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CN-121999867-A - Novel tumor immunity parting model based on tumor immunity microenvironment and tumor mutation load and application thereof

CN121999867ACN 121999867 ACN121999867 ACN 121999867ACN-121999867-A

Abstract

The invention provides a novel tumor immunity parting model based on tumor immunity microenvironment and tumor mutation load and a construction method thereof, belonging to the technical field of biology. The invention screens 7 gene markers based on IMvigor and RNA-seq data and IHC verification data of an internal immune treatment queue, and designs a tumor immune phenotype prediction model ImmPred by using Lasso-logistic regression, and the model provides a more accurate prediction mode for classifying tumor immune phenotypes. By combining ImmPred with the tumor TMB load level, a brand-new tumor immunity typing model is provided, the efficacy of the tumor immunity check point blocking therapy curative effect prediction can be remarkably improved, more accurate guidance is provided for the treatment strategy of tumor patients, and a clinician is better helped to provide individualized immunotherapy for the patients according to the invention.

Inventors

  • HU HAI
  • LUO MANLI
  • ZHAO YIMING
  • HAN ZHIREN
  • DU XIN

Assignees

  • 浙江省肿瘤医院

Dates

Publication Date
20260508
Application Date
20251231

Claims (10)

  1. 1. A group of gene markers for tumor immunophenotyping, which are characterized by comprising CD8A, IRF1, PDGFD, RABEP1, KLRC1 and CD79A, SECTM1.
  2. 2. Use of a genetic marker as claimed in claim 1 in the manufacture of a product for determining tumour immunophenotyping or predicting the efficacy of an immune checkpoint blocking therapy.
  3. 3. The method for constructing the tumor immunophenotype prediction model ImmPred is characterized by comprising the following steps of: s1, collecting data; S2, screening related genes of immune typing through ImmPort databases; S3, performing 10-time cross-validation LASSO regression analysis on the immune typing related genes obtained in the step S2, and screening immune typing candidate genes; S4, constructing a training sample data set, and adopting bidirectional stepwise logistic regression to carry out secondary screening on candidate genes for the genetic markers of tumor immunity typing; S5, constructing a verification set, acquiring the expression profile of the gene marker in S4, and dividing the patient into an immune desert type, an immune inflammation type and an immune exclusion type based on the expression condition of the gene marker.
  4. 4. The method of claim 3, wherein the data in S1 comprises RNA-seq modeling data of an external tumor patient IMvigor queue, an internal immunotherapy queue, and IHC validation data of a training sample.
  5. 5. The method of claim 3, wherein the gene marker in S4 comprises CD8A, IRF1, PDGFD, RABEP1, KLRC1, CD79A, SECTM1.
  6. 6. A tumor immunophenotype prediction model ImmPred based on a tumor microenvironment, which is characterized in that the model is constructed by adopting the construction method according to any one of claims 3 to 5.
  7. 7. The use of the model ImmPred for tumor immunophenotyping or predicting the efficacy of a clinical tumor immune checkpoint blocking therapy for diagnosis of a non-disease.
  8. 8. A novel tumor immunity typing model based on tumor immunity microenvironment and tumor mutation load is characterized in that the model is constructed by adopting a tumor immunity phenotype prediction model ImmPred and TMB load level in a combined way.
  9. 9. The novel tumor immunophenotyping model of claim 8, wherein the tumor immunophenotyping model classifies the patient into TMB-High immunoinflammatory type, TMB-Low immunoinflammatory type, TMB-High immunoexclusive type, TMB-Low immunoexclusive type and immune desert type according to the typing and TMB mutation load of the tumor immunophenotyping model ImmPred.
  10. 10. Use of the novel tumor immune typing model of claim 8 for the preparation of a product for efficacy prediction of tumor immune checkpoint blocking therapy.

Description

Novel tumor immunity parting model based on tumor immunity microenvironment and tumor mutation load and application thereof Technical Field The invention belongs to the technical field of biology, and particularly relates to a novel tumor immunity parting model based on tumor immunity and tumor mutation load and application thereof. Background Immune Checkpoint Blocking (ICB) therapies, comprising antibodies targeting cytotoxic T lymphocyte antigen 4 (CTLA 4), programmed cell death 1 (PD-1) or PD-1 ligand 1 (PD-L1), have achieved breakthroughs in therapeutic approaches for solid tumors including melanoma, non-small cell lung cancer, urothelial cancer, and the like. However, the long-lasting efficacy of ICB therapy only occurs in 10% -40% of patients, and its specific drug resistance mechanism still needs to be explored. Thus, elucidation of biomarkers and mechanisms that affect patient response and resistance after ICB treatment remains critical. Tumor immunophenotyping (immunoinflammatory, immunoexclusive, and immunodesertification) represents a widely accepted model with inadequate classification details, which has been used clinically to predict ICB efficacy, but in many cancer types (including renal and bladder cancers), the correlation between immune cell infiltration predicted by IHC alone and clinical outcome is not consistent, and thus finer tumor immunopotentiator models are needed to be widely used clinically to help doctors predict patient ICB efficacy and to individually adjust patient medication. Infiltration of immune cells in the Tumor Microenvironment (TME) is one of the key determinants of ICB therapeutic response. The hot tumors have immune activating characteristics and strong T cell infiltration, showing good response to ICB, whereas the cold tumors include immune-depleting (T cell depletion) and immune-desert (T cell depletion) subtypes, showing resistance to ICB. Current methods of classifying tumors as either hot or cold rely on quantitative detection of cd3+/cd8+ T cells at the tumor center and invasive margin. However, the presence of T cells alone is not sufficient to elicit an effective anti-tumor response, as bystander T cells or pro-tumor T cells may also infiltrate the tumor, and thus the ability to predict an immunotherapeutic response solely based on the degree of infiltration of tumor-infiltrating lymphocytes is poor. Thermal tumors also require other functional features, including PD-l1+ immune cells and existing anti-tumor immunity, to collectively define ICB-responsive patterns. There is growing evidence that the intrinsic characteristics of cancer cells themselves also have an impact on immunotherapeutic resistance, including low TMB mutation load, reduced PD-L1 expression, and insufficient antigenicity, among others. ‌ Tumor Mutation Burden (TMB) ‌ refers to the number of somatic mutations accumulated per megabase pair (or megabase) in the tumor cell genome, which is used to quantify the degree of genetic variation of a tumor cell. The higher load level of ‌ TMB generally indicates that more neoantigen is produced by tumor cells and may be more readily recognized by the immune system. Tumors with higher TMB loading levels are typically immunogenic and are characterized by an increase in neoantigens that more effectively attract and activate cancer-specific T cells, rather than bystander T cells that recognize tumor epitopes, thereby increasing the likelihood of ICB responses. However, TMB mutation burden alone is still insufficient to predict ICB response, and studies have found that TMB mutation burden is not significantly correlated with ICB reactivity of many cancer subtypes. Disclosure of Invention In view of the above problems, the present invention aims to provide a novel tumor immunity typing model based on tumor immunity microenvironment and tumor mutation load, which has more accurate prediction ability for classifying tumor immunity phenotypes, and application thereof. In order to achieve the aim, the invention adopts the technical scheme that the gene markers for tumor immune typing comprise CD8A, IRF1, PDGFD, RABEP1, KLRC1 and CD79A, SECTM. The invention also provides application of the gene marker in preparation of drugs for judging tumor immunophenotyping or predicting therapeutic effects of immune checkpoint blocking therapies. The invention also provides a construction method of the tumor immunophenotype prediction model ImmPred, which comprises the following steps: s1, collecting data; s2, jointly screening related genes of the immune typing through ImmPort database and previous researches; S3, performing 10-time cross-validation LASSO regression analysis on the immune typing related genes obtained in the step S2, and screening immune typing candidate genes; S4, constructing a training sample data set, and adopting bidirectional stepwise logistic regression to carry out secondary screening on candidate genes for the genetic markers of tumor immunity typ