ES2351328A1 - Method of obtaining useful data for the prediction of pathological response to a treatment of a patient with cancer. (Machine-translation by Google Translate, not legally binding) - Google Patents

Abstract

Method for the prediction of pathological response to a treatment of a patient with cancer. The present invention is within the field of molecular biology and medicine. Specifically, it relates to a method for predicting response to a treatment comprising a platinum derivative and a taxane of a cancer patient, by analyzing the expression profile of the aurkb, figf, il6, mmp1 and vhl genes. Preferably, this method allows to predict the response to a treatment comprising carboplatin and paclitaxel from a patient with ovarian cancer. (Machine-translation by Google Translate, not legally binding)

Description

Method for response prediction pathological to a treatment of a patient with cancer.

The present invention is within the field of molecular biology and medicine. Specifically, it refers to a method for predicting a response to a treatment comprising a platinum derivative and a taxane of a cancer patient, by analyzing the expression profile of the AURKB, FIGF, IL6, MMP1 and VHL genes . Preferably, this method allows predicting the response to a treatment comprising carboplatin and paclitaxel of a patient with ovarian cancer.

Prior art

Epithelial ovarian cancer, although relatively rare (around 2000 new cases annually in Spain) is the most lethal tumor of the female genital tract (around 1100 deaths / year in Spain) (National Epidemiology Center, Carlos III Health Institute , November 2002), due not only to its intrinsic aggressiveness, but also to the difficulty of early diagnosis, which means that almost two thirds of the women diagnosed are already in advanced stages of the disease. Long-term survival rates are for patients with stages I and II close to 80%, while patients with advanced disease have survival rates of 10 to 30% (Heintz et al , 2003. Int J Gynaecol Obstet. 83 Suppl 1: 135-66).

Currently, the treatment of choice for ovarian carcinoma, except for those in stage I, consists of surgery followed by a chemotherapy protocol based on the combination of paclitaxel and platinum derivatives. Tubal carcinoma and primary peritoneal carcinoma have biological, histological characteristics and clinical behavior similar to ovarian carcinoma, so the recommended treatment for these tumors is the same (Barda 2004 Am J Obstet Gynecol; 190 (4): 1039-45). Several retrospective studies have shown that the amount of residual tumor after the first surgery is a factor with prognostic value (Cannistra, 2004. N Engl J Med. 9; 351 (24): 2519-29). In the work carried out by the Gynecologic Oncology Group (GOG) it was shown that a residual tumor smaller than 1 cm in diameter implies greater survival. From that moment on, the most favorable modifiable prognostic factor is the presence of less than 1 cm of residual tumor after the intervention. The median overall survival for patients with a suboptimal surgical intervention is 37 months. In contrast, patients with optimal surgery have a median progression-free survival close to 22 months and a global survival of 52 months (Cannistra, 2004. N Engl J Med. 9; 351 (24): 2519-29) .

Most patients with ovarian cancer require chemotherapy to eradicate the possible disease residual. Although more than 50% of patients with stages III or IV get a complete remission after surgery and chemotherapy, the most of them will suffer a relapse of the disease during the two years later. In addition, most of these patients develops chemoresistance and dies as a result of its disease, so it is necessary to identify those patients They will not respond to treatment.

There are many works that can be found in the literature that analyze the expression of a single marker as a prognostic or predictive response factor. But in recent years we have assisted in the development of high performance gene screening techniques. These techniques applied to tumor analysis have resulted in promising advances in the knowledge of the biological and clinical behavior of tumors. One of the first works in this line is from a Dutch group (Van't Veer et al , 2002. Nature. 31; 415 (6871): 530-6), in which a gene expression profile was identified by microarray with prognostic ability in breast cancer patients. The use of this predictor is approved by the FDA ( Food and Drug Administration ) for patients diagnosed with breast cancer diagnosed early, with positive hormone receptors and no affected nodes.

There is another predictor called Oncotype Dx. The main difference with the previous one is that it determines gene expression through the use of microfluidic cards and on samples fixed in formalin and included in paraffin. With the expression results obtained from 21 genes, an estimated risk index of tumor recurrence is constructed (Cronin et al , 2004. Am J Pathol. 164 (1): 35-42; Paik et al 2004. N Engl J Med. 30; 351 (27): 2817-26). The use of this trial is recommended in the review by the American Society of Medical Oncology (ASCO) on tumor markers in breast cancer (Harris et al ., 2007. J Clin Oncol. 20; 25 (33): 5287-312) for patients diagnosed early, with positive hormonal receptors and no affected nodes. This test seeks to incorporate this molecular test into the daily clinic to assess whether genes that are frequently associated with the risk of recurrence among women with early breast cancer can be used to assign patients the most appropriate and effective treatment.

In the specific case of ovarian cancer, we can also find papers that analyze expression profiles using high performance techniques. Most of these studies aim to identify diagnostic markers by comparing cancer samples against normal tissue samples, or established cell line studies (reviewed in Crijns et al , 2006. Int J Gynecol Cancer. 16 Suppl 1: 152-65; Olivier et al , 2006. Eur J Cancer. 42 (17): 2930-8). There are fewer studies on the prediction of response to treatment, although studies with preliminary data in studies with arrays begin to appear in small tumor series (Helleman et al , 2006 Int J Cancer. 15; 118 (8): 1963-71 ; Spentzos et al , 2005. J Clin Oncol. 1; 23 (31): 7911-8; Dressman et al , 2007. J Clin Oncol. 10; 25 (5): 517-25), however, gene profiles described to date to predict the response to a certain ovarian cancer treatment still require validation tests.

Angiogenesis, initially described by Judah Folkman in 1969, is the process by which new ones are formed blood vessels from the preexisting vascular bed. The neovascularization can be induced anywhere in the organism by different stimuli such as hypoxia, ischemia, physical trauma (wounds, fractures) or inflammation, both in situation Physiological as pathological. Carcinogenesis is a process. angiodependent, the formation of new vessels being necessary to uncontrolled growth, invasion and metastasis, associated to tumor development.

Angiogenesis has a relevant role in the specific case of ovarian cancer, due to its own biology. The angiogenesis, controlled by a balance between pro and antiangiogenic agents, particularly the proteins of the family of VEGF, plays a fundamental role in the physiology of the ovary not tumor. On the other hand, we must also bear in mind that the Ovarian cancer is a very vascularized tumor.

There are a large number of studies on the involvement of angiogenic factors in ovarian carcinogenesis (Rasila et al ., 2005. Int J Gynecol Cancer. 15 (5): 710-26). Models in mice indicate that VEGF expression is associated with ascites formation. As in other tumors, VEGF expression is proportional to tumor growth and correlates with vascular microdensity. We can find several works in which it has been shown that VEGF expression in ovarian cancer samples, both of the related subtypes With angiogenesis such as those related to lymphangiogenesis, it correlates with the prognosis and aggressiveness of this disease, and is proportional to vascular microdensity (Nakanishi et al ., 1997. Int J Gynecol Pathol. 16 (3): 256-62; Yoneda et al ., 1998. J Natl Cancer Inst. 18; 90 (6): 447-54; Sood et al ., 2005. Gynecol Oncol. 97 (3): 916-23).

In recent years, new therapies have been developed whose purpose is the inhibition of the formation of new vessels in the tumor environment, as well as the maintenance of the pre-existing vasculature. Undoubtedly, the greatest advance in the field of antiangiogenic therapy occurred when the FDA ( Food and Drug Administration ) approved the use of the first antiangiogenic agent, bevacizumab, for the treatment of human cancer. This humanized antibody specifically binds to VEGF, thus preventing its binding to its receptors. By neutralizing the biological activity of VEGF, tumor vascularization is reduced and therefore its growth is inhibited. Being the first approved anti-angiogenic for use, it is the most available data. Several trials are currently underway in which the efficacy of the addition of bevacizumab to standard chemotherapy in patients with ovarian cancer is evaluated. In the case of a recurrent tumor, the final results of two studies have shown that although the treatment seems effective, with response rates between 15 and 21%, this treatment is associated with a high rate of gastrointestinal perforations as a side effect. In addition to the role as a chemotherapy enhancer, both bevacizumab and other antiangiogenic agents may also have a role as a single agent or as part of a combination regimen that does not include classical chemotherapeutics, and whose clinical trials are also ongoing (Kaye, 2007 J Clin Oncol. 20; 25 (33): 5150-2).

Although the results with antiangiogenic are encouraging, the toxicity issue remains a major pitfall importance and does not seem therefore that in the short term the treatment standard will be modified. It is therefore of great importance development of tools that help the clinician decide when Administer this treatment with a high probability of success.

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Description of the invention

The standard treatment of choice in carcinoma Advanced ovary consists of the combination of paclitaxel and a platinum derivative after cytoreductive surgery. This treatment has some associated limitations such as the acute and long-term toxicity. But more important is the fact that, although most patients will respond so initial treatment, only 50% of them will have a Survival greater than 5 years after the end of chemotherapy. There is therefore a need to find a method of analysis that allows to predict the response to treatment, and preferably at the standard treatment of choice (paclitaxel plus carboplatin) in ovarian carcinoma. This way, you can identify, on the one hand, the patients who will benefit from standard treatment And on the other hand, and more importantly, to those patients with resistant tumors, unnecessarily subjected to toxicity associated with treatment without any benefit, and in which also the administration of others is fatally delayed Alternative treatments possibly more effective.

In example 1 of this patent document, shows how the authors of the present invention have identified a set of genes related to angiogenesis that predict the probability of the response to a chemotherapeutic treatment consisting of paclitaxel plus carboplatin for carcinoma of ovary in samples fixed in formalin and included in paraffin. This gene expression profile developed by the inventors, allows predict the pathological response to a treatment comprising a derived from platinum and a taxane. Some types of cancer in which this chemotherapeutic treatment is currently being used that comprises a platinum derivative and a taxane are, for example, but not limited to ovarian cancer, tube, peritoneum, cervix, endometrium, lung or tumors of unknown origin.

Therefore, a first aspect of the invention relates to the use of the AURKB, FIGF, IL6, MMP1 and VHL genes to predict the pathological response to a treatment comprising a platinum derivative and a taxane of a cancer patient.

A preferred embodiment of this first aspect of the invention relates to the use of the AURKB, FIGF, IL6, MMP1 and VHL genes to predict the pathological response to a treatment comprising a platinum derivative and a taxane of a cancer patient, where the platinum derivative is selected from the list comprising: carboplatin, oxaliplatin or cisplatin. In a more preferred embodiment, the platinum derivative is carboplatin.

A preferred embodiment of this first aspect of the invention relates to the use of the AURKB, FIGF, IL6, MMP1 and VHL genes to predict the pathological response to a treatment comprising a platinum derivative and a taxane of a cancer patient, where the taxane is selected from the list comprising: paclitaxel or docetaxel. In a more preferred embodiment, the taxane is paclitaxel.

A more preferred embodiment of this first aspect of the invention relates to the use of the AURKB, FIGF, IL6, MMP1 and VHL genes to predict the pathological response to a treatment comprising carboplatin and paclitaxel of a cancer patient.

An even more preferred embodiment of this first aspect of the invention relates to the use of the AURKB, FIGF, IL6, MMP1 and VHL genes to predict the pathological response to a treatment consisting of carboplatin and paclitaxel of a cancer patient.

In a preferred embodiment of this first aspect of the invention, the cancer is from the list comprising: ovary, tube, peritoneum, cervix, endometrium, lung or tumor of unknown origin. In a more preferred embodiment the cancer is of ovary. In an even more preferred embodiment, ovarian cancer is an ovarian carcinoma, preferably in stage IC, II, III or IV and, more preferably, in stage III or IV.

A second aspect of the invention relates to a method of obtaining useful data to predict the response pathological to a treatment comprising a platinum derivative and a taxane from a cancer patient, comprising:

to.

obtain an isolated biological sample comprising a patient's cells, and

b.

Detect the amount of expression product of the AURKB, FIGF, IL6, MMP1 and VHL genes in the biological sample from step (a).

This method allows, therefore, to obtain data useful for determining the probability of a patient's response to a standard chemotherapeutic treatment, comprising a derivative of platinum and a taxane, and for example, help the clinician in taking decision concerning the administration of another treatment alternative in those patients for whom it was obtained a low probability of response to treatment.

A preferred embodiment of this second aspect of the invention, refers to a method of obtaining useful data to predict the pathological response to a treatment comprising a platinum derivative and a taxane of a patient with cancer, where the platinum derivative is selected from the list that comprises: carboplatin, oxaliplatin or cisplatin. In a most preferred embodiment, the platinum derivative is carboplatin

A preferred embodiment of this second aspect of the invention, refers to a method of obtaining useful data to predict the pathological response to a treatment comprising a platinum derivative and a taxane of a patient with cancer, where the taxane is selected from the list comprising: paclitaxel or docetaxel. In a more preferred embodiment, the taxane It is paclitaxel.

A more preferred embodiment of this second aspect of the invention, refers to a method of obtaining useful data to predict the pathological response to a treatment comprising carboplatin and paclitaxel of a patient with Cancer.

A more preferred embodiment of this second aspect of the invention, refers to a method of obtaining useful data to predict the pathological response to a treatment consisting of carboplatin and paclitaxel of a patient with Cancer.

In a preferred embodiment of this second aspect of the invention, the cancer is from the list comprising: ovary, tube, peritoneum, cervix, endometrium, lung or tumor of unknown origin. In a more preferred embodiment the cancer is of ovary. In an even more preferred embodiment, ovarian cancer is an ovarian carcinoma, preferably in stage IC, II, III or IV and, more preferably, in stage III or IV.

A third aspect of the invention relates to a method to predict the pathological response to a treatment that it comprises a platinum derivative and a taxane of a patient with cancer comprising:

to.

obtain an isolated biological sample which comprises cells of a patient,

b.

detecting the amount of expression product of the AURKB, FIGF, IL6, MMP1 and VHL genes , in the biological sample of step (a), and

C.

assign the patient a probability of pathological response to the treatment, where said response depends on the amount of expression product of the AURKB, FIGF, IL6, MMP1 and VHL genes in the sample obtained in (a), in relation to the amount of expression detected for these genes in a reference patient population with a known pathological response.

This method allows, therefore, to determine the probability of a patient's response to a treatment chemotherapeutic comprising a platinum derivative and a taxane, and for example, to help the clinician in the decision making regarding the administration of an alternative treatment in those patients with a low probability of response to this treatment Chemotherapeutic

Steps (b) and / or (c) of the methods described previously they can be totally or partially automated, by example, by means of a robotic sensor device for the detection of the amount of product of gene expression in step (b) or the computerized comparison in step (c). In addition to the steps specified above may comprise other steps additional, for example related to the pre-treatment of the sample or evaluation of Results obtained through these methods. For example, the method to predict the pathological response to a treatment that includes a platinum derivative and a taxane from a cancer patient, can include an additional step consisting of generating a report on the results of the patient's gene profile, which includes the probability of response to the treatment of said patient diagnosed with cancer

In a preferred embodiment of this third aspect of the invention it refers to the amount of the expression product of each gene being normalized relative to the amount of the expression product of a series of reference genes. For example, the reference genes can be, but not limited to, 18S, ACTB, B2M, GAPDH, GUSB, HMBS, HPRT1, IPO8, PGK1, PPIA, RPLP0, TBP, TFRC and UBC . In a preferred embodiment of this third aspect of the invention, the amount of the expression product of each gene is normalized relative to the amount of the expression product of at least one reference gene that is selected from the list that It comprises: 18S, ACTB, B2M, GAPDH, GUSB, HMBS, HPRT1, IPO8, PGK1, PPIA, RPLP0, TBP, TFRC and UBC . In a more preferred embodiment of this third aspect of the invention, the amount of the expression product of each gene is normalized relative to the amount of the expression product of the reference genes 18S, ACTB, B2M, GAPDH, GUSB, HMBS, HPRT1, IPO8, PGK1, PPIA, RPLP0, TBP, TFRC and UBC . In another preferred embodiment of this aspect of the invention, the amount of the expression product of each gene can be normalized relative to the average of the amount of the expression product of the chosen genes or their expression products.

In example 1 of this patent document, a model generated from the data obtained from the analysis of the gene expression of samples from a reference patient population of known pathological response is described. Based on the patients with a response to the treatment and without it, a specific weight has been assigned to each of the AURKB, FIGF, IL6, MMP1 and VHL genes , based on which the predictor is constructed, whose final result is a Probability value of treatment response in said model. Thus, using a method called Stepwise-AIC-Best Subsets approach, a combination of genes whose expression is related to a probability value of pathological response to treatment has been obtained. This value can be analyzed continuously, or by establishing cut-off points according to the established analysis, as can be seen in Table 5 of Example 1 of the patent.

In a preferred embodiment of this third aspect of the invention, the probability of pathological response is Assign using the formula:

one

where Z = independent term + \ sumPE_ {gen} x Normalized expression value_ {gen}; Being the independent term a value between 20,1430 and 17,8430 and the specific weight of each gene (PE_) a value included between 22.1130 and 19.8130 for PE_ {AURKB}, between 181.2450 and 178.9450 for PE_H FIGHT, between 15.9810 and 13.6810 for PE_6, between -34,3090 and -36,6090 for PE_ {MMP1}, and between - 32,4440 and -34,7440 for PE_ {VHL}. These values that take the coefficients are correspond to 75% of the interval of trust.

In a more preferred embodiment of this third aspect of the invention, the probability of pathological response is assigned by the formula described above, where the term independent is a value between 20.6430 and 17.3430 and the specific weight of each gene (PE_) a value between 22.6130 and 19.3130 for PE_ {AURKB}, between 181.7450 and 178.4450 for PE_FIG, between 16.4810 and 13.1810 for PE_6, between -33.8090 and -37,1090 for PE_ {MMP1}, and between -31.9440 and -35.2440 for PE_ {VHL}. These values that take the coefficients correspond with 90% of the confidence interval.

In an even more preferred embodiment of this third aspect of the invention, the probability of response Pathological is assigned by the formula described above, where the independent term is a value between 20.9530 and 17.0330 and the specific weight of each gene (PE_) a value between 22.9230 and 19.0030 for PE_ {AURKB}, between 182.0550 and 178.1350 for PE_FIG, between 16.7910 and 12.871 or for PE_ {IL6}, between -33.4990 and -37.4190 for PE_ {MMP1}, and between -31.6340 and -35.5540 for PE_ {VHL}. These values that take the coefficients correspond to 95% of the range of trust.

In an even more preferred embodiment of this third aspect of the invention, the probability of response Pathological is assigned by the formula described above, where the independent term is a value between 21.5630 and 16.4230 and the specific weight of each gene (PE_) a value between 23.5330 and 18.3930 for PE_ {AURKB}, between 182.6650 and 177.5250 for PE_FIG, between 17,4010 and 12,261 or for PE_ {IL6}, between -32.8890 and -38.0290 for PE_ {MMP1}, and between -31,0240 and -36,1640 for PE_ {VHL} - These values that take the coefficients correspond to 99% of the range of trust.

The expression "expression value normalized_ {gen} "refers to the quantity of the product of expression of each gene normalized relative to the amount of the product of the expression of a series of reference genes, as previously described elsewhere in this document.

A preferred embodiment of this third aspect of the invention, refers to a method for predicting the response pathological to a treatment comprising a platinum derivative and a taxane from a cancer patient, where the platinum derivative is selected from the list comprising: carboplatin, oxaliplatin or cisplatin In a more preferred embodiment, the derivative of Platinum is carboplatin.

A preferred embodiment of this third aspect of the invention, refers to a method for predicting the response pathological to a treatment comprising a platinum derivative and a taxane from a cancer patient, where the taxane is selected from the list comprising: paclitaxel or docetaxel. In a Most preferred embodiment, the taxane is paclitaxel.

A more preferred embodiment of this third aspect of the invention, refers to a method for predicting the pathological response to a treatment comprising carboplatin and Paclitaxel of a cancer patient.

A more preferred embodiment of this third aspect of the invention, refers to a method for predicting the pathological response to a treatment consisting of carboplatin and Paclitaxel of a cancer patient.

In a preferred embodiment of this third aspect of the invention, the cancer is from the list comprising: ovary, tube, peritoneum, cervix, endometrium, lung or tumor of unknown origin. In a more preferred embodiment the cancer is of ovary. In an even more preferred embodiment, ovarian cancer is an ovarian carcinoma, preferably in stage IC, II, III or IV and, more preferably, in stage III or IV.

A fourth aspect of the present invention is refers to a method to identify if a compound is useful for the cancer treatment, which includes:

to.

get cells derived from a Cancer,

b.

detect the amount of expression product of the AURKB, FIGF, IL6, MMP1 and VHL genes in the cells of step (a),

C.

administer the compound to the cells of (a),

d.

detect the amount of expression product of the AURKB, FIGF, IL6, MMP1 and VHL genes , after administration of the compound according to (c), and

and.

compare the amount of expression product of the AURKB, FIGF, IL6, MMP1 and VHL genes , before and after administration of the compound.

Differential expression detection indicates that the compound has activity on one or more profile genes and for therefore, said compound could be a potential agent chemotherapeutic, and would be a candidate to be selected for subsequent analyzes.

In a preferred embodiment of this room aspect of the invention, the cells are derived from a cancer of the list that includes: ovary, tube, peritoneum, cervix, endometrium, lung or tumor of unknown origin. In one embodiment More preferred is ovarian cancer. In an even more realization preferred, ovarian cancer is an ovarian carcinoma, preferably, in stage IC, II, III or IV and, more preferably, in stage III or IV.

The term "predict" or "prediction", as used in the present description, it refers to the probability of a patient responding favorably or unfavorably to a treatment or set of treatments, and to the extent of these responses, or that the patient survives, after surgical removal of a primary tumor and / or the administration of a treatment for a period of time without produce cancer recurrence.

The main cancer treatment It is usually cytoreductive surgery or elimination Surgical tumor. Some patients before surgery receive neoadjuvant treatment in order to reduce the size of the tumor, to enable or facilitate surgery. After the surgery, many patients receive adjuvant treatment with the objective of preventing cancer relapse at the primary site of the tumor or elsewhere. Adjuvant or neoadjuvant treatment may consist, for example, but not limited to radiotherapy, hormone therapy, chemotherapy or biological therapy.

The evaluation of the pathological response is performed after completing the neoadjuvant treatment. To do this, it carries out an anatomopathological study of the tumor piece excised and / or areas initially infiltrated by it. A complete pathological response is defined as the absence of residual microscopic tumor disease. The evaluation of the response to neoadjuvant treatment through study Pathologic offers greater accuracy than evaluation clinical (radiological and / or biomarkers), since it is relatively Frequently, complete clinical responses are not answers pathological complete This is due to the persistence of cells. tumor (not detectable by radiological tests or by biomarkers) who will be responsible for a relapse later.

The present invention relates to the use of the AURKB, FIGF, IL6, MMP1 and VHL genes , and to methods based on the analysis of the product of the expression of said genes that are useful for predicting the pathological response to a treatment comprising a derivative of the Platinum and a taxane from a cancer patient.

The treatment comprising a derivative of platinum and a taxane can be an adjuvant or neoadjuvant. In addition to the administration of a platinum derivative and a taxane, the treatment may include other types of therapy such as surgery, radiotherapy, other type of chemotherapy or biological therapy Preferably, the treatment comprises the administration of a platinum derivative and a taxane as adjuvant treatment after surgery cytoreducer

Radiation therapy involves the use of a particle current or high energy waves, such as X-rays, gamma rays, electrons or protons, to destroy the tumor or cancer cells.

Chemotherapy involves the use of compounds or combinations of compounds with the aim of destroying cancer cells Depending on its biological effect, others compounds administered in cancer chemotherapy that they can be administered in addition to the platinum derivative and the taxane, are, for example, but not limited to, alkylating agents, antimetabolites, antimicrotubular agents, inhibitors of topoisomerase or antitumor antibiotics. Some agents alkylating agents are, for example, but not limited to, mechlorethamine, cyclophosphamide, chlorambucil, melphalan, ifosfamide, thiotepa, hexamethylmelamine, busulfan, altretamine, procarbazine, dacarbazine, temozolomide, carmustine, lomustine or streptozocin. Some antimetabolites, are for example, but not limited to, methotrexate, 5-fluoruracil, floxuridine, cytarabine, capecitabine, gemcitabine, 6-mercaptopurine, 6-thioguanine, cladribine, fludarabine, nelarabine or pentostatin Some antimicrotubular agents, such as but not limited, estramustine, vincristine, vinblastine or Vinorelbine. Some topoisomerase inhibitors are, by example, etoposide, etoposide phosphate, teniposide, amsacrine, Irinotecan or Topotecan. Some antitumor antibiotics are for example, but not limited to, doxorubicin, daunorubicin, epirubicin, mitoxantrone, idarubicin, dactinomycin, mitomycin or bleomycin Other chemotherapeutic drugs are, for example, but not limited, hydroxyurea, mitotane, asparaginase, bexarotene, isotretinoin

The expression "biological therapy", "biotherapy" or "immunotherapy" as used in the This description refers to a treatment used to stop, control or suppress the processes that allow it to grow cancer; make cancer cells recognized and destroyed by the immune system more easily; reinforce the destructive power of immune system cells, such as cells T, natural killer cells or macrophages; alter the cancer cell growth pattern to encourage it to behave like healthy cells; block or reverse the process that causes a normal cell or precancerous cell to become cancer cell; improve the body's ability to repair or replace normal cells damaged or destroyed by others forms of cancer treatment, such as chemotherapy or radiation; or prevent cancer cells from spreading to others body parts. The term "biological therapy" includes, for example, but without limiting interferons (such as but without limitation, interferon alfa), interleukins (such as, for example, but not limited to, IL-2, IL-6 or IL-12), the factors colony stimulants (such as, but not limited to pG-CSF, GM-CSF, IL-11 or erythropoietin), antibodies monoclonal (such as, but not limited to, cetuximab, infliximab, panitumumab, bevacizumab, rituximab or trastuzumab), the vaccines, gene therapy or non-immunomodulating agents specific (such as, but not limited to, the bacillus of Calmette-Guérin or Levamisole).

The term "isolated biological sample that comprises patient cells ", as used in the description refers, but is not limited, to tissues and / or fluids biological of a subject, obtained by any method known by an expert in the field that serves this purpose. The biological sample can be a tissue, for example, but without be limited, a biopsy or a fine needle aspirate, or it can be a biological fluid, for example, but not limited to, a sample of fluid, such as blood, plasma, serum, lymph, ascites fluid or urine. Preferably, the cells are tumor cells, and more preferably they come from the cytoreduced tumor in surgery, before or after the administration of an adjuvant treatment or neoadjuvant cancer. The biological sample can be, by example, but not limited, fresh, frozen, fixed or fixed and embedded in paraffin.

The terms "tumor" or "tumor", such and as used in the present description, it refers to cells transformed that show uncontrolled growth. Depending of its possible evolution can be a benign tumor, which it remains in its starting place and does not produce metastasis; or tumor malignant, invasive or metastatic. The term "cancer" or "cancerous" as used in this description, It refers to any malignant tumor.

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Examples of cancer include, but are not limited to, ovarian cancer, tubal cancer, peritoneum cancer, cancer uterus, cervical cancer, vaginal cancer, vulvar cancer, cancer breast, colon cancer, prostate cancer, skin cancer, cancer hepatocellular, lung cancer, esophageal cancer, gastric cancer, pancreatic cancer, genitourinary tract cancer, cancer thyroid, renal cancer, melanoma, brain cancer, sarcoma, lymphoma or leukemia

The present invention relates to the use of the AURKB, FIGF, IL6, MMP1 and VHL genes , and to methods based on the analysis of the product of the expression of said genes that are useful for predicting the pathological response to a treatment comprising a derivative of the Platinum and a taxane from a cancer patient. Some types of cancer in which this chemotherapeutic treatment is currently being used are, for example, but not limited to, ovarian cancer, tubal, peritoneum, cervix, endometrium, lung or tumor of unknown origin, therefore, preferably, cancer It is from the list that includes: ovarian cancer, tube, peritoneum, cervix, endometrium, lung or tumor of unknown origin. More preferably, the cancer is ovarian cancer.

Ovarian cancer is the proliferation accelerated, disordered and uncontrolled cells belonging to different tissues of the ovary. Depending on the origin of the cells, ovarian tumors can be, for example, but not limited, epithelial tumors, germ cell tumors and tumors of the stroma-sex cords The type of malignant tumor most frequent derives from the surface epithelium and is carcinoma of ovary. Ovarian carcinomas can be, for example, but without limited, serous, mucinous, endometrioid, cell type clear or transitional. Preferably, the present invention will be refers, but is not limited to ovarian carcinoma.

Ovarian carcinoma can be classified into following stages: stage I (which is subdivided into stage IA, IB and IC), stage II (which is subdivided into stage IIIA, IIB and IIC), stage III (which is subdivided into stage IIIA, IIIB and IIIC) and stage IV

Usually in stages IA and IB the standard treatment involves performing surgery with the maximum cytoreductive effort. In stages IC, II, III and IV, the standard treatment consists of performing surgery with the maximum cytoreductive effort followed by a treatment of intravenous chemotherapy with a platinum derivative, usually carboplatin and a taxane, usually paclitaxel. Preferably, The present invention relates to, but is not limited to, a carcinoma. ovarian stage IC, II, III or IV and, more preferably, at a stage III or IV ovarian carcinoma.

For the evaluation of the pathological response to Chemotherapy of a patient with ovarian cancer is necessary perform a new surgical intervention after treatment neoadjuvant, in which all suspicious lesions will be analyzed and / or, in its absence, the areas initially infiltrated by the tumor. A complete or positive pathological response is defined as the absence of residual microscopic tumor disease, such as It is described in the examples of the present description.

The term "product of expression of genes ... ", as used in the present description, makes reference to transcription and / or translation products (RNA and / or protein) of said genes, or in any form resulting from processing of said transcription or translation products.

The AURKB or aurora kinase B gene is also called aurora-1; aurora-B; serine / threonine kinase 12 and is also abbreviated as AIK2, AIM-1, AIM1, ARK2, AurB, IPL1, STK12, STK5. It is located on chromosome 17 (17p13.1). Its reference number in the UniGene database of the National Center for Biotechnology Information (NCBI) is Hs. 442658. In the context of the present invention, the term "product of the AURKB gene expression " refers to any product of the expression of SEQ ID NO: 1 or any of its variants. SEQ ID NO: 1 corresponds to the prototypical genomic DNA sequence of AURKB . Preferably, the term "expression product of the AURKB gene" refers to the mRNA encoded by SEQ ID NO: 2 or any of its variants, or to the protein encoded by said mRNA or any of its variants.

The FIGF gene or c-fos induced growth factor (vascular endothelial growth factor D) is also called OTTHUMP00000022960; Vascular endothelial growth factor D is also abbreviated as VEGF-D and VEGFD. It is located on the X chromosome (Xp22.31). Its reference number in the NCBI UniGene database is Hs.11392. In the context of the present invention, the term "product of the expression of the FIGF gene" refers to any product of the expression of SEQ ID NO: 3 or any of its variants. SEQ ID NO: 3 corresponds to the prototypical genomic DNA sequence of FIGF . Preferably, the term " FIGF gene expression product" refers to the mRNA encoded by SEQ ID NO: 4 or any of its variants, or to the protein encoded by said mRNA or any of its variants.

The IL6 or interleukin 6 gene is also called interferon , beta 2 and is also abbreviated as BSF2, HGF, HSF, IFNB2 or IL-6. It is located on chromosome 7 (7p21). Its reference number in the NCBI UniGene database is Hs. 654458). In the context of the present invention, the term "product of the expression of the IL6 gene" refers to any product of the expression of SEQ ID NO: 5 or any of its variants. SEQ ID NO: 5 corresponds to the prototypical sequence of genomic DNA of IL6 . Preferably, the term " IL6 gene expression product" refers to the mRNA encoded by SEQ ID NO: 6 or any of its variants, or to the protein encoded by said mRNA or any of its variants.

The MMP1 or matrix metallopeptidase 1 gene is also called fibroblast collagenase; interstitial collagenase; matrix metalloprotease 1; matrix metalloproteinase 1; matrix metalloproteinase 1 (interstitial collagenase) and is also abbreviated as CLG and CLGN. It is located on chromosome 11 (11q22.3). Its reference number in the NCBI UniGene database is UniGene Hs. 83169. In the context of the present invention, the term "product of MMP1 gene expression " refers to any product of SEQ ID NO expression. : 7 or any of its variants. SEQ ID NO: 7 corresponds to the prototypical genomic DNA sequence of MMP1 . Preferably, the term " MMP1 gene expression product " refers to the mRNA encoded by SEQ ID NO: 8 or any of its variants, or to the protein encoded by said mRNA or any of its variants.

The VHL or von Hippel-Lindau tumor suppressor gene is also called elongin binding protein and is also abbreviated as HRCA1, RCA1 and VHL1. It is located on chromosome 3 (3p25.3). Its reference number in the NCBI UniGene database is UniGene Hs. 517792. In the context of the present invention, the term "product of VHL gene expression" refers to any product of the expression of SEQ ID NO. : 9 or any of its variants. SEQ ID NO: 9 corresponds to the prototypical sequence of genomic DNA of VHL . Preferably, the term "product of VHL gene expression" refers to the mRNA encoded by SEQ ID NO: 10 or any of its variants, or to the protein encoded by said mRNA or any of its variants.

In the sense used in this description, it understand that a nucleic acid is a "variant" of another when the nucleotide sequence of the first one has a degree of identity with respect to the nucleotide sequence of the second of at least one 30%, advantageously of at least 50%, preferably of, at less, 70%, more preferably, at least 80%, and more preferably of at least 90%.

The term "identity" as it is used in the present description, refers to the proportion of identical nucleotides between two nucleotide sequences, respectively, which are compared. The percent identity existing between two sequences can be easily identified by a subject matter expert, for example, with the help of a program appropriate computer to compare sequences.

The terms "gene expression profile" or "gene expression profile", as used in The present description, refer to the mRNA quantification and / or protein produced by the genes of interest in a sample biological

The detection of the product quantity of the gene expression in the sample obtained, as used in the description, it refers to the measure of the quantity or the concentration, preferably so semi-quantitative or quantitative. The measure can be carried out directly or indirectly. Direct measurement refers to the measure of the amount or concentration of product of gene expression based on a signal that is obtained directly from the product of gene expression and that is directly correlated with the number of product molecules of the expression of the gene present in the sample. This signal - to the that we can also refer to as a signal of intensity - it can obtained, for example, by measuring an intensity value of one Chemical or physical property of the gene expression product. The indirect measure includes the measure obtained from a component secondary (for example, a different component of the product of the gene expression) or a biological measurement system (for example the measurement of cellular responses, ligands, "tags" or enzymatic reaction products).

The term "quantity", as used in the description, refers to, but is not limited to, the absolute or relative quantity of the expression product of the AURKB, FIGF, IL6, MMP1 and VHL genes , as well as any other value or parameter related to them or that may be derived from them. Said values or parameters comprise values of signal intensity obtained from any of the physical or chemical properties of the product of the expression of the genes obtained by direct measurement, for example, intensity values of mass spectroscopy or nuclear magnetic resonance. Additionally, said values or parameters include all those obtained by indirect measurement, for example, any of the measurement systems described elsewhere in this document.

Thus, the "quantity detection" of gene expression product can be carried out by any method of determining the quantity of the product of the gene expression known in the state of the art.

In a preferred embodiment, the detection of the gene expression product is performed by determining the level of mRNA derived from its transcription, where the analysis of the level of mRNA of AURKB, FIGF, IL6, MMP1 and VHL can be performed, by way of title. illustrative and without limiting the scope of the invention, by amplification by polymerase chain reaction (PCR), back transcription in combination with polymerase chain reaction (RT-PCR), back transcription in combination with chain reaction of ligase (RT-LCR), or any other nucleic acid amplification method; DNA chips made with oligonucleotides deposited by any mechanism; DNA microarrays made with oligonucleotides synthesized in situ by photolithography or by any other mechanism; in situ hybridization using specific probes labeled with any method of marking; by electrophoresis gels; by membrane transfer and hybridization with a specific probe; by nuclear magnetic resonance or any other diagnostic imaging technique using paramagnetic nanoparticles or any other type of detectable nanoparticles functionalized with antibodies or by any other means.

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MRNA can be analyzed, for example, but without limitation, in samples of fresh tissue, frozen tissue, fixed tissue or tissue fixed and embedded in paraffin. The use of tissue samples fixed and embedded in paraffin presents important advantages over fresh tissue samples or frozen: they are stable at room temperature, easy to store and there is a large archive of clinical samples available together with your clinical information and disease monitoring. By therefore, in a preferred embodiment the analyte is extracted from samples of tissue fixed and embedded in paraffin.

RNA obtained from tissue samples fixed and embedded in paraffin is often very degraded. While studies using microarrays are very sensitive to RNA degradation, the use of RT-PCR, and in particular, quantitative RT-PCR (qRT-PCR) has proven to be a technique that offers better results in the face of degradation of the RNA In addition, expression analysis using microarrays is a complex technique that requires sophisticated equipment that is not available in many laboratories. Therefore, in a preferred embodiment, the detection of the mRNA of the genes is performed by the RT-PCR technique; and in a more preferred embodiment, the detection is performed by the qRT-PCR technique.

In a preferred embodiment, the detection of the gene expression product is performed by determining the level of protein derived from its transcription and translation, where the analysis of the level of AURKB, FIGF, IL6, MMP1 and VHL proteins can be performed, at Illustrative title and without limiting the scope of the invention, by incubation with a specific antibody in an immunoassay. The term "immunoassay", as used herein, refers to any analytical technique that is based on the reaction of conjugation of an antibody with the sample obtained. Examples of immunoassays known in the state of the art are, for example, but not limited to: immunoblot , enzyme-linked immunosorbent assay (ELISA), radioimmunoassay (RIA), immunohistochemistry or protein microarrays .

The term "antibody" as used herein refers to immunoglobulin molecules and immunologically active portions of immunoglobulin molecules, that is, molecules that contain an antigen binding site that specifically binds (immunoreacts) with any of the AURKB, FIGF, IL6, MMP1 and VHL proteins. Examples of portions of immunologically active immunoglobulin molecules include F (ab) and F (ab ') 2 fragments that can be generated by treating the antibody with an enzyme such as pepsin. The antibodies can be polyclonal (typically include different antibodies directed against different determinants or epitopes) or monoclonal (directed against a single determinant in the antigen). The monoclonal antibody may be biochemically altered, by genetic manipulation, or it may be synthetic, possibly lacking the antibody in whole or in part, from portions that are not necessary for the recognition of any of the AURKB, FIGF, IL6 proteins, MMP1 and VHL and being substituted by others that communicate additional advantageous properties to the antibody. The antibody can also be recombinant, chimeric, humanized, synthetic or a combination of any of the foregoing. A "recombinant antibody or polypeptide" (rAC) is an antibody that has been produced in a host cell that has been transformed or transfected with the nucleic acid encoding the polypeptide, or produces the polypeptide as a result of recombination.
homologue

The antibodies used to carry out the methods of the present invention can be polyclonal or monoclonal antibodies capable of recognizing any of the AURKB, FIGF, IL6, MMP1 and VHL proteins. Antibodies that recognize AURKB, FIGF, IL6, MMP1 and VHL proteins can be used to carry out the methods of the present invention by, for example, but not limited to, immunoblot , ELISA, RIA, immunhistochemistry or protein microarray .

In a preferred embodiment, the immunoassay is an immunoblot or Western blot . To carry out an immunoblot or Western blot , a protein extract is obtained from an isolated biological sample of a subject and the proteins are separated in a support medium capable of retaining them by electrophoresis. Once the proteins are separated, they are transferred to a different support where they can be detected through the use of specific antibodies that recognize the AURKB, FIGF, IL6, MMP1 and VHL proteins.

In another preferred embodiment, the immunoassay It is an immunhistochemistry (IHQ). Immunohistochemistry techniques allow identification, on tissue or cytological samples of characteristic antigenic determinants. The analysis by immunohistochemistry is performed on tissue cuts, either frozen or included in paraffin, from a sample biological isolated from a subject. These cuts hybridize with a monoclonal or polyclonal antibody that recognizes proteins AURKB, FIGF, IL6, MMP1 and VHL.

Among the immunohistochemical techniques that can be used to obtain expression profiles is the tissue microarray . Tissue microarray (TMA) is considered today a powerful tool for the massive analysis of the molecular profile of cancer from multiple tissue samples simultaneously, providing the possibility of studying new markers, or existing ones in bulk. In turn, the TMA preserves the original tissue samples that with traditional methods decrease in amount and deteriorate due to frequent use.

Another aspect of the invention relates to a kit comprising the suitable means for carrying out the methods of the invention. In a preferred embodiment, it comprises the means for determining the expression products of the AURKB, FIGF, IL6, MMP1 and VHL genes , in an isolated biological sample.

Said kit may comprise primers, probes, poly or monoclonal antibodies, and all those reagents necessary to use the techniques described above in This document and / or known in the state of the art. The kit It may also include, without any limitation, the use of buffers, enzymes, polymerase enzymes, cofactors to obtain a optimal activity of these, agents to prevent contamination, etc. On the other hand, the kit can include all the supports and necessary containers for commissioning and optimization. He kit can also contain other molecules, genes, proteins or probes of interest, which serve as positive and negative controls. Preferably, the Kit further comprises instructions for Carry out the first method of the invention.

Throughout the description and the claims the word "comprises" and its variants not they intend to exclude other technical characteristics, additives, components or steps. For those skilled in the art, other objects, advantages and features of the invention will be partly detached of the description and in part of the practice of the invention. The following examples and drawings are provided by way of illustration, and are not intended to be limiting of the present invention.

Description of the figures

Figure 1. Shows the ROC curves (acronym for " Receiver Operating Characteristic ", or Receiver Operating Characteristic ) of the model and LOOCV validation for pathological response.

Figure 2. Illustrative graphic (boxplot) in the that profile changes are compared between sensitive patients and no to the treatment, both of the model and after the process of LOOCV validation.

Examples

The following specific example to be provided in this patent document serves to illustrate the nature of the present invention. These examples are included For illustrative purposes only and should not be construed as limitations to the invention claimed herein. Therefore, the Examples described below illustrate the invention without limiting the field of application of it.

Example one

Profile identification associated with response Sample Population Selection

The study was conducted on 34 patients diagnosed with ovarian carcinoma, previously untreated and operated at the La Paz University Hospital between 1986 and 2003. All samples are from primary tumors and classified according to the Federation criteria. International Gynecology and Obstetrics (FIGO). The samples, fixed in formalin and included in paraffin, were selected based on a series of clinical and pathological criteria:

- Diagnosis of stage ovarian carcinoma III or IV

- Homogeneous treatment consisting of surgery cytoreducer and adjuvant chemotherapy consisting of a regimen of combination of carboplatin and paclitaxel.

- Piece in good condition.

- More than 70% of tumor cellularity in the sample.

Of all the patients included in the study, the necessary clinical data were collected, including treatment response data. The pathological response was evaluated through a second intervention performed on the patient, after chemotherapy, in which they analyzed biopsies of the suspicious lesions and in their absence the areas initially infiltrated by the tumor. A complete or positive pathological response is defined as the absence of residual microscopic tumor disease (Chiara et al , 1995. Eur J Cancer. 31 A (3): 296-301; Bolis et al , 1996. Cancer. 77 (1): 128-31).

MRNA extraction, cDNA synthesis and amplification by RT-PCR

The mRNA was extracted from each of the samples, using 7 \ mum sections and following the protocol of the kit extraction Masterpure RNA Purification Kit (EPICENTRE Biotechnologies, Madison, Wl, USA). The mRNA was extracted from each of the selected samples and the concentration and degradation status of said material before proceeding with the study. 1 µg of each sample was used for cDNA synthesis, performed according to the standard kit protocol High Capacity cDNA Reverse Transcription kit (Applied Biosystems, Foster City, CA, USA).

This material was used for the reaction of amplification, carried out through the card platform Applied Biosystems TaqMan Low Density Arrays microfluidics (TLDA), on an ABI PRISM 7900 HT Sequence Detection sequencer System (Applied Biosystems), according to the recommendations of the distributor, with a configuration that allows the detection of expression of 96 genes (Table 1) in duplicate in two samples of Simultaneously on the same card.

TABLE 1 Genes whose expression has been measured for response profile identification using Taqman probes included in the microfluidic card. Bold includes the reference genes that were used for the study

2

Pre-analysis

The raw data of the gene expression levels, obtained by means of SDS 2.2 software (Applied Biosystems) were normalized using the GeNorm program. This program allowed the selection of 5 of them (from a total of 14 reference genes) as the ideal set for the normalization of cases, based on the stability throughout the sample. The normalization process was carried out following the instructions of the Software (Vandesompele et al , 2002. Genome Biol. 2002 Jun 18; 3 (7): RESEARCH0034), and calculating a normalization factor based on the geometric mean of the selected reference genes .

The genes used as a basis for normalization are not considered as candidate genes to be included in the score of risk.

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Model selection to define the risk score and global significance of it

To find the risk index for response using the expression levels of 82 genes as variables, we used a multivariate logistic regression model that is given by the equation:

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3

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Where in this case \ hat {\ {tilde p}} is the estimated response probability treatment model and \ beta_ {i} are estimated for each covariate X {i} that includes the expression of 82 genes parameters, with i = 1, .. p. Hereinafter call Z to the linear part of this equation, that is, Z = \ sum \ limits ^ {p} _ {i = 0} \ {i} beta_ {i} X.

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The selection of candidate variables for become part of the risk index, were selected through a multi-stage algorithm:

In the first stage, the number was selected approximate variables that should enter, using a model of stepwise logistic regression with broad criteria of input (P to enter = 0.995) and output (P = 0.999). In each step of model Akaike information criterion value was observed (AIC). The function that represents the number of steps against the AIC function, has a minimum before reaching the saturated model. As the first model selected, the one constituted by the variables included up to that minimum value of the AIC. In the case of pathological response, the minimum was reached at step 5 so the Model was made up of 5 variables.

The second stage consisted of selecting others additional candidate models, using "the best subset" as statistical criteria for selecting variables among those who had the same number of variables as the number selected in the First stage or one more variable or one less variable. In all them, the AIC statistic was revalued, corrected according to the number of cases and variables.

Finally, among those who had a value similar, that model was taken that in the opinion of the researchers it had a greater biological plausibility, which turned out to be that of minimum AIC value. Table 2 shows the data of global significance of the model.

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TABLE 2 Response Prediction Model pathological

4

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The model is made up of genes indicated in Table 3.

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TABLE 3 Genes that integrate the response model pathological

5

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So that the probability associated with the Pathological response is calculated according to the specific weight of the Expression of the selected genes as follows:

First, the term Z is calculated previously defined, based on the coefficients estimated in the regression model and the expression of the model genes according to the equation (1), this is:

Z = Independent term + \ sum (PE_ {gen} x Normalized expression value_ {gen}) Depending on this term the probability of response to treatment is calculated, according to the formula:

6

So that the quantitative value of probability is proportional to the value of the variables included in the predictor

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Discriminant capacity of the model and Validation of the score of risk

The discriminant capacity of the model was assessed chosen by the index "area under the ROC curve" (Figure 1 and table 4). This index on the probability of response was estimated given by the model for each patient.

Since the selection criterion used was the AIC statistic, it was not considered necessary to perform a validation of the model construction process since there is a bibliography that indicates it, compared to cross-validation or bootstrapping methods (You et al , 2008 Clin Biochem. 41 (10-11): 785-95).

The discriminant capacity of each model was validated using the LOOCV cross-validation method ( Leave One Out Cross Validation ) for ROC curves (Simón et al , 2006. Pharmacogenomics J. 6 (3): 166-73; Varma et al , 2006 BMC Bioinformatics 23; 7: 91) as shown in Figure 1 and Table 4.

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TABLE 4 LOOCV cross validation for response pathological

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7

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In figure 2 it is represented by a box diagram the difference in terms of values of heel in responding and non-responding patients at treatment, perfectly differentiating the two groups of response based on the predictor. Although what is proposed in this study is the analysis of the heel continuously, to produce less bias, there is the possibility of assigning cuts to classify in populations at risk. These cuts can be given depending on the discriminant capacity of the model, which as indicated above has been analyzed using ROC curves, and based on the values of sensitivity and specificity generated from said analysis and that included in table 5.

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TABLE 5 Sensitivity and specificity of ROC curves generated for the pathological response predictor, and after passing the LOOCV validation

8

Assessment of the risk score against clinical variables

The model is significantly associated with the pathological response (p = 0.022, HR (95% CI) 0.368 (0.156-0.868). The effect of the same was not evaluated in presence or adjusted for other clinical factors since none of them is associated with the pathological response through a model of multivariate logistic regression.

The following have been used for the analysis statistical programs:

SAS version 9.1.3,

SPSS 9

R version 2.2 with the software package version 2.0-12.

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Claims (22)

1. Use of the AURKB, FIGF, IL6, MMP1 and VHL genes to predict the pathological response to a treatment comprising a platinum derivative and a taxane from a cancer patient. 2. Use of the genes according to claim 1, where the platinum derivative is selected from the list that comprises: carboplatin, oxaliplatin or cisplatin. 3. Use of the genes according to claim 2, where the derivative of platinum is carboplatin. 4. Use of genes according to any of the claims 1 to 3, wherein the taxane is selected from the list which comprises: paclitaxel or docetaxel. 5. Use of the genes according to claim 4, where the taxane is paclitaxel. 6. Use of genes according to any of the claims 1 to 5, wherein the cancer is from the list that comprises: ovary, tube, peritoneum, cervix, endometrium, lung or tumor of unknown origin. 7. Use of the genes according to claim 6, where the cancer is ovarian

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8. Method to predict the pathological response to a treatment comprising a platinum derivative and a taxane of a cancer patient, comprising:

to.

obtain an isolated biological sample comprising a patient's cells, and

b.

Detect the amount of expression product of the AURKB, FIGF, IL6, MMP1 and VHL genes in the biological sample from step (a).

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9. Method according to claim 8, which further understands:

C.

assign the patient a probability of pathological response to the treatment, where said pathological response depends on the amount of expression of the AURKB, FIGF, IL6, MMP1 and VHL genes in the sample obtained in (a), in relation to the amount of expression detected for said genes in a reference patient population of known pathological response.

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10. Method according to claim 9, wherein the probability of pathological response is assigned by formula: 9 where Z = independent term + \ sumPE_ {gen} x Normalized expression value_ {gen}; Being the independent term a value between 20.9530 and 17.0330 and the specific weight of each gene (PE_) a value included between 22.9230 and 19.0030 for PE_ {AURKB}, between 182.0550 and 178.1350 for PE_FIG, between 16.7910 and 12.8710 for PE_6, between 33.4990 and -37.4190 for PE_ {MMP1}, and between -31.6340 and -35.5540 for PE_ {VHL}.

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11. Method according to claim 10, wherein the independent term is a value between 20,1430 and 17.8430 and the specific weight of each gene (PE_) a value between 22.1130 and 19.8130 for PE_ {AURKB}, between 181.2450 and 178.9450 for PE_FIG, between 15.9810 and 13.6810 for PE_ {IL6}, between -34,3090 and -36,6090 for PE_ {MMP1}, and between -32.4440 and -34.7440 for PE_ {VHL}. 12. Method according to any of the claims 8 to 11, wherein the platinum derivative is selected from the list comprising: carboplatin, oxaliplatin or cisplatin 13. Use of the genes according to claim 12, where the derivative of platinum is carboplatin. 14. Use of genes according to any of the claims 8 to 13, wherein the taxane is selected from the list which comprises: paclitaxel or docetaxel. 15. Use of the genes according to claim 14, where the taxane is paclitaxel. 16. Method according to any of the claims 8 to 15, wherein the biological sample isolated from the passage (a) comprises tumor cells. 17. Method according to any of the claims 8 to 16, wherein the biological sample isolated from the passage (a) is fixed and embedded in paraffin.

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18. Method to identify if a compound is useful for the treatment of cancer, which includes:

to.

get cells derived from a Cancer,

b.

detect the amount of expression product of the AURKB, FIGF, IL6, MMP1 and VHL genes in the cells of step (a),

C.

administer the compound to the cells of (a),

d.

detect the amount of expression product of the AURKB, FIGF, IL6, MMP1 and VHL genes , after administration of the compound according to (c), and

and.

compare the amount of expression product of the AURKB, FIGF, IL6, MMP1 and VHL genes , before and after administration of the compound.

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19. Method according to any of the claims 8 to 18 wherein the gene expression product It is determined by RT-PCR. 20. Method according to any of the claims 8 to 19, wherein the cancer is from the list that comprises: ovary, tube, peritoneum, cervix, endometrium, lung or tumor of unknown origin. 21. Method according to claim 20, wherein the Cancer is ovarian. 22. Kit for carrying out the method according to any of claims 8 to 21 comprising the assays indicated in Table 1 of the description to detect the amount of product of the expression expression of the AURKB, FIGF, IL6, MMP1 genes and VHL in an isolated biological sample from a cancer patient.