a cancer.

In a third aspect, the present invention concerns a method for selecting a subject affected with a cancer for an adjuvant chemotherapy and/or radiotherapy or determining whether a subject affected with a cancer is susceptible to benefit from an adjuvant chemotherapy and/or radiotherapy, wherein the method comprises the step of determining the expression level of HPlα in a cancer sample from said subject, a high expression level of HPlα indicating that an adjuvant chemotherapy and/or radiotherapy is required.

In a last aspect, the present invention concerns a method for monitoring the response to a treatment of a subject affected with a cancer, wherein the method comprises the step of determining the expression level of HPlα in a cancer sample from said subject before the administration of the treatment , and in a cancer sample from said subject after the administration of the treatment, a decreased expression level of HPlα in the sample obtained after the administration of the treatment indicating that the subject is responsive to the treatment.

In one embodiment, the expression level of HPlα is determined by measuring the quantity of HP 1 α protein or HP 1 α mRNA.

In a further embodiment, the quantity of HPlα protein is measured by immunohistochemistry, semi-quantitative Western-blot or by protein or antibody arrays.

In another further embodiment, the quantity of HPlα mRNA is measured by quantitative or semi-quantitative RT-PCR, or by real time quantitative or semi-quantitative RT- PCR or by transcriptome approaches.

In another embodiment, the methods of the invention comprise the step of comparing the expression level of HPlα to a reference expression level. Additionally, the methods of the invention further comprise the step of determining whether the expression level of HPl α is high compared to said reference expression level.

In a further embodiment, the reference expression level is the expression level of HPl α in a normal sample. Alternatively, the reference expression level is the expression level of a gene having a stable expression in different cancer samples, such as RPLPO gene.

In still another embodiment, the method according to the invention further comprises assessing at least one another cancer or prognosis markers such as tumor grade, hormone receptor status, mitotic index, tumor size, HJURP expression level or expression of proliferation markers such as Ki67, MCM2, CAF-I p60 and CAF-I pi 50.

In still another embodiment, the cancer is a solid cancer or a hematopoietic cancer, preferably a solid cancer and more preferably, an early stage solid cancer without local or systemic invasion.

Preferably, the cancer is selected from the group consisting of breast cancer, pancreas cancer, uterus and cervix cancers, ovary cancer, prostate cancer and leukemia. More preferably, the cancer is breast cancer. Even more preferably, the cancer is an early stage breast cancer without local or systemic invasion.

BRIEF DESCRIPTION OF THE DRAWINGS

Figure 1: The expression of HPlα, but not β or γ, is downregulated in quiescence. Fig IA. Total protein levels of HPlα, β and γ are detected by Western Blot in asynchronously proliferating (As.) and quiescent (GO) WI38 lung fibroblasts, MCF7 breast cancer cells and BJ primary foreskin fibroblasts. Fibroblasts are arrested in quiescence by serum starvation and MCF7 cells by anti-estrogen treatment. Increasing amounts (x) of total cells extracts are loaded and β-actin serves as a loading control. CAF-I p60 (Polo et al, 2004) and Cyclin A are used as markers for cell proliferation. Fig IB. Flow cytometry analysis of the cell cycle distribution of the cells shown in A. Fig 1C HPlα mRNA levels in proliferating (As.) and quiescent (GO) BJ foreskin fibroblasts, as determined by quantitative RT-PCR. Levels are normalized to the reference gene ribosomal protein PO-like protein (RPLPO) (de Cremoux et al, 2004) and levels in proliferating cells are set to 100%. CAF-I p60 and CAF-I pi 50 levels are shown for comparison. Error bar represents data from three independent experiments.

Figure 2: HPlα levels progressively increase after exit from quiescence. Fig 2A. BJ primary fibroblasts are arrested in quiescence (GO) by serum starvation and released by adding back serum for the indicated time period. Total protein levels are analyzed by Western blot. CAF-I p60 (Polo et al, 2004) and Cyclin A are used as markers for cell proliferation, β-actin is used as a loading control. Fig 2B. Flow cytometry analysis of the cell cycle distribution of the cells shown in Fig 2A.

Figure 3: HPIa expression does not visibly vary during the cell cycle. Fig 3 A. HeLa cervical carcinoma cells are synchronized in the cell cycle by release from double thymidine block (Gl, Gl/S, S, G2) and by nocodazole (M). Total protein extracts are analyzed for HPl α expression levels using Western Blot, β-actin is used as a loading control and Cyclin A as a marker for G2/S phases. CAF-I p60 is shown for comparison. Fig 3B. Flow cytometry cell cycle analysis of the synchronized cells used in Fig 3A. Fig 3C. BJ foreskin primary fibroblasts are synchronized in the cell cycle by release from double thymidine block (Gl, Gl/S, S, G2) and by nocodazole (M). HPlα protein levels are analyzed in total cell extracts by Western Blot, β-actin is used as a loading control and Cyclin A as a marker for G2/S phases. CAF-I p60 is shown for comparison. Fig 3D. Flow cytometry analysis of the cell cycle distribution of the synchronized cells shown in Fig 3C. Fig 3E. HPlα mRNA levels in synchronized BJ cells, as determined by quantitative RT-PCR. Levels are normalized to the reference gene ribosomal protein PO-like protein (RPLPO) (de Cremoux et al, 2004) and levels in asynchronously proliferating cells are set to 100%. CAF-I p60 and CAF-I pi 50 levels are shown for comparison (Polo et al, 2004). Error bars represent data from two independent experiments.

Figure 4: HPlα is overexpressed in breast cancer cells and associated with chromatin. Fig. 4 A. Scheme of the experimental procedure applied to obtain total, soluble and chromatin-bound cell extracts as used in Fig. 4B. Fig. 4B. HPlα, β and γ protein levels are analyzed by Western Blot in soluble and chromatin-bound nuclear extracts from the breast cancer cell line Hs578T (T) and in the non-tumoral mammary cell line Hs578Bst (Bst), which are derived from the same patient (Hackett et al, 1977). Cyclin A and CAF-I p60 are shown for comparison. Increasing amounts (x) of total cells extracts are loaded; β-actin serves as a loading control. Fig. 4C. Relative quantification of total HPlα protein levels in tumoral (T) and non-tumoral (Bst) mammary cells, compared to the amounts of CAF-I p60 (Polo et al, 2004). Increasing amounts (x) of total cells extracts are loaded; β-actin serves as a loading control. Fig. 4D. Flow cytometry analysis of tumoral (T) and non-tumoral (Bst) mammary cells in order to assess polyploidy. Tumoral (T) and non-tumoral (Bst) cells contain 25% and 13% of cells in S-phase, respectively. Fig. 4E. Relative HPlα mRNA levels in tumoral (T) and non-tumoral (Bst) mammary cells, as determined by quantitative RT-PCR. Levels are normalized to the reference gene ribosomal protein PO-like protein (RPLPO) (de Cremoux et al, 2004) and non- tumoral cells are set to 100%. CAF-I pi 50 is shown for comparison. Error bar represents data from two independent experiments.

Figure 5: Levels of HPl proteins in soluble and chromatin-bound nuclear fractions. Fig. 5 A. Scheme depicting the extraction procedure to obtain soluble and chromatin- bound nuclear fractions of the breast cancer cell line Hs578T (T) and the healthy mammary cell line Hs578Bst (Bst), which are derived from the same patient (Hackett et al, 1977). Fig. 5B. HPlα, β and γ protein levels are analyzed by Western Blot in soluble and chromatin-bound nuclear extracts from the cancer cells Hs578T (T) and the healthy cells Hs578Bst (Bst). Loading was corrected in a manner to deposit an identical amount of cells (2x105 and 4x105 cells for each extract). Several classical loading controls were revealed. While the fractionation of α-tubulin and the presence of β-actin differ slightly between tumoral and healthy cells, GAPDH reflects best the identical loading under these experimental conditions. Cyclin A and CAF-I p60 are shown for comparison.

Figure 6: Nuclear distribution of HPl α, but not H3K9me3, is altered in breast cancer cells compared to healthy mammary cells. Fig 6A. Immunofluorescence staining of HPlα in the breast cancer cell line Hs578T (T) and in the non-tumoral mammary cell line Hs578Bst (Bst). Costaining for centromeres, using CREST patient serum, reveals a partial although incomplete colocalization with the HPlα spots in Hs578T breast cancer cells. DNA is stained with DAPI. Indicated below the microscopy images are the mean percentages of cells showing clearly distinguishable HPlα spots in the breast cancer cell line Hs578T (T) and in the healthy mammary cell line Hs578Bst (Bst). Standard error, based on two independent experiments, is indicated. Fig. 6B. Nuclear distribution of the H3K9me3 histone modification, compared to HPlα in the tumoral (T) and non-tumoral (Bst) mammary cells. DNA is revealed with DAPI. Fig. 6C. Costaining of HPlα with Cdtl (indicative for Gl phase), Cyclin A (indicative for S and G2 phase), or with histone H3 phosphorylated on SlO (H3S10P, indicative for G2 and M phase), does not reveal a correlation between cell cycle status and spotted HPlα patterns. Scale bars: 10 μm.

Figure 7: Downregulation of HPlα, but not HPlβ or γ, leads to mitotic defects in HeLa cells. Fig. 7 A. Western Blot analysis of total cell extracts from HeLa cells 72 hours after transfection with siRNA sequences targeting HPlα (named siHPlα.3), HPlβ, HPlγ or control siRNA (siGFP). Increasing amounts (x) of total cells extracts are loaded and β-actin is used as a loading control. Fig. 7B. Flow cytometry analysis of the cell cycle distribution of cells shown in A. Fig. 7C. Typical mitotic figures after transfection with siRNA sequences targeting HPlα, HPlβ, HPlγ or mock siRNA (siGFP). Fig. 7D. Percentage of aberrant mitotic figures (lagging chromosomes, misalignments, chromosome bridges) in asynchronous HeLa cells 72h after transfection with siRNA sequences targeting HPlα, HPlβ, HPlγ or mock siRNA (siGFP). Error bars represent data from three independent, blind counted, experiments. Fig. 7E. DAPI staining reveals micronuclei formation 72h after transfection with an siRNA sequence targeting HPlα. Fig. 7F. Quantification of the percentage of micronucleated cells 72h after transfection with siRNA sequences targeting HPlα, HPlβ, HPlγ or control siRNA (siGFP). Error bars represent data from three independent experiments of which two were blind counted.

Figure 8: Downregulation of HPlα in primary cells affects (pro)metaphase. Fig. 8A. BJ primary fibroblasts are transfected by nucleofection with control siRNA (siGFP) or two different siRNA sequences targeting HPlα (α.l or α.3). Total protein levels are analyzed by Western blot. HPlβ and HPlγ are revealed to show the specificity of the siRNA for the HPlα isoform. Fig. 8B. Flow cytometry analysis of the cell cycle distribution of cells shown in Fig. 8A, 72 hours after transfection with control siRNA (siGFP) or two different siRNA sequences targeting HPlα (siHPlα.1/3). Fig. 8C. Profiles of mitotic cells are analyzed by immunofluorescence 72h after transfection. Enrichment in mitotic cells is achieved by a 6 hours release from a 12h thymidine block. Depicted are typical mitotic profiles (upper panel) and the presence of each mitotic phase as a percentage of the total number of mitotic cells (graph). Error bars represent standard errors, based on three independent experiments (n>100 for each) of which two were blind counted. Fig. 8D. Time of mitosis after two subsequent transfections with control siRNA (siGFP) or HPlα siRNA (siHPlα.3), as determined by live cell imaging. DNA is visualized by expression of H2B-Cherry (red). Images were acquired every 20 minutes for a period of 24h, starting 48h after the second transfection. The time of mitosis (upper graph) was defined as the time between the condensation of DNA and the establishment of two distinct cells. The average number of images depicting mitotic cells in (pro-)metaphase, before the onset if chromosome segregation, was also determined (lower graph). Means of three independent experiments are depicted, representing a total number of 130 and 87 mitotic cells for siGFP and siHPlα, respectively. P-values were determined with a test of Mann- Whitney Wilcoxon. Mean H2B-cherry transfection efficiencies were 37% and 39% for siGFP and siHPlα, respectively. Figure 9: HPlα mRNA is overexpressed in multiple types of cancer and correlates with clinical and molecular data. Fig. 9A. Boxplot representation of microarray expression profiles of HPlα in different types of cancer compared to normal tissue. Boxes represent the 25th-75th percentile; brackets: range; black line: median; black dots: outliers; n: sample number, p-values are based on Student's T-test. Results were analyzed and plotted using ONCOMINE (Rhodes et al, 2004), and exploited data from transcriptome studies on different tumor types (Andersson et al, 2007; Pyeon et al, 2007; Quade et al, 2004; Ramaswamy et al, 2003; Richardson et al, 2006; Yu et al, 2004). Fig. 9B. Left panel: Correlation of HPlα expression levels with the time to relapse in childhood acute lymphoblastic leukemia (Kirschner-Schwabe et al, 2006). Relapse occurs very early (within 18 months after initial diagnosis), early (>18 months after initial diagnosis but <6 months after cessation of frontline treatment) or late (>6 months after cessation of frontline treatment). Boxplot representation as in Fig. 9A. Right panels: Scatter plot representation of the positive correlation of HPlα expression levels with CAF-I pi 50 and the proliferation marker Ki67 expression levels in childhood acute lymphoblastic leukemia (Kirschner-Schwabe et al, 2006). Grey line: line of best fit; R: Pearson's correlation coefficient. Results were analyzed and plotted using ONCOMINE (Rhodes et al, 2004).

Figure 10: HPlα protein is overexpressed in multiple types of human cancer. Fig. 1OA. Frozen human tissue arrays containing sections from tumoral and healthy origin were stained for HPlα by immunohistochemistry and counterstained with hematoxylin. Fig. 1OB. Frozen uterus tissue sections were stained for HPlα, β and γ by immunohistochemistry and counterstained with hematoxylin. Tissue arrays were processed identically for the three antibodies. Fig. 1OC. Two adjacent sections from a frozen medullary breast carcinoma were stained for HPlα and epithelial pan-cytokeratin marker KL-I, by immunofluorescence (IF). DNA is revealed with DAPI. Areas of HPlα overexpression correspond to regions of epithelial tumor cells. Scale bars: 100 μm.

Figure 11: Overexpression of HPlα in human tumor samples is detected with a polyclonal antibody and is not accompanied by altered H3K9me3 staining. Fig. HA. Immunohistochemistry staining, using a polyclonal HPlα antibody, of a tissue array containing frozen human tissue sections from tumoral and healthy origin. Tissues were counterstained with hematoxylin. Fig. HB. A frozen human tissue array (same batch as in Fig. 1 IA.) was stained for H3K9me3 by immunohistochemistry and counterstained with hematoxylin. Scale bars: 50 μm.

Figure 12: HPlα expression levels have a prognostic value in breast cancer patients. Fig. 12A. Boxplots representing logarithmic HPlα mRNA expression levels, according to the indicated clinico-patho logical factors, in 86 breast cancer samples with a >10 year patient follow-up. Boxes represent the 25th-75th percentile; brackets: range; black line: median; black dots: outliers. Fig. 12B. Univariate Kaplan-Meier curves of the survival, the occurrence of metastasis and the disease-free interval (interval before the occurrence of local recurrence, regional lymph node recurrence, contralateral breast cancer or metastasis) in patients expressing high (>10) or low (≤IO) levels of HPl α. The number of patients at risk at each time point is indicated below the graphs. Figure 13 : Expression levels in breast cancer sub-types. Fig. 13 A. Molecular features of studied breast cancer samples. ER: estrogen receptor; PR: progesterone receptor. Fig. 13B and 13C. Boxplots representing the expression levels of HPlα as determined at the mRNA level in microarray transcriptome data (Fig. 13B) or at the protein level using Reverse Phase Protein Arrays (Fig. 13C). Boxes represent the 25-75th percentile; brackets: range; black line: median; black dots: outliers. The number of samples per group is indicated below the graphs (n). Asterisks indicate significant difference between groups (T-test).

DETAILED DESCRIPTION OF THE INVENTION

Mammalian cells contain three closely related Heterochromatin Protein 1 iso forms, HPlα, β and γ, which, by analogy to their unique counterpart in S.pombe, have been implicated in gene silencing, genome stability and chromosome segregation.

A first possible link between HPl proteins and tumorigenesis was put forward through the observation that HPl interacts with the tumor suppressor Retinoblastoma protein (Rb) (Nielsen et al, 2001b; Williams & Grafi, 2000) and participates in the Rb-dependent silencing of cell cycle genes, such as Cyclin E (Nielsen et al, 2001b). Similarly, HPl interacts with the transcriptional co-repressor KAP-I (Ryan et al, 1999), which is involved in the regulation of the E2F1 (Wang et al, 2007) and p53 (Wang et al, 2005) proteins. Furthermore, HPlα and γ are found in a complex with Chromatin assembly factor 1 (CAF-I) (Murzina et al, 1999; Quivy et al, 2004), of which the intermediate subunit p60 is a validated proliferation marker in breast cancer (Polo et al, 2004). However, the specific and/or common regulation patterns of the three HPl isoforms in relation to cell proliferation, quiescence and cancer remained elusive.

The inventors demonstrated that HPlα shows the unique property of displaying a proliferation-dependent expression pattern and that a significant overexpression of HPlα, but not β or γ, was observed in cancer cells when compared to non-tumoral cells derived from the same patient. This HPlα overexpression was observed in pancreas, uterus, ovary, prostate and breast carcinomas. These results show that HPlα constitutes a marker for diagnosis of multiple types of cancer. Inventors herein also demonstrate that HPlα expression levels in carcinomas correlate with clinical data and disease outcome. They show that high HPlα expression levels in carcinomas correlate with decreased patient survival, early disease progression, increased disease recurrence and/or increased occurrence of metastasis over time, i.e. a poor prognosis.

Definitions

As used herein, the term "HPlα" refers to the heterochromatin protein 1 -alpha, a highly conserved nonhistone protein. Three accession numbers correspond to the human HPlα in Genbank: NP OOl 120793, NP OOl 120794, NP 036249. This protein is encoded by the gene CBX5 (GenelD: 23468).

The term "cancer" or "tumor", as used herein, refers to the presence of cells possessing characteristics typical of cancer-causing cells, such as uncontrolled proliferation, immortality, metastatic potential, rapid growth and proliferation rate, and certain characteristic morphological features. This term refers to any type of malignancy (primary or metastases). Typical cancers are solid or hematopoietic cancers such as breast, stomach, oesophageal, sarcoma, ovarian, endometrium, bladder, cervix uteri, rectum, colon, lung or ORL cancers, paediatric tumours (neuroblastoma, glyoblastoma multiforme), lymphoma, leukaemia, myeloma, seminoma, Hodgkin and malignant hemopathies. Preferably, the cancer is selected from the group consisting of breast cancer, pancreas cancer, uterus and cervix cancers, ovary cancer, prostate cancer and leukemia. Preferably the cancer is a solid cancer, more preferably an early stage solid cancer without local or systemic invasion. Preferably, the solid cancer is breast cancer, more preferably an early stage breast cancer without local or systemic invasion. As used herein, the term "treatment", "treat" or "treating" refers to any act intended to ameliorate the health status of patients such as therapy, prevention, prophylaxis and retardation of the disease. In certain embodiments, such term refers to the amelioration or eradication of a disease or symptoms associated with a disease. In other embodiments, this term refers to minimizing the spread or worsening of the disease resulting from the administration of one or more therapeutic agents to a subject with such a disease.

As used herein, the term "chemotherapeutic treatment" or "chemotherapy" refers to a cancer therapeutic treatment using chemical or biochemical substances, in particular using one or several antineoplastic agents.

The term "radiotherapeutic treatment" or "radiotherapy" is a term commonly used in the art to refer to multiple types of radiation therapy including internal and external radiation therapies or radio immunotherapy, and the use of various types of radiations including X-rays, gamma rays, alpha particles, beta particles, photons, electrons, neutrons, radioisotopes, and other forms of ionizing radiations. The term "adjuvant therapy", as used herein, refers to chemotherapy or radiotherapy given as additional treatment, usually after surgical resection of the primary tumor, in a patient affected with a cancer that is at risk of metastasizing and/or likely to recur. The aim of such an adjuvant treatment is to improve the prognosis. As used herein, the term "poor prognosis" refers to a decreased patient survival and/or an early disease progression and/or an increased disease recurrence and/or an increased metastasis formation.

As used herein, the term "subject" or "patient" refers to an animal, preferably to a mammal, even more preferably to a human, including adult, child and human at the prenatal stage. However, the term "subject" can also refer to non-human animals, in particular mammals such as dogs, cats, horses, cows, pigs, sheeps and non-human primates, among others, that are in need of treatment.

The term "sample", as used herein, means any sample containing cells derived from a subject, preferably a sample which contains nucleic acids. Examples of such samples include fluids such as blood, plasma, saliva, urine and seminal fluid samples as well as biopsies, organs, tissues or cell samples. The sample may be treated prior to its use. The term "cancer sample" refers to any sample containing tumoral cells derived from a patient, preferably a sample which contains nucleic acids. Preferably, the sample contains only tumoral cells. The term "normal sample" refers to any sample which does not contain any tumoral cells. The methods of the invention as disclosed below, may be in vivo, ex vivo or in vitro methods, preferably in vitro methods.

In previous studies, an increased expression of HPlα has been correlated with a decreased invasive potential among several breast cancer cell lines (Kirschmann et al., 2000; Norwood et al., 2006). Inventors herein surprisingly demonstrate that high expression levels of

HPlα are on the contrary associated with a poor prognosis and thus with an increase risk of death.

Accordingly, the present invention concerns a method for predicting or monitoring clinical outcome of a subject affected with a cancer, wherein the method comprises the step of determining the expression level of HPlα in a cancer sample from said subject, a high expression level of HPlα being indicative of a poor prognosis.

In an embodiment, the method further comprises the step of providing a cancer sample from the subject. The expression level of HPl α can be determined from a cancer sample by a variety of techniques. In an embodiment, the expression level of HPl α is determined by measuring the quantity of HPl α protein or HPl α mRNA.

In a particular embodiment, the expression level of HPl α is determined by measuring the quantity of HPl α protein. The quantity of HPl α protein may be measured by any methods known by the skilled person. Usually, these methods comprise contacting the sample with a binding partner capable of selectively interacting with the HPlα protein present in the sample. The binding partner is generally a polyclonal or monoclonal antibody, preferably monoclonal. Polyclonal and monoclonal antibodies anti-HP lα are commercially available. Examples of these marketed antibodies are the mouse monoclonal anti-HP lα 2HP- 1H5 from Euromedex (directed against amino acids 67-119), the rabbit polyclonal anti-HP lα H2164 from Sigma (directed against amino acids 177-191) and the mouse monoclonal anti-HP lα 2HP-2G9 from Euromedex. The other antibodies used in the different methods to quantify the HPlα protein are well known by the skilled person and are commercially available. The quantity of HPlα protein may be measured by semi-quantitative Western blots, enzyme-labeled and mediated immunoassays, such as ELISAs, biotin/avidin type assays, radioimmunoassay, immuno electrophoresis or immunoprecipitation or by protein or antibody arrays. The protein expression level may be assessed by immunohistochemistry on a tissue section of the cancer sample (e.g. frozen or formalin- fixed paraffin embedded material). The reactions generally include revealing labels such as fluorescent, chemiluminescent, radioactive, enzymatic labels or dye molecules, or other methods for detecting the formation of a complex between the antigen and the antibody or antibodies reacted therewith. Preferably, the quantity of HPlα protein is measured by immunohistochemistry or semi-quantitative western-blot. HPlα detection by immunohistochemistry does not require an antigen-unmasking step, unlike the routinely used marker Ki-67, and thus speeds up the staining process.

In another embodiment, the expression level of HPlα is determined by measuring the quantity of HPlα mRNA. Methods for determining the quantity of mRNA are well known in the art. For example the nucleic acid contained in the sample (e.g., cell or tissue prepared from the patient) is first extracted according to standard methods, for example using lytic enzymes or chemical solutions or extracted by nucleic-acid-binding resins following the manufacturer's instructions. The extracted mRNA is then detected by hybridization (e. g., Northern blot analysis) and/or amplification (e.g., RT-PCR). Preferably quantitative or semi-quantitative RT- PCR is preferred. Real-time quantitative or semi-quantitative RT-PCR is particularly advantageous. Preferably, primer pairs were designed in order to overlap an intron, so as to distinguish cDNA amplification from putative genomic contamination. An example of primer pair which may be used in this method is presented in the experimental section and is constituted by the primers of SEQ ID NO.8 and SEQ ID NO.9. Other primers may be easily designed by the skilled person. Other methods of Amplification include ligase chain reaction (LCR), transcription-mediated amplification (TMA), strand displacement amplification (SDA) and nucleic acid sequence based amplification (NASBA). Preferably, the quantity of HPlα mRNA is measured by quantitative or semi-quantitative RT-PCR or by real-time quantitative or semi-quantitative RT-PCR or by transcriptome approaches.

In an embodiment, the method further comprises the step of comparing the expression level of HPlα to a reference expression level.

In a particular embodiment, the reference expression level is the expression level of HPlα in a normal sample. The normal sample is a non-tumoral sample, preferably from the same tissue than the cancer sample. The normal sample may be obtained from the subject affected with the cancer or from another subject, preferably a normal or healthy subject, i.e. a subject who does not suffer from a cancer. Preferably, the normal sample is obtained from the same subject than the cancer sample. Expression levels obtained from cancer and normal samples may be normalized by using expression levels of proteins which are known to have stable expression such as RPLPO (acidic ribosomal phosphoprotein PO), TBP (TATA box binding protein), GAPDH (glyceraldehyde 3-phosphate dehydrogenase) or β-actin. In another embodiment, the reference expression level is the expression level of a gene having a stable expression in different cancer samples. Such genes include for example, RPLPO, TBP, GAPDH or β-actin. Preferably, the reference expression level is the expression level of the RPLPO gene. The use of the human acidic ribosomal phosphoprotein PO (RPLPO) gene as reference was described in the article of de Cremoux et al. (de Cremoux et al., 2004). In a preferred embodiment, the quantity of HPlα mRNA is normalized according to the quantity of RPLPO mRNA. The quantity of RPLPO mRNA is used as reference quantity (i.e. 100%). The quantity of HPlα mRNA is expressed as a relative quantity with respect to the quantity of RPLPO mRNA.

In a further embodiment, the method further comprises the step of determining whether the expression level of HPlα is high compared to the reference expression level.

If the reference expression level is the expression level of HPlα in a normal sample, the expression level of HPlα in the cancer sample is considered as high if, after normalization, the level is at least 1.5-fold higher than the expression level in the normal sample. Preferably, the expression level of HPlα in the cancer sample is considered as high if the level is at least 2-fold higher, or 3, 4, 5 or 6-fold higher, than the expression level in the normal sample.

If the reference expression level is the expression level of a gene having a stable expression in different cancer samples, in particular the expression level of the RPLPO gene, the expression level of HPlα is considered as high if the level or quantity of HPlα mRNA is of at least 7, 8, 9, 10, 11, 12, 13, 14 or 15% of the RPLPO mRNA level or quantity. In a preferred embodiment the expression level of HPlα is considered as high if the level or quantity of HPlα mRNA is of at least 10% of the RPLPO mRNA level or quantity. This cut-off value may be easily adjusted by the skilled person using another reference gene. This cut-off value is in particular applicable for breast cancer. This value may vary depending on the type of cancer and will be easily adapted by the one skilled in the art.

In an embodiment, the present method further comprises assessing at least one another cancer or prognosis marker such as tumor grade, hormone receptor status, mitotic index, tumor size, HJURP expression level or expression of proliferation markers such as Ki67, MCM2, CAF-I p60 and CAF-I pi 50, preferably expression of CAF-I proliferation markers. These markers are commonly used and the results obtained with these markers may be combined with the results obtained with the present method in order to confirm the prognosis. The use of these markers is well-known by the skilled person. As example, the tumor grade may be determined according the Elston & Ellis method (Elston & Ellis, 2002), the hormone receptor status (estrogen and progesterone) may be determined at the protein or at the mRNA level, the mitotic index may be determined by counting mitotic cells in ten microscopic fields of a representative tissue section and the tumor size can be detected by imaging techniques (e.g. mammography), by palpation or after surgery in the excised tissue. Expression of Ki67 and CAF-I can be assessed at the protein level or at the mRNA level. High grade, high mitotic index, large size and/or high Ki67 or CAF-I expression are indicative for a worse prognosis. The HJURP expression level may be assessed as described in Hu et al, 2010. High HJURP expression is associated with poor clinical outcomes.

Using multivariate statistical analyses, the inventors have demonstrated, in the experimental section below, that HPlα expression levels predict disease outcome better than these standard prognostic markers.

Until now, the expression level of HPl has been compared in different cancer cell lines but no study was performed to compare the HPl expression levels in tumoral and non-tumoral cells. The inventors herein show, for the first time, that HPlα is specifically overexpressed in tumoral cells when compared to the HPlα expression in non-tumoral cells derived from the same patient. Such an overexpression thus constitutes a marker for diagnosis of multiple types of cancer, in particular breast cancer.

Accordingly, the present invention concerns a method for diagnosing a cancer in a subject, wherein the method comprises the step of determining the expression level of HPl α in a sample from said subject, a high expression level of HPl α indicating that said subject suffers from a cancer.

In an embodiment, the method further comprises the step of providing a sample from the subject. Preferably, this sample is suspected to contain tumoral cells.

The expression level of HPlα in this sample is determined as described above, preferably by measuring the quantity of HPlα protein or HPlα mRNA.

In an embodiment, the method further comprises the step of comparing the expression level of HPlα to a reference expression level, preferably, the expression level of HPlα in a normal sample. The normal sample is, as described above, a non-tumoral sample, preferably from the same tissue than the sample to be tested. The normal sample may be obtained from the subject to be diagnosed or from another subject, preferably a healthy subject. Expression levels obtained from the normal sample and from the sample to be tested may be normalized using expression levels of protein which are known to have a stable expression, such as described herein above.

In a further embodiment, the method further comprises the step of determining whether the expression level of HPlα is high compared to said reference expression level. A subject is diagnosed to suffer from a cancer if the expression level of HPlα in the sample to be tested is at least 10, 25, 50 or 75% higher than in the normal sample. Preferably, the subject is diagnosed to suffer from a cancer if the expression level of HPlα in the sample to be tested is at least 25% higher than in the normal sample. In another embodiment, the present method further comprises assessing at least one another marker used to diagnose cancer such as tumor grade, mitotic index, tumor size, HJURP expression level or expression of proliferation markers such as Ki67, MCM2, CAF-I p60 and CAF-I p 150, preferably expression of CAF-I proliferation markers. These markers are commonly used for diagnostic purposes and the results obtained with these markers may be combined with the results obtained with the present method in order to confirm the diagnosis.

The present invention also concerns a method for providing useful information for the diagnosis of a cancer in a subject, wherein the method comprises the step of determining the expression level of HPlα in a sample from said subject, a high expression level of HPlα indicating that said subject suffers from a cancer. In an embodiment, the method further comprises the step of providing a cancer sample from the subject.

In a further aspect, the present invention concerns a method for selecting a subject affected with a cancer for an adjuvant chemotherapy and/or radiotherapy or determining whether a subject affected with a cancer is susceptible to benefit from an adjuvant chemotherapy and/or radiotherapy, wherein the method comprises the step of determining the expression level of HPl α in a cancer sample from said subject, a high expression level of HPl α indicating that an adjuvant chemotherapy and/or radiotherapy is required.

In an embodiment, the method further comprises the step of providing a cancer sample from the subject.

The expression level of HPl α in the cancer sample is determined as described above, preferably by measuring the quantity of HPl α protein or HPlα mRNA.

In an embodiment, the method comprises the step of comparing the reference expression level of HPlα to a reference expression level as described above in relation with the method for predicting clinical outcome. The reference expression level may be the expression level of HPlα in a normal sample or the expression level of a gene having a stable expression in different cancer samples, such as the RPLPO gene.

In a further embodiment, the method further comprises the step of determining whether the expression level of HPlα is high compared to said reference expression level. In a particular embodiment, the expression level of HPlα in the cancer sample is considered as high if, after normalization, the level is at least 1.5, 2, 3, 4, 5 or 6-fold higher than the expression level in the normal sample. Preferably, the expression level of HPlα in the cancer sample is considered as high if the level is at least 1.5-fold higher than the expression level in the normal sample. In another particular embodiment, the expression level of HPlα is considered as high if the quantity of HPlα mRNA is of at least 7, 8, 9, 10, 11, 12, 13, 14 or 15% of the RPLPO mRNA quantity. Preferably, the expression level of HPlα is considered as high if the quantity of HPlα mRNA is of at least 10% of the RPLPO mRNA quantity.

As explained above, these cut-off values are particularly adapted to breast cancer and may vary according to the type of cancer. However, the skilled person can easily adapt this cut- off.

A high expression level of HPlα indicates a decreased patient survival and/or an early disease progression and/or an increase disease recurrence and/or an increase metastasis formation. Accordingly, this type of cancer associated with poor prognosis has to be treated with adjuvant chemotherapy and/or radiotherapy in order to improve the patient's chance for survival. The type of adjuvant therapy is chosen by the practitioner.

In an embodiment, the present method further comprises assessing at least one another cancer and prognosis marker such as tumor grade, hormone receptor status, mitotic index, tumor size, HJURP expression level or expression of proliferation markers such as Ki67, MCM2, CAF-I p60 and CAF-I pi 50, preferably expression of CAF-I proliferation markers. The results obtained with these markers may be used to confirm the result obtained with the method according to the invention and/or to orientate the choice of the adjuvant therapy.

In a last aspect, the present invention further concerns a method for monitoring the response to a treatment of a subject affected with a cancer, wherein the method comprises the step of determining the expression level of HPl α in a cancer sample from said subject before the administration of the treatment, and in a cancer sample from said subject after the administration of the treatment, a decreased expression level of HPl α in the sample obtained after the administration of the treatment indicating that the subject is responsive to the treatment.

In an embodiment, the method further comprises the step of providing a cancer sample from the subject.

The treatment may be any chemotherapeutic or radio therapeutic treatment. A first cancer sample is obtained from the subject before the administration of the treatment. A second sample is obtained from the same subject after the administration of the treatment. Preferably, the second sample is collected when a significant effect on cell proliferation can be expected, dependent on the chosen treatment. In an embodiment, the second sample is collected at least 2 days after administration of the treatment, preferably one week after said administration.

The responsiveness of the patient to the treatment is evaluated by determining the expression level of HPl α in tumoral cells before and after the treatment. The expression level of HPl α in the cancer sample is determined as described above, preferably by measuring the quantity of HPl α protein or HPlα mRNA. A lower expression level of HPl α in tumoral cells contained in the sample collected after the treatment in comparison with the expression level of

HPlα in tumoral cells contained in the sample collected before the treatment indicates that the subject is responsive to the treatment.

In an embodiment, the method further comprises assessing at least one another cancer marker such as tumor grade, hormone receptor status, mitotic index, tumor size, HJURP expression level or expression of proliferation markers such as Ki67, MCM2, CAF-I p60 and CAF-I p 150, preferably expression of CAF-I proliferation markers. This method may also provide an indication of the required duration and/or intensity of the treatment. In this case, a follow-up after each cycle of treatment permits to determine if the expression level of HPlα is lower than before the treatment, and thus to adjust the treatment duration and/or intensity accordingly. The present invention further concerns the use of HPlα as a prognosis marker in cancer, preferably in human cancer and more preferably in human breast cancer. In a preferred embodiment, HPlα is used as a prognosis marker in an early stage breast cancer without local or systemic invasion. As used herein, the term "prognosis marker" refers to a compound, i.e. HPlα, used to predict or monitor clinical outcome of a subject affected with a cancer. The present invention also concerns the use of HPlα as a diagnosis marker for cancer, preferably for human cancer and more preferably for human breast cancer. As used herein, the term "diagnosis marker" refers to a compound, i.e. HPlα, used to diagnose a cancer in a subject.

The present invention also concerns the use of HPlα as a marker for selecting a subject affected with a cancer for an adjuvant therapy and/or radiotherapy or determining whether a subject affected with a cancer is susceptible to benefit from an adjuvant chemotherapy and/or radiotherapy. Preferably, the cancer is a human cancer and more preferably for human breast cancer.

The present invention further concerns the use of HPlα as a marker for monitoring the response to a treatment of a subject affected with a cancer. Preferably, the cancer is a human cancer and more preferably for human breast cancer.

HPlα may be used as marker in any one of the methods of the invention as described above.

In another aspect, the present invention further concerns a kit (a) for predicting or monitoring clinical outcome of a subject affected with a cancer; and/or

(b) for diagnosing a cancer in a subject; and/or

(c) for selecting a subject affected with a cancer for an adjuvant therapy and/or radiotherapy or determining whether a subject affected with a cancer is susceptible to benefit from an adjuvant chemotherapy and/or radiotherapy; and/or

(d) for monitoring the response to a treatment of a subject affected with a cancer, wherein the kit comprises

(i) at least one antibody specific to HPlα and, optionally, means for detecting the formation of the complex between HPlα and said at least one antibody; and/or (ii) at least one probe specific to the HPlα mRNA or cDNA and, optionally, means for detecting the hybridization of said at least one probe on HPlα mRNA or cDNA; and/or

(iii) at least one nucleic acid primer pair specific to HPlα mRNA or cDNA and, optionally, means for amplifying and/or detecting said mRNA or cDNA ; and, (iv) optionally, a leaflet providing guidelines to use such a kit.

Further aspects and advantages of the present invention will be described in the following examples, which should be regarded as illustrative and not limiting.

EXAMPLES

EXAMPLE 1

MA TERIALS AND METHODS

Cell culture and synchronization

Wi38 primary lung fibroblasts (ATCC) and BJ primary foreskin fibroblasts (ATCC) were cultured in MEMα medium (GIBCO), MCF7 breast cancer cells and HeLa cervical carcinoma cells in DMEM (GIBCO), Hs578T breast cancer cells in RPMI medium (GIBCO) containing 1OmM insulin (Sigma) and Hs578Bst healthy mammary cells (ATCC) in DMEM containing 30 ng/ml Epidermal Growth Factor (TEBU). Media were supplemented with 10% fetal calf serum (Eurobio) and 10mg/ml penicillin and streptomycin (GIBCO).

For synchronization in quiescence, primary cells were grown in serum-free medium for at least 72h and MCF7 cells for 48h in medium containing 1OnM of the anti-estrogen ICIl 82780 (Fischer Bioblock Scientific) (Carroll et al, 2000).

Synchronization was checked by flow cytometry as in (Polo et al, 2004) and data analyzed using Flow Jo (Tree Star Inc.).

HeLa cells were synchronized in the different stages of the cell cycle as described in (Polo et al, 2004). BJ cells were synchronized similarly, except that they were blocked for 14h, released for 1Oh, blocked again for 14h and released for 3h, 6h or 12h for S-phase, G2 and Gl, respectively. For mitotic BJ cells, 10ng/ml nocodozole was added 4h after the second release from thymidine and cells were harvested 1Oh later. Synchronization was analyzed by flow cytometry as described in (Polo et al, 2004). Analysis of flow cytometry data was done using Flow Jo (Tree Star Inc.) software. Transfections and siRNAs

HeLa cells, plated in medium without antibiotics, were transfected with 3OnM siRNA using Oligofectamine reagent (Invitrogen) and Optimem 1 medium (Gibco). siRNA sequences: siGFP: AAGCUGGAGUACAACUACAAC (SEQ ID No.l); siHPlα l : 5 CCUGAGAAAAACUUGGAUUTT (SEQ ID NO.2) (Obuse et al, 2004); siHPlα_3: GGGAGAAGTCAGAAAGTAA (SEQ ID NO.3); siHPlβ: AGGAATATGTGGTGGAAAA (SEQ ID No.4); siHPlγ: AGGTCTTGATCCTGAAAGA (SEQ ID No.5).

BJ primary cells were transfected at passage 27 (8 passages after reception from ATCC) using nucleofection (Amaxa), according to manufacturer's instructions. Briefly, 4xlO ⁵ cells 10 were transfected with 0.8 nmol siRNA (Dharmacon) or 1 μg of plasmid DNA in lOOul Nucleofector solution R (Amaxa), using the nucleofection program X-001. Cells were subsequently plated at a density of 7000 cells/cm2 to permit cell proliferation without reaching confluency within 4 days.

Live cell imaging

15 For live cell imaging, BJ cells were transfected twice with siRNA, with a 72h interval.

A plasmid coding for H2B-cherry was introduced in the second transfection, and cells were plated on glass bottom dishes (Mattek). Movies were made using the BioStation system (Nikon). Images were acquired every 20 minutes, during a period of 24 hours, starting 48 hours after the second transfection. Movies were analyzed using Image J.

20 Cell extracts

For total cell extracts, after a wash in PBS, cells were scraped from plates in Ix Laemmli buffer (60 mM Tris-Hcl pH 6.8 ; 10% glycerol ; 2% sodium dodecyl sulfate (SDS) ; 1% 2-mercaptoethanol and 0.002% bromophenol blue) and these extracts were boiled 10 min before storage at -20 ⁰ C.

25 Chromatin-bound cell extracts were made according to (Martini et al, 1998). Protein concentrations were determined using Bio-Rad Protein Assay solution.

Antibodies

Primary antibodies: mouse monoclonal anti-HPlα 2HP-1H5 from Euromedex and rabbit polyclonal anti-HPlα H2164 from Sigma (directed against amino acids 67-119 and 177-

30 191, respectively) for immunofluorescence and immunohistochemistry, mouse monoclonal anti-HPlα 2HP-2G9 for Western blot (Euromedex), mouse monoclonal anti-HPlβ 1MOD1A9 (Euromedex), mouse monoclonal anti-HP lγ 2MOD-lG6- AS (Euromedex), anti-CREST human serum, rabbit polyclonal anti-CAF-1 p60, mouse monoclonal anti-β-actin AC- 15 (Sigma), mouse monoclonal anti-KLl antibody (Dako), rabbit polyclonal anti-Cyclin A (Santa Cruz), mouse monoclonal anti-H3S10P (Abeam abl4955) and rabbit polyclonal anti-Cdtl (Santa Cruz 5 28262)..

Secondary antibodies: Fluorescein isothiocyanate (FITC) or Texas Red-coupled antibodies (immunofluorescence) or horseradish peroxidase-coupled antibodies (Western Blotting) were from Interchim.

Western Blotting 0 After 30min treatment with 25U benzonase nuclease (Novagen), cell extracts were loaded on 4-12% gradient gels (Invitrogen), using Ix MES migration buffer (Invitrogen), followed by Western Blotting procedures as in (Martini et al, 1998).

Immunofluorescence

After fixation in 2% paraformaldehyde, cells were permeabilized in 0.2% Triton X-IOO5 in PBS. Immunofluorescence detection was carried out as in (Martini et al, 1998). Coverslips were mounted in Vectashield mounting medium containing 4',6-Diamidino-2-phenylindole (DAPI) (Vector Laboratories).

For immunofluorescence on tissue samples, 8 μm cryosections made from frozen mammary tissues (Curie Institute, Paris, France) were fixed on glass slides in 3%0 paraformaldehyde and immunostained as above.

Immunohistochemistry

8 μm cryosections from frozen mammary tissues (Curie Institute, Paris, France) or frozen tissue arrays (FMC401, Biomax) were used. Sections, fixed on glass slides in 3% paraformaldehyde and permeabilized in PBS containing 0.5% Triton for 4 min, were incubated5 5 min in 3% H ₂ O ₂ (Prolabo) for peroxidase inhibition and blocked in PBS containing 1% BSA and 5% non-fat milk. Incubation with primary antibody diluted in blocking solution was followed by revelation with horseradish peroxidase-coupled secondary antibody (DakoCytomation) and Diaminobenzidine (DakoCytomation) before counterstaining with hematoxyline (Merck). Slides were dehydrated in increasing ethanol concentrations and toluene0 before mounting in Entellan mounting medium (Merck). RNA extraction, Quantitative RT-PCR and primers

The mRNeasy mini kit (Qiagen) was used for total RNA extraction from cell lines or frozen patient samples and cDNA were produced using Superscript II reverse transcriptase (Invitrogen) with 1 μg RNA and 3 μg of random primers (Invitrogen) per reaction. The Lightcycler 2.0 System (Roche) and the Lightcycler FastStart DNA Master SYBR Green I reaction kit (Roche) were used for quantitative PCR. For the patient samples, the 96-well plate Step One Plus system (Applied Biosystems) and the SYBR Green PCR Master mix (Applied Biosystems) were used. Duplicates were measured and three subsequent cDNA dilutions were carried out to assess primer efficiency. Primer pairs were designed in order to overlap an intron, so as to distinguish cDNA amplification from putative genomic contamination. Primers: RPLPO forward: GGCGACCTGGAAGTCCAACT (SEQ ID NO.6); RPLPO reverse: CCATCAGCACCACAGCCTTC (SEQ ID NO.7); HP lα forward:

GATCATTGGGGCAACAGATT (SEQ ID NO.8); HPlα reverse:

TGCAAGAACCAGGTCAGCTT (SEQ ID NO.9); CAF-I pi 50 forward: CAGCAGTACCAGTCCCTTCC (SEQ ID NO.10); CAF-I pl50 reverse: TCTTTGCAGTCTGAGCTTGTTC (SEQ ID NO.11); CAF-I p60 forward: CGGACACTCCACCAAGTTCT (SEQ ID NO.12); CAF-I p60 reverse: CCAGGCGTCTCTGACTGAAT (SEQ ID NO.13). The quantity of HPlα mRNA was normalized according to the human acidic ribosomal phosphoprotein PO (RPLPO) (de Cremoux et al, 2004) by applying X=E(Cp RPLPO - Cp HPlα), in which E was the mean efficiency of primer pairs and in which x reflected the quantity of HPlα mRNA relative to the quantity of RPLPO mRNA in a given sample.

Breast cancer patient samples and statistics

The present study included 92 breast cancer samples, selected from the Institut Curie Biological Resources Center for treatment with primary conservative tumorectomy (median tumor size: 18mm [6-50mm]). Patients were diagnosed in 1995 and found to be lymph node negative (NO) and metastasis free (MO). Patients were informed of research purposes and did not express opposition. Patient's and tumor characteristics are provided in the above Table I.

RNA was extracted from cryopreserved tissue and analyzed as described above. RNA of 86 samples was of sufficient quality for further analysis.

Differences between groups were analysed by χ 2 or Fisher exact tests for categorical variables and Kruskal-Wallis for continuous variables. Recurrence- free and alive patients were censored at the date of their last known contact. Survival data were defined as the time from diagnosis of breast cancer until the occurrence of disease progression, defined as local recurrence in the treated breast, regional recurrence in lymph node-bearing areas, contralateral breast cancer or distant recurrences. Determination of a cut-off value prognostic for the Disease free Interval (DFI) was computed using a Cox proportional risks model. A WaId test was used to evaluate the prognostic value of this variable on each event. The overall survival (OS), Metastasis Free Interval and DFI rates were estimated by the Kaplan-Meier method, and groups were compared using a log-rank test. Multivariate analysis was carried out to assess the relative influence of prognostic factors on OS and DFI, using the Cox stepwise forward procedure (Cox 1972). Significance level was 0.05. Analyses were performed using R software 2.5.0 version.

RESULTS

HPIa expression depends on cell proliferation

Recent studies have described a downregulation of HPl proteins in differentiated blood cells compared to undifferentiated blood cells (Baxter et al, 2004; Gilbert et al, 2003; Istomina et al, 2003; Ritou et al, 2007). This downregulation could be a common response to cell cycle exit, or a specific consequence of (blood) cell differentiation. To address this issue, the inventors examined whether transient cell cycle exit, which is not accompanied by a differentiation process, similarly results in HPl downregulation. Using two different human primary fibroblast cell lines (WI38 and BJ), in which quiescence is induced by serum starvation, the inventors observed lower protein levels of HPl α, but not β or γ, in quiescent cells compared to proliferating cells (Fig IA). MCF7 breast carcinoma cells, which are arrested in quiescence by anti-estrogen treatment (Carroll et al, 2000), show a similar downregulation of HPl α, but not β or γ. Thus, using two different means to induce quiescence, the inventors find a specific downregulation of the HPlα isoform, the extent of which correlates to the time cells have spent in quiescence. As a control, they verified the downregulation of CAF-I p60 in all quiescent cells (Polo et al, 2004) (Fig IA) and assessed synchronization efficiency by flow cytometry (Fig IB). Similarly to CAF-I pl50 and p60, HPlα downregulation in transient quiescence relates in part to transcriptional regulation, since quiescent BJ cells also show decreased HPlα mRNA levels when compared to asynchronous Iy proliferating cells (determined by quantitative RT-PCR, Fig 1C). Upon exit from the quiescent state, HPlα protein levels gradually increase between 16 and 24 hours after release (Fig 2A), which corresponds to the moment of cell cycle entry (determined by flow cytometry, Fig 2B). The accumulation of HPl α occurs earlier than the one of CAF-I p60 (Fig 2A), mostly observed at the onset of DNA replication.

The observed downregulation of HPl α in quiescence could either be specific for the quiescent state or reflect an expression restricted to a specific stage of the cell cycle. The inventors therefore analyzed HPlα levels during the cell cycle in synchronized HeLa cells. In contrast to the cell cycle marker Cyclin A, they did not observe significant variation in HPlα levels in the synchronized cell populations (Fig 3 A, B). Similarly, human primary fibroblasts, which display a normal cell cycle regulation, show essentially similar levels of HPlα protein (Fig 3C) and mRNA in the synchronized cell population (Fig 3D, E). In this respect, HPlα behaves similarly to CAF-I p60 and pi 50, which are also ubiquitously expressed during the cell cycle but downregulated in quiescence (Fig 1 and 3; (Polo et al, 2004)). In conclusion, HPlα expression levels are high at all stages of the cell cycle in proliferative cells, and HPlα downregulation is specific for the quiescent state.

HPIa is overexpressed in breast cancer cells The proliferation-dependent expression of HPlα suggests a possible differential expression between tumoral and non-tumoral cells, as found for proliferation markers including CAF-I p60 (Polo et al, 2004). To examine this issue, the inventors used mammary cells derived from the same patient, either tumoral (Hs578T) or non-tumoral (Hs578Bst) (Hackett et al, 1977), to be relevant in our comparison. Besides total cell extract, they analyzed levels of HPl proteins both in the soluble fraction and in the fraction bound to chromatin (Fig 4A). Indeed, HPl proteins distribute in different nuclear fractions, distinguished by their capacity to resist extraction with high salt concentrations or with Triton X-100 detergent. The salt- or detergent- resistant pool of HPl is considered as the active, chromatin-bound pool of HPl and represents less than 10% of total HPl in human and rodent cells, as determined by Western Blot quantification (Taddei et al, 2001) or FRAP (Cheutin et al, 2003; Dialynas et al, 2007; Festenstein et al, 2003).

Both in the chromatin-bound and in the soluble nuclear fraction, the inventors observed higher HPlα levels in tumoral Hs578T cells than in non-tumoral Hs578Bst cells, while HPlβ or γ display little differences in expression compared to the loading control β-actin (Fig 4B). Loading of identical amounts of cells also shows tumoral overexpression of HPlα, specifically (Fig 5). Semi-quantitative Western Blot on total cell extracts shows that tumoral Hs578T cells contain approximately 8 times more HPlα protein than non-tumoral Hs578Bst cells, compared to the loading control (Fig 4C). The inventors could exclude the possibility that HPlα expression levels reflect the DNA content of the cell, since the tumoral Hs578T cells display only a very moderate aneuploidy in flow cytometry (Fig 4D). The overexpression of HPl α mRNA, detected by quantitative RT-PCR (Fig 4E), further indicates a regulation that involves at least in part transcription. The present analysis of chro matin-bound and soluble fractions suggests that overexpressed HPlα in tumoral cells is partially chromatin-bound and thus possibly important for chromatin organization. This seems consistent with its nuclear localization, which is granular and diffuse in the non-tumoral mammary cells but clearly localized into discrete spots in a large fraction of the breast cancer cells (Fig 6A). These spots largely localize to centromeric regions, detected by CREST autoimmune serum (Fig 6A). Yet, the different localization of HPlα was not accompanied by an altered nuclear distribution of H3K9me3 (Fig 6B) and the different patterns of HPlα staining did not seem associated with specific stages of the cell cycle, as detected by staining for cell cycle markers (Fig 6C). In conclusion, the present cell line model shows an overexpression of HPlα, but not HPlβ or γ, in tumoral mammary cells compared to non-tumoral mammary cells. A large fraction of HPlα in breast cancer cells is chromatin-bound and localizes to centromeric regions.

HPIa downregulation results in mitotic defects

The proliferation-dependent expression of HPlα, which is not observed for HPlβ or γ, points to a unique function of this isoform and suggests that high amounts of this protein could confer an advantage for cell growth. Interestingly, downregulation of CAF-I pi 50 results in a pronounced S -phase arrest in a manner that depends on its interaction with HPl proteins (Quivy et al, 2008; Quivy et al, 2004). The inventors thus tested whether high expression levels of HPlα, β or γ are required for human cancer cell proliferation. By transfecting HeLa cells with siRNA against HPlα, β or γ, they obtained a specific downregulation of each of the HPl iso forms (Fig 7A). In contrast to downregulation of its binding partner CAF-I pi 50 (Quivy et al, 2008), downregulation of the HPl isoforms did not result in any obvious effect on cell proliferation, as assessed by flow cytometry (Fig 7B). The inventors obtained similar results for HPlα downregulation in the mammary carcinoma cell line Hs578T. However, in agreement with previous reports (Auth et al, 2006; Obuse et al, 2004), the inventors did observe an increased fraction of mitotic profiles displaying lagging chromosomes, misalignments and chromosome bridges (Fig 7C) after downregulation of HPlα. They quantified these as the fraction of aberrant mitoses (Fig 7D). Interestingly, under the present experimental conditions, downregulation of HPlβ or γ did not give rise to increased mitotic defects, suggesting that only the HPl α isoform is critical for faithful mitosis. Furthermore, defects in mitosis were supported by observation of a three-fold increase in micronuclei formation after downregulation of HPl α, but not HPlβ or γ (Fig 7E, F).

Since HeLa cells already show a high fraction of deficient mitoses (-20%) and of micronucleated cells (-10%), the inventors used primary fibroblasts, proficient for cell cycle control and checkpoint activity for further analysis. Transient transfection with two different siRNAs against HPlα resulted in a specific downregulation of this isoform (Fig 8A). Again, the inventors did not detect any significant effect on global cell cycle distribution by flow cytometry (Fig 8B), but they observed a small but reproducible increase in the percentage of prometaphases and a decreased percentage of metaphases by microscopy (Fig 8C). Interestingly, this effect mimics observations upon mutation of the Drososophila homologue of HPlα (Kellum & Alberts, 1995) or inactivation of the centromeric histone H3 variant CENPA in chicken cells (Regnier et al, 2005). Using live cell imaging, they measured a small but statistically significant (p = 4.9e-7) increase in the duration of mitosis after downregulation of HPlα compared to control (upper graph Fig 8D). Interestingly, the delay again mostly affected steps preceding actual chromosome segregation (Fig 8D, lower graph). In conclusion, the present observations in both tumoral and primary cells suggest a role for HPlα in early mitosis, possibly contributing to the correct alignment or the stable attachment of chromosomes at the metaphase plate. HPIa overexpression in human cancer samples

The proliferation-dependent expression of HPlα and its overexpression in breast cancer cells lines prompted the inventors to study HPlα expression in the physiological context of human cancer. First, data from published transcriptome studies performed in different tissue types, were analyzed using the Oncomine database (Rhodes et al, 2004). These data showed that HPlα is significantly and consistently overexpressed in several types of solid tumors, as well as in leukemia (Fig 9A) and that its expression is correlated with the expression of its binding partner CAF-I pi 50 and the proliferation marker Ki67 (Fig 9B).

The present results in cultured cells systematically showed that the difference in HPlα protein levels was more pronounced than the corresponding mRNA levels (Fig 1 and 4), possibly reflecting a post-trans lational regulation. This encouraged the inventors to analyze HPlα protein levels in frozen tumoral and non-tumoral human tissue sections by immunohistochemistry. An intense HPlα staining was systematically observed in tumoral cell nuclei in pancreas, uterus, ovary, prostate and breast malignancies (Fig 10A). In the corresponding non-tumoral tissues, HPlα levels were mostly below the limit of detection. This differential expression is specific for HPlα, since HPlβ and γ show nuclear staining both in tumoral and non-tumoral tissues (Fig 10B). The nuclei showing intense HPlα imunostaining correspond to carcinoma cells, which also stain positive for the epithelial cytokeratin marker KL-I (Fig 10C). In addition, a polyclonal antibody against HPlα, which provides a more intense staining than the monoclonal antibody used in figure 10, also showed a clear overexpression in carcinoma cells with some staining in non-tumoral tissue (Fig 1 IA). Staining for H3K9me3, however, did not show a clear difference between non-tumoral and tumoral tissues (Fig HB), suggesting either that the HPlα detection is more sensitive or that the overexpression occurs independently from H3K9me3.

To determine the importance of HPlα overexpression for tumor growth and disease outcome, cryopreserved breast carcinoma specimens that were collected in 1995, were selected. The inventors focused on node negative and metastasis- free invasive carcinoma of which the size (median 18mm ; range 6-50mm) permitted primary conservative tumorectomy. These cases would benefit from new prognostic markers for the indication of adjuvant chemotherapy. Patient's and tumor characteristics are provided in Table I as presented below. Table I: Description of the patient samples:

Age median: 53 (rang e: 26-70)

Menopaused yes 54% no 46%

Histological type 9% Ductal 88% Lobular 9% Papillary 1% Tubular 1%

Size classification T0/T1 62% T2 38%

Tumor size (mm) median: 18 (rang e: 6-50)

Grade EE I 33% II 42% III 25%

Estrogen receptor positive 86% negative 14%

Progesteron receptor positive 69% negative 31%

Mitotic index median: 8 (range : 0-105)

Ki67 15 - 40 52% <= 15 24% > 40 24%

Adjuvant chemotherapy yes 93% no 7% The median follow-up is 146 months (range 30-161). At 10 years, overall survival, distant recurrence and disease progression rates were 90% [83-97%], 87% [80-95%] and 70% [61-81%], respectively. HPlα mRNA expression levels were measured by quantitative RT- PCR in 86 samples and expression levels were normalized to the reference gene ribosomal protein PO-like protein (RPLPO) (de Cremoux et al, 2004). The inventors found that high levels of HPlα tend to associate with increased age of the patient (p=0.0014) and larger, highly mitotic, grade III tumors (non-significant) (Fig 12A). In univariate analysis, HPlα continuous expression was significantly associated with an increased risk of disease progression: a one-unit increase of log2(HPlα) increased the risk of disease progression with 3% (RR = 1.03 [1.00- 1.05], p=0.041). The inventors determined a cut-off value of 10, which divided patients in two groups (74.4% with HPlα levels <10 and 25.6% with HPlα levels >10) and was significantly associated with disease progression (p= 0.0113; Relative Risk= 2.47 [1.20-5.09]). At ten years, 75% [64-87] of the patients with low HPlα levels vs. 57% [39-83] of the patients with high HPlα levels had not shown disease progression. Moreover, this cut-off is also significantly associated with overall survival (p= 0.0134; Relative Risk= 3.76 [1.03-13.7]) and the occurrence of distant recurrences (p=0.011; Relative Risk= 3.74 [1.26-11.2]) (Fig 12B).

In multivariate analyses, adjusted for known prognostic factors (i.e. patient's age, mitotic index, tumor grade, tumor size, hormone receptor status and Ki67 levels), only HPlα expression is an independent prognostic factor for overall survival (p= 0.0431): high (>10) HPlα levels are associated with an increased risk of death (Relative Risk= 3.76 [1.03-13.7]). Similarly, adjusted for the same parameters, only high HPlα expression (p= 0.0077; Relative Risk= 3.02 [1.38-6.63]) and high tumor grade (p= 0.0170; Relative Risk for grade HI= 4.53 [1.51-13.6]) are pejorative for disease progression. In conclusion, the present results of immunohistochemistry demonstrate that HPlα, but not β or γ, is overexpressed in multiple types of human cancer cells. Furthermore, quantitative RT-PCR analysis carried out for HPlα showed significant correlation with clinopatho logical data and disease outcome. In the present series of 86 small breast tumors, high HPlα expression remained the only independent prognostic factor for overall survival after adjustment for classical prognostic markers, such as the mitotic index, tumor grade, tumor size, hormone receptor status or Ki67. Taken together, these data demonstrate that HPlα constitutes a new chromatin-related marker of cell proliferation and tumorigenesis of clinical relevance for prognosis of breast cancer and other types of cancer. DISCUSSION

A unique regulation of the HPIa isoform

The HPl family of proteins has been identified more than 20 years ago (James & Elgin,

1986), but the common or divergent functions of the three iso forms remain largely unknown. The present results show that in human cells, the HPlα isoform has unique properties, not shared by HPlβ and γ. The protein is expressed in a proliferation-dependent manner, being downregulated during transient cell cycle exit. In line with these findings, cultured cancer cells overexpress HPlα compared to non-tumoral cells. Importantly, this is validated in patient samples. These data thus demonstrate a unique regulation of HPlα, which is not paralleled by HPlβ or γ.

HPIa importance in cancer

To evaluate the clinical importance of HPlα expression, HPlα protein and mRNA levels were analyzed in human cancer by immunohistochemistry and quantitative RT-PCR. Staining of cryopreserved human tissue samples showed a significant overexpression of HPlα, but not HPlβ or γ, in tumoral cells. Thus, HPlα constitutes a marker for diagnosis of multiple types of cancer. In contrast to other proliferation markers, such as Ki67, HPlα stains all tumoral cells and is thus highly suitable to determine the exact localization and extent of the tumor.

In order to quantify HPlα expression and determine its prognostic value, HPlα mRNA levels were measured in 86 small breast tumors with >10 years follow-up. The present data reveal that high HPlα expression correlates with decreased survival and increased occurrence of metastasis over time. Furthermore, multivariate analyses demonstrate that HPlα levels predict disease outcome better than standard prognostic markers. Thus, HPlα constitutes a marker of prognostic value, in breast cancer and in other types of cancer.

EXAMPLE 2

MA TERIALS AND METHODS DNA and RNA microarray analysis

Total RNA was extracted from 158 well annotated frozen tumor samples and 19 healthy mammary tissues, selected from the Biological Resource center of the Institut Curie, using the RNeasy kit (Qiagen, France) and the RNA clean up kit (Macherey Nagel, France). The quality of each RNA sample was determined with an Agilent 2100 bioanalyzer. The quantity of RNA was measured by spectrophotometry at 260 nm. RNA was hybridized onto Ul 33 plus 2.0 Affymetrix chips. Transcriptomic data were normalized using GC-RMA (Irizarry, Hobbs et al. 2003). Raw and normalized transcriptomic data are publically available at Gene Expression 5 Omnibus (Accession number: [GSE13787]).

Reverse Phase Protein Array Analysis

For the protein arrays, 168 Frozen human tumours, among which those used for transcriptome approach, were lysed in a buffer containing 50 mM Tris (pH 6.8), 2% SDS, 5% glycerol, 2 mM DTT, 2.5 mM EDTA, 2.5 mM EGTA, 2 mM sodium ortho vanadate, 10 mM

10 sodium fluoride and a cocktail of protease (Roche, France) and phosphatase (Pierce, Perbio, France) inhibitors. Homogenization was obtained using a TissueLyser (Qiagen, France) with 5 mm stainless steel beads (Qiagen, France) for two minutes at 30 Hz. Lysates were boiled at 100 ⁰ C for 10 minutes and stored at -80 ⁰ C. Protein concentration was determined using the BCA Protein Assay Kit-Reducing Agent Compatible (Pierce, Perbio, France). For all lysates,

15 five two-fold serial dilutions were spotted in triplicates onto nitrocellulose-coated glass slides (FAST slides, Whatman) using a MicroGrid Compact arrayer (BioRobotics, Dutscher Scientific Instrumentation, France) equipped with SMP3XB pins (Tip diameter = 75 μm, volume per spot = 1.2 nl; Telechem, Proteigene, France). Next, slides were incubated with avidin, biotin and peroxydase blocking reagents (Dako, France) before saturation with TBS containing 0.1%

20 Tween-20 and 5% BSA (TBST-BSA) and overnight incubation at 4°C with primary antibody (rabbit polyclonal anti-HP lα, H2164 from Sigma) diluted in TBST-BSA. After washes in TBST, arrays were probed with horseradish peroxidase-coupled secondary antibody (Jackson ImmunoResearch Laboratories, Interchim, France) diluted in TBST-BSA for one hour at room temperature. Signal was amplified using Bio-Rad Amplification Reagent (Bio-Rad, France) for

25 10 minutes at room temperature. The slides were then rinsed with TBST containing 10% DMSO for two minutes and probed with Cy5-Streptavidin (Jackson ImmunoResearch Laboratories, Interchim, France) diluted in TBST-BSA, for one hour at room temperature. Fluorescent signal was scanned using a GenePix 4000B microarray scanner (Molecular Devices, France). Spot detection and signal quantification were determined using Micro Vigene

30 software (VigeneTech Inc, MA). Signal intensity was normalized for both a negative control (no primary antibody), and for a total protein staining. For this, one slide was fixed for 15 min in a solution of 7% acetic acid and 10% methanol and then stained with Sypro Ruby protein staining solution (Molecular Probes, Sl 1791). Statistical analysis

The R software v2.4.0 was used for statistical analyses. Data were transformed by Log(2) in order to normalize the distribution. Differential expression was assessed by T-tests. p values under 5% were considered significant. RESULTS

In the last decade, multiple studies have shown that, based on microarray mRNA expression profiles, breast cancers can be divided into four main groups: (i) the luminal breast cancers, predominantly ER positive and further divided into luminal A (low grade) and B (high grade); (ii) basal-like breast cancers, predominantly ER, PR and HER2 negative; and (iii) the HER2 overexpressing cancers (Sotiriou and Piccart 2007). HPlα expression was analyzed in these distinct classes of breast tumors.

Transcriptome data from 158 well annotated breast cancer samples and 19 healthy mammary samples were analyzed. The molecular features of the samples are summarized in figure 13 A. The obtained expression profiles demonstrate that all high-grade tumor subtypes (Luminal B, HER2+ and basal-like) show a significant overexpression of HPlα mRNA compared to the healthy tissue (figure 13B). Interestingly, HPlα overexpression is particularly important in basal-like breast cancers (figure 13B). These breast tumors, which are negative for ER, PR and HER2 overexpression, are clinically aggressive carcinomas for which effective therapies and prognostic markers are currently lacking (reviewed in (Rakha and Ellis 2009)). To confirm that HPlα might be of interest in the high-grade tumor subtypes (Luminal

B, HER2+ and basal-like), its expression level was analyzed at the protein level with the reverse phase protein array (RPPA) technology. This micro-dot blot technology consists of depositing very small amounts (1 ng) of protein lysates on glass slides covered with nitrocellulose. Proteins of interest were then revealed using specific antibodies. In this manner, protein lysates from all 168 breast tumor samples were analyzed simultaneously for their levels of HPlα protein. The profile obtained in the different tumor types closely resembled the transcriptome profile (figure 13C), with a particularly high expression level in high grade luminal B tumors and in basal-like breast cancers.

Thus, these results confirm that HPlα can be used as a prognostic and diagnostic marker. HPlα expression level is particularly relevant as a prognostic marker for breast cancers due to its high expression levels in basal-like, Luminal B and HER2 overexpressing breast cancers, which are the breast cancer subtypes with the most aggressive clinical behaviour. Furthermore, these results confirm that HPlα expression levels can be assessed in a quantitative manner not only at the mRNA level, but also at the protein level.

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