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US-20260126441-A1 - TUMOR HLA MUTATION VERSUS MATCHED NORMAL HLA

US20260126441A1US 20260126441 A1US20260126441 A1US 20260126441A1US-20260126441-A1

Abstract

Effectiveness of a neoepitope-based immunotherapeutic composition against a tumor can be increased by predicting the surface presentation of the neoepitope bound to the HLA molecule of the tumor cell. Surface presentation levels of neoepitopes can be predicted by identifying any changes in omics data of the tumor cell that may affect the expression or surface trafficking of the HLA molecule and that may affect binding affinities of neoepitopes to the HLA molecule.

Inventors

  • John Zachary Sanborn
  • Andrew Nguyen

Assignees

  • NANTOMICS LLC

Dates

Publication Date
20260507
Application Date
20251104

Claims (20)

  1. 1 . A method of improving treatment for a patient diagnosed with a tumor, comprising: obtaining respective omics data for a tumor cell and a matched normal cell; determining from the omics data of the matched normal cell a normal human leukocyte antigen (HLA) molecule of the patient; identifying a patient- and tumor-specific HLA mutation and a patient-and tumor-specific neoepitope of the tumor cell by comparing the omics data for the tumor cell and the matched normal cell, wherein the patient- and tumor-specific HLA mutation results in a mutated HLA molecule that is different from the normal HLA molecule of the patient; predicting a surface presentation level of the neoepitope on the tumor cell, wherein the neoepitope binds to the mutated HLA molecule; and selecting the neoepitope for generating a neoepitope-based immunotherapeutic composition if the predicted surface presentation level is higher than a predetermined threshold.
  2. 2 . The method of claim 1 , wherein the omics data comprises whole genome DNA sequencing, exome DNA sequencing data, or transcriptomics data.
  3. 3 . The method of claim 1 , wherein the neoepitope has a length of between 5 and 30 amino acids.
  4. 4 . The method of claim 1 , wherein the tumor-specific HLA mutation is an allele-specific mutation.
  5. 5 . The method of claim 1 , wherein the surface presentation level is predicted by determining an expression level of the mutated HLA molecule and determining a binding affinity of the neoepitope to the HLA molecule.
  6. 6 . The method of claim 1 , wherein the binding affinity is measured in silico.
  7. 7 . The method of claim 1 , wherein the binding affinity to the mutated HLA molecule is less than 500 nM.
  8. 8 . The method of claim 1 , wherein the predetermined threshold is at least 70% of predicted surface presentation level of the neoepitope associated with the normal HLA type of the patient.
  9. 9 . The method of claim 1 , wherein the immunotherapeutic composition comprises a vaccine, a neoepitope-specific affinity reagent, and/or a neoepitope-specific cell-based composition.
  10. 10 . The method of claim 9 , wherein the neoepitope-specific cell-based composition comprises an immune competent cell that is genetically modified to express a chimeric antigen receptor that specifically recognized or binds to the neoepitope.
  11. 11 . The method of claim 9 , wherein the vaccine comprises a virus, a yeast, or a bacterium, each being genetically modified to include a nucleic acid encoding the neoepitope.
  12. 12 . The method of claim 9 , wherein the neoepitope-specific affinity reagent is an antibody or fragment thereof that specifically binds to the neoepitope.
  13. 13 . The method of claim 1 , further comprising administering the immunotherapeutic composition to the patient in a dose and schedule effective to treat the tumor.
  14. 14 . The method of claim 1 , wherein the tumor cell is obtained by a biopsy.
  15. 15 . The method of claim 1 , wherein the tumor cell is a circulating tumor cell.
  16. 16 . The method of claim 1 , wherein the tumor cell is obtained during and/or after a cancer treatment.
  17. 17 . The method of claim 1 , wherein the step of identifying the patient-and tumor-specific HLA mutation and the patient-and tumor-specific neoepitope of the tumor cell is performed in silico by location-guided synchronous alignment of tumor and normal samples.
  18. 18 . The method of claim 1 , wherein the patient-and tumor-specific HLA mutation is a mutation in HLA-A, HLA-B, and HLA-C, and/or at least one of HLA-DP, HLA-DQ, and HLA-DR.
  19. 19 . The method of claim 1 , wherein the neoepitope has an expression level of at least 20% of the expression level of a corresponding matched normal sequence.
  20. 20 . The method of claim 1 , wherein the HLA molecule of the patient is determined using a de Bruijn graph that is constructed by decomposing a sequence read into a plurality of k-mers.

Description

This application is a divisional application of allowed U.S. patent application with the Ser. No. 17/279,534, filed Mar. 24, 2021, which is a 371 application of PCT/US2019/055695, filed Oct. 10, 2019, which claims priority to U.S. provisional application with the Ser. No. 62/744,511, filed Oct. 11, 2018, each of which are incorporated by reference herein in their entirety. FIELD OF THE INVENTION The field of the invention is computational analysis of omics data, and particularly as it relates to immunotherapeutic treatment to treat a tumor having a HLA mutation. BACKGROUND OF THE INVENTION The background description includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art. All publications and patent applications herein are incorporated by reference to the same extent as if each individual publication or patent application were specifically and individually indicated to be incorporated by reference. Where a definition or use of a term in an incorporated reference is inconsistent or contrary to the definition of that term provided herein, the definition of that term provided herein applies and the definition of that term in the reference does not apply. Personalized cancer treatment using patient or tumor specific mutations as a target of the treatment has gained attention as one of the most desirable options to treat cancer as such neoepitope-based treatments are expected to have increased specificity to attack the tumor by targeting the mutated molecule presented on the tumor cell. Yet, despite the expected specificity, design of an effective neoepitope-based treatment has been fraught with several challenges, including uncertainty in prediction of neoepitope sequences due to the variability in sequencing platform or systems and inaccuracies in algorithms in the prediction of the binding affinity of neoepitopes to some HLA types. In addition, even if accurate neoepitope binding to the patient's HLA type could be calculated, a neoepitope-based treatment may still not be effective to elicit an immune response against the tumor where the HLA-neoepitope complex is not properly formed and/or or sufficiently presented on the antigen presenting cell surface. Such challenges have become more evident in the recent literature. For example, Boegel et al. (OncoImmunology 3:8 e954893, Aug. 1, 2014) discloses that specific types of HLA expression can be upregulated or downregulated as a tumor escape mechanism or cancer cell adaptation mechanism, and also that many tumor cell lines show locus specific, imbalanced HLA expression levels. Similarly, McGranahan et al. (Cell, 171, 1259-1271, Nov. 30, 2018) discloses loss of heterozygosity of HLA in tumor samples (e.g., non-small cell lung cancer, etc.), which facilitates immune editing or subclonal mutations in the tumor. In still another example, Chang et al., (Journal of Chem Chem., 2015 Oct. 30; 290(44):26562-75) discloses the presence of multiple defects in HLA class I antigen-processing machinery in a recurrent melanoma metastasis, and such multiple defects can be obtained sequentially as a mechanism of immune evasion. Therefore, even if various tumor specific changes of tumor HLA types have been reported, it is largely unexplored how such changes can be taken into account in developing an immunotherapy to treat the tumor. Thus, there is still a need for improved systems and methods for identifying the tumor HLA mutations and designing the immune therapy responsive to the mutated HLA types. SUMMARY OF THE INVENTION The inventive subject matter is directed to various methods for identifying tumor-specific HLA mutations and generating an immune therapy using neoepitope sequences that are predicted to be presented on the cell surface of the antigen presenting cell with the mutated tumor HLA. Thus, one aspect of the inventive subject matter includes a method of treating a patient diagnosed with a tumor. In especially preferred method, omics data for a tumor cell and a matched normal cell from the patient is obtained, and from the omics data of the matched normal cell, an HLA type of the patient is determined. Most typically, the omics data comprises whole genome DNA sequencing, exome DNA sequencing data, or transcriptomics data. Then, by comparing the data for the tumor cell and the matched normal cell, a patient-and tumor-specific HLA mutation and a patient-and tumor-specific neoepitope of the tumor cell can be identified. It is generally preferred that the neoepitope has a length of between 5 and 30 amino acids. Then, a surface presentation level of the neoepitope in the tumor cell is predicted. Most typically, the neoepitope is associated with an HLA molecule having the tumor-specific HLA mutation. Based on the surface presentation level, especially,