WO2014072086A1 - Biomarqueurs pour le pronostic du cancer du poumon - Google Patents

Biomarqueurs pour le pronostic du cancer du poumon Download PDF

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Publication number
WO2014072086A1
WO2014072086A1 PCT/EP2013/060809 EP2013060809W WO2014072086A1 WO 2014072086 A1 WO2014072086 A1 WO 2014072086A1 EP 2013060809 W EP2013060809 W EP 2013060809W WO 2014072086 A1 WO2014072086 A1 WO 2014072086A1
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Prior art keywords
biomarker
genes
lung cancer
depicted
identified
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PCT/EP2013/060809
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English (en)
Inventor
Sam ANSARI
Stephan GEBEL
Ignacio GONZALEZ SUAREZ
Julia HOENG
Florian Martin
Manuel Peitsch
Yang Xiang
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Philip Morris Products S.A.
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Publication of WO2014072086A1 publication Critical patent/WO2014072086A1/fr

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    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING 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
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING 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
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/118—Prognosis of disease development
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING 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
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/158—Expression markers

Definitions

  • the present invention relates to biomarkers that can be used to provide a prognosis of an individual's lung cancer and to predict and monitor the outcome of an individual's lung cancer which is or will be under treatment.
  • the invention further provides kits for carrying out said methods.
  • Lung cancer is one of the most common cancers in the world and is a leading cause of cancer death in men and women in the developed world.
  • Diagnosis of lung cancer is still mainly based on chest radiograph and computed tomography (CT scan). Bronchoscopy or CT-guided biopsy may be used to obtain further information and to identify the tumor type.
  • CT scan computed tomography
  • biomarkers that may be used for risk assessment, screening, diagnosis, prognosis, and for selection and monitoring of therapies of lung cancer.
  • Semmens et al, 2005 disclose protein biomarkers that are differentially present in the samples of patients with lung cancer and in the samples of control subjects and can thus be used in diagnosing lung cancer.
  • the measurement of these markers, alone or in combination, in patient samples, is reported to provide information that can be correlated with a probable diagnosis of lung cancer or a negative diagnosis (e. g., normal or disease-free). All the markers are characterized by molecular weight.
  • Gold et al, 201 1 disclose a list of 61 biomarkers that can be used alone or in various combinations to diagnose lung cancer.
  • YIP et al, 2004 disclose a method for qualifying lung carcinoma status in a subject, which comprises analyzing a biological sample from said subject for a diagnostic level of a biomarker protein, which is differentially present in samples of a subject with lung cancer and a normal subject that is free of lung cancer.
  • YIP et al, 2004 provide a list of about 50 preferred biomarkers that may be used in such a method.
  • Sungwhan et al, 2007 disclose an epigenetic marker for lung cancer. Cigarette smoke is a major risk factor for lung cancer however, there is a subset of patients that develop lung cancers despite no history of smoking. Lung cancer in smokers and non-smokers are biologically different, with the former being usually more aggressive and resistant to conventional therapies, which often results in poor outcome and decreased survival.
  • the present invention provides biomarkers or a panel of biomarkers that are predictive for smoking-related Sung cancer development and that can be used to develop tools in order to decrease adverse health effects caused by exposure to tobacco smoke and other tobacco-related products.
  • the present invention provides biomarkers, which were identified based on gene expression patterns that are associated with smoking-related lung cancer development and can be used to provide a prognosis of a cancer or to predict the outcome of a treatment, or both.
  • the present invention relates to a method of providing a prognosis on the development of lung cancer in an individual, said method comprising the steps of i. determining in a sample taken from an individual, whose prognosis on lung cancer is to be provided, a test value for the expression of a biomarker; and
  • biomarker corresponds to at least 2 of the genes identified by GeneBank Accession numbers 204767_s_at (FE 1), 209545_s_at (RIPK2) and 213523_at (CCNE1), optionally, in combination with at least 1 and up to 108 genes, which are different from the above identified genes and are depicted depicted in table 1 , table 2, or both table 1 and table 2.
  • the present invention thus provides a method of providing a prognosis on the development of lung cancer in an individual, said method comprising the steps of i. determining in a sample taken from an individual, whose prognosis on lung cancer is to be provided, a test value of the expression of a biomarker comprising using a composition, comprising at least 2 different isolated nucleic acid molecules each of which comprising a biomarker polynucleotidecorresponding to at least 2 and up to 1 1 1 different genes depicted in table 1 , table 2, or both table 1 and table 2; and ii. comparing the values obtained for each biomarker in the panel with reference values for the biomarkers from lung cancer of a non-smoker; wherein differences in the values indicate a poor prognosis on the development of the lung cancer in the individual.
  • the present invention thus provides a method of providing a prognosis on the development of lung cancer in an individual, said method comprising the steps of i. determining in a sample taken from an individual, whose prognosis on lung cancer is to be provided, a test value of the expression of a biomarker comprising using a composition, comprising at least 2 different isolated nucleic acid molecules each of which comprising a biomarker polynucleotide corresponding to at least 2 of the genes identified by GeneBank Accession numbers 204767_s_at (FEN1 ), 209545_s_at (RIPK2) and 213523_at (CCNE1 ), optionally in combination with at least 1 and up to 108 additional genes which are different from the above identified genes and are depicted in table 1 , table 2, or both table 1 and table 2, and ii.
  • step (i) comparing the values obtained for each of the biomarkers used in step (i) with reference values for the same biomarkers from lung cancer of a non- smoker; wherein differences in the va!ues indicate a poor prognosis on the development of the lung cancer in the individual.
  • the present invention thus provides a method of providing a prognosis on the development of lung cancer in an individual, said method comprising the steps of i. determining in a sample taken from an individual, whose prognosis on lung cancer is to be provided, a test value of the expression of a biomarker comprising using a composition, comprising at least 2 different isolated nucleic acid molecules each of which comprising a biomarker polynucleotide corresponding to the genes identified by GeneBank Accession numbers 204767_s_at (FEN1) and 209545_s_at (RIPK2); or 204767_s_at (FEN1 ) and 213523_at (CCNE1); or 209545_s_at (RIPK2) and 213523_at (CCNE1 ), optionally in combination with at least 1 and up to 108 genes, which are different from the above identified genes and are depicted in table 1 , table 2, or both table 1 and table 2; and
  • the present invention thus provides a method of providing a prognosis on the development of lung cancer in an individual, said method comprising the steps of
  • determining in a sample taken from an individual, whose prognosis on lung cancer is to be provided, a test value of the expression of a biomarker comprising using a composition, comprising at least 2 different isolated nucleic acid molecules each of which comprising a biomarker polynucleotide corresponding to the genes identified by GeneBank Accession numbers 204767_s_at (FEN1), 209545_s_at (RIPK2) and 213523_at (CCNE1), optionally in combination with at least 1 and up to 108 genes, which are different from the above identified genes and are depicted in table 1 , table 2, or both table 1 and table 2; and ii. comparing the values obtained for each biomarker in the panel with reference values for the biomarkers from lung cancer of a non-smoker; wherein differences in the values indicate a poor prognosis on the development of the lung cancer in the individual.
  • At least one of the biomarker genes is a gene depicted in table 3,
  • Differential expression may be determined by way of comparison to a control sample, particularly a control sample obtained from an individual, which is a non-smoker and suffers from lung cancer.
  • differential expression can also be determined by comparison with a reference value, wherein the value is obtained from a non- smoker who has lung cancer or from a population of non-smokers who have lung cancer.
  • the difference in gene expression can be represented by the value of fold change or a logarithm of the value of the fold change in base 2 (herein referred to as log fold change).
  • the difference in expression of the at least two, and up to 111 , biomarkers in the test sample is determined to have changed relative to that in the control sample by a log fold change value of more than 0,35, 0.4, 0.5, 0.6, 0.7 0.8, 0.9, 1.0, 1 ,1 , 1 .2, 1 .3, 1.4, 1.5, 1 .6, 1.7, 1.8, 1.9, 2.0, 2.25, 2.5, 2.75, 3.0, 3.25, 3.5, 3.75, 4.0, 4.25, 4.5, 4.75, or 5.0.
  • the difference in expression of the at least 2 of the genes identified by GeneBank Accession numbers 204767_s_at (FE 1), 209545_s_at (RIPK2) and 213523_at (CCNE1), optionally in combination wit at least 1 and up to 108 genes, which are different from the above identified genes and are depicted in table 1 , table 2, or both table 1 and table 2 in the test sample, is determined to have changed relative to that in the control sample by a log fold change value of more than 0.35, 0.4, 0.5, 0.6, 0.7 0.8, 0.9, 1.0, 1 .1 , 1.2, 1.3, 1.4, 1.5, 1 ,6, 1.7, 1.8, 1.9, 2.0, 2.25, 2.5, 2.75, 3.0, 3.25, 3.5, 3.75, 4.0, 4.25, 4.5, 4.75, or 5.0.
  • the sample is obtained from the respiratory system, such as but not limited to lung cells.
  • the genes representing the biomarkers are differentially expressed in lung adenocarcinomas from smokers when compared to adenocarcinomas from non-smokers and are involved in one or more of the following networks.
  • the present invention relates to a method of any one of the preceding embodiments, comprising
  • control individual is a non-smoker suffering from lung cancer and wherein differences between the test values and the reference values indicate a prognosis on the outcome of the cancer treatment.
  • the present invention relates to a method of any one of the preceding embodiments, comprising
  • step (i) determining in a biological sample of a control individual a reference value for the expression of each of the same biomarker genes used in step (i); and iii. comparing the values obtained for each said biomarker genes with the reference value; wherein said control individual is a non-smoker suffering from lung cancer and wherein differences between the test values and the reference values indicate a prognosis on the outcome of the cancer treatment.
  • the present invention relates to a method of any one of the preceding embodiments, comprising
  • determining a reference value in a sample taken from a non-smoker suffering from lung cancer and/or a smoker suffering from lung cancer comprising using a composition comprising at least 2 different isolated nucleic acid molecules each of which comprising a biomarker polynucleotide corresponding to the genes identified in section i); andcomparing the values obtained for each said biomarker genes with the reference value; wherein said control individual is a non-smoker suffering from lung cancer and wherein differences between the test values and the reference values indicate a prognosis on the outcome of the cancer treatment.
  • the present invention relates to a method of any one of the preceding embodiments, comprising
  • determining a reference value in a sample taken from a non-smoker suffering from lung cancer and/or a smoker suffering from lung cancer comprising using a composition comprising at least 2 different isolated nucleic acid molecules each of which comprising a biomarker polynucleotide corresponding to the genes identified in section i); andcomparing the values obtained for each said biomarker genes with the reference value; wherein said control individual is a non-smoker suffering from lung cancer and wherein differences between the test values and the reference values indicate a prognosis on the outcome of the cancer treatment.
  • the difference between or the similarity in the test values and the reference values may be used to forecast or classify the subject into a poor survival group or a good survival group.
  • the invention further provides a method for predicting or monitoring the outcome of a lung cancer treatment in an individual suffering from lung cancer comprising
  • determining a reference value in a sample taken from a non-smoker suffering from lung cancer and/or a smoker suffering from lung cancer comprising using a composition comprising at least 2 different isolated nucleic acid molecules each of which comprising a biomarker polynucleotide corresponding to the genes identified in section i); andand comparing the values obtained for each said biomarker genes with the reference value; wherein said control individual is a non-smoker suffering from lung cancer, wherein at least one of the biomarker genes is a gene depicted in table 3 and wherein differences between the test values and the reference values indicate the probability of said individual's lung cancer sharing one or more treatment outcomes of smoking- related lung cancer.
  • the invention further provides a method for predicting or monitoring the outcome of a lung cancer treatment in an individual suffering from lung cancer comprising
  • the difference between a test value and a reference value which indicates the development of the lung cancer or provides a prognosis is a log fold change value of more than 0.35, 0.4, 0.5, 0.6, 0.7 0.8, 0.9, 1.0, 1.1 , 1 .2, 13, 14, 15, 1 ,6, 1 ,7, 18, 1.9, 2.0, 2.25, 2.5, 2.75, 3.0, 3.25, 3.5, 3.75, 4.0, 4.25, or 4.5.
  • a positive log fold change value of between 0.35 and 5.0 indicates a poor prognosis on the development of the lung cancer in the tested individual, and vice versa.
  • a negative log fold change value of between 0.35 and 5.0 also indicates a poor prognosis on the development of the lung cancer in the tested individual, and vice versa.
  • the log fold change value of each of the biomarker genes in table 1 and 2 can be used as exemplary threshold for each of the biomarker gene.
  • samples used in the method according to the invention as described herein may be blood, serum, plasma, sputum, saliva, tissue particularly lung tissue, obtained through biopsy, bronchia brushings, exhaled breath, or urine.
  • a biomarker or a panel of biomarkers may be used in the method according to the invention as described herein, which is (a) selected from the group of biomarker genes depicted in table 1 identified by GeneBank Accession number 200887_s_at (STAT1 ), 204785_x_at (IFNAR2); 201762_s_at (PSME2), 204279_at (PSMB9), 203915_at (CXCL9), 204533_at (CXCL10), 227458_at (CD274), 207375_s_at (IL15), 207375_s_at (IL15RA), 205207_at (IL6), 204655_at (CCL5), 204103_at (CCL4), 207072_at (IL18RAP), and 205291_at (IL2RB); or
  • a biomarker or a panel may be used in the method according to the invention as described herein of at least 2 of the genes identified by GeneBank Accession numbers 204767_s_at (FEN1), 209545_s_at (RIPK2) and 213523_at (CCNE1 ), optionally in combination with at least 1 biomarker gene, which is
  • a biomarker or a panel may be used in the method according to the invention as described herein of the genes identified by GeneBank Accession numbers 204767_s_at (FEN1) and 209545_s_at (RIPK2); or 204767_s_at (FEN1) and 2 3523_at (CCNE1 ); or 209545_s_at (R1PK2) and 213523_at (CCNE1), optionally in combination with at least 1 biomarker gene, which is
  • a biomarker or a panel may be used in the method according to the invention as described herein of the genes identified by GeneBank Accession numbers 204767_s_at (FEN1), 209545_s_at (RIPK2) and 213523_at (CCNE1 ), optionally in combination with at least 1 biomarker gene, which is
  • At least one of the biomarker genes in the above identified panel of biomarkers is a gene from table 3.
  • Fragments of the above identified genes or complementary sequences of said genes, particularly sequences having 80%, 85%, 90%, 95%, 96%, 97%, 98%, 99% sequence homology with said gene sequences may also be used within the method according to the invention as described herein in the various embodiments.
  • biomarker genes identified in section a) above are up-regulated in lung tumors in smokers and are involved in cell-to-cell signalling and the modulation of the immune response.
  • the overall effect of this group of genes is to promote immune evasion of the tumor.
  • biomarker genes identified in section b) above are up-regulated in lung tumors in smokers.
  • the overall effect of these genes is to promote tumor growth by up- regulating processes involved in cell proliferation: DNA replication, cell cycle progression, mitosis, as well the repair of DNA damage.
  • biomarker genes identified in section c) above are up-regulated in lung tumors in smokers, with the exception of SORT1 , which is down-regulated.
  • the overall effect is to promote tumor cell survival and protect tumor cells from the activation of apoptosis and other cell death pathways.
  • At least one of the biomarker genes selected from the group of genes identified by GeneBank Accession numbers 204767_s_at (FEN1), 209545_s_at (RIPK2) and 213523_at (CCNE1 ) may be used in the method according to the invention as described herein.
  • at least two of the biomarker genes selected from the group of genes identified by GeneBank Accession numbers 204767_s_at (FEN1), 209545_s_at (RIPK2) and 213523_at (CCNE1 ) may be used in the method according to the invention as described herein.
  • biomarker genes identified by GeneBank Accession numbers 204767_s_at (FEN1), 209545_s_at (RIPK2) and 213523_at (CCNE1) may be used in the method according to the invention as described herein.
  • the above biomarkers may optionally be used in combination with at least 1 and up to 108 genes, which are different from the above identified genes and are depicted in table 1 , table 2, or both table 1 and table 2.
  • At least one of the biomarker genes selected from the genes identified by GeneBank Accession numbers 204767_s_at (FEN1 ), 209545_s_at (RIPK2) and 213523_at (CCNE1 ) may optionally be used in combination with at least one of the biomarker genes depicted in table 1 , table 2 and/or table 3 in the method according to the invention as described herein.
  • At least two of the biomarker genes identified by GeneBank Accession numbers 204767_s_at (FEN1 ), 209545_s_at (RIPK2) and 213523_at (CCNE1 ) may optionally be used in combination with at least one of the biomarker genes depicted in table 1 , table 2 and/or table 3 in the method according to the invention as described herein.
  • the three biomarker genes identified by GeneBank Accession numbers 204767_s_at (FEN1), 209545_s_at (RIPK2) and 213523_at (CCNE1) may optionally be used in combination with at least one of the biomarker genes depicted in table 1 , table 2 and/or table 3 in the method according to the invention as described herein.
  • a polynucleotide or a variant thereof may be used in any one of the methods of the invention described herein in the various embodiments, which polynucleotide is complementary to a target gene as depicted in table 1 , table 2, or both table 1 and table 2, and is used as a molecular probe in a hybridization reaction or as a molecular primer in a nucleic acid extension reaction, for the determination of the target and reference value.
  • at least one of the polynucleotides or a variant thereof is complementary to a biomarker gene from table 3.
  • one or more detectably labeled antibodies may be used in any one of the methods of the invention described herein in the various embodiments for the determination of the target and reference value, which antibodies are capable of identifying biomarker gene products encoded by one or more biomarker genes depicted in table 1 , table 2, or both table 1 and table 2, or by conserved variants or peptide fragments thereof.
  • at least one of the detectably labeled antibodies is capable of identifying a biomarker gene product encoded by one or more biomarker genes depicted in table 3.
  • determination of biomarker values is accomplished by performing an in-vitro assay, particularly an in-vitro assay selected from the group consisting of an antibody-based assay such as an immunoassay, a histological or cytological assay, an expression level assay such as an RNA expression level assay and an aptamer-based assay.
  • the biomarker value may be determined by performing
  • the biomarker value is determined by performing mass spectrometry.
  • an enzyme-linked immunosorbent assay may be performed for determining biomarker values.
  • a microarray-based immunohistochemical analysis may be performed for determining biomarker values.
  • surface enhanced laser desorption/ionization may be performed for determining biomarker values.
  • data analysis is performed within a method according to any one of the preceding embodiments by one or more computer program(s).
  • the present invention provides a panel of at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, at least 40, at least 45, at least 50, at least 60, at least 70, at least 80, at least 90, at least 100, or of all 1 11 biomarker genes selected from the group of biomarker genes provided in table 1 , table 2, or both table 1 and table 2, for use in a method according to any one of the preceding embodiments.
  • at least one of the biomarker genes in this panel is a gene from table 3.
  • the present invention provides a panel of (a) at least 2, at least 3, at least 4, at least 5 biomarker genes selected from the group of markers depicted in table 3; (b) and at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, at least 40, at least 45, at least 50 biomarker genes selected from the group of markers depicted in table 1 , table 2, or both table 1 and table 2 for use in a method according to the invention as described in any one of the preceding embodiments.
  • a panel of at least 10 biomarker genes is provided selected from the group of markers depicted in table 1 , table 2, or both table 1 and table 2 for use in a method according to any one of the preceding embodiments.
  • at least one of the biomarker genes in this panel is a gene from table 3.
  • a panel of at least 50 biomarker genes is provided selected from the group of markers depicted in table 1 , table 2, or both table 1 and table 2 for use in a method according to any one of the preceding embodiments.
  • at least one of the biomarker genes in this panel is a gene from table 3.
  • the panel comprises a polynucleotide or a variant thereof, which is complementary to a target gene as depicted in table 1 , table 2, or both table 1 and table 2 and can be used as a hybridization probe or a primer.
  • at least one of the polynucleotides or a variants thereof is complementary to a biomarker gene from table 3.
  • the present invention provides a kit for predicting a prognosis on the outcome of cancer treatment in an individual suffering from lung cancer or for predicting or monitoring the outcome of a lung cancer treatment in such an individual, comprising a reagent for detecting differential expression of a panel of at least 2 and up to 50, particularly up to 111 different biomarkers selected from the biomarkers depicted in table 1 , table 2, or both table 1 and table 2.
  • a reagent for detecting differential expression of a panel of at least 2 and up to 50 particularly up to 111 different biomarkers selected from the biomarkers depicted in table 1 , table 2, or both table 1 and table 2.
  • at least one of the biomarker genes in this panel is a gene from table 3.
  • the present invention provides a kit for predicting a prognosis on the outcome of cancer treatment in an individual suffering from lung cancer or for predicting or monitoring the outcome of a lung cancer treatment in such an individual, comprising a device or reagent for detecting differential expression of biomarkes comprising using a composition, in particular a panel of at least 2 of the genes identified by GeneBank Accession numbers 204767_s_at (FEM1), 209545_s_at (RIPK2) and 213523_at (CCNE1 ), optionally in combination with at least 1 and up to 108 genes, which are different from the above identified genes and are depicted in table 1 , table 2, or both table 1 and table 2.
  • a composition in particular a panel of at least 2 of the genes identified by GeneBank Accession numbers 204767_s_at (FEM1), 209545_s_at (RIPK2) and 213523_at (CCNE1 ), optionally in combination with at least 1 and up to 108 genes, which are different from the above identified genes and are
  • the present invention provides a kit for predicting a prognosis on the outcome of cancer treatment in an individual suffering from lung cancer or for predicting or monitoring the outcome of a lung cancer treatment in such an individual, comprising a device or reagent for detecting differential expression of a panel of the genes identified by GeneBank Accession numbers 204767_s_at (FEN1) and 209545_s_at (RIPK2); or 204767_s_at (FEN1 ) and 213523_at (CCNE1); or 209545_s_at (RIPK2) and 213523_at (CCNE1), optionally in combination with at least 1 and up to 108 genes, which are different from the above identified genes and are depicted in table 1 , table 2, or both table 1 and table 2.
  • the present invention provides a kit for predicting a prognosis on the outcome of cancer treatment in an individual suffering from lung cancer or for predicting or monitoring the outcome of a lung cancer treatment in such an individual, comprising a device or reagent for detecting differential expression of a panel of genes identified by GeneBank Accession numbers 204767_s_at (FEN1), 209545_s_at (RIPK2) and 213523_at (CCNE1 ), optionally in combination with at least 1 and up to 108 genes, which are different from the above identified genes and are depicted in table 1 , table 2, or both table 1 and table 2.
  • FEN1 GeneBank Accession numbers 204767_s_at
  • RIPK2 209545_s_at
  • CCNE1 213523_at
  • the present invention relates to a panel of biomarkers selected from the biomarker genes depicted in table 1 , table 2, or both table 1 and table 2 comprising those biomarker genes from said tables which are identified by GeneBank Accession identifiers and to the use of said biomarkers or panel of biomarkers in a method or a kit according to the invention and described herein in the various embodiments.
  • at least one of the biomarker genes in this panel is a gene from table 3.
  • the present invention relates to a composition, particularly a panel of genes, comprising at least 2 different isolated nucleic acid molecules each of which comprising a biomarker polynucleotide that corresponds to a different gene identified by GeneBank Accession numbers 204767_s_at (FEN1), 209545_s_at (RIPK2) and 213523_at (CCNE1), optionally further comprising at least 1 and up to 108 different nucleic acid molecules each of which comprises a biomarker polynucleotides corresponding to genes depicted in table 1 , table 2, or both table 1 and table 2 and to the use of said nucleic acid molecules in a method or a kit according to the invention and described herein in the various embodiments.
  • a composition particularly a panel of genes, comprising at least 2 different isolated nucleic acid molecules each of which comprising a biomarker polynucleotide that corresponds to a different gene identified by GeneBank Accession numbers 204767_s_at (FEN1), 2095
  • the present invention relates to a composition, particularly a panel of genes, comprising at least 2 different isolated nucleic acid molecules each of which comprising a biomarker polynucleotide that corresponds to a different gene identified by GeneBank Accession numbers 204767_s_at (FEN1) and 209545_s_at (RIPK2); or 204767_s_at (FEN1) and 213523_at (CCNE1); or 209545_s_at (RIPK2) and 213523_at (CCNE1), optionally in combination with at ieast 1 and up to 108 genes, which are different from the above identified genes and are depicted in table 1 , table 2, or both table 1 and table 2 and to the use of said biomarkers or a composition, particularly a panel of biomarkers in a method or a kit according to the invention and described herein in the various embodiments.
  • a composition particularly a panel of genes, comprising at least 2 different isolated nucleic acid molecules each of which comprising a biomarker poly
  • the present invention relates to a composition, particularly a panel of genes, comprising at Ieast 2 different isolated nucleic acid molecules each of which comprising a biomarker polynucleotide that corresponds to a different gene identified by GeneBank Accession numbers 204767_s_at (FEN1 ), 209545_s_at (RIPK2) and 213523_at (CCNE1) optionally in combination with at Ieast 1 and up to 108 genes, which are different from the above identified genes and are depicted in table 1 , table 2, or both table 1 and table 2 and to the use of said biomarkers or a composition, particularly a panel of biomarkers in a method or a kit according to the invention and described herein in the various embodiments.
  • a composition particularly a panel of genes, comprising at Ieast 2 different isolated nucleic acid molecules each of which comprising a biomarker polynucleotide that corresponds to a different gene identified by GeneBank Accession numbers 204767_s_at (FEN1 ), 20
  • the present invention relates to a composition, particularly a panel of genes, comprising comprising genes
  • At least one of the biomarker genes in this composition, particularly this panel is a gene from table 3.
  • the present invention relates to a composition, particularly a panel of genes, comprising at least 2 different isolated nucleic acid molecules each of which comprising a biomarker polynucleotide that corresponds to a different gene comprising genes identified by GeneBank Accession numbers 204767_s_at (FEN1 ), 209545_s_at (RIPK2) and 213523_at (CCNE1 ).
  • the present invention relates to a composition, particularly a panel of genes, comprising at least 2 different isolated nucleic acid molecules each of which comprising a biomarker polynucleotide that corresponds to a different gene comprising genes identified by GeneBank Accession numbers 204767_s_at (FEN1 ) and 209545_s_at (RIPK2).
  • the present invention relates to a composition, particularly a panel of genes, comprising at least 2 different isolated nucleic acid molecules each of which comprising a biomarker polynucleotide that corresponds to a different gene comprising genes identified by GeneBank Accession numbers 204767_s_at (FEN1) and 213523_at (CCNE1 ).
  • the present invention relates to a composition, particularly a panel of genes, comprising at least 2 different isolated nucleic acid molecules each of which comprising a biomarker polynucleotide that corresponds to a different gene comprising genes identified by GeneBank Accession numbers 209545_s_at (RIPK2) and 2 3523_at (CCNE1),
  • the present invention relates to a composition, particularly a panel of genes, comprising at least 2 different isolated nucleic acid molecules each of which comprising a biomarker polynucleotide that corresponds to a different gene comprising genes identified by GeneBank Accession numbers 204767_s_at (FEN1), 209545_s_at (RIPK2) and 213523_at (CCNE1 ) optionally in combination with at least one and up to 108 genes, which are different from the above identified genes and which are depicted in table 1 , table 2, or both table 1 and table 2,
  • the present invention relates to a composition, particularly a panel of genes, comprising at least 2 different isolated nucleic acid molecules each of which comprising a biomarker polynucleotide that corresponds to a different gene comprising genes identified by GeneBank Accession numbers 204767_s_at (FEN1), 209545_s_at (RIPK2) and 213523_at (CCNE1), optionally in combination with at least one and up to 108 genes, which are different from the above identified genes and which are depicted in table 1 , table 2, and/or table 3.
  • FEN1 GeneBank Accession numbers 204767_s_at
  • RIPK2 209545_s_at
  • CCNE1 213523_at
  • the present invention relates to a composition, particularly a panel of genes, comprising at least 2 different isolated nucleic acid molecules each of which comprising a biomarker polynucleotide that corresponds to a different gene of at least 2 of the biomarker genes comprising genes identified by GeneBank Accession numbers 204767_s_at (FEW), 209545_s_at (RIPK2) and 2 3523_at (CCNE1).
  • the present invention relates to a composition, particularly a panel of genes, comprising at least 2 different isolated nucleic acid molecules each of which comprising a biomarker polynucleotide that corresponds to a different gene of at least 2 of the biomarker genes comprising genes identified by GeneBank Accession numbers 204767_s_at (FEN1), 209545_s_at (RIPK2) and 213523_at (CCNE1), optionally in combination with at least one and up to 108 genes, which are different from the above identified genes and are depicted in table 1 , table 2, or both table 1 and table 2.
  • FEN1 GeneBank Accession numbers 204767_s_at
  • RIPK2 209545_s_at
  • CCNE1 213523_at
  • the present invention relates to a composition, particularly a panel of genes, comprising at least 2 different isolated nucleic acid molecules each of which comprising a biomarker polynucleotide that corresponds to a different gene of at least 2 of the biomarker genes comprising genes identified by GeneBank Accession numbers 204767_s_at (FEN1), 209545_s_at (RIPK2) and 213523_at (CCNE1), optionally in combination with at least one and up to 108 genes, which are different from the above identified genes and are depicted in table 1 , table 2, and/or table 3.
  • FEN1 GeneBank Accession numbers 204767_s_at
  • RIPK2 209545_s_at
  • CCNE1 213523_at
  • the present invention relates to a composition, particularly a panel of genes, comprising at least 2 different isolated nucleic acid molecules each of which comprising a biomarker polynucleotide that corresponds to a different gene of the biomarker genes comprising genes identified by GeneBank Accession numbers 204767_s_at (FEN1) and 209545_s_at (RIPK2), or 204767_s_at (FEN1 ) and 213523_at (CCNE1), or 209545_s_at (RIPK2) and 2 3523_at (CCNE1 ), optionally in combination with at least one of the biomarker genes
  • composition can be a mixtue of nucleic acid molecules in e.g. a solution or a microarray, wherein the nucleic acid molecule may be immobilized on a substrate.
  • a composition may be a panel of genes.
  • Fragments of the above identified genes or complementary sequences of said genes may also be used within the composition, particularly the panel of biomarkers according to the invention as described herein in the various embodiments.
  • the present invention provides biomarkers or a combination of biomarkers that are predictive for smoking-related lung cancer development and that can be used to develop tools for monitoring adverse health effects caused by exposure to tobacco smoke and other tobacco-related products.
  • biomarkers were identified based on gene expression patterns that can detect smoking-related !ung cancer development.
  • the present invention provides biomarkers that can be used to monitor the progress of a treatment or predict the outcome of a treatment, in an individual patient.
  • the present invention provides a method for predicting or assessing prognosis on the outcome of cancer treatment in an individual suffering from lung cancer, said method, comprising
  • determining a reference value in a sample taken from a non-smoker suffering from lung cancer and/or a smoker suffering from lung cancer comprising using a composition comprising at least 2 different isolated nucleic acid molecules each of which comprising a biomarker polynucleotide corresponding to the genes identified in section i); andd comparing the values obtained for each said biomarker genes with the reference value; wherein said control individual is a non-smoker suffering from lung cancer and wherein differences between the test values and the reference values indicate a prognosis on the outcome of cancer treatment.
  • the biomarker genes depicted in table 1 are genes which have been found to be up- regulated in lung cancer cells of smokers, whereas the genes in table 2 are down- regulated.
  • a high level of expression of a biomarker gene of table 1 relative to a reference level determined in a control individual, who is a non-smoker suffering from lung cancer indicates a poor prognosis for the outcome of cancer treatment and thus a decreased survival duration relative to the control; whereas a lower level of expression of a biomarker gene, which is close to or below the reference level indicates an improved prognosis for the outcome of cancer treatment, which means a survival duration similar to or increased relative the control.
  • a poor prognosis correlates with a low level of expression as compared to the reference level and an improved prognosis with an expression level which is similar to or above the reference level.
  • the reference level of a biomarker can be established from cells from characterized cell lines, or cell samples from a non-smoker who has lung adenocarcinoma or a population of non-smokers who have lung adenocarcinoma.
  • the present invention provides a method for monitoring the progress of a lung cancer treatment in an individual, said method comprising determining at suitable time intervals before, during, or after lung cancer therapy, particularly at different time points during the treatment, in a sample taken from said individual differential expression of a composition, particularly a panel of at least 2 and up to 1 1 1 different biomarkers selected from the biomarkers depicted in Table 1 , Table 2, or both Table 1 and Table 2.
  • At least one of the biomarker genes in the composition, particularly the panel is a gene from table 3.
  • said method comprises
  • the method of the invention comprises measuring at suitable time intervals before, during, or after lung cancer therapy, the amount of biomarker gene product. Any change or absence of change in the amount of the biomarker gene product can be identified and correlated with the effect of the treatment on the subject.
  • the method comprises determining the levels of biomarker gene product levels at different time points and to compare these values with a reference level. The observed changes in the differences between the test values and the reference values over time can then be correlated with the disease course, treatment outcome or overall survival.
  • the Matthews Correlation Coefficient (MCC) for the prediction of the smoking status ranges between 0.2 and 1 , particularly between 0.3 and 1 , more particularly between 0.37 and 1.
  • Detection of the protein biomarkers described herein in a test sample may be performed in a variety of ways well known to those skilled in the art.
  • the methods of the invention rely on the detection of the presence or absence of biomarker gene expression, or the qualitative or quantitative assessment of either over- or under-expression of biomarker gene in a population of test cells relative to a standard.
  • Such methods utilize reagents such as biomarker polynucleotides and biomarker antibodies as described herein.
  • the level of expression of a biomarker gene may be determined by measuring the amount of biomarker messenger RNA, for example, by DNA-DNA hybridization, RNA-DNA hybridization, reverse transcription-polymerase chain reaction (PGR), or real time quantitative PGR; followed by comparing the results to a reference based on samples from clinically-characterized patients and/or cell lines of a known genotype/phenotype.
  • PGR reverse transcription-polymerase chain reaction
  • hybridization assays can be performed.
  • these techniques find application in microarray-based assays that can be used to detect and quantify the amount of biomarker gene transcript using cDNA- or oligonucleotide-based arrays.
  • icroarray technology allows multiple biomarker gene transcripts and/or samples from different subjects to be analyzed in one reaction.
  • mRNA isolated from a sample is converted into labeled nucleic acids by reverse transcription and optionally in vitro transcription (cDNAs or cRNAs labeled with, for example, Cy3 or Cy5 dyes) and hybridized in parallel to probes present on an array.
  • Standard Northern analyses can be performed if a sufficient quantity of the test cells can be obtained. Utilizing such techniques, quantitative as well as size related differences between biomarker transcripts can also be detected.
  • High-throughput, massively parallel DNA sequencing techniques may also be applied to measure the level of expression of a biomarker gene, e.g. sequencing with bridge amplification (lllumina), pyrosequencing (Roche Diagnostics), ligation-based methods, ion torrent technology ⁇ Life Sciences) and single-molecule sequencing (Pacific Bio). Many such methods are well known in the art and are automated in commercially available sequencing machines.
  • biomarker polynucleotides or variants thereof which can be used, for example, as hybridization probes or primers ("biomarker probes” or “biomarker primers”) to detect or amplify nucleic acids encoding a biomarker polypeptide, particularly a biomarker polypeptide encoded by a biomarker gene or polynucleotide selected from the group depicted in table 1 , table 2, or both table 1 and table 2.
  • Nucleic acid molecules comprising nucleic acid sequences encoding the biomarker polypeptides or proteins of the invention, or genomic nucleic acid sequences from the biomarker genes (e.g., intron sequences, 5' and 3' untranslated sequences), or their complements thereof (i.e. , antisense polynucleotides), are collectively referred to as "biomarker genes", “biomarker polynucleotides” or “biomarker nucleic acid sequences” of the invention.
  • biomarker polynucleotides or variants thereof which can be used, for example, as hybridization probes or primers ("biomarker probes” or “biomarker primers") to detect or amplify nucleic acids encoding a polypeptide of the invention.
  • biomarker gene product thus encompasses both mRNA as well as translated polypeptide as a gene product of a biomarker,
  • the isolated biomarker polynucleotide according to the invention may comprise flanking sequences (i.e., sequences located at the 5' or 3' ends of the nucleic acid), which naturally flank the nucleic acid sequence in the genomic DNA of the organism from which the nucleic acid is derived.
  • flanking sequences i.e., sequences located at the 5' or 3' ends of the nucleic acid
  • an isolated polynucleotide does not include an isolated chromosome, and does not include the poly(A) tail of an mRNA, if present.
  • the isolated biomarker polynucleotide can comprise less than about 5 kb, 4 kb, 3 kb, 2 kb, 1 kb, 0.5 kb or 0.1 kb of nucleotide sequences which naturally flank the coding sequence in genomic DNA of the cell from which the nucleic acid is derived.
  • the isolated biomarker polynucleotide is about 10-20, 21-50, 51 -100, 101-200, 201-400, 401-750, 751 -1000, 1001-1500 bases in length.
  • the biomarker polynucleotides of the invention are used as molecular probes in hybridization reactions or as molecular primers in nucleic acid extension reactions as described herein.
  • the biomarker polynucleotides may be referred to as biomarker probes and biomarker primers, respectively, and the biomarker polynucleotides present in a sample which are to be detected and/or quantified are referred to as biomarker polynucleotides.
  • Two biomarker primers are commonly used in DNA amplification reactions and they are referred to as biomarker forward primer and biomarker reverse primer depending on their 5' to 3' orientation relative to the direction of transcription.
  • a biomarker probe or a biomarker primer is typically an oligonucleotide which binds through complementary base pairing to a subsequence of a biomarker polynucleotide.
  • the biomarker probe may be, for example, a DNA fragment prepared by amplification methods such as by PGR or it may be chemically synthesized. A double stranded fragment may then be obtained, if desired, by annealing the chemically synthesized single strands together under appropriate conditions or by synthesizing the complementary strand using DNA polymerase with an appropriate primer.
  • a nucleic acid probe is complementary to a target nucleic acid when it will anneal only to a single desired position on that target nucleic acid under proper annealing conditions which depend, for example, upon a probe's length, base composition, and the number of mismatches and their position on the probe, and must often be determined empirically. Such conditions can be determined by those of skill in the art.
  • biomarkers may be detected in the test sample by gene expression profiling.
  • mRNA is prepared from a sample and mRNA expression levels are measured by reverse transcription quantitative polymerase chain reaction (RT-PCR followed with qPCR).
  • RT-PCR is used to create a cDNA from the corresponding mRNA.
  • the cDNA may be used in a qPCR assay to produce fluorescence as the DNA amplification process progresses. By comparison to a standard curve, qPCR can produce an absolute measurement such as number of copies of mRNA per cell.
  • Northern blots, microarrays, Invader assays, and RT- PCR combined with capillary electrophoresis may be used to measure expression levels of mRNA in a sample. Further details are provided, for example, in "Gene Expression Profiling: Methods and Protocols", Richard A. Shimkets, editor, Humana Press, 2004 and US patent application 20100070191.
  • detection of the biomarkers described herein may also be accomplished by an immunoassay procedure.
  • the immunoassay typically includes contacting a test sample with an antibody that specifically binds to or otherwise recognizes a biomarker, and detecting the presence of the antibody bio marker complex in the sample.
  • the immunoassay procedure may be selected from a wide variety of immunoassay procedures known to those skilled in the art such as, for example, competitive or non-competitive enzyme-based immunoassays, enzyme-linked immunosorbent assays (ELISA), radioimmunoassay (RIA), and Western blots, etc.
  • multiplex assays may be used, including antibody arrays, wherein several desired antibodies are placed on a support, such as a glass bead or plate, and reacted or otherwise contacted with the test sample.
  • Antibodies used in these assays may be monoclonal or polyclonal, and may be of any type such as IgG, IgM, IgA, IgD and IgE. Monoclonal antibodies may be used to bind to a specific epitope offered by the biomarker molecule, and therefore may provide a more specific and accurate result. Antibodies may be produced by immunizing animals such as rats, mice, and rabbits. The antigen used for immunization may be isolated from the samples or synthesized by recombinant protein technology.
  • the present invention also provides "biomarker antibodies” including polyclonal, monoclonal, or recombinant antibodies, and fragments and variants thereof, that immunospecifically binds the respective biomarker proteins or polypeptides encoded by the genes or cDNAs (including polypeptides encoded by mRNA splice variants) as listed in tables 1 and 2.
  • Various chemical or biochemical derivatives of the antibodies or antibody fragments of the present invention can be produced using known methods.
  • One type of derivative which is diagnostically useful as an immunoconjugate comprising an antibody molecule, or an antigen-binding fragment thereof, to which is conjugated a detectable label.
  • the biomarker antibody is not labeled but in the course of an assay, it becomes indirectly labeled by binding to or being bound by another molecule that is labeled.
  • the invention encompasses molecular complexes comprising a biomarker antibody and a label, as well as immunocomplexes comprising a biomarker polypeptide, a biomarker antibody, and immunocomplexes comprising a biomarker polypeptide, a biomarker antibody, and a label.
  • detectable substances include various enzymes, prosthetic groups, fluorescent materials, luminescent materials, bioluminescent materials, and radioactive materials.
  • suitable enzymes include horseradish peroxidase, alkaline phosphatase, ⁇ -galactosidase, or acetylcholinesterase;
  • suitable prosthetic group complexes include streptavidin/biotin and avidin/biotin;
  • suitable fluorescent materials include umbelliferones, fluoresceins, fluorescein isothiocyanate, rhodamtnes, dichlorotriazinylamine fluorescein, dansyl chloride, phycoerythrins, Alexa Fluor 647, Alexa Fluor 680, DilC ig (3), Rhodamine Red-X, Alexa Fluor 660, Alexa Fluor 546, Texas Red, YOYO-1 + DNA, tetramethylrhodamine, Alexa Fluor 594, BODIPY FL, Alexa Fluor
  • EIA enzyme immunoassay
  • ELISA enzyme-linked immunosorbent assay
  • the enzyme either conjugated to the antibody or to a binding partner for the antibody, when later exposed to an appropriate substrate, will react with the substrate in such a manner as to produce a chemical moiety which can be detected, for example, by spectrophotometric, or fluorimetric means.
  • the biological sample may be brought in contact with and immobilized onto a solid phase support or carrier such as nitrocellulose, or other solid support which is capable of immobilizing cells, cell particles or soluble proteins.
  • a solid phase support or carrier such as nitrocellulose, or other solid support which is capable of immobilizing cells, cell particles or soluble proteins.
  • the support may then be washed with suitable buffers followed by treatment with the detectably labeled biomarker antibody.
  • the solid phase support may then be washed with the buffer a second time to remove unbound antibody.
  • the amount of bound label on solid support may then be detected by conventional means.
  • a well known example of such a technique is Western blotting.
  • the present invention provides compositions comprising labeled biomarker polynucleotides, or labeled biomarker antibodies to the biomarker proteins or polypeptides or labeled biomarker polynucleotides and labeled biomarker antibodies to the biomarker proteins or polypeptides according to the invention as described herein.
  • the biomarkers described herein may also be detected and quantified by mass spectrometry.
  • Mass spectrometry is a method that employs a mass spectrometer to detect ionized protein markers or ionized peptides as digested from the protein markers by measuring the mass-to-charge ratio (m/z).
  • Biomarkers (along with other proteins) with stable heavy isotopes (deuterium, carbon-13, nitrogen-15, and oxygen- 18) can be used in quantitative proteomics. These are either incorporated metabolically in sample cells cultured briefly in vitro, or directly in samples by chemical or enzymatic reactions, Light, and heavy labeled biomarker peptide ions segregate and their intensity values are used for quantification.
  • analytes may be introduced into an inlet system of the mass spectrometer and ionized in an ionization source, such as a laser, fast atom bombardment, plasma or other suitable ionization sources known to the art.
  • the generated ions are typically collected by an ion optic assembly and introduced into mass analyzers for mass separation before their masses are measured by a detector. The detector then translates information obtained from the detected ions into mass-to-charge ratios.
  • the invention also provides compositions comprising biomarker polynucleotides, biomarker polypeptides, or biomarker antibodies according to the invention as described herein in the various embodiments.
  • the invention further provides diagnostic reagents for use in the methods of the invention, such as but not limited to reagents for flow cytometry and/or immunoassays that comprise fluorochrome- labeled antibodies that bind to one of the biomarker polypeptides of the invention as described herein.
  • the invention provides diagnostic reagents that comprise one or more biomarker probes, or one or more biomarker primers.
  • a diagnostic reagent may comprise biomarker probes and/or biomarker primers from the same biomarker gene or from multiple biomarker genes.
  • the invention also provides diagnostic compositions that comprise one or more biomarker probes and biomarker polynucleotides, or one or more biomarker primers and target polynucleotides, or biomarker primers, biomarker probes and biomarker target polynucleotides.
  • the diagnostic compositions comprise biomarker probes and/or biomarker primers and a sample suspected to comprise biomarker target polynucleotides.
  • Such diagnostic compositions comprise biomarker probes and/or biomarker primers and the nucleic acid molecules (including RNA, mRNA, cRNA, cDNA, and/or genomic DNA) of a subject in need of a diagnosis/prognosis of lung cancer.
  • kits for practicing the methods of the invention.
  • the kits can be used for clinical diagnosis and/or laboratory research.
  • a kit comprises one or more diagnostic reagents in one or more containers.
  • the kit also comprises instructions in any tangible medium on the use of the diagnostic reagent(s) in one or more methods of the invention.
  • a diagnostic reagent in the kit may comprise at least one biomarker polynucleotide, biomarker probe, and/or biomarker primer based on the biomarkers depicted in table 1 , table 2, or both table 1 and table 2.
  • the diagnostic reagents may be labeled, for example, by one or more different fluorochromes.
  • Such a kit may optionally provide in separate containers enzymes and/or buffers for reverse transcription, in vitro transcription, and/or DNA polymerization, nucleotides, and/or labeled nucleotides, including fluorochrome-labeled nucleotides.
  • Also included in the kit may be positive and negative controls for the methods of the invention.
  • a diagnostic reagent in the kit may comprise a biomarker antibody, which may be labeled, for example, by a ftuorochrome.
  • a kit may optionally provide in separate containers buffers, secondary antibodies, signal generating accessory molecules, labeled secondary antibodies, including fluorochrome-labeled secondary antibodies.
  • the kit may also include unlabeled or labeled antibodies to various cell surface antigens which can used for identification or sorting of subpopulations of cells,
  • positive and negative controls included in a kit can be nucleic acids, polypeptides, cell lysate, cell extract, whole cells from patients, or whole cells from cell lines.
  • the classification of the subject into the smoker-like group relates to the biomarker signature determined for the subject.
  • the classification into smoker-like signature may be independent of the smoking status, that means also non-smoking subjects may be comprised, which reveal a biomarker gene signature, which is usually a typical smoker tumor gene signature as described herein. If a subject is classified into the smoker-like signature group according to the present invention, the subject has a poor survival prognosis.
  • Figure 1 Interaction term.
  • A Change in expression of this gene is due only to cigarette smoke.
  • B Change in expression of this gene is specifically related to smoking-related lung cancers.
  • Y-axis represents expression level of the gene.
  • Figure 2 Apoptosis and cell survival network that characterizes cancers from smokers. The numbers below the biomarkers are the log value of the fold change and the p value.Solid lines indicate a direct interaction between the biomarkers; dotted lines indicate an indirect interaction; loops indicate self regulation.
  • Figure 3 Volcano plot for the interaction model.
  • the coefficients of the interaction model, gene 0 + ptSmoking + p 2 * Tissue+ 3 * TissuexSmoking+e, are estimated using LIMMA.
  • the genes that show significant interaction effect were selected for subsequent analysis as they capture the differences in gene expression between healthy and tumor tissue in smokers and non-smokers.
  • Figure 4 Biological processes and canonical functions associated with lung adenocarcinoma in smokers using Ingenuity Pathway Analysis.
  • the top ten biological functions (A) and canonical pathways (B) are grouped based on p values (Fisher exact test).
  • the threshold is less than 0.05.
  • Figure 5 Immune response and cell-to-cell signaling network.
  • the molecules in the network represent genes up regulated in lung tumors from smokers when compared to both healthy tissue and tumors from non-smokers.
  • Grey-shaded sections indicate groups of molecules participating in the processes indicated.
  • Color intensity is a qualitative representation of fold-change. Straight lines indicate direct interaction. Dashed lines indicate indirect interactions.
  • Figure 6 Cell proliferation (A) and cell survival (B) subnetworks.
  • the molecules in the network represent genes dysregulated in lung tumors from smokers when compared to both healthy tissue and tumors from non-smokers.
  • Grey color indicates upregulated genes.
  • Except from SORT1 which is a down regulated gene.
  • White color indicates no significant differences in fold change.
  • Color intensity is a qualitative representation of fold-change. Straight lines indicate direct interaction. Dashed lines indicate indirect interactions.
  • FIG. 7 Interactions between all networks. Note how the upstream regulators IFNG, TNF and IL1 B are heavily interacting with multiple components of the networks. Molecules represent genes dysregulated in lung tumors from smokers when compared to both healthy tissue and tumors from non-smokers. Grey color indicates upregulated genes. Except from HEXB, CAT and SORT1 , which are downregulated genes. White color indicates no significant differences in fold change. Color intensity is a qualitative representation of fold-change. Straight lines indicate direct interaction. Dashed lines indicate indirect interactions.
  • Figure 8 Heatmap of gene signature in training data.
  • the three genes identified for deriving a predictive signature shows a differentiation between smokers and non- smokers in the tumors. These three genes have a higher average expression in smokers as compared to non-smokers. Furthermore this difference is specific to the tumour samples as those genes have a significant interaction effect.
  • Grey and black colors in the side bar denote non-smokers and smokers respectively.
  • Grey scales in the heatmap denote positive (unfilled) and negative (dashed lines) Z-scores respectively.
  • Grey scale color intensity is a qualitative representation of fold-change.
  • Non-smokers are defined as either subjects that had never smoked during life or those that had stopped smoking for at least 16 years before samples were obtained.
  • the rationale behind the incorporation of former smokers that have not smoked for 16 years is that the risk of developing lung cancer for this group is comparable to the risk of a person that has never smoked.
  • Subject and sample selection was strictly based on the study purpose and the availability of tissue samples according to the experimental requirements, demographic and clinical data.
  • the group composition was analyzed with Statisfica software (Statsoft, Tulsa, US) which resulted in overall homogenous subject population. Ethical guidelines and confidentiality have been strictly assured and subjects gave written consent to participate in the study.
  • Tissue collection and preparation was performed at Indivumed Biobank. Freshly frozen lung tissue samples from the subject population were analyzed for normal and tumor cell content by staining before further sectioning. All tissues were collected under standardized conditions, snap frozen and stored in liquid nitrogen. The ischemia times are in alt cases below 15 minutes. Each tissue block was quality controlled and only tissues with low amount of necrotic and / or apoptotic areas ( ⁇ 10%) as well as a tumor content of at least 40-50% were used for the study.
  • RNA later solution 500 ⁇ RNA later solution (Qiagen) with RNAse inhibitor (Applied Biosystems) to assure RNA integrity and stored at -80°C until extraction.
  • RNA samples were DNAse-treated and extracted with Qiagen RNeasy kit following manufacturer's instructions. The quality of the prepared RNA was documented by microcapillary electrophoresis using an Agilent 2100 Bioanalyzer (Agilent Technologies). Only those RNA samples with a RIN number 7.0 were selected for hybridization.
  • RNA yield was determined by measuring the absorption at 260nm. 5. Fragmentation, hybridization, detection
  • Fragmentation of the cRNA was performed in 2X fragmentation buffer (Affymetrix kit component).
  • the fragmented cRNA was examined with an Agilent 2100 Btoanalyzer (Agilent Technologies) using non-fragmented cRNA as a control.
  • Each fragmented cRNA sample was hybridized onto Affymetrix HG U133 plus 2.0 chips together with hybridization controls, Hybridization, washing and detection were performed using an Affymetrix fluid station. Staining for detection was performed using a Streptavidin- phycoerythrin solution and scanned using an Affymetrix GeneChip scanner following manufacturer's instructions.
  • the expression values of a total of 54,613 probe sets were available in the CEL files generated by measurements of expression levels obtained from Affymetrix gene chips. Removing constant probe sets and the probesets for which the 95%-quantile does not exceed 7 in log2-scale, 19,078 probesets remained (i.e., probesests for which at least 5% of the sample values are above 7.). The remaining probe sets were subsequently mapped to gene symbols. For probeset on the gene chip, it is associated with one gene symbol but for a given gene symbol, several probesets may correspond to it. To choose a representative probeset for a given gene symbol, the interaction term and its p-value is calculated.
  • An interaction model was used to estimate the effect of smoke exposure and tissue response as well as the effects of their interactions.
  • An interaction effect is a change in the simple main effect of one variable over levels of the second variable.
  • positive interaction effect means that the effect of smoke exposure in lung is larger in tumor tissue than in healthy tissue.
  • the gene expression values are modeled as an intercept (bO) plus a smoking status effect (b1) plus a tissue effect (b2) plus an interaction term effect plus a residual term (b3).
  • the regression coefficients are estimated by the method of ordinary least squares which minimizes the sum of squared vertical distances between the observed responses in the dataset and the responses predicted by the linear approximation, i.e., minimizing [jgene -( b0+b1 * SmokingStatus+b2 * Tissue+b3 *
  • the results of the statistical analyses identified a total of 1 11 genes (including the three high priority markers identified by GeneBank Accession numbers 204767_s_at (FEN1 ), 209545_s_at (RIPK2) and 213523_at (CCNE1 )) that are specifically up regulated (88 genes) or down regulated (23 genes) in lung adenocarcinomas from smokers when compared to the lung adenocarcinoma of non-smokers.
  • FLDA Forward linear discriminant analysis
  • the FLDA takes as input thejnolecular profile, typically gene expression levels, as well as the phenotype of interest.
  • the phenotype of interest is the smoking status.
  • a predictive signature is derived from the following steps. Firstly, a moderated t-test for the two phenotypes (smoking and non-smoking) is performed for each gene (using the R-package limma). The genes are reordered according to the decreasing order of the absolute value of the statistics t; (2) Secondly, for all j, the j genes with the highest t-statistlc, in absolute value, are selected for training a classifier.
  • LDA Linear Discriminant Analysis
  • FLDA identified a gene signature composed of three genes: FEN1 , RIPK2, and CCNE1 which are strongly involved in the regulation of cell proliferation and survival.
  • An LDA model is trained on data of the present study. The heatmap of this gene signature in the training data is shown in Figure 8. By applying this model, making sure that the means for each gene are equal (centering both datasets), the smoking status for samples in the independent data set was predicted.
  • the sensitivity, specificity, and MCC are 0.63, 0.75, 0.37 respectively.
  • lung adenocarcinoma in smokers is characterized by the up-regulation of genes that are involved in cell-to-cell signaling and the modulation of the immune response: STAT1 , IFNAR2, PSME2, PSMB9, CXCL9, CXCL10, CD274, IL15, IL15RA, IL6, CCL5, CCL4, IL18RAP, IL2RB ( Figure 5).
  • STAT1 IFNAR2, PSME2, PSMB9, CXCL9, CXCL10, CD274, IL15, IL15RA, IL6, CCL5, CCL4, IL18RAP, IL2RB
  • lung adenocarcinoma in smokers are characterized by the up-regulation of CDK1 , FEN1 , CCNE1 , MCM4, CDC20, BIRC5, CDK4 and GADD45B.
  • the overall effect of these genes is to promote tumor growth by up-regulating processes involved in cell proliferation: DNA replication, cell cycle progression, mitosis, as well the repair of DNA damage (Figure 6).
  • lung adenocarcinoma from smokers are characterized by the up-regulation of: P2RY6, CFLAR, BIRC3, NFKB2, CHEK1 , CXCL12, SPP1 , LILRB2, ADA, R1PK2 and the down-regulation of SORT1.
  • P2RY6, CFLAR, BIRC3, NFKB2, CHEK1 , CXCL12, SPP1 , LILRB2, ADA, R1PK2 and the down-regulation of SORT1.
  • the overall effect of the activity of this network is to promote tumor cell survival and protect tumor cells from the activation of apoptosis and other cell death pathways.
  • PSMB9 Different studies have demonstrated a deficiency / lack of expression of HC class I molecules in the surface of many types of tumors, (Singal et al., 1996, Delp et al., 2000). PS E9 has been postulated as a tumor suppressor in cancer of the uterus (Havashi et al., 201 1)
  • PSME2 Similar to PSMB9, lower levels are associated with increased aggressiveness and resistance to therapy in melanoma (Stone et al., 2009) and gastric adenocarcinomas (Zheng et al., 2012).
  • CCL4 Increased levels of CCL4 (MIP1 b) are reported to decrease the number of metastasis in murine cell lymphoma (Menten et al., 2002) and a mouse model of lung cancer (Ishihara et al, 1998).
  • CCL5 Increased levels of CCL5 (RANTES) are associated with better prognosis and increased survival in lung adenocarcinoma (Moran et al., 2002, Qhri et al., 2010)
  • IFNAR2 Increased levels of IFNAR2 are associated with tumor suppression (Mendoza-Villanueva et al., 2008, Swann et al., 2007) yet IFNAR2 overexpression was observed in various histological types of lung cancer, and appears to be associated with lung cancers that behave aggressively (Tanaka et al., 2012). This is an example of a gene that apparently plays different roles in different settings.
  • CXCL9 Increased levels of CXCL9 (MIG) are reported to inhibit cell growth in mouse and human lung tumors (Addison et al., 2000, Winter et ah, 2007).
  • CXCL 0 Treatment with CXCL10 (INP-10) is reported to inhibit metastasis and to increase cell death in a mouse model of lung tumor (Arenberg et al., 2001) and in human non-small cell lung cancer (Ohri et al., 2010).
  • IL 8RAP No conclusive data are provided in the literature on the role of for IL18 receptor.
  • IL2RB Decreased levels of 1L2RB are reported to increase the number of metastasis in a mouse model of malignant pleural effusion using human adenocarcinoma cells (Arenberg et al., 2001 ).
  • IL15 Tumor nodule formation was retarded and tumor growth was inhibited after treatment with IL15 (Tang et al., 2008).
  • STAT1 Activation of STAT1 pathway is reported to inhibit lung cancer cell proliferation, anchorage-independent growth, tumorigenesis, cell motility, and invasion, and to slow cell cycle progression (Tsai et al., 2006). Statl is further reported to inhibit lung tumor formation by activated K-Ras (Wang et al., 2008).
  • proteasome proteasome
  • PSMB7 macropain subunit beta type, 7 200786_at 0.46300
  • POLR3F directed) polypeptide F 39 kDa 2052 8_at 0.48300
  • TGS1 trimethylguanosine synthase 1 238346_s_at 0.49800
  • GTF2E1 polypeptide 1 alpha 56kDa 205930_at 0.50300 proteasome (prosome,
  • TBP box binding protein
  • TAF5 associated factor 100kDa 210053_at 0.56100
  • GTF2E2 polypeptide 2 beta 34kDa 202680_at 0.60200 eukaryotic translation initiation
  • PSME2 (PA28 beta) 201762_s_at 0.66300 poliovirus receptor-related 2
  • PVRL2 pesvirus entry mediator B 203149_at 0.67700 small nuclear ribonucleoprotein
  • PPP3CB protein phosphatase 3 catalytic 202432_at 0.71300 subunit, beta isozyme
  • RFC3 38kDa 2Q4127_at 0.93300 nuclear factor of activated T- cells, cytoplasmic, calcineurin-
  • IL15RA interleukin 15 receptor alpha 207375 s at 1.09800 nuclear factor of kappa light
  • TAP2 (MDR/TAP) 225973_ . at 1.21000
  • CD3d molecule CD3d molecule, delta (CD3-
  • CD3D TCR complex 213539. .at 1 .23400 transporter 1 , ATP-binding
  • TAP1 MDR/TAP 202307 .
  • _s_at 1.23400 solute carrier family 7 amino
  • IL2RB interleukin 2 receptor beta 205291_at 1.26600 sphingosine-1 -phosphate
  • PSMB9 2 204279 at 1 .53500 minichromosome maintenance
  • IL6 interleukin 6 (interferon, beta 2) 205207_at 3.33600 granzyme B (granzyme 2,
  • GZMB associated serine esterase 1 210164_at 3.53000
  • Table 2 List of biomarker genes specifically downregulated in lung adenocarcinomas of smokers when compared to non-smokers
  • NAGLU N-acetylglucosaminidase, alpha 204360 s at -0.704
  • GNS 212334_at -0.460 sulfatase Table 3 List of biomarker genes specifically up regulated in lung adenocarcinomas from smokers when compared to non-smokers and reported in the prior art to have a tumor suppressor effect when overexpressed in lung and other cancers.
  • Each gene identifier was mapped to its corresponding gene object in the Ingenuity Pathways Knowledge Base. These genes were then used as the starting point for pathway analysis.
  • Canonical pathways analysis identified the pathways from the Ingenuity Pathways Analysis library of canonical pathways that were most significant to the data set. The significance of the association between the dataset and the canonical pathway was measured in two ways: (1 ) ratio of the number of genes from the data set that map to the pathway divided by the total number of genes that map to the canonical pathway was displayed, (2) Fischer's exact test was used to calculate a p-value determining the probability that the association between the genes in the dataset and the canonical pathway is explained by chance alone. Only molecules from the dataset that met the cut-off criteria (1.5 fold-change and p ⁇ 0.05) were considered for the analysis.
  • Figure 4A shows the top ten biological functions associated with lung tumors of smokers. As expected, these include functions related to cancer, but also to cellular growth and proliferation, cell death and survival, as well as different aspects of the immune response, such as immune cell trafficking, inflammatory response, and cellular movement. Moreover, the gene-sets were categorized into canonical pathways.
  • Figure 4B shows the top ten canonical pathways activated specifically in CS-related lung adenocarcinomas. Consistent with the previous figure, the most significant pathways are associated with the DNA damage response and the regulation of cell cycle progression, proliferation and apoptosis.
  • Lung adenocarcinoma is a heterogeneous disease, with specific clinical and genetic features depending on the smoking-status of the patients.
  • the findings are of potential clinical interest. On one hand, they can provide the basis for the identification of novel therapeutic targets in the treatment of lung adenocarcinoma. On the other hand, they could help select the most appropriate treatment for the patient, thus maximizing the chances for success to therapy.
  • the first network contains a number of molecules that are essential in cell-to-cell signaling and the modulation of the immune response (Figure 5).
  • the central molecules are: IL15 (interleukin 15), IL6 (interleukin 6) and STAT1 (signal transducer activator of transcription 1), IL15 is a pro-inflammatory cytokine expressed in many tissues including lung epithelium.
  • Some of its downstream signaling elements include JAK/STAT, APK and PI3K/AKT pathways, which promote the proliferation and activation of natural killer (NK) cells as well as T and B lymphocytes (Carson et al (1994 and 1997), Schluns et al.) thus initiating a strong immunological response.
  • STAT1 an essential mediator of interferon gamma (IFNG), and its downstream targets IL6, CCL4 (C-C motif ligand 4) and CCL5 (C-C motif ligand 5).
  • IL15 and STAT1 also play an important role in the development antitumoraf immune responses. In fact, due to its ability to stimulate strong T-cetl mediated cytotoxic responses IL15 is currently being evaluated as an immunotherapeutic agent (Le Maux Chansac et al., Takeuchi et al., Teague et al.).
  • STAT1 can induce growth arrest and apoptosis in cancer cells through the activation of p27 (Wang et al ), p2 WAF and caspases (Yu et al.).
  • IL15 for example, can be found soluble, but the majority of the protein is bound to the cellular membrane, either directly or through an interaction with 1L15RA (IL15 receptor subunit alpha) (Jakobisiak et al ). Pathway activation requires the binding of IL15 to the IL15 receptor complex.
  • 1L15RA IL15 receptor subunit alpha
  • this complex is formed by the alpha subunit in the host cell and IL2RB and IL2RG (IL2 receptor subunits beta and gamma, respectively) in the target cell.
  • IL15 can bind to an aberrant form of the receptor complex formed by alpha and beta chains alone. This aberrant conformation then promotes epithelial to mesenchymal transition (G iron-Michel et al.) and cell proliferation and transformation (Motegi et al). Formation of this aberrant receptor is favored by increased levels of IL15 and the alpha and beta subunits of its receptor (Giron-Michel et al., Khawam et al.). Although increased gene expression does not necessarily translate into increased protein levels, the observed upregulation of IL15, IL15RA and IL2RB genes in lung tumors from smokers strongly suggests the presence of an aberrant IL15 signaling in lung tumors from smokers.
  • IL15 also increases the expression of IL18RAP (interleukin 18 receptor accessory protein), an enhancer of IL18 receptor signaling that promotes NFKB activation (Born et al ).
  • IL15/IL18RAP activation induces the release of IFNG (Sareneva et al.), which, in turn, regulates the expression of many genes either directly or through activation of JAK/STAT pathways.
  • Interferons are a class of cytokines that modulate innate and adaptive immune responses against viruses, bacteria and tumor cells through an effect on NK cells and cytotoxic T lymphocytes.
  • INFG has important immunomodulatory functions, including T-cell differentiation, activation and homeostasis, NK cell activation, lysosomal activation in macrophages, and the promotion of antigen presentation by upregulating the expression of components of the class I major histocompatibility complex (MHC) and of the immunoproteasome (Schroder et al.).
  • MHC major histocompatibility complex
  • Schroder et al. immunoproteasome
  • IFNG plays a key role in tumor surveillance by increasing tumor immunogenicity (Dunn et al., Zaidi et al.), inhibiting tumor cell proliferation and promoting apoptosis (Zaidi et al., Ikeda et al.).
  • the therapeutic use of IFNG has already been tested in the clinic with melanoma patients, although it showed low efficacy (Schiller et al.) and surprisingly, even faster disease progression compared to non-treated patients (Meyskens et al.).
  • IFNG has the potential to drive an antitumor immune response
  • increased / sustained IFNG activation is able to inhibit apoptosis and promote tumor cell proliferation and metastasis (Zaidi et al.).
  • IFNG-mediated overexpression of these proteins is associated with alveolar destruction and emphysema (Ma et al ). Elevated levels of CXCL9 and CXCL10 can also be detected at metastatic sites in lung and colorectal carcinomas, where they promote MMP9 (matrix metalloprotease 9) mediated disruption of the endothelial barrier and cellular migration. Interestingly, CS dramatically up regulates IFNG (Ma et al.) and thus, the levels of CXCL9 and CXCL10. Increased levels of these chemokines will likely result in more tissue destruction and putative ly a higher risk for invasion and metastasis.
  • MMP9 matrix metalloprotease 9
  • IFNAR2 interferon alpha/beta receptor beta chain
  • IFNAR2 also promotes the activation of the immunoproteasome, thus increasing antigen presentation in tumor cells.
  • the immunoproteasome is further activated by the upregulation of two other relevant genes, PSME2 (proteasome activator complex subunit 2) and PSMB9 (proteasome subunit beta type-9).
  • PSME2 proteasome activator complex subunit 2
  • PSMB9 proteasome subunit beta type-9
  • NK cells respond to infected or transformed cells either by killing the abnormal cells or by releasing immunomodulatory chemokines and cytokines such as IFNG.
  • NK cells are normally restrained by different types of inhibitory receptors that recognize MHC class I molecules in the target-cell.
  • MHC-I expression is low, NK cells are liberated from the inhibitory receptors and can kill target cells more efficiently (French et al.).
  • high expression of PSME2 and PSMB9 leads to increased MHC-I expression and increases in the chances of interaction with inhibitory receptors in the NK cell, thus preventing tumor cell elimination. Therefore, upregulation of MHC-I molecules would be a very ingenious mechanism for tumors to evade immune surveillance.
  • CD274 was found (also known as programmed cell death ligand 1 , PD-L1 ) also upregulated in our network.
  • PD-L1 programmed cell death ligand 1
  • CD274 sends an inhibitory signal that inhibits the proliferation of activated T-lymphocytes, monocytes NK and dendritic cells (Riley et al.).
  • the main role of CD274 is to induce fetomaternal tolerance during pregnancy.
  • CD274 overexpression correlates with poor prognosis in non-small cell lung cancer (NSCLC), where induces immune escape by preventing the maturation of dendritic cells (Mu et al.).
  • NSCLC non-small cell lung cancer
  • IFNAR2, PMSE2 and PMSB9 lead to sustained activation of p38/MAPK and NFKB pathways.
  • NFKB can promote cellular death or survival.
  • NFKB regulates cellular fate in connivance with the tumor suppressor gene TP53.
  • TP53 mutations can be found in lung adenocarcinomas from both smokers and non- smokers, but the percentage is significantly higher in smokers, and can be directly linked to CS exposure (Couraud et al.). While in a p53 proficient cell, sustained NFKB would cause growth arrest and apoptosis, in lung tumors from smokers the opposite effect (increased proliferation and cell survival) would be expected.
  • a number of upregulated of genes was found that control cell proliferation and survival in CS-related lung tumors. Tumors are by definition, an abnormal and uncontrolled growth of a specific tissue. Therefore it is not surprising to observe activation of molecular pathways that promote cell proliferation and /or prevent cellular death. The interesting observation, however, is that these genes are upregulated not only in tumor compared to healthy tissue, but more importantly in lung tumors from smokers compared to non-smokers. In addition, most of the upregulated genes have been previously associated with poor outcome in multiple types of cancer, including those of the lung, supporting the more aggressive phenotype often observed in CS-related lung tumors.
  • CDK1 cyclin dependent kinase 1
  • CDC20 cell divison cycle 20 homolog
  • BIR5 baculoviral inhibitor of apoptosis repeat-containing 5 or survivin
  • FEN1 Flap structure-specific endonuclease 1
  • CDC20 a member of the anaphase promoting complex, is responsible for the inhibition / degradation of many cell cycle regulators like p21 ARF (i.e. inhibits CDK1 complex formation, cyclin E, Cyclin D and PCNA) (Kato et al., Qiao).
  • BIRC5 is an inhibitor of apoptosis by inhibiting BAX and FAS-mediated pathways (Tamm et al.) and a transcriptional inhibitor of the P21WAF1 gene (Tang et al.).
  • FEN1 is involved in the processing of the Okazaki fragments in the DNA lagging strand synthesis (Henneke et al.), telomere stability (Saharia et al.) and DNA- repair pathways (Klungland et al.), where is considered a limiting factor.
  • Another important component of the network is CCNE1 (Cyclin E1) which serves as a regulator of cyclin-dependent kinases and the RB family of proteins, thus promoting G1/S transition and cell cycle progression (Harbour et al., Shanahan et al.).
  • CCNE1 overexpression is particularly common in smoke-related lung tumors where it shortens cell cycle and promotes genomic instability (Ohtsubo et al., Spruck et al.).
  • MCM4 minichromosome maintenance protein 4
  • MCM4 is essential for genome replication (You et al ). Uncontrolled proliferation is further promoted by overexpression of CDK4 (cyclin dependent kinase 4).
  • CDK4 promotes G1/S transition, partially by phosphorylating RB1 , which may explain at least in part, the impairment of the retinoblastoma (RB) pathway known to occur in most lung tumors (Wikman et al.).
  • RB retinoblastoma
  • CDKN2A an important inhibitor of this pathway, CDKN2A, is most often mutated in lung adenocarcinomas (Ding et al., Imietinski et al.), suggesting the existence of constitutive activated cyclin-dependent growth signals.
  • FEN1 genes with a key role in DNA repair
  • CHEK1 Besides its role in DNA replication, FEN1 participates in the repair of different types of DNA damage, including replication-induced single and double-strand DNA breaks and it is considering a limiting factor in DNA repair (Nikoiova et al.).
  • CHEK1 is a critical component of DNA replication, intra-S phase, G2/M transition, and mitotic spindle-assembly checkpoints (Bartek et al.). In response to DNA damage, it becomes activated and blocks cell cycle progression until the damage is repaired (Bartek et al., Peng et al.).
  • SPP1 secreted phosphoprotein 1 or osteopontin
  • CS Shop et al.
  • Pazoili et al. SPP1 is able to inhibit BAX activation and prevent BCL2 down regulation, thus inhibiting caspase-9 and caspase-3 dependent cell apoptosis (Gu et al.).
  • NFKB caspase inhibitors
  • CFLAR caspase inhibitors
  • BIRC3 baculoviral inhibitor of apoptosis repeat-containing 3
  • constitutive activation of NFKB either through activating mutations or downregulation of its inhibitors (IKBs) is commonly found in lung and other tumors and often associated with increased resistance to therapy (Rayet et al.).
  • NFKB may be upregulated in tumors from smokers.
  • NFKB2 the p100 subunit of NFKB
  • RIPK2 Receptor- interacting serine/threonine-protein kinase 2
  • BIRC3 and BIRC5 have recently been identified as the E3-ubiquitin ligases responsible for of RIPK2 ubiquitinilation, a prerequisite for NFKB activation (Bertrand et at.). The combined effect of these two subnetworks is to provide the tumor with a daunting proliferative potential, while protecting cancer cells from any attempt of activation of senescence or apoptosis programs that may limit its growth.
  • IFNG tumor necrosis factor
  • IL1 B interleukin 1 beta
  • IP-10/CXCL10 interferon-gamma-inducible protein 10
  • IFN-gamma can promote tumor evasion of the immune system in vivo by down-regulating cellular levels of an endogenous tumor antigen. J Immunol, 2000. 165(10): p. 5502-8.
  • BERTRAND, M.J., et al., clAP1 2 are direct E3 ligases conjugating diverse types of ubiquitin chains to receptor interacting proteins kinases 1 to 4 (RIP1 -4).
  • CARSON W.E., et al., Interieukin (IL) 15 is a novel cytokine that activates human natural killer cells via components of the IL-2 receptor. J Exp Med, 994.
  • GIRON-MICHEL J., et al., lnterleukin-15 plays a central role in human kidney physiology and cancer through the gammac signaling pathway.
  • GOVINDAN R., et al., Genomic landscape of non-small cell lung cancer in smokers and never-smokers. Cell, 2012. 150(6): p. 121-34.
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  • MCM Minichromosome maintenance
  • TAK1 is a central mediator of NOD2 signaling in epidermal cells.
  • KOVACIC acts as a tumor promoter for leukemia development.
  • MAIO M., et al., Reduction in susceptibility to natural killer cell-mediated lysis of human FO-1 melanoma cells after induction of HLA class I antigen expression by transfection with B2m gene. J Clin Invest, 1991. 88(1): p. 282-9.
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  • MU, C.Y., et al., High expression of PD-L1 in lung cancer may contribute to poor prognosis and tumor cells immune escape through suppressing tumor infiltrating dendritic cells maturation.
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Abstract

La présente invention concerne des panels de biomarqueurs qui peuvent être utilisés pour pronostiquer un cancer du poumon chez un individu et pour prédire et surveiller les suites du cancer du poumon de l'individu qui est mis ou sera mis sous traitement. L'invention concerne également des kits pour réaliser lesdites méthodes.
PCT/EP2013/060809 2012-11-09 2013-05-24 Biomarqueurs pour le pronostic du cancer du poumon WO2014072086A1 (fr)

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WO2017082494A1 (fr) * 2015-11-13 2017-05-18 재단법인 의약바이오컨버젼스연구단 Procédé de dépistage d'un médicament anticancéreux inhibant la liaison de la méthionyl-arnt synthétase (mrs) de et la kinase dépendante à la cycline 4 (cdk4)
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