Application of IQGAP3 as breast cancer marker and therapeutic target

Abstract

The invention belongs to the technical field of medical biology, and relates to application of IQGAP3 as a breast cancer marker and a therapeutic target. The invention provides an application of IQGAP3 as a breast cancer marker, also provides an application of an IQGAP3 inhibitor in preparation of drugs for treating breast cancer, and more specifically provides an application in preparation of drugs for treating HER2 positive breast cancer resistant to targeted drugs. The invention discloses an action mechanism of IQGAP3 in breast cancer, and how to play a key role in trastuzumab drug resistance caused by PIK3CAH1047R mutation. It is revealed that the anti-tumor treatment effect can be achieved by inhibiting IQGAP3. The invention provides a new thought for formulating a treatment strategy for breast cancer patients, especially HER2 positive breast cancer patients with targeted drug resistance, and research and development of novel drugs.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of medical biotechnology, and relates to the application of IQGAP3 as a breast cancer marker and therapeutic target. BACKGROUND

[0002] Breast cancer is the second most common cancer and the fourth leading cause of death worldwide [1] , is the most common diagnosis and cause of cancer death in women, and its incidence and mortality increase with age, posing a great threat to women's health [2] . About 20% of breast cancer tumors show overexpression or amplification of human epidermal growth factor receptor 2, and the HER2-positive phenotype is associated with more aggressive disease and poor prognosis [3] .

[0003] With the deepening of understanding and recognition of HER2, drugs targeting HER2 have also been developed. Trastuzumab is the first humanized monoclonal antibody developed against HER2, which can significantly improve the overall survival (OS) and disease-free survival (DFS) of patients with HER2-positive breast cancer by binding to the extracellular domain of HER2, inhibiting intracellular signaling pathways, and mediating ADCC effects [4] . However, due to primary and / or secondary drug resistance, some patients still experience recurrence and metastasis [5] , which becomes a clinical treatment difficulty.

[0004] Subsequently developed small molecule tyrosine kinase inhibitors (TKIs) inhibit tyrosine kinase phosphorylation by acting on the HER2 intracellular adenosine triphosphate (ATP) binding domain, thereby blocking downstream signaling. Compared with intravenous injection of monoclonal antibodies, TKIs have the advantages of oral administration, multiple targets, and less cardiotoxicity. In addition, in the treatment of brain metastatic cancer, the efficacy of monoclonal antibodies may be limited to crossing the blood-brain barrier (BBB), while small molecule TKIs are considered to have permeability across the BBB [6] . Given the strong antitumor activity of lapatinib (TKI) in HER2-positive MBC in the ALTERNATIVE study, lapatinib + trastuzumab was included in the NCCN guidelines for patients with advanced HER2+ breast cancer or CRC [7] . In addition, the ExteNET trial showed that sequential use of neratinib (TKI) after neoadjuvant or adjuvant trastuzumab therapy in early breast cancer significantly reduced the recurrence rate compared with the placebo group, further improving the efficacy of anti-HER2 therapy [8,9] .

[0005] With the extensive application of neoadjuvant therapy in HER2-positive breast cancer, the problem of primary drug resistance found at the early stage of treatment has attracted more and more attention. For example, the NeoSphere clinical study showed that about 15% of patients had primary drug resistance in neoadjuvant therapy [10,11] . This phenomenon poses new requirements for existing anti-HER2 treatment strategies.

[0006] In the clinical treatment experience of our center, a number of patients were diagnosed with HER2 primary drug resistance at the early stage of neoadjuvant therapy. Through subsequent treatment with pyrotinib (Py, a TKI), good tumor shrinkage effect was achieved

supplementary data

[12] , the results of PHEDRA study showed that pyrotinib performed equally well in neoadjuvant therapy

[13] . In the PICTURE study, the treatment regimen of pyrotinib combined with capecitabine achieved good efficacy in breast cancer patients with primary trastuzumab resistance

[14] . These evidences suggest that pyrotinib has significant therapeutic potential for trastuzumab-resistant patients.

[0007] Studies have shown that PIK3CA gene mutation is one of the important mechanisms of HER2-positive breast cancer resistance, among which H1047R is the most common hotspot mutation, which can significantly enhance the activity of PI3K, abnormally activate the PI3K-AKT pathway, and further promote tumor cell proliferation and stemness through the RAS-MAPK pathway [15,16] . However, for patients with primary drug resistance caused by PIK3CA H1047R mutation, the efficacy, mechanism and predictive markers of TKI are still unclear, and further research is needed.

[0008] IQGAP3 belongs to the scaffold protein family (including IQGAP1, IQGAP2, IQGAP3), which has a multi-domain structure, allowing interaction with many different proteins

[17] . It can regulate various cellular processes such as signal transduction, cell-cell adhesion, cell movement and cell division. IQGAP1 and IQGAP3 are overexpressed in many tumors and are considered oncogenes

[18] . IQGAP3 contains a calmodulin homology domain (CHD), a WW domain, an IQ domain containing multiple IQ motifs, a gtpase activating protein (GAP) related domain (GRD), and a rasgap_c terminal domain

[19] Previous studies have found that IQGAP 3 specifically interacts with Ras, the active GTP-binding form, and promotes cell proliferation through Ras-dependent Erk activation.

[20] Junichi Matsuo et al. found that the promotion of the Ras-Erk signaling pathway by IQGAP 3 in gastric cancer is a key mechanism underlying the proliferation of gastric cancer stem cells in vivo.

[21] However, the mechanism of action of IQGAP3 in breast cancer remains unclear.

[0009] References:

[0010] [1]Siegel RL,Giaquinto AN,Jemal A.Cancer statistics,2024.CACancer JClin.2024.74(1):12-49.

[0011] [2]Giaquinto AN,Sung H,Newman LA,et al.Breast cancer statistics2024.CACancer J Clin.2024.74(6):477-495.

[0012] [3] Slamon DJ, Godolphin W, Jones LA, et al. Studies of the HER-2 / neuproto-oncogene in human breast and ovarian cancer. Science. 1989.244(4905):707-12.

[0013] [4]Cameron D, Piccart-Gebhart MJ, Gelber RD, et al.11years'follow-up oftrastuzumab after adjuvant chemotherapy in HER2-positive early breast cancer: final analysis of the HERceptin Adjuvant(HERA) trial.Lancet.2017.389(10075):1195-1205.

[0014] [5]Nahta R, Esteva FJ. Herceptin: mechanisms of action and resistance. Cancer Lett. 2006.232(2):123-38.

[0015] [6] Geyer CE, Forster J, Lindquist D, et al. Lapatinib plus capecitabine for HER2-positive advanced breast cancer. N Engl J Med. 2006. 355(26): 2733-43.

[0016] [7] Johnston S, Hegg R, Im SA, et al. Phase III, Randomized Study of Dual Human Epidermal Growth Factor Receptor 2 (HER2) Blockade With Lapatinib Plus Trastuzumab in Combination With an Aromatase Inhibitor in Postmenopausal Women With HER2-Positive, Hormone Receptor-Positive Metastatic Breast Cancer: Updated Results of ALTERNATIVE. J Clin Oncol. 2021. 39(1): 79-89.

[0017] [8] Chan A, Delaloge S, Holmes FA, et al. Neratinib after trastuzumab-based adjuvant therapy in patients with HER2-positive breast cancer (ExteNET): a multicentre, randomised, double-blind, placebo-controlled, phase 3 trial. Lancet Oncol. 2016. 17(3): 367-377.

[0018] [9] Martin M, Holmes FA, Ejlertsen B, et al. Neratinib after trastuzumab-based adjuvant therapy in HER2-positive breast cancer (ExteNET): 5-year analysis of a randomised, double-blind, placebo-controlled, phase 3 trial. Lancet Oncol. 2017. 18(12): 1688-1700.

[0019]

[10] Gianni L, Pienkowski T, Im YH, et al. Efficacy and safety of neoadjuvant pertuzumab and trastuzumab in women with locally advanced, inflammatory, or early HER2-positive breast cancer (NeoSphere): a randomised multicentre, open-label, phase 2 trial. Lancet Oncol. 2012. 13(1): 25-32.

[0020]

[11] Gianni L, Pienkowski T, Im YH, et al. 5-year analysis of neoadjuvant pertuzumab and trastuzumab in patients with locally advanced, inflammatory, or early-stage HER2-positive breast cancer (NeoSphere): a multicentre, open-label, phase 2 randomised trial. Lancet Oncol. 2016. 17(6): 791-800.

[0021]

[12] Ma F, Yan M, Li W, et al. Pyrotinib versus placebo in combination with trastuzumab and docetaxel as first line treatment in patients with HER2 positive metastatic breast cancer (PHILA): randomised, double blind, multicentre, phase 3 trial. BMJ. 2023. 383: e076065.

[0022]

[13] Wu J, Jiang Z, Liu Z, et al. Neoadjuvant pyrotinib, trastuzumab, and docetaxel for HER2-positive breast cancer (PHEDRA): a double-blind, randomized phase 3 trial. BMC Med. 2022. 20(1): 498.

[0023]

[14] Cao J, Teng Y, Li H, et al. Pyrotinib plus capecitabine for trastuzumab-resistant, HER2-positive advanced breast cancer (PICTURE): a single-arm, multicenter phase 2 trial. BMC Med. 2023. 21(1): 300.

[0024]

[15] Dogruluk T, Tsang YH, Espitia M, et al. Identification of Variant-Specific Functions of PIK3CA by Rapid Phenotyping of Rare Mutations. Cancer Res. 2015. 75(24): 5341-54.

[0025]

[16] Hanker AB, Pfefferle AD, Balko JM, et al. Mutant PIK3CA accelerates HER2-driven transgenic mammary tumors and induces resistance to combinations of anti-HER2 therapies. Proc Natl Acad Sci U S A. 2013. 110(35):14372-7.

[0026]

[17] Thines L, Roushar FJ, Hedman AC, Sacks DB. The IQGAP scaffolds: Critical nodes bridging receptor activation to cellular signaling. J Cell Biol. 2023. 222(6):e202205062.

[0027]

[18] Shi Y, Qin N, Zhou Q, et al. Role of IQGAP3 in metastasis and epithelial-mesenchymal transition in human hepatocellular carcinoma. J Transl Med. 2017. 15(1):176.

[0028]

[19] Song F, Dai Q, Grimm MO, Steinbach D. The Antithetic Roles of IQGAP2 and IQGAP3 in Cancers. Cancers (Basel). 2023. 15(4):1115.

[0029]

[20] Nojima H, Adachi M, Matsui T, Okawa K, Tsukita S, Tsukita S. IQGAP3 regulates cell proliferation through the Ras / ERK signalling cascade. Nat Cell Biol. 2008. 10(8):971-8.

[0030]

[21] Matsuo J, Douchi D, Myint K, et al. Iqgap3-Ras axis drives stem cell proliferation in the stomach corpus during homoeostasis and repair. Gut. 2021. 70(10): 1833-1846. SUMMARY

[0031] In order to overcome the deficiencies of the prior art, the present application provides a breast cancer marker and a therapeutic target.

[0032] The present application provides the application of IQGAP3 as a breast cancer marker.

[0033] The present application provides the application of IQGAP3 as a breast cancer marker in the preparation of a breast cancer diagnostic product.

[0034] The present application provides the application of IQGAP3 as a drug action target in the development and screening of drugs for treating breast cancer. Further, the present application provides the application of an IQGAP3 inhibitor in the preparation of a drug for treating breast cancer.

[0035] Further, the present application also provides the application of pyrotinib as an IQGAP3 inhibitor.

[0036] As preferred, the breast cancer described in the present application is HER2-positive breast cancer, is HER2-positive breast cancer resistant to targeted drugs, is HER2-positive breast cancer resistant to targeted drugs caused by PIK3CA mutation.

[0037] Further, the PIK3CA mutation is PIK3CA H1047R mutation.

[0038] The present application discloses the mechanism of action of IQGAP3 in breast cancer, and how to play a key role in trastuzumab resistance caused by PIK3CA H1047R mutation; it is revealed that the anti-tumor therapeutic effect can be achieved by inhibiting IQGAP3. The present application provides a new idea for the development of new drugs and the formulation of treatment strategies for breast cancer patients, especially HER2-positive breast cancer patients resistant to targeted drugs. BRIEF DESCRIPTION OF DRAWINGS

[0039] Figure 1 .PIK3CA hotspot mutation is related to clinical non-pathological complete remission

[0040] (A) Neoadjuvant cohort high frequency mutation gene distribution: The top 10 genes with the highest mutation frequency in 23 neoadjuvant breast cancer patients (column height represents the percentage of mutations, genes are ranked in descending order of frequency). The mutation frequency of PIK3CA was 34.78%, second only to TP53 (91.53%);

[0041] (B) Predictive value of PIK3CA mutation on treatment response: For the 10 genes shown in Figure A, the correlation risk analysis was performed according to whether the patient had pCR after treatment. The results showed that the risk of non-pCR in patients with PIK3CA mutation after neoadjuvant treatment containing trastuzumab was 1.69 times that of patients without mutation, and the result had statistical effect. (RR = 1.69, p = 0.023, CI = 1.076-2.653);

[0042] (C) PIK3CA hotspot mutation spectrum: The frequency and proportion of all PIK3CA gene hotspot mutations detected in 23 samples. Figure 2 . Effect of trastuzumab on the activity of HER2-positive breast cancer cell lines

[0043] (A) Sensitivity of HER2-positive cell lines to trastuzumab: Cell activity of 6 HER2-positive breast cancer cell lines after continuous treatment with gradient-diluted trastuzumab for 5 days. The results showed that HCC-1954 (containing PIK3CA H1047R mutation), MDA-MB-453 (containing PIK3CA H1047R mutation), and MDA-MB-361 (containing PIK3CA E545K mutation) had cell activity higher than 80% after continuous treatment with the maximum concentration (100 μg / mL) of trastuzumab for 5 days;

[0044] (B) Comparison of drug resistance between PIK3CA mutation group and wild type group: The 6 cells in Figure A were divided into two groups according to the presence or absence of hotspot PIK3CA mutation (HCC-1954, MDA-MB-453, and MDA-MB-361 were in the MT group, and SK-BR-3, BT-474, and ZR-75-30 were in the WT group). The cell activity after treatment with trastuzumab at a concentration of 100 μg / mL for 5 days was compared, and the results of MT vs WT were 90.13% vs 51.13%, p = 0.0012, (n = 3);

[0045] (C) H1047R overexpression induces drug resistance: Cell viability of SK-BR-3 cells stably transfected with wild-type PIK3CA overexpression plasmid, H1047R mutant PIK3CA overexpression plasmid, empty plasmid respectively after 5 days treatment with corresponding gradient dilution of trastuzumab. The results show that under the same concentration of trastuzumab treatment, the cell viability of cells stably transfected with H1047R mutant PIK3CA overexpression plasmid is higher than that of cells stably transfected with wild-type PIK3CA overexpression plasmid (n = 5);

[0046] (D) Schematic diagram of overexpression plasmid construction: Schematic diagram of wild-type PIK3CA overexpression plasmid and H1047R mutant PIK3CA overexpression plasmid.

[0047] Figure 3 .PIK3CA H1047R Mutations promote cell proliferation and resist trastuzumab drug inhibition

[0048] (A) Mutations promote proliferation and resist trastuzumab drug inhibition: Comparison of the effects of stably transfected wild-type PIK3CA overexpression plasmid and H1047R mutant PIK3CA overexpression plasmid on the proliferation rate of SK-BR-3 cells, and the change in cell proliferation rate after the addition of trastuzumab treatment; (n = 5)

[0049] (B) Quantitative analysis of EdU experiment: Quantitative analysis of EdU experiment results using Image J, and analysis of genotype changes and drug treatment using two-way ANOVA. The H1047R mutation significantly up-regulates the proportion of EdU positive cells (WT mean = 40.86 vs mutant mean = 54.71, P < 0.0001); trastuzumab treatment reduces the expression of target proteins as a whole (control group mean = 49.35 vs treatment group mean = 46.23, P = 0.0042); the inhibitory effect of trastuzumab is significant in WT cells (difference = 7.005, P = 0.0005), but ineffective in H1047R mutants (difference = -0.7704, P > 0.05), indicating that the mutation leads to drug resistance. The mean ± SD (n = 9) was determined by two-way ANOVA and Tukey post-hoc test for significance;

[0050] (C) Representative images of EdU: EdU experiment results after stably transfected overexpression plasmid and addition of 100 μg / mL trastuzumab treatment. Red: EdU positive (proliferating) cells; blue: DAPI stained nucleus. The H1047R group has a significantly higher density of proliferating cells than the wild type, and trastuzumab treatment does not reduce the number of positive cells.

[0051] Figure 4 .Effect of pyrotinib on the viability of HER2-positive breast cancer cells

[0052] (A) HER2-positive cell lines sensitivity to pyrotinib: Left panel shows cell viability of a HER2-positive breast cancer cell line after 5-day treatment with gradient concentrations of pyrotinib. Right panel demonstrates the difference of mean IC50 of pyrotinib after grouping by MT, WT. Grouping is the same as in (A). Figure 6 (A) HER2-positive cell lines sensitivity to pyrotinib: Left panel shows cell viability of a HER2-positive breast cancer cell line after 5-day treatment with gradient concentrations of pyrotinib. Right panel demonstrates the difference of mean IC50 of pyrotinib after grouping by MT, WT. Grouping is the same as in (A). Figure 2 B. No statistical difference in mean IC50; (n = 3)

[0053] (B) H1047R overexpression does not affect pyrotinib sensitivity: Cell viability of SK-BR-3 cells after 5-day treatment with gradient concentrations of trastuzumab after stable transfection of wild-type PIK3CA overexpression plasmid, H1047R mutant PIK3CA overexpression plasmid, empty plasmid respectively. No significant difference in mean IC50; (n = 5)

[0054] (C) EdU quantification analysis: Quantitative analysis of EdU experimental results using Image J, analysis of genotype change and drug treatment using two-way ANOVA. Pyrotinib significantly reduces the proportion of EdU positive cells. (Control group mean = 49.10 vs. pyrotinib group mean = 19.65, difference = 29.45, P < 0.0001); H1047R mutation enhances pyrotinib sensitivity: In H1047R mutant, pyrotinib has stronger inhibitory effect. (WT group difference = 23.18 vs. mutant group difference = 35.71, interaction P < 0.0001); H1047R mutation causes a slight increase in the proportion of EdU positive cells (WT mean = 31.50 vs. mutant mean = 37.25, P = 0.0002). Data are mean ± SD (n = 9), significance determined by two-way ANOVA and Tukey post-hoc test;

[0055] (D) Representative images of EdU: EdU experimental results after stable transfection of overexpression plasmid and addition of 50 nM pyrotinib treatment. Red: EdU positive proliferating cells; Blue: DAPI stained nucleus. Pyrotinib treatment group has significantly reduced positive cells, and the mutant group has more obvious inhibition.

[0056] Figure 5 . Pyrotinib and trastuzumab comparison of inhibition of wild-type and PIK3CA H1047R mutant SK-BR-3 cell clones and tumor sphere formation

[0057] (A) Representative images of colony formation: Plate colony experiment results after 14-day continuous treatment of wild-type and H1047R mutant SK-BR-3 cells with control drug, 50 nM pyrotinib, 100 μg / mL trastuzumab respectively;

[0058] (B) Colony formation quantification analysis: Quantitative analysis of the plate colony experiment. H1047R mutation significantly enhanced the colony formation ability (WT control mean = 52.20 vs mutant control mean = 68.67, P = 0.0304); the pyrotinib significantly inhibited the colony formation in both WT and mutant (WT inhibition difference = 34.13, P = 0.0090; mutant inhibition difference = 49.73, P = 0.0054); trastuzumab significantly inhibited only in WT (WT inhibition difference = 29.80, P = 0.0299), but was ineffective in mutant (difference = -5.800, P > 0.05). Significance was analyzed by Tukey's multiple comparison test (P < 0.05, P < 0.01, P < 0.001, P < 0.0001), data are mean ± SEM (n = 3);

[0059] (C) Tumor sphere formation images: Results of tumor sphere formation experiment after 14 days of continuous treatment of wild type and H1047R mutant SK-BR-3 cells with control drug, 50 nM pyrotinib, respectively;

[0060] (D) Tumor sphere quantification analysis: Two-way ANOVA analysis of tumor sphere experiment results, tumor sphere formation ability was significantly lower in pyrotinib treatment group than in control group (control mean = 269.2 vs pyrotinib mean = 103.0, difference = 166.2, P < 0.0001, 95% CI: 140.1-192.3); H1047R mutation had no significant effect on the basal ability of tumor sphere formation (WT mean = 183.2 vs mutant mean = 189.0, P = 0.6201), and there was no interaction between mutation and pyrotinib effect. Data are mean ± SD (n = 3).

[0061] Figure 6 . Effect of pyrotinib on cell cycle

[0062] (A) Cell cycle flow cytometry images: Results of cell cycle experiment of wild type or H1047R mutant SK-BR-3 cells after treatment with 50 nM pyrotinib or control drug;

[0063] (B) Cell cycle proportion statistics: The proportion of cells in G0 / G1 phase, S phase, and G2 phase in each group under corresponding treatment. (n = 3). Figure 7 . Effect of pyrotinib on tumor stem cells

[0064] (A) Tumor stem cell marker flow cytometry images: CD44+ / CD24- cells in wild type or H1047R mutant SK-BR-3 cells after treatment with 50 nM pyrotinib or control drug;

[0065] (B) CD44 + / CD24- Proportion analysis: One-way ANOVA was used to analyze the proportion of CD44+ / CD24- cells after different treatments in the flow cytometry results. The data were mean ± SD (n = 3), and the differences between groups were determined by one-way ANOVA and Tukey's multiple comparison test. The difference between WT control group (WT + Con) and WT pyrotinib group (WT + Py) = 16.73 (P < 0.0001); the difference between mutant control group (H1047R + Con) and mutant pyrotinib group (H1047R + Py) = 17.87 (P < 0.0001); H1047R mutation slightly enhanced the ability of basal tumor sphere formation (WT + Con mean = 36.20 vs H1047R + Con mean = 37.90, P = 0.0115); there was no significant difference in the inhibitory effect of pyrotinib in WT and mutant (WT + Py vs H1047R + Py difference = -0.5667, P = 0.5186).

[0066] Figure 8 .PIK3CA H1047R Effect of mutation on gene expression and signal pathway regulation in SK-BR-3 cells

[0067] (A) Differential gene heat map: comparison of differential genes after stable transfection of wild-type PIK3CA overexpression plasmid and H1047R mutant PIK3CA overexpression plasmid in SK-BR-3 cells (later simply expressed as WT, H1047R), red indicates up-regulation, blue indicates down-regulation; (n = 3)

[0068] (B) HALLMARK pathway enrichment: HALLMARK enrichment analysis of differential genes in WT and H1047R groups, red indicates up-regulation, blue indicates down-regulation;

[0069] (C) KEGG-GSEA analysis: GSEA enrichment analysis of all genes in WT and H1047R groups in KEGG dataset. The peak on the upper left indicates up-regulation in the H1047R group.

[0070] Figure 9 . Effect of pyrotinib on PIK3CA H1047R Effect of mutation on gene expression and signal pathway regulation in SK-BR-3 cells

[0071] (A) Drug treatment differential gene heat map: comparison of differential genes after treatment with control drug and 50 nM pyrotinib for 5 days in SK-BR-3 cells with H1047R mutant PIK3CA overexpression plasmid (later simply expressed as pyrotinib, control), red indicates up-regulation, blue indicates down-regulation; (n = 3)

[0072] (B) HALLMARK pathway inhibition: HALLMARK enrichment analysis was performed on the differentially expressed genes in both control and pyrotinib groups, red indicates up-regulation of the pathway, blue indicates down-regulation;

[0073] (C) KEGG-GSEA down-regulated pathways: GSEA enrichment analysis was performed on the expression of all genes in both control and pyrotinib groups in KEGG dataset. The peak on the lower right indicates down-regulation in the pyrotinib treatment group.

[0074] Figure 10 . Effect of trastuzumab and pyrotinib on the expression of key signaling pathway proteins

[0075] (A) Western blot of key signaling proteins: After treatment of HCC-1954, MDA-MB-453, BT-474, and SK-BR-3 breast cancer cells with control drug, 50 nM pyrotinib, and 100 μg / mL trastuzumab for 5 days, the expression of PI3K-AKT-MTOR pathway and MAPK key proteins was detected.

[0076] (B) Quantitative analysis of phosphorylated proteins: After quantification of protein changes in HCC-1954 cells after corresponding treatment using ImageJ, the results showed that phosphorylated AKT (p-AKT / AKT) decreased by 37.7% (Control mean = 0.937 vs Pyrotinib mean = 0.584, P = 0.0062) after pyrotinib treatment; phosphorylated ERK (p-ERK / ERK) decreased by 81.7% (Control mean = 1.225 vs Pyrotinib mean = 0.224, P = 0.0005); phosphorylated S6 (p-S6 / GAPDH) decreased by 37.1% (Control mean = 0.412 vs Pyrotinib mean = 0.259, P = 0.0272). Trastuzumab only significantly inhibited p-AKT (decreased by 29.2%, P = 0.0245), but had no significant effect on p-S6 (P = 0.0761), and activated p-ERK (Control mean = 1.225 vs Trastuzumab mean = 1.340, P = 0.0156). Data are mean ± SD (n = 3) by Dunnett's multiple comparison test (compared with the control group);

[0077] (C) Phospho-protein quantification analysis: Analysis of the relative protein changes after corresponding treatments in MDA-MB-453 cells using ImageJ quantification. Results showed that pyrotinib treatment decreased the level of phosphorylated AKT (p-AKT / AKT) by 35.1% (Control mean = 1.050 vs Pyrotinib mean = 0.681, P = 0.0081); phosphorylated ERK (p-ERK / ERK) by 40.3% (Control mean = 1.018 vs Pyrotinib mean = 0.608, P = 0.0046); and phosphorylated S6 (p-S6 / GAPDH) by 57.6% (Control mean = 0.654 vs Pyrotinib mean = 0.277, P = 0.0395). Trastuzumab only partially inhibited p-AKT (decrease by 17.0%, P = 0.0140) and had no significant effect on p-ERK and p-S6 (P > 0.05); p-ERK showed a non-significant increasing trend (Control mean = 1.018 vs Trastuzumab mean = 1.061, P = 0.0853). Data are mean ± SD (n = 3) by Dunnett’s multiple comparison test (compared with the control group);

[0078] (D) Phospho-protein quantification analysis: Analysis of the relative protein changes after corresponding treatments in BT-474 cells using ImageJ quantification. Pyrotinib treatment decreased the level of phosphorylated AKT (p-AKT / AKT) by 53.2% (Control mean = 1.209 vs Pyrotinib mean = 0.565, P = 0.0119); phosphorylated ERK (p-ERK / ERK) by 89.6% (Control mean = 1.075 vs Pyrotinib mean = 0.112, P = 0.0005); and phosphorylated S6 (p-S6 / GAPDH) by 58.2% (Control mean = 0.771 vs Pyrotinib mean = 0.322, P = 0.0025). Trastuzumab inhibited p-AKT (decrease by 34.9%, P = 0.0060) and p-S6 (decrease by 17.0%, P = 0.0072), but had a weaker effect on p-ERK (decrease by 51.3%, P = 0.0315). Data are mean ± SD (n = 3) by Dunnett’s multiple comparison test (compared with the control group);

[0079] (E) Phosphorylated protein quantification analysis: The relative protein changes of SK-BR-3 cells after corresponding treatments were analyzed after quantification using ImageJ. The level of phosphorylated AKT (p-AKT / AKT) was reduced by 57.7% after pyrotinib treatment (Control mean = 0.993 vs Pyrotinib mean = 0.420, P = 0.0160); the level of phosphorylated ERK (p-ERK / ERK) was reduced by 82.0% (Control mean = 1.034 vs Pyrotinib mean = 0.186, P = 0.0015); the level of phosphorylated S6 (p-S6 / GAPDH) was reduced by 21.4% (Control mean = 0.827 vs Pyrotinib mean = 0.650, P = 0.0258); trastuzumab significantly inhibited p-AKT (reduced by 26.1%, P = 0.0094) and p-ERK (reduced by 50.6%, P = 0.0013), but had no significant effect on p-S6 (P = 0.1479); data are mean ± SD (n = 3) by Dunnett's multiple comparison test (compared with the control group).

[0080] Figure 11 .PIK3CA H1047R Construction of mutant protein-specific interaction protein network and screening of IQGAP3

[0081] (A) CO-IP combined with silver staining results: silver staining results after WB experiment after COIP experiment;

[0082] (B) Mass spectrometry interaction protein quantification: mass spectrometry result analysis quantification figure, the horizontal coordinate is the expression difference fold of the protein expression pulled by wild type PIK3CA and IGG control group, the vertical coordinate is the expression difference fold of the protein expression pulled by H1047R mutant PIK3CA and IGG control group;

[0083] (C) Interaction protein screening Venn diagram: Venn diagram showing screening method and screening results.

[0084] Figure 12 .PIK3CA H1047R Verification of the mechanism of mutation-enhanced interaction with IQGAP3 protein

[0085] (A) AlphaFold3 predicted complex structure: using AlphaFold3 model to predict the interaction of H1047R mutant PIK3CA protein and IQGAP3 protein;

[0086] (B) Mutant interface binding energy analysis: prediction of the docking position of H1047R mutant PIK3CA protein and IQGAP3 protein; (C) Immunofluorescence co-localization: the results of immunofluorescence co-localization experiment, red color represents FLAG-labeled PIK3CA protein, mainly distributed in the cytoplasm. Green color represents IQGAP3 protein, mainly distributed in the cytoplasm. Blue color represents DAPI, mainly located in the nucleus. Coloc2 was used to analyze the co-localization of PIK3CA and IQGAP3, and the abscissa represents PIK3CA and the ordinate represents IQGAP3. Co-localization quantitative analysis: the Pearson correlation coefficient of H1047R group was significantly higher than that of wild type group (0.5689 ± 0.03 vs 0.4256 ± 0.02, P = 0.0004) in Coloc2 analysis. Data are mean ± SD (n = 9).

[0087] Figure 13 .COIP experimental flowchart.

[0088] Figure 14 .IQGAP3 truncated body verifies PIK3CA H1047R Mutant-specific interaction mechanism

[0089] (A) IQGAP3 truncated body schematic diagram: full-length domain of IQGAP3 and design of truncated body;

[0090] (B) IP verification experiment design: IP experiment verifies the docking experiment flowchart of PIK3CA and IQGAP3.

[0091] (C) Truncated body interaction detection: IP experiment verifies the docking region of IQGAP3 and mutant PIK3CA.

[0092] Figure 15 .Clinical significance and prognostic value of IQGAP3 in cancer

[0093] (A) Pan-cancer tissue expression difference: IQGAP3 expression difference in cancer and paracancer tissues in pan-cancer database;

[0094] (B) Survival analysis: KM database analysis of survival time difference between high expression group and low expression of IQGAP3 in HER2 positive breast cancer.

[0095] Figure 16 .IQGAP3 high expression group enrichment pathway (A) Pathway enrichment analysis: GSEA analysis of up-regulated pathways enriched in IQGAP3 high expression group.

[0096] Figure 17 .Knockdown of IQGAP3 on PIK3CA H1047R Effect on mutant cell proliferation and change in sensitivity to trastuzumab

[0097] (A) Cell proliferation curves: comparison of the effect of IQGAP3 knockdown using siRNA and control treatment on cell proliferation in MDA-MB-453, and change in the rate of cell proliferation after 5 days of treatment with 100 pg / mL trastuzumab in combination; (n=5)

[0098] (B) Cell proliferation curves: comparison of the effect of IQGAP3 knockdown using siRNA and control treatment on cell proliferation in HCC-1954 cells, and change in the rate of cell proliferation after 5 days of treatment with 100 pg / mL trastuzumab.

[0099] Figure 18 . Effect of trastuzumab on PIK3CA H1047R mutant cell proliferation capacity after IQGAP3 knockdown

[0100] (A) EdU representative images: comparison of the EdU results after IQGAP3 knockdown using siRNA and 5 days of treatment with 100 pg / mL trastuzumab in MDA-MB-453 and HCC-1954 cells, and corresponding control treatments;

[0101] (B) EdU quantification analysis: Image J was used for the quantification analysis of EdU experimental results. In MDA-MB-453 cells, the proportion of EdU positive cells in SiIQGAP3 group was significantly lower than that in Scramble group (difference = 23.20, P < 0.0001, 95% CI: 20.75-25.66); in Scramble cells, trastuzumab only slightly inhibited the proportion of EdU positive cells (difference = 4.848, P > 0.05); in SiIQGAP3 cells, trastuzumab significantly inhibited the proportion of EdU positive cells (difference = 17.60, P < 0.0001). IQGAP3 knockdown enhanced the inhibitory effect of trastuzumab by 12.75 units (P = 0.0017, 95% CI: 6.364-19.14), suggesting that IQGAP3 is a regulatory factor of trastuzumab resistance. In HCC-1954 cells, the proportion of EdU positive cells in SiIQGAP3 group was significantly lower than that in Scramble group (difference = 20.80, P < 0.0001, 95% CI: 17.33-24.27); in Scramble cells, trastuzumab only slightly inhibited the activity (difference = -3.750, P > 0.05); in SiIQGAP3 cells, trastuzumab significantly inhibited the activity (difference = 17.13, P < 0.0001); IQGAP3 knockdown enhanced the inhibitory effect of trastuzumab by 20.88 units (P < 0.0001, 95% CI: 16.79-24.97), suggesting that IQGAP3 is a potential regulatory factor of trastuzumab resistance. Data are mean ± SD (n = 9 biological replicates), and significance was determined by two-way repeated measures ANOVA and post-hoc test.

[0102] Figure 19 . Effect of trastuzumab on cell cycle after IQGAP3 knockdown

[0103] (A) Cell cycle flow cytometry: cell cycle experimental results of siRNA knockdown or non-knockdown groups after treatment with 100 μg / mL trastuzumab or control drug;

[0104] (B) Cycle proportion statistics: the proportion of cells in G0 / G1 phase, S phase, and G2 phase in each group under corresponding treatment; (n = 3). Figure 20 . Effect of trastuzumab on the proportion of tumor stem cells after IQGAP3 knockdown

[0105] (A) Tumor stem cell marker flow cytometry: CD44+ / CD24- cells in siRNA knockdown or non-knockdown groups after treatment with 100 μg / mL trastuzumab or control drug;

[0106] (B) CD44 + / CD24- Proportion quantification: One-way ANOVA was used to analyze the proportion of CD44+ / CD24- cells in different treatments in flow cytometry results. Data were mean ± SD (n = 3). Differences between groups were determined by one-way ANOVA and Tukey's multiple comparison test. In MDA-MB-453 cells, SiIQGAP3 knockdown significantly reduced the proportion of CD44+ / CD24- cells (Scramble + Con mean = 91.20 vs SiIQGAP3 + Con mean = 81.93, P < 0.0001); in Scramble cells, trastuzumab had a slight inhibitory effect (Scramble + Con vs Scramble + Tras difference = 2.367, P = 0.0008); in SiIQGAP3 knockdown cells, trastuzumab further significantly inhibited activity (SiIQGAP3 + Con vs SiIQGAP3 + Tras difference = 2.667, P = 0.0003); the inhibitory effect of IQGAP3 knockdown combined with trastuzumab was the strongest (Scramble + Con vs SiIQGAP3 + Tras difference = 11.93, P < 0.0001), and significantly better than the effect of trastuzumab monotherapy in Scramble cells (difference = 9.567, P < 0.0001). In HCC-1954 cells, SiIQGAP3 knockdown significantly reduced the proportion of CD44+ / CD24- cells (Scramble + Con mean = 90.10 vs SiIQGAP3 + Con mean = 85.80, P < 0.0001); in Scramble cells, trastuzumab had no significant inhibitory effect (Scramble + Con vs Scramble + Tras difference = 0.5333, P = 0.0928); in SiIQGAP3 knockdown cells, trastuzumab further inhibited the proportion of CD44+ / CD24- cells (SiIQGAP3 + Con vs SiIQGAP3 + Tras difference = 0.9000, P = 0.0070); the inhibitory effect of IQGAP3 knockdown combined with trastuzumab was the strongest (Scramble + Con vs SiIQGAP3 + Tras difference = 5.200, P < 0.0001); the inhibitory effect of trastuzumab in the knockdown group was significantly better than that in the Scramble group (SiIQGAP3 + Tras vs Scramble + Tras difference = 4.667, P < 0.0001).

[0107] Figure 21 Prediction and verification of small molecule pyrotinib docking with IQGAP3

[0108] (A) Molecular docking 2D structure: The 2D structure predicts the docking site of pyrotinib with IQGAP3;

[0109] (B) 3D binding mode analysis: 3D structure simulation shows that the active ingredient of small molecule pyrotinib can bind to the active pocket on the surface of IQGAP3 protein;

[0110] (C) IQGAP3 protein expression detection: WB experiment detects the inhibitory effect of pyrotinib on IQGAP3 protein expression.

[0111] Figure 22 . Effect of overexpression of IQGAP3 on the effect of pyrotinib on cell proliferation

[0112] (A) Representative images of EdU: EdU experiment results of overexpression of IQGAP3 and addition of 50nM pyrotinib for continuous treatment for 5 days in MDA-MB-453 and HCC-1954 cells and corresponding control treatment;

[0113] (B) Quantitative analysis of EdU: Quantitative analysis of EdU experiment results using Image J. Cell activity / survival rate of IQGAP3 OE group is significantly higher than that of Mock group (Mock mean = 18.62 vs OE mean = 27.54, difference = -8.924, P < 0.0001, 95% CI: -10.56 to -7.287); in the Mock group, pyrotinib significantly inhibits cell activity (Control mean = 27.23 vs Pyrotinib mean = 18.94, difference = 8.289, P < 0.0001, 95% CI: 6.652-9.927); in the IQGAP3 OE group, the inhibitory effect of pyrotinib is significantly weakened (inhibition difference = 4.613, P < 0.0001); data are mean ± SD (n = 9 biological replicates), and significance is determined by two-way ANOVA and post-hoc test.

[0114] Figure 23 . Effect of pyrotinib on cell cycle after overexpression of IQGAP3

[0115] (A) Cell cycle flow chart: cell cycle experiment results of overexpression of IQGAP3 or control group after treatment with 50nM pyrotinib or control drug for 5 days;

[0116] (B) Cycle proportion statistics: the proportion of cells in G0 / GI phase, S phase, and G2 phase in each group under corresponding treatment.

[0117] Figure 24 . Effect of pyrotinib on tumor stem cells after overexpression of IQGAP3

[0118] (A) Tumor stem cell marker flow cytometry: the percentage of IQGAP3 or control CD44+ / CD24- cells after 10 nM pyrotinib or control drug treatment for 5 days;

[0119] (B) CD44 + / CD24 - Ratio quantification: one-way ANOVA of the percentage of CD44+ / CD24- cells after corresponding treatment. The results showed that in Mock cells, pyrotinib significantly inhibited the proportion of CD44+ / CD24- cells (Control mean = 32.87 vs Pyrotinib mean = 19.33, difference = 13.53, P < 0.0001); IQGAP3 overexpression significantly enhanced the basal activity of cells (Mock + Control mean = 32.87 vs IQGAP3 OE + Control mean = 37.17, difference = -4.300, P < 0.0001); in IQGAP3 OE cells, the inhibitory effect of pyrotinib was weakened (inhibition difference = 5.967, P < 0.0001), which was only 44% of the Mock group (5.967 vs 13.53); IQGAP3 overexpression reduced the inhibitory effect of pyrotinib by 11.87 units (Mock + Pyrotinib vs IQGAP3 OE + Pyrotinib difference = -11.87, P < 0.0001). Data are mean ± SD (n = 3 biological replicates), and significance was determined by Tukey's multiple comparison test.

[0120] Figure 25 . Procedure of animal experiment and results of subcutaneous tumor formation

[0121] (A) Schematic diagram of experimental procedure: the procedure of animal model construction, the frequency and dose of drug treatment, and the time nodes of data collection;

[0122] (B) Transplanted tumor samples: specific grouping methods and final subcutaneous tumors collected from mice (n = 5).

[0123] Figure 26 . Changes in subcutaneous tumor volume and live imaging of two groups of mice

[0124] (A) Tumor growth curve: changes in the volume of tumors in each group;

[0125] (B) Comparison of live imaging: comparison of changes in tumor size before and after drug treatment in the whole cycle of live imaging of animals; (C) Body weight changes: changes in the body weight of mice during the whole process of animal experiment.

[0126] Figure 27 . Typical images and quantitative analysis of immunohistochemistry of transplanted tumors in wild-type group mice

[0127] (A) Immunohistochemistry representative images: Immunohistochemistry results of wild-type mouse subcutaneous tumor paraffin-embedded sections;

[0128] (B) HER2 expression quantification: Quantitative analysis of HER2 expression immunohistochemistry results, one-way ANOVA showed no significant difference between groups. KI67 expression quantification analysis: In wild-type PIK3CA tumorigenic group, pyrotinib (P=0.0059) and trastuzumab (P=0.0088) alone treatment significantly inhibited KI67 expression, but there was no difference between the two (P=0.9971); the combination of the two drugs significantly inhibited the effect of single drug (Py+Tras vs Py difference=0.06694, P=0.0021; Py+Tras vs Tras difference=0.06992, P=0.0014). The inhibition rate of the combination treatment group was 46.2% higher than that of the control group (difference=0.1261, P<0.0001). IQGAP3 expression quantification analysis. In the wild-type PIK3CA tumorigenic group, pyrotinib alone significantly reduced IQGAP3 expression (Control mean=24.61% vs Py mean=18.07%, P<0.0001); trastuzumab alone had no significant effect on IQGAP3 expression (Control vs Tras difference=1.17%, P=0.5799); the combination of the two drugs had no difference with pyrotinib alone (Py vs Py+Tras difference=0.40%, P=0.9704), but was significantly stronger than trastuzumab alone (Tras vs Py+Tras difference=5.77%, P<0.0001).

[0129] Figure 28 .PIK3CA H1047R Typical images and quantitative analysis of immunohistochemistry of mutant mouse transplanted tumor

[0130] (A) Immunohistochemistry representative images: Immunohistochemistry results of H1047R mutant mouse subcutaneous tumor paraffin-embedded sections;

[0131] (B) HER2 expression quantification: Quantitative analysis of HER2 expression immunohistochemistry results showed no significant difference between groups by One-way ANOVA. KI67 expression quantification: In H1047R mutant PIK3CA tumorigenic group, pyrotinib monotherapy significantly reduced KI67 expression (Control mean = 36.05% vs Py mean = 23.00%, P < 0.0001); trastuzumab monotherapy had no significant effect on KI67 expression (Control vs Tras difference = 2.96%, P = 0.4131); the combination had a significantly stronger inhibitory effect than trastuzumab monotherapy (Tras vs Py+Tras difference = 6.62%, P = 0.0127), but was not different from pyrotinib monotherapy (Py vs Py+Tras difference = -3.47%, P = 0.2821). Data are mean ± SD (n = 5 biological replicates), with significance determined by Tukey’s multiple comparison test. IQGAP3 expression quantification: In H1047R mutant PIK3CA tumorigenic group, pyrotinib monotherapy significantly reduced IQGAP3 expression (Control mean = 26.03% vs Py mean = 15.59%, P < 0.0001); trastuzumab monotherapy had no effect on IQGAP3 expression (Control vs Tras difference = -0.29%, P = 0.9955); the combination had a significantly stronger inhibitory effect than pyrotinib monotherapy (Py vs Py+Tras difference = -2.00%, P = 0.4051), but was not different from trastuzumab monotherapy (Tras vs Py+Tras difference = 8.73%, P < 0.0001). Data are mean ± SD (n = 5 independent samples), with significance determined by Tukey’s multiple comparison test.

[0132] Figure 29 :1 case of PIK3CA mutant patient drug resistance reversal report. DETAILED DESCRIPTION

[0133] Before further description of the specific embodiments of the present application, it is to be understood that the scope of the present application is not limited to the specific details described below; it is also to be understood that the terminology used herein is for the purpose of describing the specific embodiments only and is not intended to limit the scope of the present application; in the specification and claims of the present application, the singular forms "a", "an" and "the" include the plural forms unless the context clearly indicates otherwise.

[0134] When numerical ranges are given in the embodiments, it should be understood that, unless otherwise stated in this invention, both endpoints of each numerical range and any value between the two endpoints may be selected. Unless otherwise defined, all technical and scientific terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art. In addition to the specific methods, equipment, and materials used in the embodiments, based on the prior art mastery of one of ordinary skill in the art and the description of this invention, any prior art methods, equipment, and materials similar to or equivalent to those described, used, and materials in the embodiments of this invention may be used to implement this invention. Unless otherwise stated, the experimental methods, detection methods, and preparation methods disclosed in this invention all employ conventional techniques in molecular biology, biochemistry, chromatin structure and analysis, analytical chemistry, cell culture, recombinant DNA technology, and related fields.

[0135] Example 1:

[0136] 1.1PIK3CA H1047R Mutations promote cell proliferation, leading to decreased sensitivity of HER2-positive breast cancer cells to trastuzumab.

[0137] Retrospective analysis of past acceptance Data from Foundation Medicine, Inc. on neoadjuvant therapy for breast cancer patients. Of 23 HER2-positive patients, clinical evaluation revealed resistance to TH or THP regimens in 9 cases. Among these, 3 patients had PIK3CA. H1047R Mutation, 1 case with PI3KCA E545K Mutation, another case has PIK3CA E542K Mutations. In contrast, none of the 14 patients who responded clinically to the TH or THP regimens had PIK3CA mutations. H1047R Mutation, PIK3CA detected in only 1 case. E545A Mutations. Genetic testing results showed that among the 23 submitted samples, the 10 genes with the highest mutation frequencies were TP53 (91.3%), PIK3CA (34.78%), BRCA2 (30.43%), etc. Figure 1 A. Statistical analysis of the relative risks of these gene mutations and patient clinical outcomes revealed that the probability of non-PCR after neoadjuvant therapy containing trastuzumab in the PIK3CA mutation group was 1.69 times higher than that in the PIK3CA non-mutation group (p = 0.023, 95% CI = 1.076–2.653). Figure 1 B]. Furthermore, among all detected PIK3CA mutations, H1047R had the highest frequency, at 37.5%, which is consistent with previous reports. Figure 1 C].

[0138] To verify this clinical phenomenon, first, 6 commonly used breast cancer cell lines that have been proven to be HER2 positive were selected for treatment with trastuzumab. Among them, HCC1954, MDA-MB-453 have PIK3CA H1047R mutations, MDA-MD-361 has PIK3CA E545K mutations. Cell viability experiment results show that PIK3CA hotspot mutation cell lines exhibit decreased sensitivity to trastuzumab. After 5 days of treatment with 100 ug / ml trastuzumab, there is a significant difference in cell viability (P = 0.0012)

Figure 2 A, 2B

[0139] Given that PIK3CA H1047R is the most frequently occurring mutation in PI3KCA, some previous studies have also reported that it leads to trastuzumab resistance. To address the issue of clinical treatment options for patients with H1047R mutation-induced trastuzumab resistance, a PIK3CA H1047R overexpression plasmid was used to construct stable transfection cells in SKBR3 cell lines without PIK3CA mutation. WT The PIK3CA H1047R overexpression plasmid was used as a control group

Figure 2 C, 2D

Figure 3 A, 3B, 3C

[0140] 1.2 Pyrotinib inhibits PIK3CA H1047R cell proliferation, blocks G1 cell cycle, and inhibits tumor cell stemness

[0141] CCK8 experiments were used to analyze the sensitivity of the aforementioned 6 HER2-positive breast cancer cells to pyrotinib. The results show that at a blood concentration (220.85 nM) of pyrotinib, the cell viability of cells containing PIK3CA H1047R mutations is less than 50%. There is no statistically significant difference in the average IC50 of cells with and without PIK3CA hotspot mutations after 48 hours of pyrotinib treatment

Figure 4 A

[0142] The aforementioned PIK3CA has stabilized. H1047R Overexpression and PIK3CA WT In SKBR3 cells overexpressing pyrotinib, experiments were performed using CCK8 and EdU assays. CCK8 results showed that, compared to untreated cells, PIK3CA levels were significantly reduced in cells treated with the corresponding concentration of pyrotinib. H1047R Overexpression and PIK3CA WT The IC50 of all overexpression groups was upregulated, but there was no statistically significant difference. Figure 4 B]. EdU results showed that, compared to the control group, PIK3CA H1047R Cell proliferation was increased in the control group, but cell proliferation was significantly inhibited after pyrotinib treatment, with no significant difference compared to the control group. Figure 4 C, 4D]. Flow cytometry analysis of the cell cycle showed that PIK3CA... H1047R The proportion of G1 phase cells in the treatment group was higher than that in the control group, but it decreased after pyrotinib treatment, suggesting that pyrotinib can block PIK3CA. H1047R The transition of tumor cells from G1 phase to S phase. Figure 6 A, 6B].

[0143] The purpose of the plate colony assay was to study the long-term effects of pyrotinib on cell proliferation. Results showed that the cell colony formation rate in the pyrotinib-treated group was significantly lower than that in the control group. Figure 5 [A, 5B]. Studies have shown that tumor stem cells play an important role in tumor growth and colony formation. Therefore, the proportion of stem cells in cell suspensions before and after treatment was detected by flow cytometry. The results showed that pyrotinib significantly reduced PIK3CA. H1047R The ratio of CD44+ / CD24- cells in the group was consistent with the results of the tumor spheroidization assay. Figure 5 C, 5D, 7A, 7B.

[0144] 1.3 Transcriptome sequencing results, pathways, and changes in pathways after drug administration

[0145] To explore the effect of pyrotinib on PIK3CA H1047R The mechanism by which mutation-induced trastuzumab resistance significantly inhibits cell proliferation and stemness was investigated using absolute quantitative transcriptome sequencing to detect the mechanism of PIK3CA mutations. H1047R Overexpression plasmids and PIK3CA WT SKBR3 cells overexpressing the plasmid and PIK3CA after pyrotinib treatment H1047R SKBR3 cells. Sequencing results showed that, compared to PIK3CA... WT Control group, PIK3CA H1047R The group had 244 upregulated genes and 346 downregulated genes. Figure 8A】. GSEA-HALLMARK pathway enrichment results showed that multiple proliferation and cell cycle related pathways were upregulated Figure 8 B】. GSEA-KEGG enrichment results showed that ERBB signaling and PI3K-AKT-MTOR, MAPK and other downstream key pathways were upregulated Figure 8 C】. Comparison of PIK3CA H1047R Group pyrotinib treated and control treated gene data, the results showed that the pyrotinib treatment group 702 genes were up-regulated, 985 genes were down-regulated Figure 9 A】. GSEA enrichment results showed that the key pathways downstream of ERBB and related DNA repair, cell cycle and other pathways were inhibited Figure 9 B, 9C】.

[0146] To further verify the effect of the drug on the key signaling pathways downstream of ERBB, we detected the changes of key proteins in PI3K-AKT-MTOR and MAPK pathways in control group, pyrotinib treatment, trastuzumab treatment in HCC-1954 and MDA-MB-453 cells containing PIK3CA H1047R mutations and SK-BR-3 and BT-474 cells without mutations Figure 10 A】. Statistical results showed that in the two cells of the PIK3CA H1047R group, pyrotinib could significantly inhibit the PI3K-AKT-MTOR pathway and the MAPK pathway, while the inhibitory effect of trastuzumab on the upstream of the PI3K-AKT-MTOR pathway was significantly lower than that of pyrotinib, and there was no significant inhibitory effect on the downstream PS6 protein. In addition, the MAPK pathway may be activated compensatorily Figure 10 B, 10C】. In the two cells of the PIK3CA WT group, pyrotinib and trastuzumab both had inhibitory effect on the PI3K-AKT-MTOR pathway and the MAPK pathway downstream of ERBB2 Figure 10 D, 10E】.

[0147] 1.4 H1047R mutation leads to enhanced interaction between PIK3CA and IQGAP3

[0148] Minkyu Ki et al. explored how common and rare mutations in breast cancer in triple negative breast cancer cell lines affect the reconstruction of protein-protein interaction network by applying affinity purification mass spectrometry. And found that different PIK3CA mutations will form specific PPI network and have an impact on the downstream signaling pathway. Using the same method, using FLAG tag as bait, in stable transfected cells, respectively pull out PIK3CA H1047R and PIK3CA WTInteracting proteins, interacting proteins were acquired by AP-MS Figure 11 A】. 16 proteins interacting with PIK3CA H1047R only were found. By joint analysis with the RNA-seq results described above, 5 key proteins were locked

Figure 11 B, 11C

[0149] By comparing the predicted docking scores of the above key proteins with PIK3CA H1047R and PIK3CA WT proteins respectively by AlphaFold3, the IQGAP3 protein with the highest docking possibility was locked

Figure 12 A

Figure 12 B

[0150] Uniprot database shows that both IQGAP3 and PIK3CA are expressed in the cytoplasm, with a small amount expressed in the nucleus. By immunofluorescence co-localization experiment, the co-localization score of IQGAP3 and FLAG-labeled PIK3CA H1047R protein in the cytoplasm was significantly higher than that of PIK3CA WT protein

Figure 12 C

[0151] To determine the interaction of proteins in cells, we verified the interaction of IQGAP3 and PIK3CA H1047R by IP experiment in SKBR3 cells stably transfected with FLAG-PIK3CA H1047R

Figure 13 A, 14B

Figure 14 A

[0152] 1.5 IQGAP3 function exploration: knockdown of IQGAP3 can inhibit PIK3CA H1047R cell proliferation, reduce tumor cell stemness, and improve trastuzumab sensitivity.

[0153] Through the data in the database, it was found that the expression of IQGAP3 in breast cancer tissue was significantly higher than that in the adjacent cancer tissue

Figure 15 A

Figure 15 B

Figure 16 A

[0154] In breast cancer cells containing PIK3CA H1047R mutation, the effects of adding trastuzumab on cell proliferation and stemness were compared after using small interfering RNA to knock down IQGAP3. The results of cell proliferation and EdU experiment showed that the addition of trastuzumab had no significant inhibitory effect on cell proliferation in the non-knockdown group. The cell proliferation rate of the knockdown group slowed down, and the cell proliferation inhibition rate after adding trastuzumab was significantly higher than that of the non-knockdown group

Figure 17 A, 17B, 18A, 18B

Figure 19 A, 19B

Figure 20 A, 20B

[0155] 1.6 Inhibition of IQGAP3 protein function by pyrotinib.

[0156] To explore the effect of pyrotinib on IQGAP3 protein, the crystal structure of IQGAP3 protein and the 2D structure file of compound Pyrotinib dimaleate were obtained from RCSB PDB database, and after processing by Schrodinger software, the best binding site was predicted. The results showed that Pyrotinib dimaleate was bound to the surface of the active pocket of IQGAP3 protein, and the residues PHE1589, LEU1591, MET1607, LEU1599 of IQGAP3 protein formed hydrophobic forces with Pyrotinib dimaleate. The ligand formed one hydrogen bond with each of the residues LYS1608 and ASN1611, and one π-π bond with each of the residues PHE1589 and PHE1581. The MM-GBSA analysis result was -50.49 kcal / mol, showing that the binding stability of the ligand and the protein was high. Figure 21 A, 21B】and the interaction of small molecules and proteins was verified by MTS experiment.

[0157] PIK3CA H1047R HCC1954 cells resistant to trastuzumab were treated with SiIQGAP3 and pyrotinib respectively, and the WB results showed that pyrotinib could significantly inhibit IQGAP3 protein, which was similar to the effect of knocking down IQGAP3. In addition, knocking down IQGAP3 inhibited the PI3K-AKT-MTOR pathway and the MAPK pathway. Figure 21 C】.

[0158] In the rescue experiment, IQGAP3 overexpression plasmid was transiently transfected in SK-BR-3 cells stably transfected with PIK3CA H1047R , and the effect on the action of pyrotinib was observed. The results of EdU, cell cycle, and cell stemness experiments showed that the overexpression of IQGAP3 weakened the inhibitory effect of pyrotinib on cell proliferation and stemness, and affected the blocking effect on cell cycle. Figure 22 A, 22B, 23A, 23B, 24A, 24B】.

[0159] 1.7 PIK3CA H1047R mutation IQGAP3 expression is enhanced and can be inhibited by pyrotinib

[0160] Stably transfected SK-BR-3 cells were injected subcutaneously into the right side of BALB / c nude mice to establish a xenograft model, and the effects of pyrotinib and trastuzumab on the growth of PIK3CA H1047R and PIK3CA WT tumor cells in vivo were evaluated. The grouping and treatment are shown in the figure. Figure 25 A, 25B】. PIK3CA H1047RIn the PIK3CA WT In the PIK3CA Figure 26 A, 26B]. There was no significant difference in body weight among the mice in each treatment group Figure 26 C].

[0161] After the end of the experiment, the expression of HER2, Ki-67, and IQGAP3 in the transplanted tumors was detected by immunohistochemistry, and quantitatively analyzed by ImageJ software. The results showed that the expression of Ki-67 and IQGAP3 was significantly reduced after pyrotinib treatment, while the effect of trastuzumab on Ki-67 was not significant in the PIK3CA H1047R In the PIK3CA Figure 27 A, 27B, 28A, 28B].

[0162] Example Two:

[0163] The patient was diagnosed as HER2-positive invasive breast cancer by puncture. Then the patient received neoadjuvant chemotherapy, and the initial regimen was EC-TH. After 4 cycles of EC chemotherapy, the patient reported that the mass had significantly reduced in size and became soft. The corresponding ultrasound and imaging results also showed that the mass had significantly reduced in size. Then the patient received 2 cycles of sequential TH regimen chemotherapy, and the patient complained that the mass had increased in size and became hard. Then the patient was diagnosed by imaging. The patient was diagnosed as primary TH drug resistance. The treatment regimen was adjusted to XPy (capecitabine combined with pyrotinib). After one cycle, the mass was significantly reduced in size. Then the patient continued to use XPy for 5 cycles. The size of the mass did not further increase. The PIK3CA mutation patient drug resistance reversal report is as follows Figure 29 .

Claims

1. Application of IQGAP3 as a breast cancer marker.

2. Application of IQGAP3 as a drug action target in development and screening of drugs for treating breast cancer.

3. Application of an IQGAP3 inhibitor in preparation of a drug for treating breast cancer.

4. Application of an IQGAP3 inhibitor in preparation of a drug for treating HER2 positive breast cancer.

5. Application of an IQGAP3 inhibitor in preparation of a drug for treating HER2 positive breast cancer with drug resistance to a targeted drug.

6. Application of an IQGAP3 inhibitor in preparation of a drug for treating HER2 positive breast cancer with drug resistance to a targeted drug caused by PIK3CA mutation.

7. Use according to claim 6, wherein The PIK3CA mutation is PIK3CA H1047R mutation.

8. Use according to any one of claims 1 to 6, characterised in that, The IQGAP3 inhibitor is pyrotinib.

9. Use of pyrotinib as an IQGAP3 inhibitor.

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