WO2023073075A1 - Biomarqueur pour le cancer sensible à un inhibiteur de point de contrôle immunitaire - Google Patents

Biomarqueur pour le cancer sensible à un inhibiteur de point de contrôle immunitaire Download PDF

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WO2023073075A1
WO2023073075A1 PCT/EP2022/080026 EP2022080026W WO2023073075A1 WO 2023073075 A1 WO2023073075 A1 WO 2023073075A1 EP 2022080026 W EP2022080026 W EP 2022080026W WO 2023073075 A1 WO2023073075 A1 WO 2023073075A1
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ici
cancer
treatment
subject
treatable
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PCT/EP2022/080026
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English (en)
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Cinzia DONATO
Benjamin ESSIGMAN
Woong-Yang Park
Nayoung Kim
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Scailyte Ag
Geninus Inc.
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Publication of WO2023073075A1 publication Critical patent/WO2023073075A1/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
    • C12Q2600/106—Pharmacogenomics, i.e. genetic variability in individual responses to drugs and drug metabolism
    • 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 invention relates to methods for diagnosing, predicting disease development, disease progression and/or disease outcome, predicting susceptibility to treatment and/or classification in the context of immune checkpoint inhibitor treatable cancer, wherein a combination of biomarkers from Table 1 is determined.
  • the invention further relates to pharmaceutical products for use in patients stratified according to the methods of the invention and to compositions comprising reagents for the detection of the combination of biomarkers from Table 1 for the diagnosis of immune checkpoint inhibitor treatable cancer.
  • Cancer is a major health and economic burden for individuals and society. Response to cancer treatments varies between subjects and over the treatment course.
  • Immunohistochemical receptor analysis gives guidance to physicians to help them determine whether or not a cancer, for example a lung cancer, of a patient is susceptible to immune checkpoint inhibitor treatment.
  • lung cancer is the second most commonly diagnosed cancer and the leading cause of cancer death in 2020, representing approximately one in 10 (11.4%) cancers diagnosed and one in 5 (18.0%) deaths.
  • About 80% to 85% of lung cancers are NSCLC.
  • the main subtypes of NSCLC are adenocarcinoma, squamous cell carcinoma, and large cell carcinoma. The mean overall 5 year survival is 10-20%.
  • Immune checkpoint inhibitors have been FDA approved for first line treatment of advanced NSCLC patients (30-55% of NSCLC patients) with a PD-L1 score >50%.
  • PD-1/PD-L1 IHC staining on lung biopsies is still the only accepted biomarker for ICI treatment decision (Lower thresholds are also accepted as PD-L1 >1 %) but its scoring is limited to the antibody clones and IHC kit quality of staining and thresholds defined or detected by the pathologists. In fact, certain PD-1 negative patients benefit from the treatments as well. Overall, more or less 30% of patients will respond to ICI, highlighting another unmet medical need which is the prediction of response to the prescribed ICI treatment.
  • the invention relates to, inter alia, the following embodiments:
  • a method for determining the frequency of immune checkpoint inhibitor (ICI)- sensitive cancer signature cells in a plurality of cells comprising the steps of: i) determining the levels of at least two biomarkers selected from Table 1 in a plurality of cells; and ii) determining the frequency of ICI-sensitive cancer signature cells in the plurality of cells based on the levels of the at least two biomarkers selected from Table 1 .
  • ICI immune checkpoint inhibitor
  • a method for determining an ICI-sensitive cancer signature in a sample comprising the steps of: i) determining the levels of at least two biomarkers selected from Table 1 in a sample; and ii) determining the ICI-sensitive cancer signature in the sample based on the levels of the at least two biomarkers selected from Table 1 .
  • the method comprises at least one step of pre-selection of at least one cell lineage, preferably using at least one cell lineage marker selected from the group of: a) ITGAM (encoding CD11 b), ITGB2 (encoding CD18), CD44, FCGR3A
  • CD16 CD16
  • FCGR2A CD32
  • S100A8 or S100A9 CD32
  • c) COL18A1 , COL4A2, COL4A1 , VIM or CALD1 CD14
  • CD79A and/or CD3E CD3E
  • PPBP PPBP
  • determining the levels of the at least two biomarkers comprises a nucleic acid detection technique.
  • the method additionally comprises determining at least one non-molecular marker, preferably wherein the non-molecular marker comprises a marker selected from the group consisting of: age, weight, BMI, smoking history, tumor histology.
  • a method for determining the susceptibility to an ICI-treatment of a subject having ICI treatable cancer or at risk of having ICI-treatable cancer comprising the steps of: a) i) determining the frequency of ICI-sensitive cancer signature cells in a sample of a subject according to the method of any one of embodiments 1 , 3 to 9; and/or ii) determining an ICI-sensitive cancer signature in a sample of a subject according to the method of any one of embodiments 2 to 9; b) comparing the frequency determined in a)i) and/or the signature determined in a)ii) to a treatment reference pattern; and c) determining whether the subject is susceptible to a treatment based on the comparison in step b), preferably wherein a frequency of ICI-treatable cancer signature cells and/or an ICI- treatable cancer signature above the treatment reference pattern is indicative of the subject being susceptible to the treatment.
  • a method for prediction of disease development, disease progression and/or disease outcome of a subject having ICI treatable cancer or at risk of having ICI treatable cancer comprising the steps of: a) i) determining the frequency of ICI-sensitive cancer signature cells in a sample of a subject according to the method of any one of embodiments 1 , 3 to 9; and/or ii) determining an ICI-sensitive cancer signature in a sample of a subject according to the method of any one of embodiments 2 to 9; b) comparing the frequency determined in a)i) and/or the signature determined in a)ii) to a prediction reference pattern; and c) predicting disease development, disease progression and/or disease outcome of the subject based on the comparison in step b), preferably wherein a frequency of ICI-sensitive cancer signature cells and/or an ICI-sensitive cancer signature above the prediction reference pattern is indicative of an increased likelihood of disease development, increased disease progression and/or worsened disease outcome.
  • obtaining the prediction reference pattern or the treatment reference pattern from reference subjects comprises a machine-learning technique, preferably a convolutional neural network and/or logistic regression.
  • a method for classification of a subject having ICI treatable cancer or at risk of having ICI treatable cancer into a class comprising the steps of: a)i) determining the frequency of ICI-sensitive cancer signature cells in a sample of a subject according to the method of any one of embodiments 1 , 3 to 9; ii) determining an ICI-sensitive cancer signature in a sample of a subject according to the method of any one of embodiments 2 to 9; iii) predicting a disease development, disease progression and/or disease outcome of a subject according to the method of any one of embodiments 11 to 13; and/or iv) predicting susceptibility to an ICI-treatment of a subject according to the method of any one of embodiments 10, 12 or 13; and b) classifying the subject according to the frequency determined in i), the signature determined in ii), the prediction of iii), and/or the prediction in iv).
  • a pharmaceutical product comprising a PD-1 inhibitor for use in treatment of a subject having ICI treatable cancer or at risk of having ICI treatable cancer, wherein the subject is classified as having an increased susceptibility to a PD-1 inhibitor treatment according to the method for classification of embodiment 15 or 16.
  • a pharmaceutical product comprising a PD-L1 inhibitor for use in treatment of a subject having ICI treatable cancer or at risk of having ICI treatable cancer, wherein the subject is classified as having an increased susceptibility to a PD-L1 inhibitor treatment according to the method for classification of embodiment 15 or 16.
  • a composition comprising reagents for the detection of biomarkers for the determination of IC l-sensitivity of ICI-treatable cancer, the biomarkers comprising or consisting of at least two biomarkers of Table 1 .
  • non-small-cell lung carcinoma is stage IV non-small-cell lung carcinoma, preferably stage IV treatment-naive non-small-cell lung carcinoma.
  • a computer program product comprising instructions to execute the method of any one of embodiments 9 to 16, 22 to 26, wherein the method is computer- implemented.
  • the invention relates to a method for determining the frequency of immune checkpoint inhibitor-sensitive cancer signature cells in a plurality of cells, the method comprising the steps of: i) determining the levels of expression of at least two biomarkers selected from Table 1 in a plurality of cells; and ii) determining the frequency of ICI-sensitive cancer signature cells in the plurality of cells based on the levels of the at least two biomarkers selected from Table 1 .
  • biomarker refers to a molecule that is part of and/or generated by a cell and serves as an indicator for a disease. Often a biomarker is a gene variant or a gene product, for example an RNA or a polypeptide.
  • determining a level of a biomarker refers to using a nucleic acid detection technique, a peptide or protein detection technique and/or retrieval of information indicative of a level of a biomarker from a data source.
  • the “level of a biomarker” described herein is an expression level.
  • expression level refers to the absolute frequency/abundance of a biomarker described herein or the relative frequency/abundance as compared to a reference, in particular a known frequency/abundance on a healthy cell or a diseased cell to which the determined frequency/abundance can be compared.
  • the expression level of a biomarker in a single cell may be measured by any method known in the art.
  • the expression level of a biomarker may be measured on the nucleic acid level or on the protein level.
  • subject refers to a mammal, such as a mouse, guinea pig, rat, dog or human. It is understood that the preferred subject is a human.
  • plurality of cells refers to two or more than two cells.
  • a “ICI-sensitive cancer signature cell” or “Immune checkpoint inhibitor sensitive cancer signature cell” is a cell that is indicative of ICI treatment sensitivity. That is, if a certain relative frequency of ICI-sensitive cancer signature cells is determined in a plurality of cells that has been obtained from a subject, the cancer and/or the subject is determined as being sensitive to ICI treatment. Further, determining the relative frequency of ICI-sensitive cancer signature cells in samples from the same subject at two or more time points allows to monitor the progression of ICI-sensitivity in said subject.
  • the present invention relates to a method for the determination of ICI sensitivity with high specificity and sensitivity.
  • the method of the present invention allows measuring the level of biomarkers at the single-cell level. That is, for each cell in a plurality of cells, the level of two or more, three or more, preferably four or more, biomarkers is determined and based on the level of these biomarkers, it is decided for each cell if it is indicative of ICI sensitivity.
  • the frequency of these indicative cells in a plurality of cells may then be used for determining if a subject from which the plurality of cells has been obtained, the donor, suffers from a certain medical condition and/or for determining the progression of a certain medical condition in a subject from which the plurality of cells has been obtained.
  • the invention is at least in part based on the finding that the combination of biomarkers is particularly useful for the detection of ICI sensitive cancer.
  • the invention relates to a method for determining an ICI- sensitive cancer signature in a sample, the method comprising the steps of: i) determining the levels of at least two biomarkers selected from Table 1 in a sample; and ii) determining the ICI-sensitive cancer signature in the sample based on the levels of the at least two biomarkers selected from Table 1 .
  • ICI-sensitive cancer signature refers to the level(s) and/or ratio(s) of biomarker(s) that is/are indicative of the ICI sensitivity.
  • the ICI sensitive cancer signature may comprise bulk RNA, protein levels and/or data indicative of RNA or protein levels. Therefore, the sample may be processed and does not require living cells. This enables fast, standardized and robust analysis of samples.
  • biomarkers represented by the signature in a sample enable the detection of IC l-sensitivity with high specificity and sensitivity.
  • the invention relates to the method of the invention, wherein the at least two biomarkers selected from Table 1 comprise at least one biomarker selected from the Table 2.
  • biomarkers in Table 2 are particularly useful to enable the detection of ICl-sensitivity with high specificity and sensitivity.
  • the invention relates to the method of the invention, wherein at least 3, 4, 5, 6, 7, 8 or 9 biomarkers are determined. In certain embodiments, the invention relates to the method of the invention, wherein at least 3, 4, 5, 6, 7, 8, 9 or more biomarkers are determined, wherein at least one biomarker is selected from Table 3.
  • the level of any number of biomarkers may be determined. It is assumed that the sensitivity and specificity increase with the number of biomarkers that are used in the method of the invention. At the same time, the number of biomarkers that can be used in the method of the invention may be limited by the experimental method to determine the levels of the biomarkers and the availability of suitable binding agents.
  • the invention relates to the method of the invention, wherein the method comprises at least one step of pre-selection of at least one cell lineage.
  • the pre-selection described herein is achieved by a method selected from the group of immunomagnetic cell separation, fluorescence-activated cell sorting, density gradient centrifugation, immunodensity cell isolation, microfluidic cell sorting, sedimentation, adhesion, microfluidic cell separation.
  • the invention relates to the method of the invention, wherein the method comprises at least one step of pre-selection of at least one cell lineage using at least one cell lineage marker.
  • the invention relates to the method of the invention, wherein the method comprises at least one step of pre-selection of at least one cell lineage using at least one cell lineage marker selected from the group of: a) ITGAM (encoding CD11 b), ITGB2 (encoding CD18), CD44, FCGR3A (CD16), FCGR2A (CD32), S100A8 or S100A9; b) DRC3, RSPH3, ARMC2, LRRC23, C16orf46, ZNF487 or BBOF1 ; c) COL18A1 , COL4A2, COL4A1 , VIM or CALD1 ; d) CD14; e) CD79A and/or CD3E; and f) PPBP.
  • ITGAM encoding CD11 b
  • ITGB2 encoding CD18
  • CD44 CDGR3A
  • FCGR2A CD32
  • S100A8 or S100A9 b
  • the invention relates to the method of the invention, wherein the method comprises at least one step of pre-selection of at least one cell lineage using at least one cell lineage marker selected from the group of: a) ITGAM (encoding CD11 b), ITGB2 (encoding CD18), CD44, FCGR3A (CD16), FCGR2A (CD32), S100A8 or S100A9; b) DRC3, RSPH3, ARMC2, LRRC23, C16orf46, ZNF487 or BBOF1 ; and c) COL18A1 , COL4A2, COL4A1 , VIM or CALD1 .
  • the method comprises at least one step of pre-selection of at least one cell lineage using at least one cell lineage marker selected from the group of: a) ITGAM (encoding CD11 b), ITGB2 (encoding CD18), CD44, FCGR3A (CD16), FCGR2A (CD32), S100A8 or S100A9;
  • the invention relates to the method of the invention, wherein the method comprises at least one step of pre-selection of at least one cell lineage using at least one cell lineage marker selected from the group of: a) CD14; b) CD79A and/or CD3E; and c) PPBP.
  • the set of biomarkers described herein may be adapted to obtain adapted panels for use in the method of the invention and to maintain high sensitivity and specificity, wherein the adapted panel consists of the same or a lower number of biomarkers by a method comprising the steps of:
  • the biomarker(s) to be added to the panel can be any biomarker but is/are preferably (a) biomarker(s) selected from the group listed in Table 1.
  • (one of) the biomarker(s) to be added to the panel of the current invention is known to be characteristic for a similar biologic function and/or a same cell type as one of the biomarkers of the panel of the current invention.
  • the biomarker(s) to be added to the panel may be chosen based on various reasons, including but not limited to economic reasons, availability of reagents and compatibility with the measurement equipment.
  • placing a weight may be done using ScaiVision as described in the examples, or using any suitable weighting method known to the skilled person.
  • the full alternative panel and/or a certain number of the biomarkers of the alternative panel can be tested to obtain information for placing a weight to the biomarkers.
  • alternative panel-minus-one controls may be used to obtain information regarding weighting (e.g., as described by Tung, James W et al. Clinics in laboratory medicine vol. 27,3 (2007): 453-68).
  • step (iii) of the method to obtain an adapted panel the biomarker with the lowest weight is excluded.
  • step (iv) of the method to obtain an adapted panel the specificity and selectivity of the provisional adapted panel may be verified as described in the examples. Provisional adapted panels that have a specificity and selectivity below a certain specificity and selectivity threshold, are excluded.
  • the invention relates to the method of the invention, wherein determining the levels of the at least two biomarkers comprises a nucleic acid detection technique.
  • nucleic acid detection techniques are well known in the art (see e.g. Kolpashchikov, D. M., & Gerasimova, Y. V. (Eds.)., 2013. Nucleic Acid Detection: Methods and Protocols. Humana Press.)
  • the nucleic acid detection technique described herein is at least on method selected from the group of: qPCR, isothermal amplification techniques, assays with visual or electric signals for point-of-care diagnostics, fluorescent in situ hybridization and signal amplification techniques.
  • the invention relates to the method of the invention, wherein the level(s) of the biomarker(s) comprise(s) a protein level.
  • the protein level can be determined by any method known in the art.
  • the protein level described herein is determined by an antibody-based assay. That is, any assay that comprises the use of antibodies and is suitable for determining the expression level of a biomarker may be used in the present invention.
  • antibodies are used that bind directly to the biomarker.
  • the antibodies are preferably labeled to facilitate detection and/or quantification of a biomarker.
  • antibodies may be labeled with a fluorophore to allow detection and/or quantification of biomarkers in flow cytometry- based assays or metal isotopes to allow detection and/or quantification of biomarkers in mass cytometry-based assays.
  • the invention relates to the method according to the invention, wherein the antibody-based assay is an antibody- based flow cytometry or mass cytometry assay.
  • the protein level described herein is determined by ELISA, preferably multiplexed ELISA.
  • the invention relates to the method of the invention, wherein the levels are determined in a blood sample, preferably a plasma sample, a serum sample or a PBMC sample.
  • the invention relates to the method of the invention, wherein the method additionally comprises determining at least one non-molecular marker.
  • non-molecular marker refers to any marker that describes a characteristic of a subject that is not a nucleic acid, peptide or protein.
  • the invention relates to the method of the invention, wherein the method additionally comprises determining at least one non-molecular marker, wherein the non-molecular marker comprises a marker selected from the group consisting of: age, weight, BMI, smoking history, tumor histology.
  • non-molecular markers can improve the sensitivity and/or specificity of the method of the invention.
  • the invention relates to the method of the invention, wherein the method is at least partially computer-implemented and wherein the levels of the at least two biomarkers are determined by retrieving data indicative of the levels of the at least two biomarkers.
  • the invention relates to a method for determining the susceptibility to an ICI-treatment of a subject having ICI treatable cancer or at risk of having ICI treatable cancer, the method comprising the steps of: a) i) determining the frequency of ICI-sensitive cancer signature cells in a sample of a subject according to the method of the invention; and/or ii) determining an ICI-sensitive cancer signature in a sample of a subject according to the method of the invention; b) comparing the frequency determined in a)i) and/or the signature determined in a)ii) to a treatment reference pattern; and c) determining whether the subject is susceptible to a treatment based on the comparison in step b).
  • immune checkpoint inhibitor treatable cancer or “ICI treatable cancer”, as used herein, refers to any type of cancer for which at least one immune checkpoint inhibitor treatment is approved or investigated with at least one clinical study. As such, the ICI treatable cancer does not need to be immune checkpoint inhibitor sensitive per se, it is sufficient if the cancer belongs to a type of cancer that is potentially immune checkpoint inhibitor sensitive.
  • the methods described herein enable distinguishing between the sensitive and non-sensitive cancer subtypes in the type of cancer that is potentially immune checkpoint inhibitor sensitive.
  • the ICI treatable cancer described herein is a cancer selected from the group of: breast cancer, bladder cancer, cervical cancer, colon cancer, head and neck cancer, Hodgkin lymphoma, liver cancer, lung cancer, renal cell cancer, skin cancer, stomach cancer and rectal cancer.
  • the ICI treatable cancer described herein is a pre-surgery ICI treatable cancer. In some embodiments, the ICI treatable cancer described herein is a post-surgery ICI treatable cancer.
  • risk of having ICI treatable cancer refers to having a risk factor for ICI treatable cancer and/or at least one symptom of ICI treatable cancer disease.
  • ICI-treatment refers to any treatment comprising a compound inhibiting the function of an immune inhibitory checkpoint protein. Inhibition includes reduction of function and full blockade.
  • Preferred immune checkpoint inhibitors are antibodies that specifically recognize immune checkpoint proteins. A number of immune checkpoint inhibitors are known and in analogy of these known immune checkpoint protein inhibitors, alternative immune checkpoint inhibitors may be developed in the (near) future.
  • the immune checkpoint inhibitors include peptides, antibodies, nucleic acid molecules and small molecules.
  • the ICI-treatment described herein is a treatment comprising a compound selected from the group of ipilimumab, nivolumab, pembrolizumab, atezolizumab, avelumab, durvalumab and cemiplimab. In some embodiments, the ICI-treatment described herein is a treatment comprising a compound selected from the group of ipilimumab, nivolumab, atezolizumab, avelumab, durvalumab and cemiplimab. In some embodiments, the ICI-treatment described herein is an adjuvant. In some embodiments, the ICI-treatment described herein is a neoadjuvant.
  • reference pattern refers to a predetermined pattern that can be used for comparison and is preferably obtained from reference subjects.
  • the reference pattern comprises at least one datapoint, such as a datapoint that can be used as a threshold.
  • the reference pattern is a machine learning model.
  • the method of the invention is at least in part based on the finding that the combination of biomarkers described herein enables accurate determination of the susceptibility to an ICI-treatment.
  • the invention relates to a method for determining the susceptibility to an ICI-treatment of a subject having ICI treatable cancer or at risk of having ICI treatable cancer, the method comprising the steps of: a) i) determining the frequency of ICI-sensitive cancer signature cells in a sample of a subject according to the method of the invention; and/or ii) determining an ICI-sensitive cancer signature in a sample of a subject according to the method of the invention; b) comparing the frequency determined in a)i) and/or the signature determined in a)ii) to a treatment reference pattern; and c) determining whether the subject is susceptible to a treatment based on the comparison in step b), wherein a frequency of ICI-sensitive cancer signature cells and/or an ICI-sensitive cancer signature above the treatment reference pattern is indicative of the subject being susceptible to the treatment.
  • the invention relates to a method for prediction of disease development, disease progression and/or disease outcome of a subject having ICI- sensitive cancer or at risk of having ICI treatable cancer, the method comprising the steps of: a) i) determining the frequency of ICI-sensitive cancer signature cells in a sample of a subject according to the method of the invention; and/or ii) determining an ICI-sensitive cancer signature in a sample of a subject according to the method of the invention; b) comparing the frequency determined in a)i) and/or the signature determined in a)ii) to a prediction reference pattern; and c) predicting disease development, disease progression and/or disease outcome of the subject based on the comparison in step b).
  • the invention relates to a method for prediction of disease development, disease progression and/or disease outcome of a subject having ICI treatable cancer or at risk of having ICI treatable cancer, the method comprising the steps of: a) i) determining the frequency of ICI-sensitive cancer signature cells in a sample of a subject according to the method of the invention; and/or ii) determining an ICI-sensitive cancer signature in a sample of a subject according to the method of the invention; b) comparing the frequency determined in a)i) and/or the signature determined in a)ii) to a prediction reference pattern; and c) predicting disease development, disease progression and/or disease outcome of the subject based on the comparison in step b), wherein a frequency of ICI-sensitive cancer signature cells and/or an ICI-sensitive cancer signature above the prediction reference pattern is indicative of an increased likelihood of disease development, increased disease progression and/or worsened disease outcome.
  • the method of the invention is at least in part based on the finding that the combination of biomarkers described herein enables accurate prediction of disease development, disease progression and/or disease outcome.
  • the invention relates to the method of the invention, wherein the prediction reference pattern or the treatment reference pattern is obtained from reference subjects, wherein at least one of the reference subjects is diagnosed with ICI treatable cancer.
  • the invention is at least in part based on the finding that data from at least one diseased subject is particularly useful for the reference pattern in the methods described herein.
  • the invention relates to the method of the invention, wherein obtaining the prediction reference pattern or the treatment reference pattern from reference subjects comprises a machine-learning technique.
  • machine-learning technique refers to a computer- implemented technique that enables automatic learning and/or improvement from an experience (e.g., training data and/or obtained data) without the necessity of explicit programming of the lesson learned and/or improved.
  • the machine learning technique comprises at least one technique selected from the group of Logistic regression, CART, Bagging, Random Forest, Gradient Boosting, Linear Discriminant Analysis, Gaussian Process Classifier, Gaussian NB, Linear, Lasso, Ridge, ElasticNet, partial least squares, KNN, DecisionTree, SVR, AdaBoost, GradientBoost, neural net and ExtraTrees.
  • the invention relates to the method of the invention, wherein obtaining the prediction reference pattern or the treatment reference pattern from reference subjects comprises a convolutional neural network and/or logistic regression.
  • the ScaiVision convolutional neural network has been described previously (Arvaniti, E., & Claassen, M., 2017, Nature communications, 8(1 ), 1 -10.Bodenmiller et al., Nat Biotechnol, 2012, 30(9), 858-867; Amir et al., Nat Biotechnol, 2013, 31 (5), 545-552; Levine et al., Cell, 2015, 162(1 ), 184-197; Horowitz et al., Sci Transl Med, 2013, 5(208), 208ra145) and is publicly available (https://github.com/eiriniar/ScaiVision). Further, it is described in the Examples how the ScaiVision convolutional neural network may be used in the context of the invention.
  • the invention relates to a method for classification of a subject having ICI treatable cancer or at risk of having ICI treatable cancer into a class, the method comprising the steps of: a)i) determining the frequency of ICI-sensitive cancer signature cells in a sample of a subject according to the method of the invention; ii) determining an ICI-sensitive cancer signature in a sample of a subject according to the method of the invention; iii) predicting a disease development, disease progression and/or disease outcome of a subject according to the method of the invention; and/or iv) predicting susceptibility to an ICI-treatment of a subject according to the method of the invention; and b) classifying the subject according to the frequency determined in i), the signature determined in ii), the prediction of iii), and/or the prediction in iv).
  • the invention relates to the method of the invention, wherein the ICI-treatment comprises a PD-1 inhibitor treatment and a PD-L1 inhibitor treatment.
  • PD-1 inhibitor refers to any agent capable of inhibiting the PD-1 signalling pathway in a cell.
  • the PD-1 inhibitor described herein is at least one agent selected from the group of pembrolizumab, nivolumab, cemiplimab, JTX-4014, spartalizumab, camrelizumab, sintilimab, tislelizumab, toripalimab, dostarlimab, INCMGA00012, AMP-224 and AMP-514.
  • the PD-1 inhibitor described herein is at least one agent selected from the group of nivolumab, cemiplimab, JTX-4014, spartalizumab, camrelizumab, sintilimab, tislelizumab, toripalimab, dostarlimab, INCMGA00012, AMP-224 and AMP- 514.
  • PD-L1 inhibitor refers to any agent capable of inhibiting the PD-L1 signalling pathway in a cell.
  • the PD-L1 inhibitor described herein is at least one agent selected from the group of atezolizumab, avelumab, durvalumab, KN035, CK-301 , AUNP12, CA-170 and BMS-986189.
  • inhibitor includes the decrease, limitation, or blockage, of, for example a particular action, function, or interaction.
  • the invention relates to the method of the invention, wherein the PD-L1 inhibitor is atezolizumab and the PD-1 inhibitor is pembrolizumab or nivolumab.
  • the invention relates to the method of the invention, wherein the PD-L1 inhibitor is atezolizumab and the PD-1 inhibitor is nivolumab.
  • the invention relates to a pharmaceutical product comprising a PD-1 inhibitor for use in treatment of a subject having ICI treatable cancer or at risk of having ICI treatable cancer, wherein the subject is classified as having an increased susceptibility to a PD-1 inhibitor treatment according to the method for classification of the invention.
  • pharmaceutical product refers to a preparation which is in such form as to permit the biological activity of an active ingredient contained therein to be effective, and which contains no additional components which are unacceptably toxic to a subject to which the formulation would be administered.
  • the invention relates to the pharmaceutical product according to the invention, wherein the PD-1 inhibitor is pembrolizumab or nivolumab and wherein the subject is classified as having an increased susceptibility to pembrolizumab treatment or nivolumab treatment according to the method for classification of the invention.
  • the invention relates to the pharmaceutical product according to the invention, wherein the PD-1 inhibitor is nivolumab and wherein the subject is classified as having an increased susceptibility to nivolumab treatment according to the method for classification of the invention.
  • the invention relates to a pharmaceutical product comprising a PD-L1 inhibitor for use in treatment of a subject having ICI treatable cancer or at risk of having ICI treatable cancer, wherein the subject is classified as having an increased susceptibility to a PD-L1 inhibitor treatment according to the method for classification of the invention.
  • the invention relates to the pharmaceutical product according to the invention, wherein the PD-L1 inhibitor is atezolizumab and wherein the subject is classified as having an increased susceptibility to atezolizumab treatment according to the method for classification of the invention.
  • the inventors found that, using the method(s) of the invention, subject populations that are particularly sensitive to certain pharmaceutical products can be identified. As such, the pharmaceutical products have a surprisingly enhanced risk/benefit ratio in this/these subject population(s).
  • the invention relates to a composition
  • a composition comprising reagents for the detection of biomarkers for the determination of ICI-sensitivity of ICI-treatable cancer, the biomarkers comprising or consisting of at least two biomarkers of Table 1 .
  • the invention relates to the method of the invention, the pharmaceutical product for use of any one of the invention or the composition of the invention, wherein the ICI treatable cancer is a PD-L1 IHC negative ICI treatable cancer.
  • PD-L1 IHC negative ICI treatable cancer refers to ICI treatable cancer that has shown at least one negative result on the PD-L1 IHC test (see e.g. Lu, S., et al., 2019, JAMA oncology, 5(8), 1195-1204).
  • the threshold to distinguish between PD-L1 IHC negative and positive ICI treatable cancer can depend on the specific detection technique, on the scoring method, on the cancer type/stage and/or on the treatment. The person skilled in the art is familiar with setting this threshold (see e.g. Silva MA, et al., 2018, PLoS One. 2018;13(6):e0196464).
  • the threshold for PD-L1 IHC negative ICI treatable cancer is based on a less than 50%, less than 45%, less than 40%, less than 35%, less than 30%, less than 25%, less than 20%, less than 15%, less than 10%, less than 5%, less than 4%, less than 3%, less than 2%, less than 1 %, or 0% staining threshold. In some embodiments, the threshold for PD-L1 IHC positive ICI treatable cancer is based on a more than 50%, more than 10%, more than 1 % or more than 0% staining threshold.
  • the methods described herein can identify subject populations that are sensitive to ICI treatment. These subject populations can even be identified within subject populations with PD-L1 IHC negative ICI treatable cancer.
  • the invention is at least in part based on the finding that the methods of the invention can identify that are sensitive to ICI treatment that are not considered susceptible to ICI treatment (i.e. false negatives) by the methods known in the art
  • the invention relates to the method of the invention, the pharmaceutical product for use of any one of the invention or the composition of the invention, wherein the ICI treatable cancer is a PD-L1 IHC positive IC I treatable cancer.
  • the methods described herein can identify subject populations that are not sensitive to ICI treatment. These subject populations can even be identified within subject populations with PD-L1 IHC positive ICI treatable cancer.
  • the invention is at least in part based on the finding that the methods of the invention can identify false positives of the methods known in the art. Exclusion of false positive subjects improves the risk/benefit ratio of the pharmaceutical product.
  • the invention relates to the method of the invention, the pharmaceutical product for use of any one of the invention or the composition of the invention, wherein the ICI treatable cancer, the PD-L1 positive ICI treatable cancer or the PD-L1 negative ICI treatable cancer is a cancer selected from the group of: breast cancer, bladder cancer, cervical cancer, colon cancer, head and neck cancer, Hodgkin lymphoma, liver cancer, lung cancer, renal cell cancer, skin cancer, stomach cancer and rectal cancer.
  • the invention relates to the method of the invention, the pharmaceutical product for use of the invention or the composition of the invention, wherein ICI treatable cancer, the PD-L1 positive ICI treatable cancer or the PD-L1 negative ICI treatable cancer is lung carcinoma.
  • the invention relates to the method of the invention, the pharmaceutical product for use of the invention or the composition of the invention, wherein the lung carcinoma is non-small-cell lung carcinoma.
  • the invention relates to the method of the invention, the pharmaceutical product for use of the invention or the composition of the invention, wherein the non-small-cell lung carcinoma is stage IV non-small-cell lung carcinoma, preferably stage IV treatment-naive non-small-cell lung carcinoma.
  • the invention is at least in part based on the finding that the methods described herein are particularly sensitive and/or specific in certain types of cancers.
  • the invention relates to a computer program product comprising instructions to execute the method of the invention, wherein the method is computer-implemented.
  • the computer program product described herein may comprise computer-readable program instructions that can be downloaded to respective computing/processing devices from a computer-readable storage medium or to an external computer or external storage device via a network.
  • Computer-readable program instructions for carrying out operations of the present invention may be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state-setting data, or either source code or object code written in any combination of one or more programming languages, including an object- oriented programming language such as Smalltalk, C++ or the like, and conventional procedural programming languages, such as the “C” programming language or similar programming languages.
  • ISA instruction-set-architecture
  • machine instructions machine-dependent instructions
  • microcode firmware instructions
  • state-setting data or either source code or object code written in any combination of one or more programming languages, including an object- oriented programming language such as Smalltalk, C++ or the like, and conventional procedural programming languages, such as the “C” programming language or similar programming languages.
  • the computer-readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server.
  • Fig 2 Heatmap of the biomarker signature identified by ScaiVision. Filter 1 represents Response. Filter 0 represents non-Response.
  • LIMAP highlighting the subset of cell types expressing the signature A) CD3E, B) CD79A, C) CD14, D) PPBP.
  • PBMCs were isolated from the blood of 76 patients with stage IV NSCLC at baseline, before administration of PD-1 or PD-L1 inhibitor drugs. Patients were subsequently administered with one type of drug: 27 patients received PD-L1 inhibitor Atezolizumab (Roche), 40 patients received PD-1 inhibitor Pembrolizumab (MSD), 9 patients received PD-1 inhibitor Nivolumab (BMS).
  • the response to the treatment was assessed based on the progression of the disease during and at the end of the treatment cycles. Stable disease for 6 months or more was considered response while stable disease for less than 6 months was considered non-response.
  • Clinical Parameters Fully anonymized clinical data i.e. age, gender, drug type and period of administration, response to the treatment (progressive disease, partial or complete response, stable disease for more or less than 6 months), tumor stage, tumor histology, PD-L1 histology score, smoking history etc..
  • RNA expression profile performed on PBMC cells from 76 patients.
  • the biomarkers were identified through analysis of a patient cohort. Blood samples, taken at baseline from 76 patients before receiving PD-1 or PD-L1 inhibitor drugs, have been processed for the extraction of PBMCs. PBMC samples were frozen for further gene expression analysis.
  • Gene expression Cell capture and cDNA library generation was performed using a Chromium system (10X Genomics). The cDNA library was sequenced using an Illumina platform.
  • cDNA average size was considered optimal when between 1000-1600 base pairs and of a total cDNA concentration > 35ng.
  • Final libraries were considered optimal when of an average size between 450-600bp and of a total final concentration > 350 ng.
  • Medical data collected was curated into a format for integration into our internal deep learning platform ScaiVisionTM or another suitable data analysis workflow that uses patient data as a tool to identify disease-related molecular profiles/or cell identity biomarkers.
  • Biomarker discovery was carried out on a cohort of PBMC samples collected from 76 patients directly prior to a planned immunotherapeutic drug treatment consisting of PD- 1 or PD-L1 inhibitor compounds. Single-cell RNA sequencing was performed on all the isolated PBMC samples measuring detectable levels of RNA transcripts in single cells.
  • MultiQC (Ewels, P. et al., 2016, Bioinformatics, 32(19), 3047-3048.) was run on raw fastqc files to ensure sequencing quality. The data was then processed into a Seurat V3 (Stuart, Tim, et al., 2019, Cell 177.7: 1888-1902.) object and further quality controls were run to assess the number of mitochondrial genes, sequencing depth and batch effects. The data was found to be satisfactory on all counts.
  • Gene expression was then normalised over single cells using the SCTransform method (Hafemeister, C., & Satija, R., 2019, Genome biology, 20(1 ), 1-15.). Included is the detection and removal of outlier cells based on transcript and gene metrics, detection of possible doublet cells and batch effects.
  • Patient samples were divided into two groups, consisting of those patients that responded to the PD-1/PD-L1 treatment (responders; 36 patients) and those that did not respond to the same treatments (non-responders; 40 patients).
  • Responders were defined based on the progression of the disease during and at the end of the treatment cycles.
  • the disease is defined as “progressing” when the tumor sites identified are expanding in size and/or spreading in the body.
  • the disease is defined as “regressing” when the tumor sites identified are shrinking in size and not spreading in the body.
  • Stable disease, or no disease progression is meant when the tumor sites are not expanding nor shrinking in size and there are no signs of further spreading in the body. Stable disease for 6 or more months was considered to be a response to the treatment. While a stable disease for less than 6 months was considered non-response to the treatment.
  • a gene signature was derived from the filters predicting responders and non- responders (Table 2) in the best-performing network using the consensus from the top- weighted genes associated with response or non-response from all Atezolizumab- treated samples ( Figure 2). Each gene was identified by the weight assigned in the process of the model generation, which is used as an estimate of their influence on the prediction of response versus non-response.
  • the gene signature was cross-validated through the differential expression analysis of all genes in the dataset. The analysis shows that 62.96% of the ScaiVision-derived predictive genes are differentially expressed between responder versus non-responder samples (Table 3; Figure 3 and Figure 4 A, B, C)).
  • the inventors Using the weights from the filters positively or negatively correlated with response or non-response from ScaiVision predictive networks, the inventors calculated filter response scores for every cell in the dataset, one per CV-split. These scores were used to set thresholds to determine the cells predictive of response in both Atezolizumab- and Pembrolizumab-treated samples. Specific subsets of myeloid and lymphoid cells associated with platelets were identified to be expressing the biomarker gene signatures predictive of response (Figure 5).
  • the myeloid cells are characterized by the expression of CD14.
  • the lymphoid cells are characterized by the following marker expression: CD3E and CD79A.
  • a common denominator of all subsets was the expression of the platelet-associated marker PPBP.
  • PBMCs will be obtained from the patients in the validation cohort and will be analyzed using the same single- cell RNA-sequencing method as for the discovery cohort. The same pre-processing steps for the data will be applied.
  • the responsiveness to ICI status of all samples in the validation cohort will be predicted using the best-performing ScaiVision network trained on the discovery cohort. Using single-cell RNA-sequencing data alone, we will aim at achieving accuracies of AUC > 0.85.
  • the responsiveness to ICI status of all samples in the validation cohort will be determined using an optimized and reduced set of genes from Table 1. Characterization of each gene and its performance will be deeply assessed in several human tissue types to provide a comprehensive, specific and sensitive assay to predict response to ICI. Using nucleotide and protein measurements, we will extend and specialize the use of our panel.

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Abstract

L'invention concerne des procédés de diagnostic, de prédiction du développement de la maladie, de la progression de la maladie et/ou de l'issue de la maladie, de prédiction de la sensibilité au traitement et/ou de classification dans le contexte d'un cancer pouvant être traité par un inhibiteur de point de contrôle immunitaire, et pour lesquels une combinaison de biomarqueurs du tableau 1 est déterminée. L'invention concerne également des produits pharmaceutiques à utiliser chez des patients stratifiés selon les procédés de l'invention et des compositions comprenant des réactifs pour la détection de la combinaison de biomarqueurs du tableau 1 pour le diagnostic d'un cancer pouvant être traité par un inhibiteur de point de contrôle immunitaire.
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