Method for predicting overall survival of cancer patients

Abstract

To provide a method for accurately predicting a prognosis, especially overall survival period, of a subject suffering from cancer from a blood-derived sample of the subject.SOLUTION: The problem is solved by a method that includes: a first process in which a blood-derived sample of a subject cancer patient collected before administration of an antibody drug is applied to a column packed with an insoluble carrier on which an Fc-binding protein is immobilized, and gamma globulin contained in the sample is separated to obtain a separation pattern of the gamma globulin; a second process to calculate each peak area from the separation pattern obtained in the first step and to calculate a ratio of the areas; and a process to predict an overall survival period of the patient based on the ratio obtained in the second process.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] The present invention relates to a method for predicting overall survival of a cancer patient, and in particular to a method for accurately predicting overall survival of a cancer patient by analyzing components contained in a blood-derived sample of the patient. [Background technology]

[0002] Diagnosis that clarifies the prognosis of cancer patients provides important information for treatment policy and monitoring of treatment effects, and is therefore a useful indicator for selecting the optimal therapy. Prognostic diagnosis provides doctors with information about the risks and survival probability of the patient's disease, allowing them to select the optimal therapy, thereby reducing the risk of unnecessary treatment for the patient. Therefore, it not only saves costs for unnecessary treatment, but also contributes to improving patient prognosis by selecting the optimal treatment.

[0003] Diagnosis using soluble tumor antigens is being performed as a diagnostic aid for treatment. Because soluble tumor antigens are secreted by tumor cells, they can be detected in blood or tissue samples, and many diagnostic attempts have been made using them, such as to monitor the effectiveness of treatment. For example, CEA (Carcinoembryonic Antigen) and CA19-9 (Carbohydrate Antigen 19-9) are used as tumor markers for gastrointestinal cancer. However, because soluble tumor antigens are also released upon destruction of tumor cells, they do not necessarily adequately reflect the prognosis of cancer patients.

[0004] Circulating tumor cells (CTCs) present in blood-derived samples have been used as cancer diagnostic markers in place of soluble tumor antigens. Patent Document 1 discloses a method for providing a prognostic indicator for disease progression and mortality by assessing the absolute number and changes in CTCs expressing epithelial markers in patients with metastatic breast cancer. Furthermore, Patent Document 2 discloses a method for accurately predicting the prognosis of cancer patients by detecting and counting CTCs present in blood-derived samples that barely express leukocyte markers and epithelial markers. However, blood-derived samples contain extremely low numbers of CTCs, with only approximately 10 per mL of blood-derived sample. Therefore, unless CTCs are appropriately collected from blood-derived samples, accurate prognosis predictions for cancer patients cannot be achieved. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Special Publication No. 2008-533487 [Patent Document 2] Japanese Patent Application Laid-Open No. 2017-129584 Summary of the Invention [Problem to be solved by the invention]

[0006] An object of the present invention is to provide a method for accurately predicting the prognosis, particularly the overall survival time, of a cancer patient from a blood-derived sample of the patient. [Means for solving the problem]

[0007] As a result of intensive research to solve the above-mentioned problems, the present inventors discovered that the overall survival time of cancer patients can be accurately predicted based on differences in the sugar chain structures of gamma globulins contained in blood samples of the cancer patients, and thus completed the present invention.

[0008] That is, the present invention can be exemplified as follows.

[0009] [1] A method for predicting overall survival in a subject suffering from cancer, comprising: The method includes the following steps (1) to (3): (1) subjecting a blood-derived sample collected from the subject to a column packed with an insoluble carrier onto which an Fc-binding protein has been immobilized, and separating gamma globulins contained in the sample, thereby obtaining a separation pattern of the gamma globulins; (2) calculating the area of each peak from the separation pattern obtained in (1) and calculating the ratio of the areas; (3) predicting the overall survival time of the subject based on the ratio obtained in (2); and wherein the blood-derived sample is a sample collected before administration of an antibody drug to the subject.

[0010] [2] The method according to [1], wherein the subject is a patient who has undergone prior chemotherapy.

[0011] [3] The method according to [1] or [2], wherein the cancer is lung cancer.

[0012] [4] The method according to any one of [1] to [3], wherein the Fc-binding protein is a human Fcγ receptor.

[0013] [5] The method according to [4], wherein the human Fcγ receptor is a polypeptide selected from the following (i) to (iii): (i) a polypeptide comprising a sequence consisting of amino acid residues 17 to 192 of the amino acid sequence set forth in SEQ ID NO: 1, in which at least valine at position 176 of SEQ ID NO: 1 is substituted with phenylalanine; (ii) a polypeptide comprising a sequence consisting of amino acid residues 17 to 192 of the amino acid sequence set forth in SEQ ID NO: 1, in which the amino acid sequence has at least a substitution of valine at position 176 of SEQ ID NO: 1 with phenylalanine, and further has substitution, deletion, insertion, and / or addition of one or several amino acid residues at one or several positions other than position 176, and which has antibody-binding activity; (iii) A polypeptide having an amino acid sequence that is 70% or more identical to the sequence consisting of amino acid residues 17 to 192 of SEQ ID NO: 1, in which the amino acid residue corresponding to valine at position 176 of SEQ ID NO: 1 is substituted with phenylalanine, and which has antibody-binding activity. [Effects of the Invention]

[0014] The present invention features a method for predicting the overall survival of a cancer patient by subjecting a blood sample collected from the patient before administration of an antibody drug to a column packed with an insoluble carrier immobilized with an Fc-binding protein to obtain a separation pattern of gamma globulins contained in the sample, calculating the area ratio of each peak from the separation pattern, and predicting the patient's overall survival based on the ratio. Predicting overall survival allows for stratification of patients into those with good or poor prognosis, which can serve as an indicator for determining treatment strategies and for identifying targets for the development of new therapeutic drugs. In particular, the method of the present invention uses a blood sample collected before administration of an antibody drug, thereby providing an indicator for determining treatment strategies before treatment is initiated and reducing the risk of unnecessary treatment for the patient. Furthermore, because the method of the present invention targets gamma globulins, which are abundant in blood-derived samples, only a very small amount of blood-derived sample is required for measurement, thereby reducing the burden on the patient associated with blood collection. [Brief explanation of the drawings]

[0015] [Figure 1] FIG. 1 shows an example of the separation patterns of a standard substance and a measurement sample obtained by analyzing an antibody using a column packed with an Fc-binding protein-immobilized gel. [Figure 2]FIG. 1 shows box plots of the first peak area percentage and the third peak area percentage when gamma globulins derived from healthy individuals and lung cancer patients were analyzed using a column packed with an Fc-binding protein-immobilized gel. [Figure 3] This figure shows progression-free survival and overall survival times, calculated by the Kaplan-Meier method, when patients were divided into high and low value groups based on the median of the measured values obtained from each patient, relative to the first peak area / total area obtained by analyzing gamma globulin derived from lung cancer patients using a column packed with Fc-binding protein-immobilized gel. [Figure 4] This figure shows progression-free survival and overall survival times, calculated using the Kaplan-Meier method, when patients were divided into high and low value groups based on the median of the second peak area / total area obtained by analyzing gamma globulin derived from lung cancer patients using a column packed with Fc-binding protein-immobilized gel. [Figure 5] This figure shows progression-free survival and overall survival times, calculated using the Kaplan-Meier method, when patients were divided into high and low value groups based on the median value of the third peak area / total area obtained by analyzing gamma globulin derived from lung cancer patients using a column packed with Fc-binding protein-immobilized gel. [Figure 6] Gamma globulin derived from lung cancer patients was analyzed using a column packed with Fc-binding protein-immobilized gel, and the third peak area / first peak area ratio was obtained. Patients were divided into high and low value groups based on the median of the corresponding measurement value obtained from each patient. This figure shows the progression-free survival and overall survival times, calculated using the Kaplan-Meier method. [Figure 7] Gamma globulin derived from lung cancer patients was analyzed using a column packed with Fc-binding protein-immobilized gel, and the third peak area / second peak area was obtained. The patients were divided into high and low value groups based on the median of the corresponding measurement values obtained from each patient. This graph shows the progression-free survival and overall survival times, calculated using the Kaplan-Meier method. [Figure 8]Gamma globulin derived from lung cancer patients was analyzed using a column packed with Fc-binding protein-immobilized gel, and the second peak area / first peak area ratio was obtained. Patients were divided into high and low value groups based on the median of the corresponding measurement value obtained from each patient. This figure shows the progression-free survival and overall survival times, calculated using the Kaplan-Meier method. [Figure 9] Box plots of the first peak area percentage and the third peak area percentage when gamma globulins derived from healthy individuals, lung cancer patients, and COPD patients were analyzed using a column packed with an Fc-binding protein-immobilized gel. DETAILED DESCRIPTION OF THE INVENTION

[0016] The present invention will be described in detail below.

[0017] The present invention provides a method for predicting the overall survival time of a cancer patient, which comprises calculating the area ratio of each peak from a separation pattern obtained by separating gamma globulins (hereinafter also referred to as "antibodies") contained in a blood-derived sample using an insoluble carrier onto which an Fc-binding protein has been immobilized, and using the area ratio to calculate the area ratio of each peak from the separation pattern.

[0018] Specifically, the method of the present invention comprises the following steps: <1> from <5> The method may be a method for predicting overall survival of the diseased individual (subject), comprising: <1> adding a sample derived from the subject's blood to a column packed with an insoluble carrier onto which an Fc-binding protein has been immobilized, and allowing the antibody contained in the sample to be adsorbed onto the carrier; <2> adding an equilibration solution to the column to equilibrate the column; <3> adding an eluate to the column to elute the antibodies adsorbed to the carrier, thereby obtaining a separation pattern of the antibodies; <4> calculating the area of each peak from the separation pattern and calculating the ratio of the areas; <5> A step of predicting overall survival time in the subject based on the area ratio.

[0019] Below is the process <1> from <5> These steps are also referred to as the "adsorption step", "equilibration step", "elution step", "peak area calculation step", and "prediction step", respectively.

[0020] <Subject's blood-derived sample> The "subject" of the method of the present invention refers to a human individual suffering from cancer who is the subject of overall survival prediction. The subject may be male or female. The subject may be of any age, including children, young people, middle-aged people, and elderly people.

[0021] The blood-derived sample used in the method of the present invention is characterized by being collected from the subject before administration of an antibody drug. By targeting gamma globulin contained in a blood-derived sample collected before administration of an antibody drug, the overall survival time of the subject can be predicted with high accuracy, and since prognosis can be predicted before the start of treatment with the antibody drug, it can also be used as an indicator for formulating an appropriate treatment plan without performing unnecessary treatment. In particular, using a blood-derived sample from a patient who has undergone prior chemotherapy and has been collected before administration of the antibody drug is preferable because it allows for even more accurate prediction of overall survival time.

[0022] Here, "pre-chemotherapy history" refers to a cancer subject who has undergone chemotherapy before undergoing the prediction method of the present invention. There are no particular limitations on the chemotherapeutic agent used in the chemotherapy, as long as it is a small molecule drug. Examples of chemotherapeutic agents for lung cancer include platinum preparations such as cisplatin, carboplatin, and nedaplatin, etoposide, irinotecan, paclitaxel, docetaxel, vinorelbine, gemcitabine, amrubicin, nogitecan, pemetrexed, nab-paclitaxel, tegafur-uracil, and tegafur-gimeracil-oteracil potassium.

[0023] The term "blood-derived sample" refers to a blood-derived sample that contains or may contain antibodies obtained from a subject. Examples of blood-derived samples include blood samples such as blood (whole blood), diluted blood, serum, plasma, cerebrospinal fluid, umbilical cord blood, and apheresis; samples that may contain blood-derived components such as urine, saliva, semen, feces, sputum, amniotic fluid, and ascites; and samples that may contain antibodies separated from or contained in these samples. The blood-derived sample may be used in the adsorption step directly or after appropriate pretreatment. The pretreatment may be performed, for example, by a standard method. Examples of pretreatment include centrifugation and column purification. Specifically, for example, gamma globulin may be purified and used in the adsorption step. The blood-derived sample is used in the adsorption step in the form of a solution containing antibodies. That is, the blood-derived sample may be appropriately prepared in the form of a solution containing antibodies and used in the adsorption step. For example, the blood-derived sample or its pretreated product as exemplified above may be dissolved, suspended, dispersed, or solvent-exchanged in a liquid medium as appropriate, and used in the adsorption step as a solution containing an antibody. For such a liquid medium, the description of the equilibration liquid described below can be applied mutatis mutandis. The liquid medium may or may not be the same as the equilibration liquid. The blood-derived sample that has undergone the pretreatment and the solution containing the antibody are collectively referred to as a "blood-derived sample" in this specification.

[0024] You cannot be sure that you will not be able to do anything else. There is no such thing as an abagovoma b、abatacept、abciximab、ABT-414、adalimumab、adalimumab mab-atto、aducanumab、afelimomab、aflibercept、aflibercept、alefacept、alemtuzumab、alirocumab、altumomab、ALX-0061 、amatuximab、amivantamab、anifrolumab、arcitumomab、atezolizumab、avelumab、bapineuzumab、basiliximab、bavituximab、begelomab、 belatacept、belimumab、benralizumab、besilesomab、bevacizumab、bezlotoxumab、bimagrumab、blinatumomab、bococizumab、brentuximab vedotin、Briakinumab、brodalumab、canakinumab、capromab、certolizumab pegol、cetuximab、crenezumab、daclizumab、daclizumab、daratumumab、demcizumab、denosumab、denosumab、dupilumab、durvalumabzuliedzu、ectumab colomab、efalizumab、efungumab、elotuzumab、epratuzumab、etanercept、etanercept、etanercept-szzs、etaracizumab、etrolizumab、evolocumab、fresolimumab、bgene ozogamicin、gevokizumab、girentuximab、golimumab、GSK2398852、guselkumab、ibritumabtiuxetan、idarucizumab、igovomab、imciromab pentetate、infliximab、infliximab、infliximab、infliximab-dyyb、inotuzumab ozogamicin、ipilimumab、ixekizumab、labetuzumab、lampalizumab、lebrikizumab、lifastuzumab vedotin、lintuzumab、lorvotuzumab mertansine、lulizumab pegol、margetuximab、mavrilimumab、mepolizumab、milatuzumab、mitumomab、mogamulizumab、motavizumab、moxetumomab pasudotox、muromonab-CD3、natalizumab、natalizumab、necitumumab、necitumumab、nesvacumab、nimotuzumab、nivolumab、nivolumab、nofetumomab、obiltoxaximab、obinutuzumab、ocrelumab izumab、ofatumumab、olaratumab、omalizumab、otelixizumab、ozanezumab、palivizumab、panitumumab、pascolizumab、pembrolizumab、pemtumomab、pertuzumab、pidilizumab、polyzumab vedotin、racotumomab、ramucirumab、ranibizumab、raxibacumab、reslizumab、rilonacept、rilotumumab、rituximab、romiplostim、romosozumab、sacituzumabgovitecan, satumomab, secukinumab, seribantumab, sifalimumab, silutuximab, simtuzumab, sirukumab, solanezumab, sulesomab, tabalumab, tanezumab, tarextumab, tildrakizumab, tilmanocept, tocilizumab, tositumomab, tralokinumab, trastuzumab, trastuzumab emtansine, trastuzumab Examples include deruxtecan, tremelimumab, ustekinumab, vantictumab, vedolizumab, veltuzumab, votumumab, yttrium(90Y) clivatuzumab tetraxetan.

[0025] <1> Adsorption process The adsorption step is a step in which a blood sample collected from the subject is added to a column packed with an insoluble carrier to which an Fc-binding protein has been immobilized, and the antibody contained in the sample is adsorbed onto the carrier.

[0026] "Antibody (gamma globulin)" refers to a molecule containing an Fc region. An antibody may consist of an Fc region, or may contain other regions in addition to the Fc region. An example of an Fc region is the Fc region of an immunoglobulin. An antibody may have a glycosylation chain attached. For example, an antibody may have a glycosylation chain attached to at least its Fc region. An antibody may be a monoclonal antibody or a polyclonal antibody. An example of an antibody is an immunoglobulin. An example of an immunoglobulin is IgG, IgM, IgA, IgD, and IgE. An example of an immunoglobulin is IgG, in particular. An example of an IgG is IgG1, IgG2, IgG3, and IgG4. Among the sugar chains attached to antibodies, those that may particularly contribute to antibody separation include G0, G0F, G1, G0F+GN, G1Fa, G1Fb, G1F+GN, G2, G2F, G1F+SA, G2F+SA, G2F+2SA, G2F+GN, G2+SA, G2+2SA, S1, S2, and S3 (GN stands for bisecting GlcNAc, F for fucose, and SA for sialic acid).

[0027] Human-derived antibodies typically contain antibodies with sialic acid (SA). The content of sialic acid in human-derived antibodies can be, for example, about 0.1 to 20% by weight of the total antibody content. Human-derived antibodies often have two sialic acids bound to the terminal sugar chains. Furthermore, human-derived antibodies typically contain bisecting GlcNAc (GN) in an amount of about 1 to 20% by weight of the total antibody content. On the other hand, hamster- and mouse-derived antibodies typically do not contain bisecting GlcNAc and have zero or one sialic acid bond at the terminal sugar chains.

[0028] The antibody subjected to the adsorption step may be a mixture containing multiple types of antibody molecules. Specifically, the antibody subjected to the adsorption step may be a mixture containing multiple types of antibody molecules with different sugar chain structures. More specifically, the antibody subjected to the adsorption step may be a mixture containing multiple types of antibody molecules with different sugar chain structures attached to the Fc region.

[0029] The term "Fc-binding protein" is not particularly limited, as long as it is a polypeptide that has the ability to bind to the Fc region of an antibody contained in a sample and can recognize differences in the antibody's sugar chain structure (e.g., the sugar chain structure of the Fc region). For example, when the antibody is derived from a human, the Fc-binding protein can be a human Fc-binding protein. Preferred examples of human Fc-binding proteins include human Fc receptors. Human Fc receptors include the human Fcγ receptor, which is a receptor for human immunoglobulin G (IgG), the human Fcα receptor, which is a receptor for human immunoglobulin A (IgA), the human Fcδ receptor, which is a receptor for human immunoglobulin D (IgD), and the human Fcε receptor, which is a receptor for human immunoglobulin E (IgE), and any of these receptors can be used as the human Fc-binding protein in the present invention. As used herein, a "human-derived antibody" is any gamma globulin (antibody) that has at least a human-derived Fc region, and may be a human antibody, a humanized antibody, or a chimeric antibody.

[0030] Specific examples of human Fcγ receptors include polypeptides comprising at least a partial sequence of the extracellular region of human FcγRI (CD64), human FcγRIIa (CD32a), human FcγRIIb (CD32b), human FcγRIIc (CD32c), human FcγRIIIa (CD16a), or human FcγRIIIb (CD16b), as well as polypeptides in which some of the amino acid residues constituting the polypeptides have been substituted, deleted, inserted, and / or added. Among these, polypeptides comprising at least a partial sequence of the extracellular region of human FcγRIIIa and polypeptides in which some of the amino acid residues constituting the polypeptides have been substituted, deleted, inserted, and / or added are preferred as human Fcγ receptors used as human Fc-binding proteins in the present invention.

[0031] Specific examples of polypeptides comprising at least a partial sequence of the extracellular region of human FcγRIIIa, or polypeptides in which some of the amino acid residues constituting such polypeptides have been substituted, deleted, inserted, and / or added, include the polypeptides described in (i) to (iii) below. (i) a polypeptide comprising a sequence consisting of amino acid residues 17 to 192 set forth in SEQ ID NO: 1, in which at least valine at position 176 set forth in SEQ ID NO: 1 is substituted with phenylalanine; (ii) a polypeptide comprising a sequence consisting of amino acid residues 17 to 192 set forth in SEQ ID NO: 1, in which at least valine at position 176 set forth in SEQ ID NO: 1 is substituted with phenylalanine, and further having substitutions, deletions, insertions, and / or additions of one or several amino acid residues at one or several positions other than position 176, and having antibody-binding activity; (iii) A polypeptide having an amino acid sequence that is 70% or more identical to the sequence consisting of amino acid residues 17 to 192 of SEQ ID NO: 1, in which the amino acid residue corresponding to valine at position 176 of SEQ ID NO: 1 is substituted with phenylalanine, and which has antibody-binding activity.

[0032] An example of the polypeptide described in (ii) above is: a polypeptide comprising at least the amino acid residues 24 to 199 of the amino acid sequence set forth in SEQ ID NO: 2; Fc-binding proteins disclosed in JP 2015-086216 A; Fc-binding proteins disclosed in JP 2016-169197 A; Fc-binding proteins disclosed in JP 2017-118871 A; Fc-binding proteins disclosed in JP 2018-197224 A; Fc-binding proteins disclosed in WO2019 / 083048; Examples include:

[0033] Examples of the substitution, deletion, insertion, and addition described in (ii) above include the substitutions of amino acid residues disclosed in the aforementioned publications (JP 2015-086216 A, JP 2016-169197 A, JP 2017-118871 A, JP 2018-197224 A, and WO 2019 / 083048). The term "one or several" in (ii) above may mean, for example, 1 to 50, preferably 1 to 40, more preferably 1 to 30, even more preferably 1 to 20, and particularly preferably 1 to 10. The substitution of "one or several" amino acid residues may occur at positions other than those disclosed in the above-mentioned publications, for example, as long as the antibody has binding activity to the antibody.

[0034] In (iii) above, "homology" refers to similarity or identity, and can be determined using an alignment program such as BLAST (Basic Local Alignment Search Tool) or FASTA. For example, "amino acid sequence identity" may refer to the identity between amino acid sequences calculated using blastp, specifically, the identity between amino acid sequences calculated using blastp with default parameters. The homology may be 70% or more, and may be 80% or more, 85% or more, 90% or more, or 95% or more (e.g., 96% or more, 97% or more, 98% or more, 99% or more).

[0035] Furthermore, in the present invention, the "position" of each amino acid residue refers to the order in which the first methionine is placed as position 1 in the amino acid sequence set forth in each SEQ ID NO. Therefore, "position 176" according to the present invention refers to position 176 in the amino acid sequence set forth in SEQ ID NO: 1. Furthermore, "the amino acid residue corresponding to valine at position 176 in SEQ ID NO: 1" refers to an amino acid residue in the amino acid sequence having 70% or more homology, which is arranged at the same position as valine at position 176 in the amino acid sequence set forth in SEQ ID NO: 1, when the amino acid sequence is aligned with the sequence consisting of amino acid residues 17 to 192 in SEQ ID NO: 1.

[0036] An Fc-binding protein can be produced, for example, by expressing a gene encoding the Fc-binding protein in a host harboring the gene. The gene encoding the Fc-binding protein can be obtained, for example, by cloning, chemical synthesis, mutagenesis, or a combination thereof. The host is not particularly limited as long as it can express the Fc-binding protein. Examples of the host include animal cells, insect cells, and microorganisms. Examples of animal cells include COS cells, CHO cells, Hela cells, NIH3T3 cells, and HEK293 cells. Examples of insect cells include Sf9 cells and BTI-TN-5B1-4 cells. Examples of microorganisms include yeast and bacteria. Examples of yeast include yeasts of the genus Saccharomyces, such as Saccharomyces cerevisiae, yeasts of the genus Pichia, such as Pichia pastoris, and yeasts of the genus Schizosaccharomyces, such as Schizosaccharomyces pombe. Examples of bacteria include bacteria of the genus Escherichia, such as Escherichia coli. Examples of Escherichia coli include the W3110 strain, the JM109 strain, and the BL21(DE3) strain. Fc-binding proteins can also be produced, for example, by expressing a gene encoding the Fc-binding protein in a cell-free protein synthesis system.

[0037] In the present invention, the term "insoluble carrier" refers to a carrier that is insoluble in a liquid passed through a column (e.g., a liquid used for antibody adsorption or elution, such as an equilibration liquid or an elution liquid). The insoluble carrier may have a functional group (e.g., a hydroxy group) for covalently immobilizing an Fc-binding protein. Examples of insoluble carriers include carriers derived from inorganic substances such as zirconia, zeolite, silica, and coated silica; carriers derived from natural organic polymers such as cellulose, agarose, and dextran; and carriers derived from synthetic organic polymers such as polyacrylic acid, polystyrene, polyacrylamide, polymethacrylamide, polymethacrylate, and vinyl polymers.

[0038] The Fc-binding protein is immobilized on an insoluble carrier. The Fc-binding protein can be immobilized on the carrier by covalent bonding, for example, by utilizing a functional group (e.g., a hydroxyl group) possessed by the insoluble carrier for covalently immobilizing the Fc-binding protein. For example, if the insoluble carrier has hydroxyl groups on its surface, an activator can be used to form an activated group capable of covalently bonding to the Fc-binding protein, and the activated group can then be covalently bonded to the Fc-binding protein to achieve immobilization. Specific examples of activators for hydroxyl groups include epichlorohydrin (which forms an epoxy group as the activated group), 1,4-butanediol diglycidyl ether (which forms an epoxy group as the activated group), tresyl chloride (which forms a tresyl group as the activated group), and vinyl bromide (which forms a vinyl group as the activated group). Alternatively, the hydroxyl group can be converted to an amino group, carboxyl group, or the like, and then activated by the action of an activator. Specific examples of activators for amino groups, carboxyl groups, etc. include N-succinimidyl 3-maleimidopropionate (which forms a maleimide group as the activating group), 1,1'-carbonyldiimidazole (which forms a carbonylimidazole group as the activating group), and halogenated acetic acids (which form a haloacetyl group as the activating group).

[0039] A blood-derived sample collected from a subject in a sample collection step is added to a column (hereinafter also referred to as an "antibody separating agent column") packed with an insoluble carrier (hereinafter also referred to as an "antibody separating agent") on which an Fc-binding protein has been immobilized, thereby allowing the antibodies contained in the sample to be adsorbed onto the antibody separating agent. The blood-derived sample can be added to the column using a liquid delivery means such as a pump. Adding a liquid to a column is also referred to as "delivering a liquid to the column." The conditions for the adsorption step, such as the amount of blood-derived sample added, the type of liquid phase, the liquid phase delivery rate, and the column temperature, are not particularly limited as long as the antibodies contained in the sample can be adsorbed onto the antibody separating agent. The conditions for the adsorption step can be appropriately set depending on various conditions, such as the type of antibody, the type of Fc-binding protein, the type of insoluble carrier, and the scale of the column. Examples of the liquid phase include the equilibration liquid described below. For example, when the column has an inner diameter of 4.6 mm, the liquid flow rate may be 0.1 mL / min to 2.0 mL / min, 0.2 mL / min to 1.5 mL / min, or 0.4 mL / min to 1.2 mL / min. The liquid flow rate may be set, for example, to be proportional to the square of the inner diameter of the column. The column temperature may be, for example, 0°C to 50°C.

[0040] <2> Equilibration process The equilibration step is a step of equilibrating the antibody separating agent column with an equilibration solution (also referred to as "equilibration buffer" for the same purpose) to equilibrate the antibody adsorbed to the antibody separating agent in the adsorption step. The column may be equilibrated with the equilibration solution before the antibody-containing solution is added to the column. That is, the present invention may include a step of adding an equilibration solution to the column to equilibrate it before the adsorption step.

[0041] Equilibration removes from the antibody separating agent column antibodies that do not bind to the Fc-binding protein immobilized on the insoluble carrier, or antibodies that adsorb to the antibody separating agent in the adsorption step but cannot adsorb in the equilibration buffer. The unadsorbed fraction is the fraction containing antibodies that cannot adsorb (desorb) to the antibody separating agent in the equilibration step. This fraction is the region in which the peak detected after adding a blood-derived sample to the column reaches its minimum value during equilibration. A separation time that separates the unadsorbed fraction from the peak region detected after adding the eluent is preferable for high separation accuracy. A constant detection value between the unadsorbed fraction and the peak region detected after adding the eluent indicates that the unadsorbed fraction has been sufficiently removed from the column by the equilibration step. The term "constant value" includes not only a constant value but also a state in which the detection value changes with a constant slope.

[0042] Examples of the equilibration solution (equilibration buffer solution) include aqueous buffer solutions. The equilibration solution is a weakly acidic to weakly alkaline buffer solution with a pH greater than 5.0 and less than 9.0, preferably a buffer solution with a pH of 5.2 or greater and a pH of 8.0 or less, and more preferably a buffer solution with a pH of 5.4 or greater and a pH of 7.5 or less. The components of the buffer solution can be selected appropriately depending on various conditions, such as the pH of the buffer solution. Examples of buffer solution components include phosphoric acid, acetic acid, formic acid, MES (2-Morpholinoethanesulfonic acid), MOPS (3-Morpholinopropanesulfonic acid), citric acid, succinic acid, glycine, and piperazine. Furthermore, a salt may be further added to the buffer solution, and the salt is not particularly limited as long as it is a salt that can be easily imagined by a person skilled in the art, such as sodium chloride or potassium chloride.

[0043] <3> Elution process The elution step is a step in which an elution solution (hereinafter also referred to as "elution buffer") is added to the antibody separation agent column equilibrated in the equilibration step, the antibodies adsorbed to the separation agent are eluted, and an antibody separation pattern is obtained.

[0044] That is, the antibodies adsorbed to the antibody separating agent can be eluted by adding an elution solution to the column. The conditions for the elution step, such as the type of elution solution, the elution solution delivery format, the liquid phase delivery rate, and the column temperature, are not particularly limited as long as the antibodies are separated in the desired manner, e.g., as long as the desired separation pattern is obtained. The conditions for the elution step can be appropriately set depending on various conditions, such as the type of antibody, the type of Fc-binding protein, the type of insoluble carrier, and the scale of the column. The elution solution can be a solution that weakens the affinity between the antibody and the Fc-binding protein. Examples of the elution solution include aqueous buffer solutions with a lower pH than the liquid phase before elution (e.g., the equilibration solution). Specific examples of the elution solution include acidic buffer solutions with a pH of 2.5 to 4.5. For example, if the liquid phase before elution (e.g., the equilibration solution) is a weakly acidic to weakly alkaline buffer solution with a pH of 5.0 to 8.0, the elution solution can be an acidic buffer solution with a pH of 2.5 to 4.5. The components of the buffer solution can be appropriately selected depending on various conditions, such as the pH of the buffer solution. Examples of buffer components include phosphoric acid, acetic acid, formic acid, MES (2-morpholinoethanesulfonic acid), MOPS (3-morpholinopropanesulfonic acid), citric acid, succinic acid, glycine, and piperazine. The eluent may be delivered in a gradient or isocratic manner. The eluent may be delivered in a gradient manner, particularly by increasing the ratio of the eluent in the liquid phase. The gradient may be, for example, a linear gradient, a stepwise gradient, or a combination thereof. Specifically, the gradient may be set so that the ratio of the eluent in the liquid phase increases from 0% (v / v) to 100% (v / v) over a period of 10 to 60 minutes, 15 to 50 minutes, or 20 to 40 minutes. For example, when the inner diameter of the column is 4.6 mm, the liquid delivery rate may be 0.1 mL / min to 2.0 mL / min, 0.2 mL / min to 1.5 mL / min, or 0.4 mL / min to 1.2 mL / min. The liquid delivery rate may be set, for example, to be proportional to the square of the inner diameter of the column.The column temperature may be, for example, 0°C or higher and 50°C or lower.

[0045] The elution step may result in the production of a separated antibody. The separated antibody may be obtained, for example, as an elution fraction containing the antibody. That is, the separated antibody is obtained by collecting the elution fraction containing the separated antibody. The elution fraction can be collected, for example, by a conventional method. Specifically, the elution fraction can be collected, for example, by an automatic fraction collector such as an autosampler. Furthermore, the separated antibody may be recovered from the elution fraction. The separated antibody can be recovered from the elution fraction, for example, by a conventional method. Specifically, the separated antibody can be recovered from the elution fraction by, for example, a known method used for separating and purifying proteins.

[0046] The antibody separation pattern can be obtained by detecting the antibody with a detector, such as an ultraviolet-visible detector or a mass detector. The antibody separation pattern can be a chromatogram of the antibody elution.

[0047] <4> Peak area calculation process The peak area calculation step is a step of extracting elution peaks from the antibody separation pattern obtained in the elution step, calculating the area of each extracted elution peak, and then calculating the peak area ratio. The antibody separation pattern used for elution peak detection may be used for elution peak extraction as is, or after appropriate correction such as baseline correction. The elution peak for which the peak area is to be calculated is hereinafter also referred to as the "target peak." Note that elution peaks with a peak area % of less than 1%, as described below, may be excluded from the target peaks.

[0048] The target peak can be selected appropriately depending on various conditions. For example, when an insoluble carrier on which a polypeptide comprising at least a partial sequence of the extracellular region of human FcγRIIIa or a polypeptide in which some of the amino acid residues constituting said polypeptide have been substituted, deleted, inserted, and / or added (hereinafter also referred to as a "human FcγRIIIa ligand") is immobilized is used as an antibody separation agent, three elution peaks are extracted from the antibody separation pattern (named the first, second, and third peaks in order of decreasing binding affinity to the human FcγRIIIa ligand), and any of the first to third peaks may be used as the target peak. Furthermore, when the aforementioned insoluble carrier onto which the human FcγRIIIa ligand has been immobilized is used as the antibody separation agent and the elution step is performed by gradient elution based on pH change, the first peak may be designated, for example, as the peak that first elutes when the liquid phase pH is 5.4 or less, 5.2 or less, 5.0 or less, or 4.8 or less, or the peak that elutes during the period when the liquid phase pH is 5.4 to 4.4, 5.2 to 4.5, or 5.0 to 4.6. The pH of the liquid phase is calculated using the following formula (I) when the pH of the liquid phase (e.g., equilibration solution) before the start of elution is X, the pH of the elution solution is Y, and the proportion of the elution solution in the liquid phase is Z%. The pH at which the peak elutes is appropriately corrected taking into account the volume of the flow path, such as the volume of the column.

[0049] pH of the liquid phase = X-((XY)×Z[%]) (I).

[0050] The present invention predicts overall survival time by using relative values, rather than absolute values, of target peak areas. Examples of relative values include the ratio of a specific target peak area to another target peak area, or the ratio of a specific target peak area to the sum of all target peak areas. As the other target peaks, one target peak may be used, or two or more target peaks may be used in combination. A specific example of a peak area ratio is peak area %. "Peak area %" refers to the area ratio (%) of a specific target peak to the sum of all target peak areas.

[0051] In addition, when calculating the target peak area, corrections such as correction based on the peak obtained with an internal standard or correction based on the characteristics of the subject may be made. For example, the peak area may be corrected based on the age of the subject. That is, for example, if the peak area is affected by the age of the subject, the peak area may be corrected based on the age of the subject before being used in the prediction step.

[0052] <5> Forecasting Process The prediction step is a step of predicting the overall survival time of a subject suffering from cancer using the peak area ratio (relative value of the target peak area) obtained in the peak area calculation step as an index.

[0053] Cancers include brain tumors, breast cancer, uterine cancer, cervical cancer, ovarian cancer, esophageal cancer, stomach cancer, appendix cancer, colon cancer, liver cancer, gallbladder cancer, bile duct cancer, pancreatic cancer, adrenal cancer, gastrointestinal stromal tumor (GIST), mesothelioma, head and neck cancer, kidney cancer, lung cancer, osteosarcoma, Ewing's sarcoma, chondrosarcoma, prostate cancer, testicular tumors, renal cell carcinoma, bladder cancer, rhabdomyosarcoma, skin cancer, and anal cancer. Cancers particularly include lung cancer.

[0054] The prediction of the overall survival time of a subject refers to predicting the survival time of the subject from the start date of treatment allocation or the start date of treatment in a clinical trial, and also includes risk assessment of whether the survival prognosis is good or bad. For example, in a lung cancer patient, if the peak area ratio of the third peak area / total area is ≥ 43.6%, the overall survival time (median) can be determined to be 900 days or more (good survival prognosis). On the other hand, if the third peak area / total area is < 43.6%, the overall survival time (median) can be determined to be 600 days or less (poor survival prognosis).

[0055] The prediction step can be performed, for example, using the magnitude of the peak area ratio value (i.e., whether the peak area ratio value is high or low) as an index. The magnitude of the peak area ratio value can be determined, for example, by comparing the peak area ratio value with a predetermined threshold. In other words, the prediction step may include, for example, a step of comparing the peak area ratio value with a threshold. That is, "a high peak area ratio value" may mean, for example, that the peak area ratio value is high relative to the threshold. "a high peak area ratio value relative to the threshold" may mean, for example, that the peak area ratio value is equal to or greater than the threshold, that the peak area ratio value exceeds the threshold, or that the peak area ratio value is statistically significantly higher than the threshold. Specifically, "the peak area ratio value is high relative to the threshold value" may mean, for example, that the peak area ratio value is 1.01 times or more, 1.02 times or more, 1.03 times or more, 1.05 times or more, 1.07 times or more, 1.1 times or more, 1.2 times or more, 1.3 times or more, 1.5 times or more, 1.7 times or more, 2 times or more, 2.5 times or more, or 3 times or more of the threshold value. Furthermore, "the peak area ratio value is low" may mean, for example, that the peak area ratio value is low relative to the threshold value. "The peak area ratio value is low relative to the threshold value" may mean, for example, that the peak area ratio value is equal to or less than the threshold value, that the peak area ratio value is less than the threshold value, or that the peak area ratio value is statistically significantly lower than the threshold value. Specifically, "the value of the peak area ratio is low relative to the threshold value" may mean, for example, that the value of the peak area ratio is 0.99 times or less, 0.98 times or less, 0.97 times or less, 0.95 times or less, 0.93 times or less, 0.9 times or less, 0.85 times or less, 0.8 times or less, 0.7 times or less, 0.6 times or less, 0.5 times or less, 0.4 times or less, or 0.3 times or less of the threshold value.

[0056] The peak area ratio value may be divided into a risk range based on, for example, a threshold value. The peak area ratio value may be divided into a non-risk range based on, for example, a threshold value. Specifically, the peak area ratio value may be divided into a risk range and a non-risk range based on, for example, a threshold value. The "risk range" may refer to a range in which the peak area ratio value indicates a high probability that the subject is at risk of having a short overall survival time (hereinafter simply referred to as "risk"). The "non-risk range" may refer to a range in which the peak area ratio value indicates a high probability that the subject is not at risk. That is, if the peak area ratio value is within the risk range, the subject may be determined to be at risk or at high risk. On the other hand, if the peak area ratio value is within the non-risk range, the subject may be determined to be at no risk or at low risk. For example, in a lung cancer patient, if the peak area ratio (third peak area / total area) is ≧43.6%, the 3-year survival rate can be determined to be 40% or higher (low risk). On the other hand, if the third peak area / total area is <43.6%, it can be determined that the 3-year survival rate is 20% or less (high risk).

[0057] The threshold value can be appropriately set by a person skilled in the art depending on various conditions, such as the content of the peak area ratio and the desired accuracy of determination. The threshold value may be set for each symptom to be determined, such as disease or aging. The means for determining the threshold value is not particularly limited. The threshold value can be determined, for example, according to a known method used in data analysis for dividing a population into two groups.

[0058] The threshold can be determined, for example, based on the peak area ratio value of an antibody sample obtained from a control subject. The peak area ratio obtained from a control subject is also referred to as the "control peak area ratio." The control peak area ratio may be used to determine the threshold and then used in the detection step. Specifically, the control peak area ratio may be used to determine the threshold and then used for comparison with the peak area ratio. In other words, the detection step may include, for example, a step of comparing the peak area ratio with the control peak area ratio. When comparing two different data groups, statistical probability (P value) can be used to evaluate whether the difference between the peak area ratios obtained from the two different sample groups is significant. It is said that the smaller the P value, the more significant the evaluation result, and when the P value is less than the significance level, the evaluation result indicates a statistically significant difference. The significance level is generally 10%.

[0059] Controls include positive controls and negative controls. A "positive control" may refer to an individual who can be determined to be at risk or high risk. A "negative control" may refer to an individual who can be determined to be at no risk or low risk. Positive controls include individuals who currently have or have previously had cancer, individuals with advanced cancer pathology, or individuals with a combination of these characteristics. Negative controls include individuals who do not currently have or have never had cancer (particularly the same cancer as the cancer being detected for risk), individuals with no advanced cancer pathology, or individuals with a combination of these characteristics. The threshold may be determined solely based on the peak area ratio value calculated from the measurement of the positive control, solely based on the peak area ratio calculated from the measurement of the negative control, or based on the peak area ratio value calculated from the measurement of both the positive and negative controls. Typically, the threshold may be determined based on the peak area ratio value calculated from the measurement of both blood-derived samples of the positive and negative controls. The number of positive and negative controls to be measured is not particularly limited, as long as a threshold value that enables risk determination with the desired accuracy is obtained. The number of people measured for the positive control and the negative control may each be one, two, or more. The number of people measured for the positive control and the negative control may each usually be more than one. The number of people measured for the positive control and the negative control may each be, for example, 5 or more, 10 or more, 20 or more, or 50 or more. The number of people measured for the positive control and the negative control may each be, for example, 10,000 or less, 1,000 or less, or 100 or less.

[0060] When determining the threshold value solely based on the peak area ratio value calculated by measuring the positive control, the threshold may be set, for example, as a value selected from the range from the upper limit to the lower limit of the peak area ratio values calculated by measuring multiple positive control individuals, e.g., the average value. Furthermore, for example, the threshold may be determined so that a predetermined percentage of the positive control falls within the critical range in the distribution of peak area ratio values calculated by measuring multiple positive control individuals. The predetermined percentage may be, for example, 70% or more, 80% or more, 90% or more, 95% or more, 97% or more, or 100%.

[0061] When determining the threshold value solely based on the peak area ratio value measured and calculated for the negative control, the threshold may be set, for example, as a value selected from the range of the peak area ratio values measured and calculated for multiple negative control individuals, e.g., the average value. Furthermore, for example, the threshold may be determined so that a predetermined percentage of the negative control falls within a non-risk range in the distribution of peak area ratio values measured and calculated for multiple negative control individuals. The predetermined percentage may be, for example, 70% or more, 80% or more, 90% or more, 95% or more, 97% or more, or 100%.

[0062] When determining the threshold based on both the peak area ratio values measured and calculated for the positive control and the peak area ratio values measured and calculated for the negative control, the threshold may be determined, for example, so that a predetermined percentage of the positive control falls within the risk range and a predetermined percentage of the negative control falls within the non-risk range. It is preferable that both the percentage of positive controls falling within the risk range and the percentage of negative controls falling within the non-risk range are high. These percentages may be, for example, 70% or more, 80% or more, 90% or more, 95% or more, 97% or more, or 100%. If it is difficult to increase both of these percentages, the threshold may be set so that one of the percentages is preferentially increased depending on various conditions, such as the intended use of the prediction results according to the present invention. For example, to reduce the false negative rate, the threshold may be set so that the percentage of positive controls falling within the risk range is preferentially increased.

[0063] The threshold may be determined, for example, using software. For example, statistical analysis software may be used to determine a threshold that allows for the most appropriate statistical discrimination between the negative control and the positive control. Examples of such software include statistical analysis software such as "R."

[0064] The control may also be the subject itself (e.g., a past subject). That is, for example, the risk in a subject may be determined using fluctuations in separation data from the subject as an index. A "high peak area ratio value" may include an increase in the peak area ratio value. An "increased peak area ratio value" may specifically mean that the peak area ratio value has increased compared to a past value. A "low peak area ratio value" may include a decrease in the peak area ratio value. A "decreased peak area ratio value" may specifically mean that the peak area ratio value has decreased compared to a past value. That is, a past value may also be used as the threshold. A "past value" refers to the peak area ratio value of an antibody sample obtained from a target subject at a certain time in the past. The target subject at a certain time in the past may be, for example, a positive control or a negative control.

[0065] When the variation in the peak area ratio in a subject is used as an index, an increase or decrease in the risk in the subject may be determined. "At or high risk" may include a case where the risk has increased. "Increased risk" may specifically mean that the risk has increased compared to a certain point in the past. Furthermore, "no or low risk" may include a case where the risk has decreased. "Decreased risk" may specifically mean that the risk has decreased compared to a certain point in the past.

[0066] The phrase "obtaining a certain peak area ratio value and using it as an index for risk detection" does not necessarily mean obtaining the peak area ratio value itself and using it as an index for risk detection, but also includes obtaining other values reflecting the peak area ratio value and using them as an index for detection. For example, when the aforementioned insoluble carrier on which the human FcγRIIIa ligand is immobilized is used as the antibody separation agent, the first, second, and third peaks are extracted as elution peaks. In this case, the phrase "obtaining the peak area % of the first peak and using it as an index for risk detection" does not necessarily mean obtaining the peak area % of the first peak itself and using it as an index for risk detection, but also includes obtaining other values reflecting the peak area % of the first peak, such as the sum of the peak area % of the second to third peaks, and using them as an index for detection. In either case, when the peak area ratio used for risk detection consists of the first to third peaks, the values of the threshold and the like are appropriately corrected depending on the peak area ratios. For example, if the elution peaks consist of the first, second, and third peaks, then the relationship "X = 100% - Y" holds, where X is the peak area percentage of the first peak and Y is the total peak area percentage of the second and third peaks. Therefore, when the total peak area percentage of the second and third peaks (i.e., "Y") is used as the detection index instead of the peak area percentage of the first peak itself (i.e., "X"), "X satisfies a certain criterion (e.g., is low or high, or falls within a certain range)" should be interpreted as "the corrected value of Y (i.e., "100% - Y") satisfies the criterion."

[0067] The risk detection results may be used as an indicator for determining whether to implement risk-reducing treatment (hereinafter also referred to as "risk reduction treatment") on a subject. In other words, by implementing the prediction method of the present invention, an indicator for determining whether to implement risk reduction treatment on a subject can be obtained. That is, for example, if a subject is determined to be at risk or at high risk by the detection method of the present invention, a decision may be made to implement risk reduction treatment on the subject. The detection method of the present invention may be used, for example, alone or in combination with other means, as an indicator for determining whether to implement risk reduction treatment on a subject. For example, for a condition determined to be at risk or at high risk in a subject by the prediction method of the present invention, a definitive diagnosis may be made by other means, and then a decision may be made to implement risk reduction treatment on the subject. Risk reduction treatment may be a medical or non-medical procedure. Examples of medical procedures include starting, stopping, or changing medication and selecting or changing treatment methods such as radiation therapy or surgical treatment. Examples of non-medical procedures include changing diet and starting, stopping, or changing exercise, but there are no particular limitations as long as they are within the scope of what a person skilled in the art can easily imagine. [Example]

[0068] The present invention will be described in more detail below with reference to examples and comparative examples, but the present invention is not limited to these examples.

[0069] <Preparation of antibody separation column (FcR9_F column)> The Fc-binding protein FcR9_F_Cys (SEQ ID NO: 2) obtained by the method of JP 2018-197224 A was immobilized on an insoluble carrier (gel) by the method described below to prepare an FcR9_F column. In FcR9_F_Cys (SEQ ID NO: 2), the portion from the first methionine (Met) to the 22nd alanine (Ala) is the improved PelB signal peptide, the portion from the 24th glycine (Gly) to the 199th glutamine (Gln) is the amino acid sequence of the Fc-binding protein FcR9_F (JP 2018-197224 A) (corresponding to the region from the 17th to the 192nd of SEQ ID NO: 1), and the portion from the 200th glycine (Gly) to the 207th glycine (Gly) is the cysteine tag sequence. Furthermore, the FcR9_F is a polypeptide consisting of the amino acid residues 17 to 192 of native human FcγRIIIa shown in SEQ ID NO: 1, with the following 10 amino acid substitutions: Substitution of valine (Val) at position 27 of SEQ ID NO: 1 (position 34 of SEQ ID NO: 2) with glutamic acid (Glu) Substitution of phenylalanine (Phe) at position 29 of SEQ ID NO: 1 (position 36 of SEQ ID NO: 2) with isoleucine (Ile) Tyrosine (Tyr) at position 35 of SEQ ID NO: 1 (position 42 of SEQ ID NO: 2) is replaced with asparagine (Asn) Substitution of glutamine (Gln) at position 48 of SEQ ID NO: 1 (position 55 of SEQ ID NO: 2) with arginine (Arg) Phenylalanine (Phe) at position 75 of SEQ ID NO: 1 (position 82 of SEQ ID NO: 2) is replaced with leucine (Leu) Substitution of asparagine (Asn) at position 92 of SEQ ID NO: 1 (position 99 of SEQ ID NO: 2) with serine (Ser) Substitution of valine (Val) at position 117 of SEQ ID NO: 1 (position 124 of SEQ ID NO: 2) with glutamic acid (Glu) Substitution of glutamic acid (Glu) at position 121 of SEQ ID NO: 1 (position 128 of SEQ ID NO: 2) with glycine (Gly) Substitution of phenylalanine (Phe) at position 171 of SEQ ID NO: 1 (position 178 of SEQ ID NO: 2) with serine (Ser) Valine (Val) at position 176 of SEQ ID NO: 1 (position 183 of SEQ ID NO: 2) was substituted with phenylalanine (Phe).

[0070] (1) The hydroxyl groups on the surface of 2 mL of hydrophilic vinyl polymer for separation agent (manufactured by Tosoh Corporation: packing material for liquid chromatography) were activated with iodoacetyl groups, and then 4 mg of FcR9_F_Cys obtained by the method of JP 2018-197224 A was reacted to obtain an FcR9_F immobilized gel.

[0071] (2) 1.2 mL of the FcR9_F-immobilized gel prepared in (1) was packed into a φ4.6 mm × 50 mm stainless steel column to prepare an FcR9_F column.

[0072] (Reference Example 1) <Separation of gamma globulin from lung cancer patients and healthy individuals> (1) Serum samples were obtained from 97 lung cancer patients (including 75 with a history of prior chemotherapy) who had not yet received immune checkpoint inhibitors, and from 50 healthy individuals provided by the Tohoku Medical Megabank Organization, after obtaining informed consent. The serum samples were diluted 20-fold with PBS (Phosphate Buffered Saline) (pH 7.4) and then passed through a 0.2 μm filter (Merck Millipore) to prepare serum samples.

[0073] (2) The FcR9_F column prepared above was connected to a high-performance liquid chromatography system (manufactured by Tosoh Corporation) and equilibrated with 10 mM citrate buffer (pH 6.5) containing 100 mM sodium chloride (hereinafter also referred to as "equilibration solution"). Then, 10 μL of a 1 mg / mL rituximab (manufactured by Zenyaku Kogyo, trade name: Rituxan Intravenous Infusion 100 mg) antibody solution was added as a standard substance at a flow rate of 1.2 mL / min. The detector was used to acquire data every 1 / 5 second.

[0074] (3) After washing with the equilibration solution for 7 minutes at a flow rate of 1.2 mL / min, the adsorbed gamma globulin was eluted with a pH gradient (a gradient in which the eluate reached 100% in 11 minutes) using 10 mM citrate buffer (pH 4.5) containing 500 mM sodium chloride (hereinafter also referred to as the "eluate"), and a separation pattern was obtained.

[0075] (4) After the analysis of the standard substance, 10 μL of the serum sample prepared in (1) was added as the measurement sample in the same manner as in (2) and (3), and the analysis was performed to obtain the gamma globulin separation pattern. The analysis was performed by alternately measuring the standard substance and the measurement sample.

[0076] (5) The separation patterns obtained in (3) and (4) were baseline corrected so that the detection values were 0 at both the time when the pH gradient started (7 min after the start of elution) and the time when the pH gradient ended (i.e., the eluate reached 100%) (18 min after the start of elution).

[0077] (6) From the baseline-corrected separation pattern of the reference material (Figure 1), the peak regions were defined as the two elution time regions where the derivative of the valley region between the three peaks detected between 7 and 18 minutes after the start of elution (Peak 1, Peak 2, and Peak 3, in order of shorter elution time (lowest binding ability to FcR9_F) was zero. That is, the peak region was defined as the range from 7 minutes after the start of elution to the elution time where the derivative of the valley region between Peak 1 and Peak 2 was zero. The peak region was defined as the range from the elution time where the derivative of the valley region between Peak 1 and Peak 2 was zero to the elution time where the derivative of the valley region between Peak 2 and Peak 3 was zero. The peak region was defined as the range from the elution time where the derivative of the valley region between Peak 2 and Peak 3 was zero to 18 minutes after the start of elution. The peak regions defined for the reference material were applied to the measurement sample (Figure 1) measured immediately after the analysis of the reference material, and the peak regions of the measurement sample were defined using the reference material.

[0078] (7)(6) Calculate the peak area of each peak region of the measurement sample defined, and calculate the percentage of each peak area from the value obtained by dividing the peak area by the total value of the peak areas between 7 minutes and 18 minutes after the start of elution (that is, the sum of the first peak area, the second peak area, and the third peak area).

[0079] The results of Reference Example 1 are shown in Figure 2. Compared with healthy subjects, in lung cancer patients, the value of the percentage of the first peak area of gamma globulin contained in the blood was significantly higher, and the value of the percentage of the third peak area was significantly lower.

[0080] (Example 1) <Blood antibody analysis using FcR9_F column (peak area ratio)> (1) As samples, only 97 specimens of lung cancer patients who had obtained informed consent before administration of any of the immune checkpoint inhibitors Nivolumab, Pembrolizumab, and Atezolizumab (including 75 specimens with a history of pre-chemotherapy treatment) were used, and the peak regions of the measurement samples were defined in the same manner as in Reference Example 1 (1) to (6).

[0081] (2) Calculate the peak area of each peak region of the measurement sample defined in (1), and calculate the ratio of each peak area from the value obtained by dividing the peak area by the total value of the peak areas between 7 minutes and 18 minutes after the start of elution, and the value obtained by dividing each peak area by each other.

[0082] (3) Based on the ratios of the peak areas calculated in (2), the correlation with the overall survival period was evaluated by obtaining the Spearman rank correlation coefficient. The significance of the obtained Spearman rank correlation coefficient was evaluated with P value < 0.1 being significant and P value < 0.05 being even more significant.

[0083] (Comparative Example 1) <Blood antibody analysis using FcR9_F column (peak area)> In Example 1 (3), the Spearman rank correlation coefficient was obtained in the same manner as in Example 2, except that the correlation with the overall survival period was evaluated based on the absolute value of each peak area.

[0084] The results of Example 1 and Comparative Example 1 are summarized and shown in Tables 1 and 2. Table 1 shows the results of analysis for all specimens subjected to measurement, and Table 2 shows the results of analysis for specimens with a pretreatment history before chemotherapy.

[0085] From Table 1, significant differences were observed between the overall survival period in terms of the peak area ratios of the second peak area / total area, the third peak area / total area, and the third peak area / second peak area (Example 1). On the other hand, when evaluated based on the absolute values of each peak area, no significant difference was observed between the overall survival period (Comparative Example 1). From the above results, it can be seen that each peak area ratio has a higher correlation with the overall survival period as an evaluation index.

[0086] From Table 2, significant differences were observed between the overall survival period in terms of the first peak area / total area, the second peak area / total area, the third peak area / total area, the third peak area / first peak area, and the third peak area / second peak area (Example 1). On the other hand, when evaluated based on the absolute values of each peak area, no significant difference was observed between the overall survival period (Comparative Example 1). From the above results, it can be seen that each peak area ratio has a higher correlation with the overall survival period as an evaluation index. Also, when evaluation was performed on specimens with a pretreatment history before chemotherapy, the value of the correlation coefficient showed a stronger correlation than when evaluation was performed on all specimens subjected to measurement, and furthermore, the P-value also showed a more significant result. Therefore, it can be seen that the prediction accuracy of the overall survival period has been improved.

[0087] [Table 1]

[0088] [Table 2]

[0089] (Comparative Example 2) Blood antibody analysis using an FcR9_F column (progression-free survival period) In Example 1(3), the Spearman's rank correlation coefficient was determined in the same manner as in Example 1, except that the correlation with the progression-free survival period was evaluated based on each peak area ratio and each peak area.

[0090] The results of Comparative Example 2 are shown in Tables 3 and 4. Table 3 shows the results of analysis for all specimens subjected to measurement, and Table 4 shows the results of analysis for specimens with a pre-chemotherapy treatment history. In the results of analysis for specimens with a pre-chemotherapy treatment history (Table 4), a significant difference was observed between the progression-free survival period and the ratio of the third peak area to the second peak area (P = 0.080), and no other significant differences were observed. From the above results, it can be seen that, unlike the overall survival period, the correlation is poor in the progression-free survival period.

[0091] [Table 3]

[0092] [Table 4]

[0093] (Comparative Example 3) Blood antibody analysis using an FcR9_F column (after administration of an antibody drug) In Example 1(1), using blood collected from lung cancer patients after administration of any one of the immune checkpoint inhibitors Nivolumab, Pembrolizumab, and Atezolizumab, in Example 1(3), the Spearman's rank correlation coefficient was determined in the same manner as in Example 1, except that the correlation with the progression-free survival period and the overall survival period was evaluated based on each peak area ratio and each peak area.

[0094] The results of Comparative Example 3 are shown in Tables 5 and 6. Table 5 shows the results of analysis for all specimens subjected to measurement, and Table 6 shows the results of analysis for specimens with a pre-chemotherapy treatment history. No significant differences were confirmed in either the progression-free survival period, and only a significant difference was observed in the total survival period in terms of the second peak area / total area (P = 0.055 for all specimens [Table 5], P = 0.084 for specimens with a pre-chemotherapy treatment history [Table 6]). Compared with the results before administration of the antibody drug (Example 1), no significant differences were obtained in each peak area ratio, indicating that using a blood-derived sample before administration of the antibody drug rather than after administration has a higher correlation with the total survival period.

[0095]

Table 5

[0096]

Table 6

[0097] (Example 2) Blood antibody analysis using an FcR9_F column (Kaplan-Meier method, total survival period) In Example 1(3), for specimens divided into a high-value group and a low-value group using the median value of each peak area ratio calculated in Example 1(2) as a threshold value, the correlation with the total survival period was evaluated by the Kaplan-Meier method, and the significance was determined by the log-rank test to obtain the P value. Evaluation was performed in the same manner as in Example 1 for other aspects.

[0098] (Comparative Example 4) Blood antibody analysis using an FcR9_F column (Kaplan-Meier method, progression-free survival period) Evaluation was performed in the same manner as in Example 2, except that the correlation with the progression-free survival period was evaluated by the Kaplan-Meier method.

[0099] The results of Example 2 and Comparative Example 4 are summarized and shown in FIGS. 3 to 8. FIG. 3 shows the first peak area / total area, FIG. 4 shows the second peak area / total area, FIG. 5 shows the third peak area / total area, FIG. 6 shows the third peak area / first peak area, FIG. 7 shows the third peak area / second peak area, and FIG. 8 shows the second peak area / first peak area, respectively. Also, in each figure, (a) and (b) are the results of all specimens used for measurement, (b) and (d) are the results of specimens with a chemotherapy pretreatment history, respectively, (a) and (c) are the results of the progression-free survival period, and (b) and (d) are the results of the overall survival period, respectively. The median values as the thresholds for the high-value and low-value groups in each figure are as follows: first peak area / total area: 25.1%, second peak area / total area: 30.9%, third peak area / total area: 43.6%, third peak area / first peak area: 1.73, third peak area / second peak area: 1.38, and second peak area / first peak area: 1.24. No significant differences were observed in the correlations with the progression-free survival period (FIGS. 3 to 8 (a) and (c)). On the other hand, for the overall survival period, except for the result of analyzing the first peak area / total area for all specimens used for measurement (FIG. 3 (b)), the P value was less than 0.1 and a significant difference was observed (FIG. 3 (d) and FIGS. 4 to 8 (b) and (d)). The result of FIG. 3 (b) also had a P value of 0.1006, which can be said to be almost significant.

[0100] From FIGS. 3 (d), FIGS. 4 (b) and (d), it can be seen that the lower the values of the first peak area / total area and the second peak area / total area, the longer the overall survival period, and from FIGS. 5 (b) and (d), it can be seen that the higher the value of the third peak area / total area, the longer the overall survival period.

[0101] (Comparative Example 5) <Separation of gamma globulin derived from COPD patients)> As patient specimens, 42 specimens of COPD (chronic obstructive pulmonary disease) patients who gave informed consent were used, and the peak area percentages were calculated in the same manner as in Reference Example 1.

[0102] The results of Reference Example 1 and Comparative Example 5 are shown together in Figure 9. The P values shown in the figure are values obtained by 1-way ANOVA. Compared with COPD patients, who have smoking histories similar to those of lung cancer patients, lung cancer patients had significantly higher first peak area % values of gamma globulin in their blood and significantly lower third peak area % values. This result shows a similar tendency to that compared with healthy subjects, indicating that the significant changes in each gamma globulin peak area % values were due to the onset of cancer, rather than smoking history. [Industrial Applicability]

[0103] As described above, the present invention makes it possible to accurately predict the prognosis, particularly the overall survival time, of cancer patients. Clarifying the prognosis of a cancer patient provides important information for determining treatment strategies and monitoring treatment effects, and is therefore a useful indicator for selecting the optimal therapy. Prognostic diagnosis provides doctors with information regarding the risks and survival rates of the patient's condition, allowing them to select the optimal therapy, thereby reducing the risk of subjecting patients to unnecessary treatment. In this way, it not only contributes to saving costs for unnecessary treatment, but also contributes to improving patient prognosis by selecting the optimal treatment. Therefore, the present invention is useful in the development of companion diagnostics, as well as pharmaceuticals and medical devices used therein.

Claims

1. 1. A method for providing an index for predicting overall survival of a subject suffering from cancer, comprising: The method includes the following steps (1) to (3): (1) subjecting a blood-derived sample collected from the subject to a column packed with an insoluble carrier onto which an Fc-binding protein has been immobilized, and separating gamma globulins contained in the sample, thereby obtaining a separation pattern of the gamma globulins; (2) calculating the area of each peak from the separation pattern obtained in (1) and calculating the ratio of the areas; (3) using the ratio obtained in (2) as an index for predicting the overall survival time of the subject; the blood-derived sample is a sample collected before administration of an antibody drug to the subject; and the area ratio is the ratio of the area of a specific peak to the area of another peak, or the ratio of the area of a specific peak to the sum of all peak areas; method.

2. The method of claim 1, wherein the subject is a patient who has been previously treated with chemotherapy.

3. 3. The method of claim 1 or 2, wherein the cancer is lung cancer.

4. The method of any one of claims 1 to 3, wherein the Fc binding protein is a human Fcγ receptor.

5. The method of claim 4, wherein the human Fcγ receptor is a polypeptide selected from any one of the following (i) to (iii): (i) a polypeptide comprising a sequence consisting of amino acid residues 17 to 192 of the amino acid sequence set forth in SEQ ID NO: 1, in which at least valine at position 176 of SEQ ID NO: 1 is substituted with phenylalanine; (ii) A polypeptide comprising a sequence consisting of amino acid residues 17 to 192 of the amino acid sequence set forth in SEQ ID NO: 1, in which the amino acid sequence has at least a substitution of valine at position 176 set forth in SEQ ID NO: 1 with phenylalanine, and further has substitution, deletion, insertion and / or addition of one or several amino acid residues at one or several positions other than position 176, and has antibody-binding activity; (iii) A polypeptide having an amino acid sequence that is 70% or more identical to the sequence consisting of amino acid residues 17 to 192 of SEQ ID NO: 1, in which the amino acid residue corresponding to valine at position 176 of SEQ ID NO: 1 is substituted with phenylalanine, and which has antibody-binding activity.

Images