WO2013098457A1 - Procédé de classification du carcinome non microcytique du poumon basé sur l'identification d'une réponse immunitaire intratumorale - Google Patents

Procédé de classification du carcinome non microcytique du poumon basé sur l'identification d'une réponse immunitaire intratumorale Download PDF

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WO2013098457A1
WO2013098457A1 PCT/ES2012/070919 ES2012070919W WO2013098457A1 WO 2013098457 A1 WO2013098457 A1 WO 2013098457A1 ES 2012070919 W ES2012070919 W ES 2012070919W WO 2013098457 A1 WO2013098457 A1 WO 2013098457A1
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genes
prognosis
expression
group
stage
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Spanish (es)
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Julian SANZ ORTEGA
Milagros FERRER ALDEA
Susana HERNÁNDEZ PRIETO
Alejandro ROMERA LÓPEZ
Beatriz PÉREZ-VILLAMIL SALGADO
Florentino HERNANDO TRANCHO
Ana María GÓMEZ MARTÍNEZ
José Ramón JARABO SARCEDA
Antonio José TORRES GARCÍA
José Antonio LÓPEZ GARCÍA-ASENJO
José Luís GONZÁLEZ LARRIBA
Javier PUENTE VÁZQUEZ
Eduardo DÍAZ-RUBIO GARCÍA
José Luís SUBIZA GARRIDO-LESTACHE
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Fundación Para La Investigación Biomédica Del Hospital Clínico San Carlos
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Priority claimed from ES201230250A external-priority patent/ES2420079B1/es
Application filed by Fundación Para La Investigación Biomédica Del Hospital Clínico San Carlos filed Critical Fundación Para La Investigación Biomédica Del Hospital Clínico San Carlos
Publication of WO2013098457A1 publication Critical patent/WO2013098457A1/fr

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    • C12Q1/00Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C12Q1/6886Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
    • CCHEMISTRY; METALLURGY
    • C12BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12QMEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00Oligonucleotides characterized by their use
    • C12Q2600/118Prognosis of disease development
    • CCHEMISTRY; METALLURGY
    • C12BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12QMEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00Oligonucleotides characterized by their use
    • C12Q2600/158Expression markers

Definitions

  • the present invention relates to an in vitro method of classification of non-small cell lung carcinoma based on the differential expression of 50 genes. These genes identify an intratumoral immune response.
  • patients with an expression profile of genes associated with an immune response that is associated with a good prognosis are distinguished and patients without that expression profile have a worse prognosis.
  • This classification can be used as a prognostic marker, as a tumor classifier as a function of the antitumor immune response ("immunoscore") or as a biomarker predictor of immune system-based therapies (immunotherapy).
  • the present invention also relates to a kit that It comprises a set of probes that recognize the 50 genes of the invention, so the invention could be framed in the medical field.
  • STATE OF THE TECHNIQUE Lung cancer is the leading cause of cancer death with an annual rate of more than 1.1 million people worldwide, and with a five-year survival rate of only 15%. Approximately 80% of the diagnosed cases are classified as non-small cell lung carcinoma (CNMP) and the remaining 20% correspond to small cell lung carcinoma (CMP). In the CNMP, the most frequent types are squamous or squamous cell carcinoma and adenocarcinoma.
  • CNMP non-small cell lung carcinoma
  • CMP small cell lung carcinoma
  • TNM staging system ⁇ 7- edition
  • T tumor size
  • N lymph node involvement
  • M distant metastases
  • stage II surgery with curative intent is the treatment of choice, the benefit of adjuvant chemotherapy to reduce the high recurrence rate after surgical resection ranging between 30- 35% of patients.
  • adjuvant platinum-based chemotherapy such as cisplatin
  • stage II adjuvant platinum-based chemotherapy, such as cisplatin
  • cisplatin has been shown to improve the survival of certain subgroups but, on the other hand, there is a percentage of patients who despite not relapse after surgery receive adjuvant treatment and which are therefore patients treated in excess. This over-treatment affects problems in these patients associated with the side effects of these treatments.
  • stages I which includes subgroups IA and IB
  • NCN National Comprehensive Cancer Network
  • the technical problem that the invention solves is that of providing an alternative in vitro method that determines the existence of an immune response within the non-small cell lung carcinoma (CNMP) to obtain a personalized treatment of the patient.
  • CNMP non-small cell lung carcinoma
  • an in vitro method for classifying the CNMP that is characterized by the detection and / or quantification of an expression product of the set of 50 genes, which are shown in Table 1 in the biological sample of a subject.
  • the present invention also relates to the use of the expression products of said 50 genes as CNMP cancer prognostic biomarkers.
  • the method of the invention provides a 50 gene predictor for CNMP. The strategy used to obtain this predictor began with a detection and / or quantification of the global gene expression of CNMP tumors in early stages (I and II).
  • the predictor of the invention consists of 50 genes shown in Table 1, hereafter referred to as "50 genes of the invention”.
  • the 50 genes in table 1 are overexpressed in the good prognosis group.
  • the function described for these genes indicates that their overexpression is largely due to the presence of an intratumoral immune response, which is also associated with a better prognosis.
  • the 50 genes in Table 1 are mostly related to structural elements of immune system cells or immune functions (maturation, recruitment, proliferation and survival), especially in B lymphocytes and intratumoral plasma cells. Many of these genes code for immunoglobulin (Ig) molecules (constant heavy and light chains, the J chain, the variable regions of the heavy and light chains), the B cell receptor (CD79a), the specific lineage marker of B cell (CD19), the specific transcription co-activator in B cells (POU2AF1) or the specific folding factor for IgM assembly (pERpI).
  • Ig immunoglobulin
  • TNFRSF17 B cell maturation factor
  • POU2AF1 Zao C. et al. 2008 Oncogene 27: 63-75
  • POU2AF1 Zao C. et al. 2008 Oncogene 27: 63-75
  • POU2AF1 Zao C. et al. 2008 Oncogene 27: 63-75
  • POU2AF1 Zao C. et al. 2008 Oncogene 27: 63-75
  • POU2AF1 the receptor for the B cell activation factor
  • CXCL13 a chemoattractant cytokine of B cells
  • IRF4 a member of the family of transcription factors of the interferon regulatory factor, which have shown to have critical functions in several stages of the development of B cells (Havelange V. et al. Blood 201 1, 1 18 (10): 2827-9), or of CD38, which supports the proliferation and survival of B cells ( Malavasi et al. Blood, 201 1, 1 18 (13) 3470-3478).
  • CD38 is strongly expressed in plasma cells as well as CD27, which is a marker of memory cells that is also within the 50 overexpressed genes in the present study. It is interesting to note that Pim-2, a serine / threonine kinase that is also one of the 50 overexpressed genes, has recently been described as an anti-apoptotic mediator in plasma cells (Asano et al. Leukemia 201 1, 25, 1 182 -1 188).
  • a gene from table 2 ⁇ Homo sapiens ephrin-A4 (EFNA4), transcript variant 3, mRNA), whose reference in the NCBI (National Center for Biotechnology Information, US National Library of Medicine) gene database is NM_182690, is overexpressed in the group of poor prognosis.
  • EFNA4 Homo sapiens ephrin-A4
  • mRNA transcript variant 3, mRNA
  • NCBI National Center for Biotechnology Information, US National Library of Medicine
  • predictor refers herein to a differential gene expression profile or gene expression profile.
  • Gene expression profile means the gene profile obtained after quantification of the expression product of the genes of interest.
  • expression product means messenger RNA (mRNA), complementary DNA (cDNA), complementary RNA (cRNA) and / or the protein produced by the genes of interest or biomarkers, that is, by the genes of Table 1, in an isolated biological sample.
  • the expression profile of the genes is preferably performed by determining the level of mRNA derived from its transcription, after extracting the total RNA present in the isolated biological sample, which can be performed by protocols known in the state of the art.
  • the level of mRNA derived from the transcription of the genes in Table 1 can be determined, for example, but not limited to, by amplification by polymerase chain reaction (PCR), back transcription in combination with the chain reaction of the polymerase (RT-PCR), quantitative RT-PCR, back transcription in combination with the ligase chain reaction (RT-LCR), or any other nucleic acid amplification method; analysis in gene expression series (SAGE, SuperSAGE); DNA or RNA microarrays made with oligonucleotides or probes 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 nano
  • the gene expression profile could also be obtained by the detection and / or quantification of the proteins resulting from the translation of the mRNA derived from the transcription of the genes in Table 1, for example, but not limited to, immunodetection by immuno blotting, immunohistochemistry. , chromatography or microarray.
  • the present invention could also refer to an in vitro method for classifying the CNMP that is characterized by the detection of the number of copies in the DNA of the 50 genes shown in Table 1, as well as epigenetic alterations such as hypermethylation of the promoter of the genes or as of the alteration of the mRNA stability due among other factors to transcriptional modifications that affect for example the tail of Poly Adenines.
  • the present invention also relates to the use of these 50 gene alterations as prognostic biomarkers of CNMP cancer, as "immunoscore" or as a biomarker predictive of immunotherapy response.
  • the gene expression profile could also be obtained by detecting and / or quantifying the number of copies of the genes present in Table 1, as well as the levels of epigenetic alterations such as the level of promoter methylation or stability levels of the messenger of these same genes.
  • This detection could be carried out, although not limited by microarrays, CGH (Comparative Genomic Hybridization) or FISH (fluorescent in situ hybridization). It could also be made from material included in paraffin.
  • This invention could also be applied for advanced stages (III and IV).
  • a first aspect of the invention relates to an in vitro method of obtaining useful data for the prognosis of stage I or II CNMP characterized by the detection and / or quantification of the expression product of the genes of the Table 1 in the isolated biological sample of a subject. From now on we will refer to this as the "first method of the invention”.
  • in vitro refers to the method of the invention being performed outside the subject's body.
  • prognosis in the present invention refers to the ability to detect patients who have a high or low probability of recurrence after surgery. A high probability of recurrence is associated with a poor prognosis while a low probability of recurrence is associated with a good prognosis.
  • Recurrence is understood as the recurrence of the disease, in this case of lung cancer.
  • probability of non-recurrence and “probability of ILE (disease-free interval)" are used interchangeably herein.
  • non-small cell lung cancer refers to a type of lung cancer or tumor according to histological classification comprising the subtype squamous or squamous cell carcinoma, adenocarcinoma, adenoescamoso, sarcomatoid carcinoma, and large cell carcinoma.
  • Stim means the phase or classification of lung cancer based on the TNM classification.
  • the TNM classification refers to tumor size (T), lymph node involvement (N) and involvement of other organs (M).
  • Stage I refers to the IA or IB substations.
  • the IA substation refers to lung tumors classified as T1 N0M0.
  • the IB substation includes lung tumors classified as T2aN0M0.
  • Stage II refers to any of the IIA or IIB substations.
  • Sub-stage IIA refers to lung tumors classified as T1 N1 M0, T2aN1 M0 and T2bN0M0.
  • Sub-stage IIB includes lung tumors classified as T2bN1 M0 and T3N0M0.
  • T1 refers to when the tumor ⁇ 3 cm of maximum dimension, is surrounded by lung tissue or visceral pleura and without invasion proximal to the lobar bronchus in fibrobronchoscopy.
  • T1 a is a tumor ⁇ 2 cm and T1 b is a tumor> 2cm and ⁇ 3cm.
  • T2 refers to a tumor> 3 cm in maximum dimension and ⁇ 7 cm or a tumor with at least one of the following characteristics: infiltrate the main bronchus 2 cm or less from the carina, invade visceral pleura or be associated with atelectasis or pneumonitis obstructive T2a is a tumor> 3 cm and ⁇ 5 cm and T2b is a tumor> 5 and ⁇ 7 cm.
  • T3 refers to a tumor> 7 cm or a tumor that affects the costal wall (including tumors of the upper fissure), diaphragm, mediastinal pleura or pericardium; no involvement of the heart, large vessels, trachea, esophagus, vertebral bodies; or a tumor of the main bronchus less than 2 cm from the carina, without infiltration thereof; where atelectasis affects an entire lung and there may be non-malignant pleural effusion. It does NOT refer to the lung tumor without lymph node involvement.
  • N1 refers to the tumor that has involvement of the ipsilateral peribronchial or hilar lymph nodes or both.
  • M0 refers to the lung tumor that does not have distant metastases.
  • the terms “early stages”, “initial stages” or “early stages” refer to CNMP stage I or II.
  • the term “immunoscore” refers to a method to classify the intratumoral immune response (Galón 2012).
  • the present invention by detecting and / or quantifying the expression of the 50 genes in Table 1, it is possible to identify a group of patients with the presence of an intratumoral immune response associated with a good prognosis against a group in which no intratumoral immune response is identified that is associated with poor prognosis.
  • immunotherapy refers to a therapy or treatment against cancer based on or related to the performance of the immune system of the individual in which the tumor occurs, by facilitating an antitumor immune response and recognition or by preventing actions of the immune system that favor tumor growth.
  • genes from table 1 or "50 genes” refers to the 50 genes described in table 1 shown below.
  • Entrez Identifier or “Entrez ID” refer to the gene reference number in the NCBI (National Center for Biotechnology Information, U.S. National Library of Medicine) gene database.
  • AMPD1 It catalyzes the deamination of adenosine monophosphate (AMP) to inosine monophosphate (IMP) in skeletal muscle and plays an important role in The purines cycle.
  • AMP adenosine monophosphate
  • IMP inosine monophosphate
  • TNFRSF17 This receptor is expressed in mature B lymphocytes and is important for the development of B cells and in the autoimmune response. It has as ligand member 13b of the tumor necrosis factor superfamily and activates the nuclear factor of the light chain polypeptide gene enhancer Kappa in B cells (NF-kappaB) and mitogen-activated protein kinase 8 (MAPK8 / JNK). It also binds to other ligands and sends signals of cell survival and proliferation.
  • CD19 A molecule that binds to the B-cell antigen receptor to lower the threshold of lymphocyte stimulation through antigen stimulation.
  • CD27 Member of the tumor necrosis factor receptor superfamily. The receptor has the function of generating and maintaining for a long time the immunity of T cells.
  • the CD70 ligand binds to it and works in the activation of B cells and in the synthesis of immunoglobulins.
  • the adapter proteins called Factor Associated to Receptors of Tumor Necrosis Factors 2 and 5 (TRAF2 and TRAF5) mediate this process.
  • CD27 binding protein (SIVA) is a proapoptotic protein that plays an important role in apoptosis mediated by this receptor.
  • CD38 It is a multifunctional ectoenzyme that is expressed in a multitude of cells and tissues especially in leukocytes. CD38 also has functions in cell adhesion, signal transduction and calcium signaling.
  • CD79A and CD79B code for the lg-alpha and lg-beta proteins that are components of the B lymphocyte antigen receptor.
  • the lg-alpha and lg-beta molecules are necessary for the expression and function of this receptor.
  • GZMB Cytolytic T lymphocytes (CTL) and "natural killer” cells (NK) have the ability to recognize, bind and lyse specific target cells. GZMB is crucial for the rapid induction of apoptosis of the target cells through the immune response generated by the cytolytic T lymphocytes or even in the mediated by B lymphocytes.
  • IGHA1 and IGHA2 Antibody with an important presence in the mucous secretions and that represents the first line of defense of the organism. There are two subclasses Immunoglobulin A1 (lgA1) and Immunoglobulin (lgA2).
  • IGHG1 This gene is translocated in chronic B-cell lymphocytic leukemia with the Cyclin D1 gene (CCND1) and in subclasses of MALT lymphomas (Mucosa Associated Lymphoid Tissue) with the genes "LIM homeobox 4" (LHX4) and "Forkhead box P1 "(FOXP1).
  • IGJ Its function is to join two monomers of either Immunoglobulin M (IgM) or Immunoglobulin A (IgA). It also has the function of binding these immunoglobulins to the secretory component.
  • Each immunoglobulin molecule has two identical heavy chains and two identical light chains. There are two kinds of light chains that are kappa and lambda. This gene encompasses the lambda light chain locus that includes segment V (variable), segment J (junction) and segment C (constant).
  • IGLL1 It is a gene of the immunoglobulin superfamily that codes for the light chain replacing the preB cell receptor. Mutations in this gene can cause B-cell deficiency or agammaglobulinemia.
  • IRF4 It belongs to the family of interferon regulatory factors. It is lymphocyte specific and negatively regulates Toll-like receptors (or TLR), which is a central molecule in the activation of the innate and adaptive immune response.
  • TLR Toll-like receptors
  • KCNN3 Regulates neuronal excitability.
  • KRT81 It is a member of the keratin family.
  • CXCL9 Its function is not well defined but it seems to be involved in T-cell traffic.
  • PNOC It is a neuropeptide that acts as an endogenous ligand of the "Opiate Receptor-Like 1" receptor (ORL1).
  • POU2AF1 It is a specific co-activator of B cells and its absence seems to be related to defects in the development of B cells and the lack of germ centers.
  • BFSP2 also called phakinin, it is a structural protein of cytoskeleton filaments. Next to the filensin forms the BF ("beaded filament").
  • CXCL13 Promotes the migration of B lymphocytes preferably against T lymphocytes and macrophages by calcium stimulation.
  • PIM2 It is a serin / threonine / protein kinase. Prevents apoptosis and promotes cell survival. It is an anti-apoptotic mediator of plasma cells.
  • SMR3A It is a functional homolog of the Vcsal gene ("Variable Coding Sequence A1"). It has been associated as a marker of erectile dysfunction associated with both diabetic and non-diabetic etiology.
  • MZB1 It is associated with the heavy and light chains of immunoglobulin type M (IgM), promoting the assembly of IgM and its secretion.
  • IgM immunoglobulin type M
  • FKBP11 It belongs to the FKBP family which catalyze the folding of proline-containing polypeptides. Its function is inhibited by FK506 and by rapamycin.
  • LAX1 A negative regulator of lymphocyte signaling.
  • CPNE5 Calcium-dependent membrane binding protein that appears to be involved in the regulation of molecular phenomena at the interface of the cell membrane and in the cytoplasm.
  • SLAM7 It is involved in the activation of NK cells and in the regulation of B lymphocyte proliferation during the immune response.
  • DUSP26 It is associated with the inactivation of the protein kinase activated by mitogens 1 and 3 (MAPK1 and MAPK3), as well as with the inhibition of epithelial cell proliferation, which could suggest a role as a tumor suppressor gene.
  • FCRL2 It is part of the immunoglobulin receptor superfamily. It can be a prognostic marker of chronic lymphocytic leukemia.
  • FCRL5 It is also part of the immunoglobulin receptor superfamily. It is involved in the development of B cells and lymphomagenesis.
  • FCRLA This receptor mediates the destruction of antigens recognized by Immunoglobulin G (IgG). It is selective B cell protein and may be involved in its development.
  • IgG Immunoglobulin G
  • DERL3 Protein that is located in the endoplasmic reticulum with the function of degrading misfolded glycoproteins.
  • MTSS1L May be involved in actin packaging. It belongs to the MTSS1 family (Type 1 Metastasis Suppressors).
  • JSRP1 The sarcoplasmic reticulum is a cellular compartment that controls the concentration of intracellular calcium and is involved in the excitation-contraction functions of this cellular compartment. In mice it has been seen This protein interacts with key proteins involved in these excitation-contraction processes.
  • C5orf20 This gene is expressed in dendritic cells, which are potent antigen presenting cells involved in activating native T cells to initiate the antigen-specific immune response.
  • MEI1 Defects in its expression are related to stopping in meiosis and is associated with azoospermia phenomena.
  • GPR114 Protein G associated with receptors with an N-terminus that contains regions rich in serine / threonine. Its expression in cytotoxic lymphocytes has been described. IGHV5-78, FER1L4, IGKV1D-8, KIAA0125, LOC401847, LOC642424, LOC100132941, LOC100133862, LOC100287723, IGHV1-24 and LOC100293440: as of today, the function of these genes is still unknown.
  • biological sample includes, but is not limited to, tissues and / or biological fluids of an individual, obtained by any method known to a person skilled in the art that serves this purpose.
  • subject refers to an individual, preferably human, who has been diagnosed with CNMP.
  • a preferred embodiment of the first aspect of the invention relates to a method that further comprises comparing the useful data obtained from the isolated biological sample of a new subject, with the reference expression values for the genes in Table 1 obtained from subjects with CNMP stage I or II in which the prognosis is known (reference sample). The comparison allows the identification of the new subject as a subject of good prognosis or bad prognosis. From now on, we will refer to this method as the "second method of the invention".
  • reference samples refers, for example, but not limited to samples obtained from individuals having a known molecular profile. This molecular profile can be of good prognosis or of poor prognosis.
  • a person skilled in the art could classify a new patient in the group of good or in the group of poor prognosis when comparing his expression data for the 50 genes of the invention with the expression data for the 50 genes in the reference samples.
  • These reference samples are a group of samples of which the expression profile of the 50 genes is known and the presence or absence of recurrence.
  • a new subject whose expression profile is similar to the good prognosis reference group can be classified as belonging to the good prognosis group, which has an average 3-year probability of ILE at 85% and / or 5 years of 79%.
  • a new subject whose expression profile is similar to the bad prognosis reference group can be classified as belonging to the bad prognosis group, which has an average 3-year probability of ILE at 62% and / or 5 years of 48%.
  • the determination of the prognosis of new patients diagnosed with CNMP in stages I or II implies the classification of these patients into one of the two previously defined reference groups: a group with a good prognosis or a group with a poor prognosis. These reference groups consist of the reference samples.
  • the comparison of the useful data obtained from the biological sample of a new subject, with the reference expression values for the genes of table 1 obtained from subjects with CNMP stage I or II in which the prognosis is known can be carried out by any statistical prediction method known in the state of the art, such as, but not limited to, in any of the methods described in Simón R. et al. J Clin Oncol 2005; 23: 7332-41.
  • the comparison is made by the nearest compact centroid method.
  • the "closest shrunken centroid method” is the classification method described in Tibshirani R. et al. PNAS 2002, 99: 6567-6572 and applied through the Prediction analysis of microarray tool (PAM).
  • the "PAM” tool was developed by Standford University and is freely accessible.
  • the determination of the CNMP prognosis of stages I or II can be established, but not limited, by determining a "reference value" for the group of good prognosis (value 1) and another for the group of poor prognosis (value 2 ).
  • the forecast can be made by estimating the distance between the expression values of the new sample and the "reference values" of each of the two groups. If the distance between the new sample and the value 1 is less than the distance between the new sample and the value 2, the favorable forecast can be determined. On the contrary, if the distance between the new sample and the value 1 is greater than the distance between the new sample and value 2, the unfavorable forecast can be determined.
  • the reference values of each group can be calculated based on the expression values of the 50 genes in the samples of the reference matrix or "development matrix" and will therefore be expressed by a vector of 50 components.
  • the calculation of the reference value of each group is obtained by adding to the global average value of all the samples, a second factor defined as the distance (statistic "t") between the average expression value of the 50 genes of said group with respect to the average expression value of the 50 genes of all the samples included in the training matrix.
  • the data of the second factor will be standardized taking into account the variability of expression of each of the 50 genes within the analyzed group and taking into account a convergence value ⁇ that allows to evaluate the predictive power of each of the genes. It is understood as distance between two samples, groups or subtypes, the quantification of their expression differences.
  • the "closest shrunken centroid" method is able to assign new samples (which in our case make up the validation matrix) to each of the defined groups.
  • the distance between the new sample and each of the groups is relative to the difference between the expression values of the 50 genes in the new sample with respect to the components of the compact centroid ("shrunken centroid") that represent each group.
  • the quantification of distances could be measured, but not limited, by Euclidean distance (Tibshirani R. Diagnosis of multiple cancer types by shrunken centroids of gene expression. PNAS 2002; 99 (10): 6567-72). As mentioned earlier, the new sample will be assigned to the group from which it is at a smaller distance.
  • a second aspect of the invention relates to an in vitro method for the prognosis of stage I or II CNMP characterized by: to. the detection and quantification of the expression product of the genes of table 1 in a reference sample;
  • a preferred embodiment of the fourth method of the invention relates to the method where the nearest compact centroid method is carried out through the application of Microarray Analysis Prediction (PAM).
  • PAM Microarray Analysis Prediction
  • a preferred embodiment of the first and second aspects of the invention refers to the method where the reference sample and the study samples have been previously normalized before comparison.
  • Normalization means the use of a control sample that serves to eliminate experimental variations between the different samples.
  • Another preferred embodiment of the first and second aspects of the invention refers to the method that also comprises the detection and / or quantification of at least one expression product of the genes described in Table 2.
  • Another preferred embodiment of the first and second aspects of the invention relates to the method where the expression product is messenger RNA.
  • An even more preferred embodiment refers to the method where the detection and / or quantification of messenger RNA is performed by microarrays.
  • a more preferred embodiment also refers to the method where the detection and / or quantification of messenger RNA is performed by RT-PCR.
  • Another preferred embodiment of the first and second aspects of the invention relates to the method where the expression product is a protein.
  • An even more preferred embodiment refers to the method where the detection and / or quantification of the protein is performed by immuno blotting, immunohistochemistry, chromatography or microarrays.
  • the detection and quantification of the expression product can be performed using methods known to those skilled in the art. For example, by determining the level of mRNA derived from its transcription, after extracting the total RNA present in the isolated biological sample, which can be done by protocols known in the state of the art. For this, the isolated biological sample can be physically or mechanically treated to break up the cellular tissue or structures and release the intracellular components to an aqueous or organic solution to prepare the nucleic acids for further analysis. Nucleic acids are extracted from the sample by procedures known to those skilled in the art and commercially available.
  • the level of mRNA derived from the transcription of the genes in Table 1 can be determined, for example, but not limited to, by amplification by chain reaction of the polymerase (PCR), retrotranscription in combination with the polymerase chain reaction (RT-PCR), quantitative RT-PCR, retrotranscription in combination with the ligase chain reaction (RT-LCR), or any other amplification method of nucleic acids; serial analysis of gene expression (SAGE, SuperSAGE); microarrays, micromatrices or DNA chips made with oligonucleotides deposited by any mechanism or 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.
  • PCR polymerase
  • the present invention demonstrates that the detection and quantification of the total mRNA of a biological sample of a subject with stage I or II CNMP is useful for the prognosis of said disease. Therefore, in a preferred embodiment of this aspect of the invention, the expression product detected and quantified is mRNA.
  • the expression product is mRNA.
  • "Microarray” expression microarray, chip or microarray
  • probes oligonucleotides or cDNAs
  • Each of the probes specifically represents a gene determined by having a sequence complementary to the mRNA transcribed by said gene, thus enabling the measurement of the expression levels of all the genes that make up the genome at the same time and in a single experiment.
  • the experimental phase of the microarray can consist of the steps described below.
  • the total RNA is retrotranscribed using as a primer a messenger specific primer (PolidT) and a retrotranscriptase enzyme.
  • a primer a messenger specific primer (PolidT) and a retrotranscriptase enzyme.
  • the cRNA was synthesized, while the process of amplification and marking of the sample was carried out.
  • the labeled cRNA obtained was purified by columns.
  • the cRNA is fragmented into smaller sequences and hybridized to the microarray. Said hybridization process is carried out in a hybridization oven for a long period of time. In this process the labeled cRNA binds specifically to the oligonucleotides synthesized in the microarray.
  • the expression product preferably mRNA or cDNA or complementary RNA (cRNA) obtained from cDNA
  • Detectable labels include, for example, radioactive isotopes, fluorescent labels, chemiluminescent labels, bioluminescent labels or enzymatic labels.
  • the fluorescent labels may be different in the case of the mapping of the expression product of the biological sample and the expression product of the control sample.
  • the detection and quantification can also be carried out by RT-PCR, whereby another preferred embodiment of the first aspect of the invention refers to a method according to claim 7 wherein the detection and / or quantification of the mRNA is performed by RT-PCR or preferably by real-time RT-PCR.
  • the RT-PCR process can be carried out in two phases:
  • Retrotranscription the union between a primer and the mRNA is produced by a joint incubation process of both products. Then the retrotranscription itself takes place using reverse transcription enzymes.
  • PCR polymerase chain reaction
  • cDNA denaturation phase oligonucleotide specific binding phase of the gene under study to the denatured cDNA strand
  • elongation phase from the bound oligonucleotide by which a new strand of synthesized will be synthesized.
  • CDNA Being a process that is measured in real time, it is necessary to use a fluorescent molecule to monitor what happens throughout the process.
  • Quantification on the other hand can also be performed by determining the level of protein derived from the translation of transcribed mRNAs from the 50 genes of the invention.
  • This protein quantification can be performed by any method known to a person skilled in the art that serves this purpose, such as, but not limited to, immunodetection methods (such as western blot, ELISA, immunohistochemistry, immunocytochemistry, immunofluorescence), methods based on isobaric (such as iTRAQ - isobaric Tag for Relative and Absolute Quantitation-, or ICAT -Isotope-Coded Affinity Tag-) or in isotopic (such as SILAC -Stable Isotopes Labeling by Amino Acids in Cell Culture-) or based on fluorescent (such as 2D-DIGE -Difference in Gel Electrophoresis-), as well as methods based on mass spectrometry (MRM, -Multiple Reaction Monitoring-).
  • immunodetection methods such as
  • the expression product is a protein.
  • Another preferred embodiment of the first and second aspect of the present invention relates to the method where the detection and / or quantification of the Protein is made by immuno blotting, immunohistochemistry, chromatography or protein expression arrays.
  • amino acid sequence or “protein” are used interchangeably herein, and refer to a polymeric form of amino acids of any length, which may or may not be chemically or biochemically modified.
  • reduct corresponds to an amino acid.
  • Another preferred embodiment of the first and second aspects of the present invention relates to the method where the biological sample is selected from the list comprising: tissue, blood, plasma, serum, lymph, bronchoalveolar lavage or ascites fluid.
  • Another also preferred embodiment of the first and second aspects of the present invention relates to the method where the biological sample is fresh, frozen, fixed or fixed and embedded in paraffin.
  • Another preferred embodiment of the first and second aspects of the invention relates to a method where the subject is a human.
  • a third aspect of the invention relates to the in vitro use of the expression products of the genes in Table 1 as a prognostic marker of stage I or II CNMP.
  • a fourth aspect of the invention relates to the in vitro use of the expression products of Table 1 to classify the intratumoral immune response in stage I or II CNMP.
  • a fifth aspect of the invention relates to the in vitro use of the expression products of Table 1 as a biomarker predictive of therapeutic response to immunotherapy in the CNMP of stage I or II.
  • a sixth aspect of the invention relates to a kit comprising the probes that recognize the messenger RNA, product of the expression of the genes of table 1, or the cRNA or cDNA to said mRNA, or antibodies that recognize a protein product of expression of the genes in table 1.
  • the amount of probes used for each gene may vary in number.
  • the kit comprises probes, which consist of probes that recognize the messenger RNA resulting from the expression of the genes in Table 1. More preferably the probes are the sequences described as SEQ ID NO: 1 to SEO ID NO: 66 and that specifically recognize the 50 genes in Table 1.
  • this kit comprises probes, which consist of probes that recognize the messenger RNA resulting from the expression of the genes in Table 1. More preferably the probes are the sequences described as SEQ ID NO: 1 to SEO ID NO: 66 and that specifically recognize the 50
  • a preferred embodiment of the sixth aspect of the invention relates to the kit which further comprises at least one probe or an antibody that recognizes an expression product of the genes in Table 2.
  • this kit is the "second kit of the invention”.
  • kits being able to comprise at least one retrotransciptase, or an RNA polymerase or a fluorophore.
  • a preferred embodiment of the third aspect of the invention refers to a kit that also comprises at least one of the reagents selected from the list comprising: retrotranscriptase, an RNA polymerase or a fluorophore.
  • the kit may comprise a mixture of tri-phosphate deoxynucleotides (dNTPs), a mixture of tri-phosphate nucleotides (NTPs), deoxyribonuclease (DNase), ribonuclease inhibitors (RNase), Dithiothreitol (DTT), inorganic pyrophosphatase (PPi) and the necessary buffers for the enzymes provided in the kit.
  • the present invention also relates to the kit where the probes or antibodies are preferably located on a solid support, for example, but not limited to, glass, plastic, tubes, multiwell plates, membranes, or any other known support.
  • a preferred embodiment of the sixth aspect of the invention refers to a kit where the probes or antibodies are preferably located on a solid support.
  • a seventh aspect of the invention relates to the use of the kit of the sixth aspect of the invention to obtain useful data for the prognosis of CNMP stages I or II.
  • data collection may be useful for the administration of adjuvant treatment, for example chemotherapy.
  • adjuvant treatment for example chemotherapy.
  • the use of the first kit of the invention for the evaluation of the need to provide such treatment.
  • An eighth aspect of the invention relates to the use of the kit of the sixth aspect of the invention for obtaining useful data for the classification of the intratumoral immune response of the CNMP of stages I or II.
  • the kit of the present invention can be used to know if there is an intratumoral immune response in the patient.
  • a ninth aspect of the invention relates to the use of the kit of the sixth aspect of the invention to obtain useful data to predict the response to immunotherapy of the stage I or II CNMP.
  • Fig. 1 Shows the probability of ILE in the two main histological subtypes of CNMP.
  • Kaplan-Meier curve showing the probability of ILE of the two main histological subtypes of the CNMP, adenocarcinoma and squamous carcinoma in the development matrix.
  • ILE disease free interval; p, is the probability associated that the differences found in the ILE between the subgroups analyzed are due to chance.
  • Fig. 2. Shows the probability of disease-free interval in stages I and II. .
  • Kaplan-Meier curve showing the probability of ILE for stages I and II of CNMP in the development matrix.
  • ILE disease free interval
  • p is the probability associated that the differences found in the ILE between the subgroups analyzed are due to chance.
  • Fig. 3. It shows the hierarchical grouping of the samples of the development matrix analyzed according to their molecular profile with 3,232 genes.
  • the hierarchical clustering of 84 samples with 3,232 genes is shown (see filtering 3 of example 1) according to the method described in Quackenbush J. Nat Rev Genet. 2001; 2 (6): 418-27.
  • the samples are differentiated according to the histological subtype: continuous line, adenocarcinoma subtype; striped line, squamous subtype; continuous line terminated in * , other CNMP subtypes.
  • "Molecular profile" is defined: as the set of genomic data (in our cases mRNA expression levels) capable of characterizing and identifying a subject or sample.
  • the molecular subtypes found show a clear association with the histological subtypes of the tumors.
  • Kaplan-Meier curve showing the probability of ILE of the two main molecular subtypes of the CNMP found in the development matrix.
  • ILE disease free interval
  • p is the probability associated that the differences found in the ILE between the subgroups analyzed are due to chance.
  • Fig. 5 It shows the hierarchical grouping of the samples of the development matrix analyzed according to their molecular profile with 2,160 genes.
  • Fig. 6 It shows the probability of ILE in the three molecular groups obtained based on their molecular profile with 2,160 genes in the development matrix.
  • Kaplan-Meier curve showing the probability of ILE of the three molecular groups obtained using the list of 2,160 genes and the "k-means" technique.
  • ILE disease free interval; p, is the probability associated that the differences found in the ILE between the analyzed subgroups are due to chance, (x), indicates the number of samples in each of the analyzed groups.
  • Fig. 7 Shows the probability of ILE in the validation matrix samples according to the classification of 3 molecular groups.
  • Kaplan-Meier curve showing the probability of ILE for the validation matrix samples (external series, Roepman et al.) Grouped according to molecular profiles (Group 1, Group 2 and Group 3) previously observed in The development matrix and defined through a predictor of 1,000 genes generated with the application "PAM”.
  • ILE disease free interval; p, is the probability associated that the differences found in the ILE between the analyzed subgroups are due to chance, (x), indicates the number of samples that there are in each of the analyzed groups.
  • Fig. 8. Shows the probability of ILE in the validation matrix samples according to the classification established by the predictor of 50 genes.
  • Kaplan-Meier curve showing the probability of ILE of the two molecular groups obtained in the validation matrix using the 50 gene predictor.
  • ILE disease free interval; p, is the probability associated that the differences found in the ILE between the subgroups analyzed are due to chance, (x) indicates the number of samples in each of the branches of the Kaplan-Meier curve.
  • Fig. 9 Probability of ILE in the validation matrix samples according to the classification established by the predictor of 50 genes independently for stages I and II.
  • Kaplan-Meier curve showing the probability of ILE of the two molecular groups obtained in the validation matrix with the 50 gene predictor generated with the "PAM" application for: A, stage I, and B, stage II.
  • ILE disease free interval; p, is the probability associated that the differences found in the ILE between the subgroups analyzed are due to chance, (x) indicates the number of samples in each of the branches of the Kaplan-Meier curve.
  • Example 1 Obtaining the 50 gene predictor
  • the data collected for the study are divided into clinical data of the patient (age of diagnosis, sex and smoking habit) and histological data of the tumor (histological subtype, tumor size, tumor stage -7- TNM Classification (Kligerman S. American Journal of Roentgenology 2010. 194: 562-573) -, degree of differentiation, keratinization, presence of polymorphonuclear lymphocytes - PMN-, lymph node involvement, k-ras mutations, necrosis, tumor stroma, chronic inflammation, presence of intratumoral lymphocytes -TIL-, location by pulmonary lobes and type of recurrence - regional or distant madness).
  • Tumor samples RNA extraction and purification.
  • CNMP tumors were collected immediately after surgery and frozen and stored at -80 Q C. Histopathological review of the frozen tumors was carried out with the so that all patients included in the study had a tumor representation as a minimum of 70% in the sample used. At the same time, samples of non-tumor pulmonary parenchyma were also collected from these same patients, which were also frozen following the same protocol. RNA from these latter samples was used to create the control sample (a pool of normal tissue RNA). In all cases, the total ribonucleic acid (RNA or RNA) was extracted directly from the frozen samples using Trizol® and a tissue homogenizer.
  • Trizol® Trizol®
  • RNA was measured in Bioanalyzer 2100® using the RIN (or RNA Integrity Number) and only samples with a good RNA quality (RIN> 7.5), were included for the study.
  • the expression profile of the 84 tumors was determined using Agilent® full genome oligonucleotide microarrays (G41 12F) following the protocol provided by the manufacturer. Briefly, double marking was used, with cyanine-5 (Cy5) for each of the 84 tumors included in the study and with cyanine-3 (Cy3) for the control sample, consisting of a "pool" of 42 parenchyma samples not lung tumor.
  • This control sample was introduced in each of the experiments (the same in all of them) in order to identify and correct the technical variations introduced during the experimental phase of the analysis. After this correction (called normalization) the data generated is the ratio between the fluorescence of the tumor and the control sample.
  • Spikelns which are 10 control transcripts synthesized in vitro that derive from the adenovirus E1 A transcriptome, that do not interact with human mRNA and whose initial concentration is known, were included during the stages of screening and hybridization.
  • the "a priori" knowledge of the initial concentration of each of the “Spikelns”, allows us to predict at what level of fluorescence these transcripts should emit once hybridized in the microarray and therefore can be used as quality control of the experimental phase .
  • the microarrays were scanned and quantified using the Agilent® scanner and the Feature Extraction® program (10.7.3) respectively.
  • the Lowess or "Locally Weighted Scatterplot Smoothing” technique was used.
  • ⁇ Cleveland WS Journal of the American statistical Association 1979, 74: 829-836; Cleveland WS, et al. Journal of the American Statistical Association 1988, 83: 596-610.
  • the differentially expressed genes (p-value ⁇ 0.01 and expression difference> 1, 5) were selected and the generated list (1,072 genes) was excluded from the initial list (3,232 genes). Therefore, a list of 2,160 genes (genes shown in Table 2) that are used for the final molecular classification of the 84 tumors is generated.
  • the strategy used for the discovery of the molecular groups consisted in applying first a method of unsupervised analysis, clustering or hierarchical clustering (Fig. 5A), and then an improvement of the molecular groups obtained by means of a second method, method of k-Means (Fig. 5B), which allows to reduce intra-group heterogeneity and increase inter-group variability.
  • the list of 2,160 genes is used to initially construct the molecular classification (which has 3 groups). Once these molecular groups were generated, the molecular classification obtained was evaluated to determine whether or not there was an association with the disease-free interval (ILE) (Fig. 6).
  • ILE disease-free interval
  • the ILE is defined as the time that elapses from the date of surgery until the patient's recurrence is confirmed.
  • the validation matrix includes the expression data of 162 patients diagnosed with the same histological subtypes as those of the invention.
  • validation matrix refers to the set of samples published by Roepman et al used for the validation of molecular classification.
  • Mitrix means the set of expression data obtained in a series of patients using microarrays.
  • a common data matrix has been generated that includes 246 samples (84 of the development matrix + 162 of the validation matrix) each with 17,881 genes.
  • a predictor was obtained through the PAM application (Microarray Prediction Analysis) (Tibshirani R. et al. PNAS 2002; 99 (10): 6567-72) that was evaluated in the validation matrix by studying its association, through the Kaplan-Meier curve, with the ILE.
  • the Cox proportional regression model was used to confirm the prognostic power of our predictor.
  • the forecast classification process requires as a starting point the calculation of a "reference value” for each of the two groups.
  • These "reference values” are obtained from the samples of the patients that make up the so-called “training matrix” or “development matrix” and of which "a priori” their classification is known (as they were with them with the that defined what the group of good and bad prognosis was).
  • each of the reference values will be expressed as a vector of 50 components (one for each of the genes of the invention) and will be calculated as the sum of two subvectors each also expressed with 50 components.
  • the first subvector is common for the two reference values while the second is specific for each of the two reference values to be calculated.
  • the first subvector consists of 50 components, each of which corresponds to the average expression value of one of the 50 genes throughout all the samples that make up the training or development matrix regardless of the group in which they are classified (i.e. the 84 tumors of our matrix).
  • the second subvector will also be defined by 50 components (each of which represents a gene) that will be defined by a "t" statistic that compares for that gene the differences between the first subvector and the average expression value of that gene in the Samples included in the group for which the reference value is to be calculated (either the good prognosis group (29 samples) or the poor prognosis group (55 samples)).
  • the data of the second subvector will be standardized taking into account the variability of expression of each of the 50 genes within the analyzed group and taking into account a convergence value ⁇ that allows to evaluate the predictive power of each of the genes.
  • the distance between the new sample and the "reference value 1" is less than the distance between the new sample and the "reference value 2"
  • the favorable prognosis for the new patient can be determined.
  • the distance between the new sample and the "reference value 1" is greater than the distance between the new sample and "reference value 2”
  • the unfavorable prognosis for the new patient can be determined.
  • factors that correct the result are also introduced, taking into account the variability of expression within the groups and the probability of belong to a certain group taking into account their sample size with respect to the population analyzed. The quantification of distances is measured using the Euclidean distance. 1.2.- RESULTS
  • a first statistical analysis was carried out to verify if there was an association between the most important histopathological variables in the routine management of the CNMP (the histological classification of the tumor, the stage, etc.), with the ILE.
  • HR Group 1 vs. 2 not significant.
  • the present invention demonstrates the usefulness of the method of the invention, as well as the use of the invention.
  • ID Entrez is not indicated or is genes that have no information in the NCBI database and in which the name of the genome oligonucleotide microarray probe has been indicated in the gene symbol complete used (Agilent®, G41 12F).

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Abstract

La présente invention concerne un procédé in vitro de classification du carcinome non microcytique du poumon basé sur l'expression différentielle de 50 gènes. Ces gènes identifient une réponse immunitaire intratumorale. Au moyen du procédé de l'invention, les patients sont différenciés avec un profil d'expression de gènes associés à une réponse immunitaire qui s'associe à un bon pronostic et des patients sans ce profil d'expression qui ont un pronostic moins bon. Cette classification peut être utilisée comme marqueur de pronostic, comme classificateur des tumeurs en fonction de la réponse immunitaire antitumorale ("inmunoscore") ou comme biomarqueur prédicteur de thérapies basées sur le système immunitaire (immunothérapie). La présente invention concerne également un nécessaire qui comprend un ensemble de sondes qui reconnaissent les 50 gènes de l'invention.
PCT/ES2012/070919 2011-12-30 2012-12-28 Procédé de classification du carcinome non microcytique du poumon basé sur l'identification d'une réponse immunitaire intratumorale WO2013098457A1 (fr)

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ES201132151A ES2411833B1 (es) 2011-12-30 2011-12-30 Método de pronóstico del carcinoma no microcítico de pulmón de estadio I o II.
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ES201230250A ES2420079B1 (es) 2012-02-17 2012-02-17 Método de clasificación del carcinoma no microcítico de pulmón basado en la identificación de una respuesta inmune intratumoral.
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116042832A (zh) * 2023-01-30 2023-05-02 南方医科大学南方医院 一种预测非小细胞肺癌免疫治疗获益程度及预后的生物标志物及应用

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2008147205A1 (fr) * 2007-06-01 2008-12-04 Agendia B.V. Signature d'expression génique pronostique pour les patients souffrant du cancer du poumon à cellules non petites
US20090062144A1 (en) 2007-04-03 2009-03-05 Nancy Lan Guo Gene signature for prognosis and diagnosis of lung cancer
WO2010007093A1 (fr) 2008-07-17 2010-01-21 Universität Zu Köln Procédé pour la détection et le pronostic précoces du cancer du poumon
WO2011094483A2 (fr) * 2010-01-29 2011-08-04 H. Lee Moffitt Cancer Center And Research Institute, Inc. Signatures géniques immunitaires dans le cancer

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090062144A1 (en) 2007-04-03 2009-03-05 Nancy Lan Guo Gene signature for prognosis and diagnosis of lung cancer
WO2008147205A1 (fr) * 2007-06-01 2008-12-04 Agendia B.V. Signature d'expression génique pronostique pour les patients souffrant du cancer du poumon à cellules non petites
WO2010007093A1 (fr) 2008-07-17 2010-01-21 Universität Zu Köln Procédé pour la détection et le pronostic précoces du cancer du poumon
WO2011094483A2 (fr) * 2010-01-29 2011-08-04 H. Lee Moffitt Cancer Center And Research Institute, Inc. Signatures géniques immunitaires dans le cancer

Non-Patent Citations (35)

* Cited by examiner, † Cited by third party
Title
AGILENT TECHNOLOGIES: "Agilent SurePrint G3 Human Catalog CGH Microarrays", INTERNET CITATION, 8 January 2009 (2009-01-08), pages 1 - 8, XP002660065, Retrieved from the Internet <URL:http://www.chem.agilent.com/Library/brochures/5990-3368en_lo.pdf> [retrieved on 20110926] *
AGILENT TECHNOLOGIES: "Microarray Ordering Guide Catalog", 26 May 2009 (2009-05-26), USA, pages 1 - 8, XP055062784, Retrieved from the Internet <URL:https://www.usc.es/export/sites/default/gl/investigacion/riaidt/secuenciacion/agilent/descargas/Microarray_Ordering_Guide.pdf> [retrieved on 20130514] *
ASANO ET AL., LEUKEMIA, vol. 25, 2011, pages 1182 - 1188
ASCIERTO ET AL., BREAST CANCER RES TREAT., vol. 131, no. 3, 2012, pages 871 - 80
BENJAMINI Y; HOCHBERG Y, JOURNAL OF THE ROYAL STATISTICAL SOCIETY., 1995
BROUSSAD E.K. ET AL., J. CLIN ONCOL, vol. 29, no. 6, 2011, pages 602 - 603
CHEN HY ET AL., NEW ENGL J MED, vol. 356, no. 1, 2007, pages 11 - 20
CLARK TG., BRITISH JOURNAL OF CANCER, vol. 89, 2003, pages 232 - 238
CLEVELAND WS ET AL., JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, vol. 83, 1988, pages 596 - 610
CLEVELAND WS: "Locally Weighted Scatterplot Smoothing", JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, vol. 74, 1979, pages 829 - 836
GALON ET AL., J TRANSL MED., vol. 10, 3 January 2012 (2012-01-03), pages 1
HAGN ET AL., IMMUNOLOGY AND CELL BIOLOGY, 2 August 2011 (2011-08-02)
HAVELANGE V. ET AL., BLOOD, vol. 118, no. 10, 2011, pages 2827 - 9
KARAPANIAGIOTOU E ET AL., OPEN LUNG CANCER J, vol. 2, 2009, pages 24 - 30
KLIGERMAN S, AMERICAN JOURNAL OF ROENTGENOLOGY, vol. 194, 2010, pages 562 - 573
KLIGERMAN S., AMERICAN JOURNAL OF ROENTGENOLOGY, vol. 194, 2010, pages 562 - 573
LEE JK ET AL., J IMMUNOL., vol. 179, no. 7, 2007, pages 4672 - 8
MARCO MALAVASI ET AL., BLOOD, vol. 118, no. 13, 2011, pages 3470 - 3478
MOOTHA VK ET AL., NAT GEN, 2003
NATIONAL COMPREHENSIVE CANCER NETWORK, 2011
QUACKENBUSH, J. NAT REV GENET., vol. 2, no. 6, 2001, pages 418 - 27
RAPONI M ET AL., CANCER RES, vol. 66, 2006, pages 7466 - 7472
RAZ DJ ET AL., CLIN CANCER RES, vol. 14, no. 17, 2008, pages 5565 - 5570
ROEPMAN P ET AL., CLIN CANCER RES, vol. 15, 2009, pages 284 - 290
ROEPMAN P ET AL: "An immune response enriched 72-gene prognostic profile for early-stage non-small-cell lung cancer", CLINICAL CANCER RESEARCH, THE AMERICAN ASSOCIATION FOR CANCER RESEARCH, US, vol. 15, no. 1, 1 January 2009 (2009-01-01), pages 284 - 290, XP002547977, ISSN: 1078-0432, DOI: 10.1158/1078-0432.CCR-08-1258 *
ROEPMAN P. ET AL., CLIN CANCER RES, vol. 15, 2009, pages 284 - 290
SAEZ ET AL., BLOOD, vol. 118, no. 6, 11 December 2010 (2010-12-11), pages 1560 - 9
SIMON R. ET AL., J CLIN ONCOL, vol. 23, 2005, pages 7332 - 41
SUBRAMANIAN ET AL., PNAS, vol. 102, no. 43, 2005, pages 15545 - 15550
SUBRAMANIAN J. ET AL., J NATL CANCER INST., vol. 102, 2010, pages 1 - 11
TIBSHIRANI R. ET AL., PNAS, vol. 99, no. 10, 2002, pages 6567 - 72
TIBSHIRANI R. ET AL., PNAS., vol. 99, 2002, pages 6567 - 6572
TIBSHIRANI R.: "Diagnosis of multiple cancer types by shrunken centroids of gene expression", PNAS, vol. 99, no. 10, 2002, pages 6567 - 72, XP002988576, DOI: doi:10.1073/pnas.082099299
TRUNG CHU V. ET AL., J. IMMUNOL, vol. 179, 2007, pages 5947 - 5957
ZAO C. ET AL., ONCOGENE, vol. 27, 2008, pages 63 - 75

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116042832A (zh) * 2023-01-30 2023-05-02 南方医科大学南方医院 一种预测非小细胞肺癌免疫治疗获益程度及预后的生物标志物及应用
CN116042832B (zh) * 2023-01-30 2023-11-21 南方医科大学南方医院 一种预测非小细胞肺癌免疫治疗获益程度及预后的生物标志物及应用

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