KRT6A gene expression inhibitor and application thereof in preparation of medicine for treating gemcitabine drug-resistant pancreatic cancer

Abstract

The invention belongs to the technical field of medicines, and discloses a KRT6A gene expression inhibitor and application thereof in preparation of a medicine for treating gemcitabine drug-resistant pancreatic cancer. Researches find that KRT6A is abnormally highly expressed in pancreatic cancer and is closely related to poor curative effect of gemcitabine. According to the inhibitor, KRT6A gene expression is specifically silenced in a tumor targeted delivery mode, expression and functions of nucleoside transporter ENT1 are recovered, and cellular uptake of gemcitabine is enhanced; the compound can inhibit MIF-CD44 / CD74 signal axis mediated tumor-associated macrophage M2 type polarization, reduce exogenous pyrimidine nucleoside supply and weaken competitive inhibition of the compound and gemcitabine in nucleoside transport and metabolic pathways, so that effective uptake and efficacy of gemcitabine in pancreatic cancer cells are synergistically improved, and gemcitabine drug resistance is reversed or relieved. The invention provides a new and effective technical scheme for clinical treatment of gemcitabine drug-resistant pancreatic cancer.

Description

Technical Field

[0001] This invention belongs to the field of pharmaceutical technology, specifically relating to KRT6A gene expression inhibitors and their application in the preparation of drugs for treating gemcitabine-resistant pancreatic cancer. Background Technology

[0002] Pancreatic cancer is a highly malignant tumor of the digestive system, and gemcitabine is a first-line chemotherapy drug for pancreatic cancer. However, intrinsic and acquired resistance severely limits its efficacy. Chemotherapy resistance is not only related to the genetic and metabolic adaptations of tumor cells themselves, but also closely related to the immunosuppressive tumor microenvironment (TIME). Tumor-associated macrophages (TAMs) are the main immune components of TIME, participating in gemcitabine resistance by secreting cytokines, remodeling the extracellular matrix, promoting angiogenesis, and inhibiting T cell function. Liposome delivery systems, as an emerging strategy for cancer treatment, can precisely deliver drugs and nucleic acids, enhancing anti-tumor efficacy by regulating TIME.

[0003] However, the application of combination therapies based on liposome nucleic acid liposome delivery systems in pancreatic cancer still needs further exploration. Summary of the Invention

[0004] This invention aims to solve at least one of the technical problems existing in the prior art. To this end, this invention proposes a KRT6A gene expression inhibitor and its application in the preparation of a drug for treating gemcitabine-resistant pancreatic cancer. This KRT6A gene expression inhibitor, by specifically silencing KRT6A gene expression, restores the expression and function of the nucleoside transporter ENT1, inhibits TAM-M2 polarization and pyrimidine nucleoside secretion, thereby reducing the uptake of pyrimidine nucleoside by pancreatic cancer cells and significantly improving their uptake efficiency of the therapeutic drug gemcitabine, thus reversing or alleviating gemcitabine resistance, providing a new and effective technical solution for the clinical treatment of gemcitabine-resistant pancreatic cancer.

[0005] This invention provides a KRT6A gene expression inhibitor comprising KRT6A siRNA with a nucleotide sequence as shown in SEQ ID NO.1.

[0006] 5'-GCTATGGCTTTGGTGGCGCC-3' (SEQ ID NO. 1).

[0007] The present invention also provides the application of the above-mentioned KRT6A gene expression inhibitor in the preparation of a drug for treating gemcitabine-resistant pancreatic cancer.

[0008] Gemcitabine is an anticancer drug derived from a cytosine nucleoside derivative. It primarily inhibits the growth and spread of cancer cells by suppressing their DNA synthesis and has been widely used to treat various malignant tumors, currently serving as a cornerstone and first-line treatment for pancreatic cancer. This invention demonstrates that the KRT6A gene reduces gemcitabine uptake by pancreatic cancer cells by inhibiting ENT1-mediated drug uptake. Simultaneously, KRT6A can activate the MIF-CD74 / CD44 signaling axis, promoting TAM-M2 polarization and enhancing the secretion of pyrimidine nucleosides such as cytosine, thereby creating an immunosuppressive and pyrimidine-enriched state in the tumor microenvironment. These pyrimidine nucleosides can be transported and absorbed by pancreatic cancer cells via ENT1, competitively occupying the transport channel with gemcitabine, further inhibiting gemcitabine uptake and ultimately leading to gemcitabine resistance in pancreatic cancer. Based on this, this invention provides a KRT6A gene expression inhibitor and indicates its potential use in the treatment of gemcitabine-resistant pancreatic cancer.

[0009] This invention also provides a pancreatic cancer-targeting liposome nanoformulation, wherein the surface of the pancreatic cancer-targeting liposome nanoformulation is modified with cyclic arginine-glycine-aspartic acid, and the internal structure encapsulates KRT6A siRNA with the nucleotide sequence shown in SEQ ID NO.1. The preparation method includes the following steps:

[0010] Using 1,2-dioleoyl-3-trimethylammonium propane (DOTAP), 1,2-distearyl-sn-glycerol-3-phosphocholine (DSPC), cholesterol, 1,2-distearyl-sn-glycerol-3-phosphoethanolamine-N-[methoxy(polyethylene glycol)-2000] (DSPE-PEG2000), and 1,2-distearyl-sn-glycerol-3-phosphoethanolamine-N-[methoxy(polyethylene glycol)-2000]-cyclic arginine-glycine-aspartic acid (DSPE-PEG2000-cRGD) as lipid components and the aforementioned KRT6AsiRNA as the drug component, the pancreatic cancer-targeting liposome nanoformulation was prepared by a thin-film hydration method.

[0011] Among them, DOTAP is a cationic lipid that can bind to negatively charged KRT6A siRNA through electrostatic interactions, which is beneficial to improving the encapsulation efficiency of siRNA; DSPC, as a structural lipid, is used to form a stable lipid bilayer framework; cholesterol is used to regulate the fluidity and stability of the liposome membrane and improve the structural integrity of the liposome during in vivo circulation; DSPE-PEG2000 can form a polyethylene glycol protective layer on the liposome surface, thereby reducing non-specific protein adsorption and prolonging the circulation time of the liposome in vivo; DSPE-PEG2000-cRGD modifies the liposome surface with cyclic arginine-glycine-aspartic acid (cRGD), enabling the liposome to specifically recognize and bind to pancreatic cancer cells or tumor neovascular endothelial cells that highly express integrin receptors, thereby achieving active targeted drug delivery to pancreatic cancer.

[0012] Preferably, the molar ratio of 1,2-dioleoyl-3-trimethylammonium propane, 1,2-distearyl-sn-glycerol-3-phosphocholine, cholesterol, 1,2-distearyl-sn-glycerol-3-phosphoethanolamine-N-[methoxy(polyethylene glycol)-2000], and 1,2-distearyl-sn-glycerol-3-phosphoethanolamine-N-[methoxy(polyethylene glycol)-2000]-cyclic arginine-glycine-aspartic acid is (12–16):(45–60):(25–35):(2–5):1.

[0013] More preferably, the molar ratio of 1,2-dioleoyl-3-trimethylammonium propane, 1,2-distearyl-sn-glycerol-3-phosphocholine, cholesterol, 1,2-distearyl-sn-glycerol-3-phosphoethanolamine-N-[methoxy(polyethylene glycol)-2000], and 1,2-distearyl-sn-glycerol-3-phosphoethanolamine-N-[methoxy(polyethylene glycol)-2000]-cyclic arginine-glycine-aspartic acid is 15:50:30:4:1.

[0014] The present invention also provides a pharmaceutical composition for treating pancreatic cancer, comprising the following (a) and (b):

[0015] (a) Gemcitabine;

[0016] (b) The above-mentioned KRT6A gene expression inhibitor or the above-mentioned pancreatic cancer-targeting liposome nanoformulation.

[0017] Preferably, the pharmaceutical composition further comprises pharmaceutically acceptable excipients.

[0018] Preferably, the dosage form of the pharmaceutical composition is an injection.

[0019] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0020] This invention experimentally demonstrates that KRT6A is not only significantly overexpressed in pancreatic cancer tissues, but its overexpression also severely shortens the overall survival of pancreatic cancer patients. Furthermore, it indicates that high KRT6A expression is significantly correlated with reduced response to gemcitabine treatment, such as by reducing ENT1-related nucleoside transport capacity, thereby inhibiting gemcitabine uptake and promoting drug resistance. Inhibiting KRT6A expression can effectively improve the efficacy of gemcitabine. Therefore, this invention proposes a corresponding KRT6A gene expression inhibitor and its targeted nanoformulation, which can be used to prepare drugs for treating gemcitabine-resistant pancreatic cancer, possessing broad application prospects and practical value. Attached Figure Description

[0021] Figure 1 Volcano plots / heatmaps of differential expression of drug-resistant and parental cells in the GSE35141, GSE80617, and GSE106336 datasets, and GO-KEGG enrichment analysis of upregulated genes;

[0022] Figure 2 The intersection of commonly upregulated genes in drug-resistant cells from the three datasets (Venn diagram) and the set of candidate genes are derived.

[0023] Figure 3 The results of qRT-PCR validation of KRT6A in the model cell line (n=3);

[0024] Figure 4 The results of Pearson correlation analysis of KRT6A and ENT1 mRNA expression in the CCLE database;

[0025] Figure 5 Spatial distribution and colocalization characteristics of KRT6A, ENT1, MIF, MRC1, and CD74 / CD44 in the spatial transcriptome;

[0026] Figure 6 The results of UMAP dimensionality reduction clustering and differentially expressed gene (DEG) analysis of PANC-1 and PANC-GEM cells in GSE186960 are shown.

[0027] Figure 7 The difference in expression of MIF and ENT1 in PANC-1 and PANC-GEM cells (violin plot).

[0028] Figure 8 Results of pseudo-temporal trajectory analysis of PANC-1 and PANC-GEM cells;

[0029] Figure 9 A heatmap showing the dynamic expression of MIF, ENT1, and related gene clusters during the simulated time progression;

[0030] Figure 10 Differential expression analysis of KRT6A transcriptional levels between pancreatic cancer tissues and adjacent normal tissues in multiple GEO datasets;

[0031] Figure 11 Comparative analysis of representative images and scores of KRT6A immunohistochemical staining in pancreatic cancer tissue and adjacent normal tissue;

[0032] Figure 12 A figure showing the Kaplan-Meier overall survival analysis results for pancreatic cancer patients based on KRT6A transcriptional levels;

[0033] Figure 13 The results of the Kaplan-Meier overall survival analysis for pancreatic cancer patients based on KRT6A protein expression levels;

[0034] Figure 14 A representative illustration of KRT6A protein expression and corresponding imaging features in patients in different RECIST 1.1 efficacy groups;

[0035] Figure 15 The distribution of KRT6A protein expression in different clinical efficacy groups among patients treated with gemcitabine;

[0036] Figure 16 Comparison of disease progression rates, disease control rates (DCR), and objective response rates (ORR) among patients treated with gemcitabine in high and low KRT6A expression groups;

[0037] Figure 17 IC50 of PANC-1 and AsPC-1 cells against gemcitabine under KRT6A knockdown or overexpression conditions 50 Value change;

[0038] Figure 18 Changes in the clonogenic ability of PANC-1 and AsPC-1 cells after KRT6A knockdown or overexpression;

[0039] Figure 19 Changes in EdU incorporation levels in pancreatic cancer cells after KRT6A knockdown or overexpression;

[0040] Figure 20 Results of a scratch healing experiment on pancreatic cancer cells after KRT6A knockdown or overexpression;

[0041] Figure 21 Results of Transwell assays for pancreatic cancer cell migration after KRT6A knockdown or overexpression;

[0042] Figure 22 Results of Matrigel invasion assay of pancreatic cancer cells after KRT6A knockdown or overexpression;

[0043] Figure 23 Western blot results of KRT6A and ENT1 in AsPC-1 and AsPC-1-GEM cells under KRT6A overexpression or knockdown conditions;

[0044] Figure 24 A schematic diagram illustrating the process of constructing subcutaneous xenograft and lung metastasis models in AsPC-1 cells under different KRT6A expression states;

[0045] Figure 25 Quantitative statistical results of representative images and number of lung metastatic nodules in mice with different KRT6A expression states (n=6);

[0046] Figure 26 Representative appearance images of subcutaneous xenografts in different KRT6A expression groups and statistical results of tumor weight at the endpoint of each group (n=6).

[0047] Figure 27 Growth curves of subcutaneous xenografts in each group (volume change over time, n=6).

[0048] Figure 28 HE staining results of lung tissues from mice in different KRT6A expression groups (showing metastatic lesions);

[0049] Figure 29 IHC / IF results of KRT6A, Ki67, N-cadherin, E-cadherin, ENT1, MIF, CD74, and CD44 in xenograft tissue;

[0050] Figure 30 Transmission electron microscopy (TEM) morphology images and particle size distribution (DLS) analysis results of c-Lip@siKRT6A nanoparticles;

[0051] Figure 31 The particle size stability curve and zeta potential detection results of c-Lip@siKRT6A in aqueous solution over 7 days are shown.

[0052] Figure 32 Agarose gel electrophoresis results showing the protective effect of c-Lip@siKRT6A on KRT6A siRNA;

[0053] Figure 33 Comparison of UV-Vis absorption spectra of free ICG and c-Lip@siKRT6AICG;

[0054] Figure 34Confocal imaging of Lip@siKRT6AICG and c-Lip@siKRT6AICG at different incubation times in AsPC-1-GEM cells;

[0055] Figure 35 Quantitative analysis of intracellular ICG fluorescence intensity at different incubation time points;

[0056] Figure 36 Real-time fluorescence imaging results in mice after intravenous injection (Lip@siKRT6AICG vs c-Lip@siKRT6AICG).

[0057] Figure 37 Quantitative analysis of fluorescence signal intensity in tumor regions at different time points;

[0058] Figure 38 The results are 24-hour in vitro fluorescence imaging of major organs and tumors.

[0059] Figure 39 Quantitative comparison of fluorescence signal intensity in major organs and tumors;

[0060] Figure 40 A schematic diagram illustrating the process of establishing subcutaneous xenograft tumors and orthotopic pancreatic cancer models of gemcitabine-resistant AsPC-1-GEM cells;

[0061] Figure 41 Representative external images, weight statistics, and volume / burden comparison analysis of orthotopic pancreatic tumors;

[0062] Figure 42 Representative appearance images of tumors in different treatment groups in the subcutaneous xenograft model and statistical results of tumor weight in each treatment group (n=5).

[0063] Figure 43 A comparative analysis of the growth curves (n=5) and growth trends of subcutaneous xenograft tumors over time;

[0064] Figure 44 Image showing the results of HE staining and immunofluorescence analysis of fibrosis / related indicators in tumor tissue after treatment;

[0065] Figure 45 UMAP dimensionality-reduced clustering diagram of tumor cells and TAM in pancreatic cancer single-cell data and KRT6A⁺ tumor subset identification results;

[0066] Figure 46 Dot plot showing the results of differential expression of key TAM marker genes between tumor cells;

[0067] Figure 47The results show the quantitative comparison between the proportion of tumor cell subpopulations (top) and the proportion of TAM subpopulations (bottom) in each pancreatic cancer sample after stratification by the abundance of tumor cells or TAM subpopulations.

[0068] Figure 48 KRT6A + Analysis of key signaling pathways contributing to tumor cell TAM subsets (highlighting MIF-related pathways).

[0069] Figure 49 KRT6A + Overview of cell communication networks between tumor cells and TAM subsets (ligand-receptor interaction analysis).

[0070] Figure 50 MIF-CD74 / CD44 ligand-receptor interaction in KRT6A + Communication strength and significance between tumor cells and TAM subsets;

[0071] Figure 51 KRT6A + Results show the directionality of MIF signaling communication and receptor combination (CD74 / CD44) between tumor cells and TAM subsets;

[0072] Figure 52 Results of Transwell co-culture of AsPC-1-GEM and TAM and quantitative determination of M2 macrophage proportion (c-Lip@siKRT6A vs control, n=3);

[0073] Figure 53 Quantitative results of MIF concentration in the supernatant of AsPC-1-GEM cell culture after c-Lip@siKRT6A treatment (n=3).

[0074] Figure 54 The results of the correlation analysis between KRT6A and MIF expression in the TCGA pancreatic cancer cohort;

[0075] Figure 55 KRT6A + Pathway enrichment analysis results of upregulated genes in tumor cells;

[0076] Figure 56 The results are based on the metabolic flux inference from MetaFlux.

[0077] Figure 57 The results of quantitative analysis of cytidine concentration in the culture supernatant after c-Lip@siKRT6A treatment in the co-culture system (n=3);

[0078] Figure 58Schematic diagram of the experimental procedure for establishing subcutaneous xenografts of AsPC-1-GEM and treating them with gemcitabine and c-Lip@siKRT6A (n=3).

[0079] Figure 59 Volcano plot of differentially expressed genes from bulk RNA-seq in xenograft tumors (c-Lip@siKRT6A vs. control);

[0080] Figure 60 Heatmap of differentially expressed genes from bulk RNA-seq in xenograft tumors (c-Lip@siKRT6A vs. control);

[0081] Figure 61 GO enrichment analysis (left) and KEGG enrichment analysis (right) for differentially expressed genes in xenograft tumors.

[0082] Figure 62 UMAP representation of pancreatic cancer single-cell data after mapping the tumor bulk phenotype to pancreatic cancer single-cell data using the Scissor algorithm (Scissor) + (cell annotation)

[0083] Figure 63 For Scissor + Volcano plot of differential expression of relevant representative genes;

[0084] Figure 64 For Scissor + Spatial mapping of tumor cells and regional expression distribution characteristics of ENT1, MIF, MRC1 and CD74 / CD44;

[0085] Figure 65 A schematic diagram of the drug administration process for the establishment and control of the AsPC-1-GEM subcutaneous xenograft model, Gem, c-Lip@siKRT6A and combination therapy;

[0086] Figure 66 A schematic diagram of an in vivo recovery experiment for TAM-M2 or cytidine supplementation based on combination therapy;

[0087] Figure 67 Representative appearance images and weight statistics of subcutaneous xenografts at the endpoint in different treatment groups (n=6), as well as growth curves of subcutaneous xenograft tumor volume over time (n=6).

[0088] Figure 68 Comparison of tumor growth trends in subcutaneous xenografts across different treatment groups (n=6);

[0089] Figure 69 Multiplex immunofluorescence and combined channel images of KRT6A / MIF / ENT1 in transplanted tumor tissue (showing spatial co-distribution characteristics);

[0090] Figure 70 The results are based on the quantitative analysis of TAM-M2 abundance / proportion in xenograft tumor tissue using immunofluorescence staining.

[0091] Figure 71 To recover representative appearance images, weight statistics (n=6), and tumor growth curves (n=6) of subcutaneous xenografts at the endpoint of different treatment groups in the experiment.

[0092] Figure 72 To retrieve the results of the comparison of tumor growth trends in subcutaneous xenografts in different treatment groups (n=6);

[0093] Figure 73 To reproduce representative images of KRT6A and total TAM immunofluorescence staining in experimental xenograft tissue;

[0094] Figure 74 To reproduce representative images of KRT6A and M2 macrophages from experimental xenograft tissue using immunofluorescence staining;

[0095] Figure 75 Results of the c-Lip@siKRT6A hemolysis experiment;

[0096] Figure 76 The curves showing the change in mouse body weight within 15 days after tail vein injection of PBS, Lip@siKRT6A, or c-Lip@siKRT6A;

[0097] Figure 77 The results of H&E staining of major organs (heart, liver, spleen, lung, and kidney) 15 days after tail vein injection (scale bar 100 μm).

[0098] Figure 78 The results of routine blood tests in mice 15 days after tail vein injection;

[0099] Figure 79 The results of biochemical indicators related to liver function in mice 15 days after tail vein injection;

[0100] Figure 80 The results of biochemical indicators related to renal function in mice 15 days after tail vein injection;

[0101] Figure 81 A diagram illustrating the mechanism by which KRT6A promotes gemcitabine resistance in pancreatic cancer and the therapeutic mechanism of c-Lip@siKRT6A. Detailed Implementation

[0102] To enable those skilled in the art to more clearly understand the technical solutions described in this invention, the following embodiments are provided for illustration. It should be noted that the following embodiments do not constitute a limitation on the scope of protection claimed by this invention.

[0103] Unless otherwise specified, the raw materials, reagents or devices used in the following examples are available from conventional commercial sources or can be obtained by existing known methods.

[0104] Example

[0105] (I) Multi-omics screening and validation of KRT6A as a key gene for gemcitabine resistance in pancreatic cancer

[0106] 1. Integration screening and in vitro experimental validation of drug resistance-related genes

[0107] To screen key regulatory genes associated with gemcitabine resistance in pancreatic cancer, this invention employs a method combining multi-cohort transcriptome data integration analysis with in vitro experimental validation. The specific bioinformatics steps are as follows: The raw expression matrices and annotation files of transcriptome datasets GSE35141, GSE80617, and GSE106336 associated with gemcitabine resistance in pancreatic cancer were downloaded from the GEO database; each dataset was preprocessed in the R language environment, including background correction, log2 transformation, and quantile standardization (by data type); differential expression analysis was performed using the limma software package, with resistant cells and parental cells as the comparison groups. Empirical Bayesian methods were used to calculate statistics, and the Benjamini–Hochberg method was used for multiple test correction to obtain the adjusted p-value. Genes with p < 0.05 were screened for differentially expressed genes. The differential expression results were displayed using volcano plots and hierarchical clustering heatmaps. GO (BP / CC / MF) and KEGG pathway enrichment analyses were performed on upregulated genes in drug-resistant cells using the clusterProfiler software package. Adjusted p-values ​​and gene counts were used as the criteria for significance determination. Finally, the online Venn analysis tool was used to find the intersection of commonly upregulated genes in drug-resistant cells from the three datasets to obtain a consistent set of candidate drug-resistant genes across cohorts. Figure 1 In the figure, A, B, and C are volcano plots / heatmaps of differential expression of drug resistance and parental cells in the GSE35141, GSE80617, and GSE106336 datasets, respectively, as well as GO-KEGG enrichment analysis of upregulated genes.

[0108] Furthermore, by taking the intersection of the upregulated genes in drug-resistant cells from the above three datasets, five common candidate genes were obtained: KRT6A, AADAC, MCTP1, GSDMC, and HBEGF. Figure 2 The intersection of upregulated genes in drug-resistant cells from the three datasets (Venn diagram) and the set of candidate genes were determined, and KRT6A was identified as the preferred key gene related to drug resistance based on subsequent in vitro validation results.

[0109] In in vitro experimental verification, this invention selected AsPC-1 cells (human metastatic pancreatic cancer cells) and their gemcitabine-resistant strain AsPC-1-GEM, as well as PANC-1 cells (human pancreatic cancer cells) and their gemcitabine-resistant strain PANC-1-GEM as model cell lines. The cell culture conditions were RPMI-1640 medium (containing 10% fetal bovine serum and 1% penicillin-streptomycin), cultured at 37℃ and 5% CO2 until the logarithmic growth phase. qRT-PCR verification was performed as follows: total RNA was extracted from parental and resistant cells using TRIzol reagent, and the concentration and purity were detected; equal amounts of RNA were reverse transcribed into cDNA using a commercial reverse transcription kit; real-time quantitative PCR amplification was performed using SYBR Green as the fluorescence system, with an amplification program of 40 cycles after initial denaturation (each cycle including denaturation and annealing / extension); the relative expression level was obtained by normalization calculation using the internal reference gene and the 2-ΔΔCt method; three biological replicates were set for each group, and the results are expressed as mean ± standard deviation. Figure 3 The results of qRT-PCR validation of KRT6A in the model cell line (n=3) are shown. Figure 3 In Figure A, the qRT-PCR validation results of KRT6A in AsPC-1 and AsPC-1-GEM cells (n=3) are shown. Figure 3 Figure B shows the qRT-PCR validation results of KRT6A in PANC-1 and PANC-1-GEM cells (n=3). The experimental results showed that KRT6A levels in AsPC-1-GEM and PANC-1-GEM cells were significantly higher than those in the corresponding parental cells, thus validating the stable correlation between KRT6A and gemcitabine resistance.

[0110] 2. Correlation analysis of KRT6A expression with gemcitabine transport-related gene ENT1

[0111] To further elucidate the potential mechanism by which KRT6A participates in gemcitabine resistance, this invention conducts expression correlation analysis based on transcriptome data from the CCLE database: downloading mRNA expression data of KRT6A and ENT1 from CCLE; calculating the correlation between KRT6A and ENT1 expression using Pearson correlation coefficient, and outputting the correlation coefficient r and significance p-value; Figure 4 The results of Pearson correlation analysis of KRT6A and ENT1 mRNA expression in the CCLE database show that KRT6A and ENT1 expression are significantly negatively correlated, suggesting that high KRT6A expression may inhibit gemcitabine uptake and promote drug resistance by reducing ENT1-related nucleoside transport capacity.

[0112] 3. Characteristics of the KRT6A-related immune microenvironment and dynamic changes in drug resistance formation

[0113] To elucidate the role of KRT6A in the tumor immune microenvironment and drug resistance evolution, this invention combines spatial transcriptomics and single-cell RNA sequencing data for analysis. The spatial transcriptomics analysis steps are as follows: Spatial transcriptomics data and accompanying tissue images from pancreatic cancer derived from HTAN WUSTL were obtained; the spatial expression matrix was imported using Read10X and spatial analysis objects were constructed in Seurat, aligning spatial coordinates with tissue images; the spatial transcriptomics data were normalized using SCTransform; the reference scRNA-seq data were also normalized using SCTransform, and anchor points between single cells and spatial data were constructed using FindTransferAnchors; single-cell annotations were projected onto spatial spots using TransferData; finally, the spatial distribution and co-localization characteristics of KRT6A, ENT1, MIF, MRC1, and CD74 / CD44 in tissues were displayed using methods such as SpatialFeaturePlot (e.g., Figure 5 As shown in the figure, this reveals the spatial coupling relationship between the KRT6A high-expression region and immunosuppression-related factors and TAM-related markers.

[0114] Furthermore, this invention compares the transcriptional differences between PANC-1 and gemcitabine-resistant PANC-GEM cells based on GSE186960 single-cell RNA sequencing data. The analysis steps are as follows: download the original GSE186960 expression matrix; perform single-cell data preprocessing using Seurat, including low-quality cell filtering, normalization, screening for hypervariable genes, and data scaling; perform dimensionality reduction and clustering, and then visualize the data using UMAP. Figure 6 (A); differential expression analysis was performed between the PANC-1 and PANC-GEM groups to obtain DEGs ( Figure 6 (Middle B); and a violin diagram is used to illustrate the expression differences of MIF and ENT1 in the two cell types, such as Figure 7 As shown, the results indicate that MIF is significantly upregulated and ENT1 is significantly downregulated in drug-resistant cells.

[0115] This invention further reveals the dynamic changes in drug resistance formation through pseudo-temporal trajectory analysis. The SCP software package is used for trajectory inference and pseudo-temporal analysis: after completing single-cell clustering and cell population annotation, the expression matrix is ​​input to infer cell state transitions, obtaining pseudo-temporal trajectories of cells along tumor progression / drug resistance evolution (e.g., ...). Figure 8 (as shown); and calculate the dynamic expression changes of key genes and gene clusters on the pseudo-timeline (e.g. Figure 9 As shown in the figure, the results showed that MIF gradually increased and ENT1 gradually decreased along the pseudo-time sequence; at the same time, the expression of MIF, ENT1 and related gene clusters along the pseudo-time sequence was displayed in the form of a heatmap to reflect the stage changes of the drug resistance-related transcriptional program.

[0116] (II) Expression characteristics of KRT6A in pancreatic cancer and its prognostic and chemotherapy response significance

[0117] 1. Abnormally high expression of KRT6A in pancreatic cancer tissues

[0118] To clarify the expression characteristics of KRT6A in pancreatic cancer tissues, this invention first analyzed the differential expression levels of KRT6A between pancreatic cancer tissues and adjacent normal tissues (ANT) based on transcriptome data published in multiple GEO databases. The specific steps were as follows: expression matrices containing pancreatic cancer tissues and corresponding adjacent normal tissues were downloaded from the GEO databases; background correction, log2 transformation, and standardization were performed on the raw data in the R language environment; statistical methods were used to compare the expression differences of KRT6A between tumor tissues and adjacent normal tissues, and the results were visualized in the form of box plots or scatter plots. The analysis results are as follows: Figure 10 As shown, the results indicate that KRT6A is significantly overexpressed in pancreatic cancer tissues, while its expression level is significantly reduced in adjacent normal tissues.

[0119] Furthermore, to verify the above results at the protein level, this invention uses tissue microarray immunohistochemistry (IHC) to detect the expression of KRT6A in pancreatic cancer tissue and adjacent normal tissue. The specific steps are as follows: Paraffin-embedded tissue microarrays containing pancreatic cancer tissue (n=164) and adjacent normal tissue (n=113) were selected; dewaxing, hydration, and antigen retrieval were performed sequentially; endogenous peroxidase was blocked with 3% hydrogen peroxide, followed by blocking non-specific binding sites with bovine serum albumin; anti-KRT6A primary antibody was added and incubated overnight at 4°C; after washing with PBS, HRP-labeled secondary antibody was added and incubated; DAB staining was performed and counterstained with hematoxylin; after dehydration and mounting, the microscopic observation was performed. Figure 11 (A). Two pathologists scored the immunohistochemical results under blinded conditions based on staining intensity and the proportion of positive cells, and calculated the immunohistochemical score. Figure 11 (Middle B). The results showed that the expression of KRT6A protein and the IHC score in pancreatic cancer tissue were significantly higher than those in adjacent normal tissue, confirming that KRT6A is abnormally highly expressed in pancreatic cancer.

[0120] 2. Correlation between KRT6A overexpression and poor prognosis

[0121] To assess the relationship between KRT6A expression levels and prognosis in pancreatic cancer patients, this invention performs survival analyses at both the transcriptional and protein levels. In the transcriptional analysis, based on KRT6A expression data from GEO or publicly available cohorts, patients were divided into high-expression and low-expression groups according to the median or a preset threshold. Overall survival curves were plotted using the Kaplan-Meier method, and the survival differences between the two groups were compared using the log-rank test. Figure 12 The figure shows the overall survival results of pancreatic cancer patients based on KRT6A transcriptional levels according to Kaplan–Meier analysis. The analysis results show that patients with high KRT6A expression have significantly shorter overall survival than those with low expression.

[0122] In protein level analysis, patients were divided into high-expression and low-expression groups based on the KRT6A immunohistochemical score in tissue microarrays; survival analysis was performed using the same Kaplan-Meier method and log-rank test, and the results showed that patients with high KRT6A expression had a significantly poorer prognosis. Figure 13 ).

[0123] Furthermore, this invention combines imaging assessment results under the RECIST 1.1 criteria to compare and analyze the expression of KRT6A protein in tumor tissues of patients in different clinical prognostic groups (CR, PR, SD, PD). Specifically, contrast-enhanced CT images of patients were collected and efficacy was graded according to RECIST 1.1; the immunohistochemical staining intensity and score of KRT6A in corresponding tissue samples were analyzed simultaneously. The results showed significant differences in KRT6A protein expression among patients in different prognostic groups, and the expression gradually increased with disease progression, suggesting that KRT6A protein levels are closely related to poor prognosis in pancreatic cancer. Figure 14 ).

[0124] 3. Predictive relationship between KRT6A and gemcitabine efficacy

[0125] To further evaluate the predictive value of KRT6A in response to gemcitabine treatment, this invention retrospectively analyzed a cohort of pancreatic cancer patients (n=90) who received gemcitabine treatment. The specific steps were as follows: patients receiving gemcitabine as their primary treatment were screened; patients were divided into efficacy groups (CR, PR, SD, and PD) according to RECIST 1.1 criteria; immunohistochemical scoring of KRT6A protein expression in tumor tissues of each patient was performed, and the expression differences between different efficacy groups were compared. The results showed that as the treatment outcome shifted from disease control to disease progression, KRT6A protein expression in tumor tissues gradually increased. Figure 15 ).

[0126] Furthermore, this invention divides patients into high-expression and low-expression groups based on KRT6A protein expression levels, and compares the disease progression rate, disease control rate (DCR), and objective response rate (ORR) between the two groups. The analytical steps include: statistically analyzing the proportions of PD, SD, PR, and CR patients in the high and low KRT6A expression groups; and comparing the differences between the two groups using a chi-square test or Fisher's exact test. Figure 16 As shown, the proportion of disease progression in patients treated with gemcitabine differed between those with high and low KRT6A expression. Figure 16 (A) Disease Control Rate (DCR) Figure 16 Comparison of Chinese B with objective response rate (ORR) Figure 16 The results of the comparison between the Chinese and American groups showed that the proportion of patients with disease progression was significantly increased in the high KRT6A expression group, while the disease control rate and objective response rate were significantly reduced, indicating that high KRT6A expression was significantly associated with a reduced response to gemcitabine treatment.

[0127] (III) The promoting effect of KRT6A on malignant phenotype and gemcitabine resistance in pancreatic cancer cells

[0128] 1. Establishment and culture conditions of experimental cell models

[0129] This invention uses human pancreatic cancer cell lines AsPC-1 and PANC-1, and their corresponding gemcitabine-resistant cell lines AsPC-1-GEM and PANC-1-GEM, while using human mononuclear cell line THP-1 as an immune-related control cell. All cells were cultured in RPMI-1640 medium containing 10% fetal bovine serum and 1% penicillin-streptomycin mixture at 37°C, 5% CO2, and saturated humidity. Cells were passaged when they reached approximately 70%–80% confluence, and all experiments were performed using cells in the logarithmic growth phase.

[0130] To regulate KRT6A expression levels, this invention employs gene intervention to construct cell models with different expression states. The gene interventions include: (1) siRNA-mediated transient knockdown model; (2) shRNA-mediated stable knockdown model; and (3) KRT6A stable overexpression model. The differences between the three are as follows: siRNA provides short-term transient inhibition (generally used for functional verification within 48-72 h) and does not change the stable expression state of the genome; shRNA continuously expresses interfering sequences in cells through a vector (preferably a lentiviral vector), and after screening, cell lines with long-term stable silence can be obtained, which are suitable for long-term experiments and in vivo tumor / metastasis models; the KRT6A overexpression model uses a lentiviral overexpression system to stably express KRT6A in cells, which is used for long-term phenotypic observation and in vivo experiments.

[0131] (1) Transient knockdown of siRNA (short-term intervention): The RNA sequence used to knock down KRT6A is 5'-GCTATGGCTTTGGTGGCGCC-3' (SEQ ID NO.1). The procedure includes: seeding pancreatic cancer cells into suitable culture plates, and starting transfection when the cell confluence reaches about 50%–70%; diluting siRNA and liposome transfection reagent separately with serum-free medium, incubating at room temperature to form a complex, and then adding it to the cell culture system; continuing culture and replacing with serum-containing complete medium at about 4–8 h; collecting cells 48 h after transfection for subsequent functional experiments (such as CCK-8 IC50 assay). 50 (EdU, migration and invasion) or extract proteins for Western blot verification to knock down efficiency, and if necessary, extract RNA simultaneously for qRT-PCR verification.

[0132] (2) Stable knockdown of shRNA (long-term intervention / in vivo experiment): The shRNA sequence targeting KRT6A and the scramble control shRNA were cloned into lentiviral vectors respectively; the shRNA vector and packaging plasmid were co-transfected into HEK293T cells, and the supernatant containing lentiviral particles was collected after culturing and cell debris was removed by filtration to obtain viral fluid; pancreatic cancer cells were seeded in culture dishes, and when the cell confluence was about 30%–60%, the viral fluid was added for infection. Polybrene was added during infection to improve the infection efficiency; after infection, fresh complete culture medium was replaced and cultured again; puromycin was added for selection 24–48 h after infection until all uninfected control cells died and a stable surviving cell population was obtained; after selection, the cells were expanded and cultured, and the stability of long-term KRT6A silencing was verified by Western blot; the obtained stable knockdown cell line was used for long-term in vitro experiments and animal tumor / metastasis model construction.

[0133] (3) Stable overexpression of KRT6A (stable transduction / stable conversion): The full-length human KRT6A cDNA was constructed into a lentiviral overexpression vector, and the empty vector was used as a negative control. The viral fluid was prepared in HEK293T cells and infected with pancreatic cancer cells using the same lentiviral packaging and infection process as the stable knockdown. After infection, antibiotic screening (purinemycin) was performed to obtain a stable overexpressing cell population. After screening, the cells were expanded and cultured, and the stable overexpression of KRT6A was verified at the protein level by Western blot. The stable overexpressing cells were used for long-term functional experiments and in vivo experiments (subcutaneous tumorigenesis, lung metastasis, etc.).

[0134] 2. The promoting effect of KRT6A on gemcitabine resistance in pancreatic cancer cells.

[0135] To evaluate the effect of KRT6A on the gemcitabine sensitivity of pancreatic cancer cells, this invention modulates the expression level of KRT6A in PANC-1 and AsPC-1 cells and detects the half-maximal inhibitory concentration (IC50) of gemcitabine. 50 The specific experimental steps are as follows: Cells that have undergone KRT6A knockdown, KRT6A overexpression, and corresponding control treatments are seeded in 96-well plates at a seeding density of approximately 5 × 10⁶ cells per well. 3 Cells were collected; after cell adhesion, gemcitabine at different concentration gradients was added and the treatment continued for 72 h; then CCK-8 reagent was added to each well and incubated for approximately 2 h; absorbance was measured at 450 nm using a microplate reader; dose-response curves were plotted based on cell viability at different drug concentrations and IC50 was calculated. 50 value. Figure 17 IC50 of PANC-1 and AsPC-1 cells against gemcitabine under KRT6A knockdown or overexpression conditions 50 The experimental results showed that KRT6A knockdown significantly reduced gemcitabine's IC50 in PANC-1 and AsPC-1 cells. 50 Value, while KRT6A overexpression significantly improved IC50. 50 The values ​​suggest that KRT6A expression level is positively correlated with the drug sensitivity of pancreatic cancer cells to gemcitabine.

[0136] 3. The promoting effect of KRT6A on the proliferation of pancreatic cancer cells

[0137] To investigate the regulatory effect of KRT6A on the proliferation of pancreatic cancer cells, this invention employs clonogenic assays and EdU incorporation assays for verification.

[0138] In the clonogenic assay, PANC-1 and AsPC-1 cells treated with KRT6A knockdown, KRT6A overexpression, or control were seeded at low density in six-well plates (800 cells per well); they were cultured continuously for about 14 days under standard culture conditions; after culture, the cells were fixed with paraformaldehyde and stained with crystal violet; the number of clones with more than 50 cells in a single clone was observed under a microscope and counted to assess the long-term proliferative capacity of the cells.

[0139] In the EdU incorporation experiment, cells from different treatment groups were seeded in culture plates, and EdU working solution was added according to the kit instructions and incubated for a certain period of time. Subsequently, the cells were fixed, permeabilized, and stained with fluorescently labeled azide. Simultaneously, the cell nuclei were counterstained with DAPI. The proportion of EdU-positive cells was observed and counted using a fluorescence microscope to reflect DNA synthesis activity and cell proliferation levels. Figure 18 , Figure 19The experimental results showed that KRT6A knockdown significantly reduced the clonogenic ability and EdU positivity rate of pancreatic cancer cells, while KRT6A overexpression significantly enhanced the above proliferation-related indicators, indicating that KRT6A plays an important role in promoting the proliferation of pancreatic cancer cells.

[0140] 4. The promoting effect of KRT6A on the migration and invasion of pancreatic cancer cells.

[0141] To further evaluate the effect of KRT6A on the migration and invasion phenotypes of pancreatic cancer cells, this invention uses scratch assay, Transwell migration assay, and Matrigel-coated Transwell invasion assay for detection.

[0142] In the scratch assay, PANC-1 and AsPC-1 cells treated with different methods were seeded into six-well plates and cultured until complete confluence. A straight scratch was made vertically in the cell monolayer using a sterile pipette tip. After gently washing to remove detached cells, the culture medium was replaced with serum-free medium. Images of the scratched area were taken at 0 h and 24 h, and the scratch closure area was calculated using image analysis software to assess cell migration ability.

[0143] In the Transwell migration assay, cells were resuspended in serum-free medium and seeded into the upper chamber of the Transwell, while serum-containing medium was added to the lower chamber as a chemokine. After 24 h of culture, unmigrated cells from the upper chamber were removed, and the migrating cells on the membrane surface of the lower chamber were fixed, stained, and counted under a microscope.

[0144] In the Transwell invasion assay, Transwell chambers pre-coated with Matrigel were used, and the remaining steps were similar to those in the migration assay, to assess the invasive ability of cells to cross the matrix barrier.

[0145] Experimental results showed that KRT6A knockdown significantly inhibited the migration and invasion of pancreatic cancer cells, while KRT6A overexpression significantly enhanced the above-mentioned motility and invasion phenotypes, indicating that KRT6A plays a key regulatory role in promoting the migration and invasion of pancreatic cancer cells (e.g., Figure 20 , Figure 21 , Figure 22 (As shown).

[0146] (iv) KRT6A inhibits ENT1 and regulates the in vivo progression of pancreatic cancer via the MIF-CD74 / CD44 axis.

[0147] 1. The regulatory relationship of KRT6A on ENT1 expression and its verification by Western blot.

[0148] To verify the regulatory relationship between KRT6A and ENT1 expression, this invention established KRT6A overexpression and KRT6A knockdown models in AsPC-1 cells and gemcitabine-resistant AsPC-1-GEM cells, respectively, and used Western blot to detect changes in KRT6A and ENT1 protein expression. The specific experimental steps are as follows:

[0149] (1) Cell preparation: AsPC-1 and AsPC-1-GEM cells were cultured in RPMI-1640 (containing 10% fetal bovine serum and 1% penicillin antibody) at 37°C and 5% CO2 until the logarithmic growth phase.

[0150] (2) Regulation of KRT6A expression: The specific steps are as follows (III.1);

[0151] (3) Protein extraction: Cells were lysed using RIPA lysis buffer containing protease / phosphatase inhibitors, and the supernatant was collected by centrifugation; protein concentration was determined by BCA method;

[0152] (4) Electrophoretic transfer: Take an equal amount of protein, separate it by SDS-PAGE, and then transfer it to a PVDF membrane;

[0153] (5) Blocking and antibody incubation: The membrane was blocked in TBST with 5% skim milk powder or BSA at room temperature for 1 h; and incubated with primary antibody (KRT6A, ENT1, GAPDH) overnight at 4°C.

[0154] (6) Secondary antibody and color development: After washing with TBST, incubate with HRP-labeled secondary antibody at room temperature for 1 h; ECL luminescence development and imaging;

[0155] (7) Result determination: Gray-scale analysis was used to quantify the bands, and GAPDH normalization was used to compare the differences between groups.

[0156] Figure 23 Western blot results of KRT6A and ENT1 in AsPC-1 and AsPC-1-GEM cells under KRT6A overexpression or knockdown conditions. The results showed that ENT1 protein expression was significantly reduced when KRT6A was overexpressed; knockdown of KRT6A in drug-resistant cells significantly restored ENT1 expression, suggesting that KRT6A has a negative regulatory effect on ENT1 and providing molecular evidence for subsequent in vivo drug resistance / progression mechanisms.

[0157] 2. Effects of KRT6A on the in vivo growth and metastatic potential of pancreatic cancer (subcutaneous tumorigenesis and lung metastasis models)

[0158] To evaluate the impact of KRT6A expression changes on in vivo progression (tumor growth and distant metastasis) of pancreatic cancer, this invention established a subcutaneous xenograft model and an experimental lung metastasis model, respectively, and compared the in vivo phenotypic differences (e.g., KRT6A overexpression, KRT6A knockdown, and control group) in the same background cells. Figure 24 The specific animal experiment steps are as follows:

[0159] (1) Experimental animals: Female BALB / c nude mice (4-6 weeks old) or nude mice as described in the article were selected and housed in an SPF environment; they were randomly grouped and numbered for blind measurement; n=6 per group;

[0160] (2) Construction of stable expression cells: AsPC-1 or AsPC-1-GEM cells were transduced into KRT6A overexpression vector (OE-KRT6A), KRT6A knockdown vector (shKRT6A) or corresponding negative control vector (NC), respectively, and stable lines were obtained by puromycin screening; KRT6A expression changes were verified by Western blot before in vivo experiments.

[0161] (3) Establishment of lung metastasis model: Logarithmic growth phase cells were taken, washed twice with PBS and resuspended, and the cell concentration was adjusted to 1×10⁻⁶. 6 cells / mL; 1×10 cells / mL was injected into each mouse via tail vein. 5 100 μL of cells were used to establish an experimental lung metastasis model; the cells were fed for another 4 weeks before being sacrificed to harvest the lungs.

[0162] (4) Assessment of lung metastatic nodules: Take lung tissue and photograph it; count the number of metastatic nodules on the lung surface under a dissecting microscope and record the size of the nodules; then fix the lung tissue and embed it in paraffin for HE staining to verify the metastatic lesions;

[0163] (5) Establishment of subcutaneous tumorigenesis model: Logarithmic growth phase cells were collected and suspensions were prepared; 5×10 cells were subcutaneously injected into the right axilla / groin of each mouse. 5 100 μL of cells;

[0164] (6) Subcutaneous tumor growth monitoring: The long and short diameters of the tumor were measured weekly, the tumor volume was calculated and the growth curve was plotted; at the end of the experiment, the tumor was euthanized, dissected and weighed, and the differences between groups were compared.

[0165] Experimental results showed that KRT6A overexpression significantly promoted subcutaneous tumor growth and increased lung metastatic nodules; KRT6A knockdown significantly inhibited subcutaneous tumor growth and reduced lung metastasis, thus demonstrating that KRT6A promotes in vivo progression of pancreatic cancer (e.g., Figure 25 , Figure 26 , Figure 27 (As shown).

[0166] 3. Effects of KRT6A on tumor histopathology and proliferative / epithelial-mesenchymal phenotype (HE + IHC / IF)

[0167] To clarify the effects of KRT6A on tumor tissue pathological features, proliferation levels, and invasion-associated epithelial-mesenchymal transition (EMT) phenotype, this invention performed HE staining and immunohistochemical / immunofluorescence detection on lung tissue and subcutaneous xenograft tissue obtained from the above animal models. The specific steps are as follows:

[0168] (1) Tissue acquisition and fixation: Lung tissue and subcutaneous tumor tissue were immediately obtained after the animals were euthanized; and fixed in 4% paraformaldehyde or 10% neutral formalin.

[0169] (2) Paraffin embedding and sectioning: After fixation, routine dehydration, clearing, paraffin impregnation and paraffin embedding are performed. The section thickness is in accordance with the pathological routine (paraffin sectioning process is described in the text).

[0170] (3) HE staining: After dewaxing and hydration, the sections were stained with hematoxylin for the nuclei and eosin for the cytoplasm, then dehydrated, cleared and mounted; the presence and extent of lung metastases were observed under a microscope, and the differences in lesions among different groups were compared;

[0171] (4) IHC detection of proliferation / EMT markers: After dewaxing and hydration of sections, antigen retrieval was performed (e.g., microwave heating with citrate buffer), endogenous peroxidase was blocked with 3% hydrogen peroxide; BSA blocking; primary antibody incubation overnight at 4℃ (Ki67, E-cadherin, N-cadherin, etc.), followed by washing with PBS and incubation with HRP secondary antibody; DAB staining, hematoxylin counterstaining, dehydration and mounting;

[0172] (5) Immunofluorescence detection: Fluorescent labeling detection can be performed on the same or adjacent slices (e.g. for co-localization or expression comparison of multiple indicators);

[0173] (6) Result determination: The lung tissue was mainly used to observe metastatic lesions and their histological evidence; the tumor tissue was compared to the degree of Ki67 positivity, the expression trends of E-cadherin and N-cadherin, and the differences between groups were compared by image acquisition and semi-quantitative / quantitative analysis.

[0174] Figure 28 HE staining results of lung tissues from mice with different KRT6A expression states (showing metastatic lesions). The results showed that the lung tissue of the KRT6A high expression group had more obvious metastatic lesions; Ki67 and N-cadherin expression was increased and E-cadherin expression was decreased in subcutaneous xenografts; the KRT6A knockdown group showed the opposite changes, proving that KRT6A promotes proliferation and invasion-related phenotypes in vivo.

[0175] 4. In vivo modulation of the MIF-CD74 / CD44 signal axis by KRT6A

[0176] To verify that KRT6A participates in the regulation of pancreatic cancer progression in vivo through the MIF-CD74 / CD44 signaling axis, this invention simultaneously detects the expression of molecules such as KRT6A, ENT1, MIF, CD74, and CD44 in transplanted tumor tissues, and performs a comparative analysis with proliferation / EMT phenotype. The specific steps are as follows:

[0177] (1) Sample source: Paraffin sections of tumor tissue from the endpoint of the subcutaneous xenograft in Part 2;

[0178] (2) IHC / IF detection procedure: Follow the immunohistochemistry / immunofluorescence steps in Part 3. The key indicators to be detected include KRT6A, ENT1, MIF, CD74, and CD44. Ki67, E-cadherin, and N-cadherin are also detected simultaneously for phenotypic association.

[0179] (3) Result evaluation: The staining intensity and positive range of each indicator were recorded and compared. It was observed whether ENT1 showed reverse change when KRT6A was upregulated / downregulated and whether MIF-CD74 / CD44 were activated synchronously. In the same tissue, it was analyzed whether the expression of KRT6A and MIF (and its downstream axis) showed a consistent trend.

[0180] Figure 29 Immunohistochemical and immunofluorescence assays of KRT6A, Ki67, N-cadherin, E-cadherin, ENT1, MIF, CD74, and CD44 in transplanted tumor tissues were performed (comparison of different KRT6A expression states). Results showed that in the KRT6A overexpression group, the expression of MIF, CD74, and CD44 was enhanced, while ENT1 was decreased. In the KRT6A knockdown group, the expression of these molecules decreased, and ENT1 was restored, suggesting that KRT6A can participate in the regulation of pancreatic cancer progression in vivo by activating the MIF-CD74 / CD44 signaling axis and inhibiting ENT1.

[0181] (V) Preparation and characterization of c-Lip@siKRT6A

[0182] 1. Selection and ratio of lipid components: 1,2-dioleoyl-3-trimethylammonium propane (DOTAP), 1,2-distearyl-sn-glycerol-3-phosphocholine (DSPC), cholesterol, 1,2-distearyl-sn-glycerol-3-phosphoethanolamine-N-[methoxy(polyethylene glycol)-2000] (DSPE-PEG2000) and DSPE-PEG2000-cyclic arginine-glycine-aspartic acid (cRGD) were selected in a molar ratio of 15:50:30:4:1.

[0183] 2. Preparation method: Thin-film hydration (also known as thin-film hydrolysis) was used. The above lipid components were dissolved in chloroform and dried with nitrogen to form a thin film. The film was then hydrated in siKRT6A solution (the nucleotide sequence of siKRT6A is shown in SEQ ID NO.1) at 40°C for 30 minutes and sonicated for 10 minutes to obtain c-Lip@siKRT6A.

[0184] 3. Preparation of fluorescent labeling agent: If fluorescent labeling is required, add indocyanine green (ICG) at a concentration of 100 μg / mL during the film formation step. The remaining steps are the same as above to obtain c-Lip@siKRT6A. ICG .

[0185] 4. Morphological observation: Observation using transmission electron microscopy (TEM) revealed that c-Lip@siKRT6A exhibits a typical spherical structure with uniform size and a core-shell structure (e.g., ...). Figure 30 (As shown in A).

[0186] 5. Particle size and potential: Dynamic light scattering (DLS) detection showed that the c-Lip@siKRT6A hydrodynamic particle size was approximately 100 nm (e.g., Figure 30 As shown in Figure B), the zeta potential is positive (e.g., Figure 31 As shown in Figure B), and remains stable in aqueous solution for 7 days (as shown in Figure B). Figure 31 (As shown in A).

[0187] 6. siRNA protection verification: Agarose gel electrophoresis confirmed that the lipid carrier can effectively encapsulate KRT6A siRNA, preventing its degradation (e.g., Figure 32 (As shown).

[0188] 7. ICG Loading Validation: Successful labeling was verified using UV-Vis spectroscopy, c-Lip@siKRT6A ICG The normalized absorption spectrum showed a characteristic peak at approximately 800 nm, consistent with the absorption peak of free ICG. This result confirms that ICG has been successfully loaded into c-Lip@siKRT6A (e.g., Figure 33 (As shown).

[0189] (vi) Tumor-targeted delivery characteristics of c-Lip@siKRT6A

[0190] 1. Cell uptake assay: AsPC-1-GEM cells were incubated with Lip@siKRT6A. ICG Or c-Lip@siKRT6A ICG After co-incubation for 1, 2, and 4 hours, laser confocal microscopy revealed that the intracellular fluorescence intensity of c-Lip@siKRT6A was significantly higher than that of the non-targeted control group, and the uptake efficiency was approximately doubled at 4 hours (e.g., ...). Figure 34 , Figure 35 (As shown).

[0191] 2. In vivo distribution: IVIS fluorescence imaging showed that c-Lip@siKRT6A was specifically enriched at the tumor site, reaching a peak at 9 h. The tumor fluorescence intensity was 5 times that of the control group, with less distribution in major organs (e.g., Figure 36 , Figure 37 , Figure 38 , Figure 39 (As shown).

[0192] (vii) In vivo therapeutic effects of c-Lip@siKRT6A combined with gemcitabine

[0193] To systematically evaluate the therapeutic effect of c-Lip@siKRT6A combined with gemcitabine on gemcitabine-resistant pancreatic cancer in vivo, this invention compared the antitumor effects of gemcitabine combined with non-targeted nano-formulation (Lip@siKRT6A) versus targeted nano-formulation (c-Lip@siKRT6A) in subcutaneous xenograft models and orthotopic pancreatic cancer models. The therapeutic effects were comprehensively evaluated using histological and immunofluorescence analyses. The preparation method of the non-targeted Lip@siKRT6A is essentially the same as that of c-Lip@siKRT6A, except that the lipid component does not contain DSPE-PEG2000-cRGD, but is replaced with an equimolar amount of DSPE-PEG2000.

[0194] 1. Establishment of subcutaneous and in situ models of gemcitabine-resistant pancreatic cancer

[0195] This invention uses gemcitabine-resistant pancreatic cancer cells AsPC-1-GEM to construct an in vivo model, such as... Figure 40 As shown, the specific steps are as follows:

[0196] (1) Experimental animals: Female BALB / c nude mice (4–6 weeks old) were selected, raised under SPF conditions, and randomly grouped;

[0197] (2) Cell preparation: AsPC-1-GEM cells were cultured in RPMI-1640 medium until the logarithmic growth phase, washed twice with PBS and resuspended.

[0198] (3) Subcutaneous xenograft model: The cell concentration was adjusted to 5 × 10⁻⁶. 5 Cells / 100 μL PBS, subcutaneously injected into the right back of each mouse;

[0199] (4) Orthotopic pancreatic cancer model: After anesthetizing mice, a small incision was made in the left abdomen to expose the pancreas. AsPC-1-GEM cells (which can be mixed with Matrigel) were slowly injected into the pancreatic parenchyma. The pancreas was then repositioned and the incision was sutured.

[0200] (5) Modeling confirmation: After the operation, observe the animal's condition. Once the subcutaneous tumor volume reaches about 100 mm³ or the in situ tumor is successfully formed, the drug intervention experiment will begin.

[0201] 2. Dosing regimen of gemcitabine in combination with Lip@siKRT6A or c-Lip@siKRT6A

[0202] After the model was successfully established, the mice were randomly assigned to groups and received the following treatment regimens:

[0203] (1) Gemcitabine administration: Gemcitabine is administered via intraperitoneal injection at a dose of 50 mg / kg twice a week;

[0204] (2) Nanoformulation administration: Lip@siKRT6A or c-Lip@siKRT6A was administered via tail vein injection. The administration volume and siRNA dosage were determined according to the aforementioned formulation experiments.

[0205] (3) Combined treatment cycle: Nanoparticles and gemcitabine were administered in combination until the end of the experiment;

[0206] (4) Control settings: Both models included two groups: gemcitabine + Lip@siKRT6A and gemcitabine + c-Lip@siKRT6A, to compare the effect of targeted modification on in vivo treatment efficacy.

[0207] 3. Evaluation of treatment efficacy in an orthotopic pancreatic cancer model

[0208] In the orthotopic pancreatic cancer model, mice were sacrificed at the experimental endpoint and pancreatic tumor tissue was obtained. The specific analysis steps are as follows:

[0209] (1) Tumor dissection and imaging: Complete dissection of the in situ pancreatic tumor and photographic recording;

[0210] (2) Tumor weight measurement: The tumor weight of each group was measured using a precision electronic balance;

[0211] (3) Tumor volume assessment: Quantitative comparison of tumor burden based on endpoint measurement results or imaging information;

[0212] (4) Statistical analysis: Compare the differences between the two groups of gemcitabine combined with Lip@siKRT6A and combined with c-Lip@siKRT6A.

[0213] Figure 41 Image A shows representative appearance images of tumors from different treatment groups in an orthotopic pancreatic cancer model. Figure 41 Figure B shows the statistical analysis results of tumor weight in each treatment group in the orthotopic pancreatic cancer model (n=6). Figure 41In the middle (C), the tumor volume of each treatment group in the orthotopic pancreatic cancer model is compared (n=6). The experimental results show that, compared with non-targeted nano-formulations, c-Lip@siKRT6A combined with gemcitabine significantly reduced the weight and volume of orthotopic pancreatic tumors.

[0214] 4. Evaluation of treatment efficacy in subcutaneous xenograft models

[0215] In the subcutaneous xenograft model, tumor growth was dynamically monitored and systematically analyzed at the endpoint. The specific steps are as follows:

[0216] (1) Tumor volume monitoring: Starting from the start of drug administration, the long and short diameters of the tumor were measured weekly using vernier calipers, and the tumor volume was calculated;

[0217] (2) Tumor growth curve plotting: Record the tumor volume at different time points and plot the growth curve;

[0218] (3) Endpoint removal and weighing: At the end of the experiment, the mice were sacrificed, the subcutaneous tumors were removed and weighed;

[0219] (4) Intergroup comparison: compare the inhibitory effects of gemcitabine combined with Lip@siKRT6A and combined with c-Lip@siKRT6A on subcutaneous tumor growth.

[0220] Figure 42 Image A shows representative appearance images of tumors from different treatment groups in the subcutaneous xenograft model. Figure 42 Figure B shows the statistical results of tumor weight in each treatment group (n=5); Figure 43 In the figure, A represents the growth curve of tumor volume over time in a subcutaneous xenograft model (n=5). Figure 43 Figure B shows the comparative analysis results of tumor growth trends in the subcutaneous xenograft model. The experimental results show that c-Lip@siKRT6A combined with gemcitabine can significantly delay subcutaneous tumor growth and reduce the endpoint tumor weight.

[0221] 5. Histological and immunofluorescence analyses to verify the therapeutic effect.

[0222] To further evaluate the treatment efficacy at the histological level, this invention performs pathological and immunofluorescence analyses on subcutaneous xenograft tumors and orthotopic tumor tissues. The specific steps are as follows:

[0223] (1) Tissue processing: The tumor tissue was fixed in 10% neutral formalin, routinely dehydrated, embedded in paraffin and sectioned;

[0224] (2) HE staining: After dewaxing and hydration, the sections were stained with hematoxylin and eosin to observe the overall tissue structure and pathological features of the tumor.

[0225] (3) Immunofluorescence detection: Multiple immunofluorescence staining was performed on tumor sections to detect fibrosis and related pathological features in the tumor tissue;

[0226] (4) Result determination: Compare the differences in the degree of fibrosis and pathological characteristics in tumor tissues between the gemcitabine combined with Lip@siKRT6A and the combined c-Lip@siKRT6A treatment groups.

[0227] The results showed that fibrosis and related pathological abnormalities in tumor tissue were significantly reduced in the c-Lip@siKRT6A combined with gemcitabine treatment group, suggesting that targeted delivery of siKRT6A can significantly improve the in vivo therapeutic effect of gemcitabine-resistant pancreatic cancer (e.g., Figure 44 (As shown).

[0228] (viii) KRT6A promotes TAM-M2 polarization and cytidine secretion via the MIF-CD74 / CD44 axis.

[0229] 1. Spatial and transcriptional association characteristics of KRT6A-positive tumor cells and TAM subsets

[0230] To elucidate the transcriptional and compositional associations between KRT6A-positive tumor cells and tumor-associated macrophage (TAM) subsets, this invention integrates and analyzes single-cell RNA sequencing datasets from multiple pancreatic cancer sources, including GSE154778, GSE155698, GSE156405, and GSE197177. The steps are as follows:

[0231] (1) Data acquisition: Download the original expression matrix and cell annotation information of the above single-cell dataset from the GEO database;

[0232] (2) Seurat pretreatment: Seurat was used for quality control (filtering low-quality cells), normalization, screening for highly variable genes and data scaling;

[0233] (3) Batch effect correction: The Harmony algorithm is used to perform batch correction on different datasets and then integrate them;

[0234] (4) Cell type identification: The main cell populations were identified based on classic marker genes, and tumor cell populations and TAM cell populations were extracted from the integrated object for subsequent analysis;

[0235] (5) Tumor cell subpopulation classification: Tumor cells were clustered twice and divided into multiple subpopulations (the figure shows three subpopulations). Based on the KRT6A expression level, tumor cell subpopulations with significant high KRT6A expression were identified. + Tumor subgroups), such as Figure 45 As shown;

[0236] (6) Visualization and Gene Expression Display: UMAP was used for dimensionality reduction visualization to show the transcriptional heterogeneity of tumor cells and TAM, and DotPlot and other methods were used to show the expression differences of key marker genes between tumor cells and TAM, such as Figure 46 As shown;

[0237] (7) Sample composition association analysis: For each sample, the relative proportions of different tumor cell subsets and TAM subsets in the sample were calculated and analyzed according to KRT6A. + Stratified comparisons of tumor subpopulation enrichment levels revealed a synergistic relationship between the proportion of tumor cell subpopulations and the proportion of TAM subpopulations, which could be used to indicate KRT6A. + Tumor cells and specific TAM subsets may exhibit synergistic enrichment and functional association (e.g. Figure 47 (As shown).

[0238] 2. KRT6A-mediated MIF-CD74 / CD44 signaling and TAM-M2 polarization modulation

[0239] 2.1 Ligand-receptor interaction and MIF-CD74 / CD44 signal enrichment analysis (CellChat)

[0240] To identify KRT6A + This invention analyzes intercellular ligand-receptor interactions using the integrated single-cell data to explore key cell communication pathways between tumor cells and TAM subsets. For example... Figure 48 , Figure 49 , Figure 50 and Figure 51 As shown, the specific steps and results are as follows:

[0241] (1) Import the normalized single-cell expression matrix and cell type annotation into CellChat and construct a CellChat object;

[0242] (2) Filter low-expression genes and load the CellChatDB.human database;

[0243] (3) Identify the ligands and receptors that are highly expressed in each cell population and calculate the communication probability;

[0244] (4) Summarize communication strength at the pathway level and screen significant communications through permutation test;

[0245] (5) Focus on extracting KRT6A + Communication between tumor subsets and TAM subsets showed significant enrichment of the MIF-CD74 / CD44 pathway, suggesting KRT6A. + Tumor cells may drive changes in TAM functional state through MIF signaling.

[0246] 2.2 Transwell co-culture verification of KRT6A's regulation of TAM-M2 polarization

[0247] To verify the regulatory effect of KRT6A on TAM-M2 polarization in vitro, this invention established a Transwell co-culture system and performed c-Lip@siKRT6A intervention on the tumor cell side. The specific experimental steps are as follows:

[0248] (1) Transwell device selection: A 0.4 μm pore size Transwell system was used to ensure that the two types of cells do not have direct contact but can perform paracrine communication;

[0249] (2) Tumor cell preparation: Gemcitabine-resistant AsPC-1-GEM cells were seeded in the upper chamber and, after adhesion, were treated with c-Lip@siKRT6A or control preparation (treatment method is the same as the previous nano-preparation cell experiment procedure).

[0250] (3) TAM source and culture: THP-1 cells were cultured in the lower chamber and induced to obtain macrophage state according to the experimental design (if PMA induction is used, the PMA conditions in the animal recovery experiment above can be used as a reference) so that they can respond to the signals secreted by tumor cells.

[0251] (4) Co-culture: The upper and lower chambers were co-cultured for 72 h;

[0252] (5) M2 polarization detection: Lower chamber cells were collected and the positive rate of M2 markers (such as CD206) was detected by immunofluorescence. The c-Lip@siKRT6A group and the control group were compared.

[0253] (6) Data processing: n=3 biological replicates were set for each group. The results were expressed as mean ± standard deviation and statistical tests were performed between groups.

[0254] Figure 52 The results of Transwell co-culture of AsPC-1-GEM and TAM and the quantitative analysis of the proportion of M2 macrophages (c-Lip@siKRT6A vs. control, n=3) showed that silencing / inhibiting KRT6A significantly reduced the proportion of TAM polarization towards the M2 type, verifying the role of KRT6A in promoting TAM-M2 polarization.

[0255] 2.3 In vitro quantification of MIF secreted by tumor cells

[0256] To verify that KRT6A affects MIF secretion, this invention measures the MIF concentration in the supernatant of tumor cell culture. The specific steps are as follows (consistent with the previous description):

[0257] (1) AsPC-1-GEM cells were treated with c-Lip@siKRT6A or as a control, respectively;

[0258] (2) Collect the cell culture supernatant after processing and centrifuge to remove cell debris;

[0259] (3) Use a commercial MIF detection kit and follow the instructions: add standards and samples to a 96-well plate pre-coated with antibody and incubate at 37°C; after washing the plate, add enzyme-linked detection antibody and incubate again; after adding substrate for color development, read the absorbance at 450 nm.

[0260] (4) Calculate the MIF concentration of the sample based on the standard curve; n=3 biological replicates per group.

[0261] Figure 53 Quantitative results of MIF concentration in the supernatant of AsPC-1-GEM cell culture after c-Lip@siKRT6A treatment (n=3). The results showed that c-Lip@siKRT6A treatment significantly reduced MIF secretion levels.

[0262] 2.4KRT6A and MIF cohort correlation verification

[0263] To support the KRT6A-MIF association at the clinical transcriptome level, this invention uses TCGA pancreatic cancer transcriptome data for correlation analysis, the steps of which are as follows:

[0264] (1) Obtain expression data of KRT6A and MIF in the TCGA pancreatic cancer cohort;

[0265] (2) Calculate the correlation using the Pearson correlation coefficient and give the r and p values;

[0266] (3) Display the correlation in the form of a scatter plot. Figure 54 The results of the correlation analysis between KRT6A and MIF expression in the TCGA pancreatic cancer cohort showed that the two were significantly positively correlated.

[0267] 3. Validation of KRT6A-related cytidine metabolic remodeling and in vivo transcriptional characteristics

[0268] 3.1 Pathway enrichment of upregulated genes in the KRT6A+ tumor subset

[0269] To identify KRT6A + Functional bias in tumor cells, this invention addresses KRT6A + Pathway enrichment analysis was performed on upregulated genes in tumor subgroups, following the steps (consistent with similar methods described above):

[0270] (1) Compare differentially expressed genes between the KRT6A+ tumor subset and other tumor cell subsets in single-cell data;

[0271] (2) Extract the set of upregulated genes;

[0272] (3) Use clusterProfiler to perform pathway enrichment (such as KEGG / GO) and output significant enriched entries. Figure 55 KRT6A + Pathway enrichment analysis of upregulated genes in tumor cells. Results showed enrichment of pathways related to pyrimidine / nucleoside metabolism.

[0273] 3.2 MetaFlux metabolic flux inferences cytidine uptake / secretion patterns

[0274] To infer cytidine metabolic exchange between tumor cells and TAM, this invention uses the MetaFlux framework for metabolic flux estimation:

[0275] (1) Input the single-cell expression matrix into MetaFlux;

[0276] (2) Gene-reaction mapping is performed based on enzyme-reaction rules and reaction activity scores are calculated;

[0277] (3) Metabolic flux characteristics were obtained by aggregation according to cell type / subpopulation;

[0278] (4) Compare the “import / export potential” of tumor cells and TAM subsets in cytidine-related responses to infer uptake and secretion trends;

[0279] (5) A schematic diagram is used to illustrate the predicted cytidine uptake and secretion patterns of different cell populations. Figure 56 Metabolic flux projections based on MetaFlux: Predicted cytidine uptake / secretion profiles of tumor cells and TAM subsets. Results suggest that TAMs are more biased towards cytidine secretion, while KRT6A... + Tumor cells are more inclined to take up cytidine.

[0280] 3.3 Determination of cytidine content in co-culture supernatant

[0281] To experimentally verify changes in cytidine secretion, the concentration of cytidine in the culture supernatant was measured in an AsPC-1-GEM and TAM co-culture system, as follows (consistent with the previous description):

[0282] (1) Constructing a Transwell co-culture system: AsPC-1-GEM cells in the upper chamber and TAM cells in the lower chamber;

[0283] (2) After being treated with c-Lip@siKRT6A or the control, tumor cells were co-cultured for 72 h.

[0284] (3) Collect the co-culture supernatant and centrifuge to remove cell debris;

[0285] (4) Use the cytidine detection kit to perform ELISA / colorimetric detection according to the instructions: add standard and sample, incubate, wash, add enzyme-linked antibody, develop color and read at 450 nm;

[0286] (5) Calculate cytidine concentration based on the standard curve; n=3 biological replicates per group. Figure 57 The results of quantitative analysis of cytidine concentration in the culture supernatant after c-Lip@siKRT6A treatment in the co-culture system (n=3) showed that the cytidine level in the supernatant was significantly reduced after KRT6A silencing.

[0287] 3.4 In vivo tumor bulk RNA-seq validation of c-Lip@siKRT6A-induced immune / metabolic pathway alterations

[0288] To verify the effects of KRT6A silencing on immunosuppression and nucleoside metabolism-related pathways in vivo, this invention established AsPC-1-GEM subcutaneous xenografts and performed transcriptome sequencing analysis after c-Lip@siKRT6A treatment. The animal modeling and drug administration process is consistent with the procedures described in the previous sections "Animal experiments (subcutaneous model)" and "c-Lip@siKRT6A combined treatment experiments"; the workflow in this figure is executed according to the following steps (e.g.) Figure 58 ):

[0289] (1) Establishment of subcutaneous xenografts: AsPC-1-GEM cells were inoculated to form tumors;

[0290] (2) Treatment group and administration: Gemcitabine and c-Lip@siKRT6A (or control) were administered;

[0291] (3) Sample collection: Tumor tissue was collected by euthanizing the animals at specified time points (n=3 / group);

[0292] (4) RNA extraction and library construction and sequencing: Perform the steps in “Transcriptomic sequencing and analysis” above, including RNA quality testing, cDNA library construction, and DNBseq paired-end sequencing;

[0293] (5) Quality control and alignment: Use SOAPnuke to remove low-quality reads and adapter sequences; align clean reads to the human reference genome GRCh38;

[0294] (6) Difference analysis: Compare the control group with the c-Lip@siKRT6A group, screen DEGs and draw volcano maps and heat maps (e.g. Figure 59 , Figure 60 (as shown)

[0295] (7) Enrichment analysis: DEGs were enriched with GO and KEGG to reveal changes in immune signaling and nucleoside / pyrimidine metabolism pathways (e.g. Figure 61 (As shown).

[0296] The 3.5 Scissor algorithm maps tumor bulk features back to single cells and identifies KRT6A-related cell populations.

[0297] To localize bulk transcriptome changes in vivo to specific single-cell populations, this invention employs the Scissor algorithm to map xenograft bulk phenotypic features to pancreatic cancer single-cell data. The steps are as follows:

[0298] (1) Input: bulk transcriptome data of xenografts (including treatment / control phenotypes) and single-cell expression matrix;

[0299] (2) Run the Scissor: Select the most relevant subset of single cells based on bulk phenotypic features, and define it as the Scissor. + Cells (representing cell states associated with high KRT6A / treatment-free intervention);

[0300] (3) UMAP display: Scissor + Cells were labeled in UMAP space, and their correspondence with tumor cell subsets was observed (e.g., ...). Figure 62 (as shown)

[0301] (4) Marker gene identification: for Scissor + With Scissor - Differential analysis of cells was performed, and representative enriched genes were output and displayed in a volcano plot (e.g.) Figure 63 (As shown).

[0302] 3.6 Mapping Scissor+ cells to the spatial transcriptome and displaying the ENT1 / MIF / MRC1 / CD74 / CD44 region features.

[0303] To further present the microenvironmental characteristics related to KRT6A at the spatial level, this invention will use Scissor + Cells were mapped to pancreatic cancer spatial transcriptome data, and the expression of relevant molecular regions was observed. Spatial analysis steps:

[0304] (1) Import HTAN WUSTL spatial transcriptome data and construct objects using Seurat;

[0305] (2) Normalization using SCTransform;

[0306] (3) Connect single-cell annotations with Scissor via FindTransferAnchors / TransferData+ State is projected onto the space spot;

[0307] (4) Spatial Feature Plot was used to display the expression of ENT1, MIF, MRC1 and CD74 / CD44 regions, and combined with Scissor + Regional localization observations revealed its spatial colocalization characteristics of "low ENT1, high MIF, high M2 marker (MRC1), and high CD74 / CD44," serving as spatial evidence for the KRT6A-driven immunosuppression and nucleoside enrichment microenvironment (e.g., Figure 64 (As shown).

[0308] (ix) c-Lip@siKRT6A enhances the in vivo efficacy of gemcitabine by reshaping the tumor microenvironment.

[0309] 1. Animal model establishment, grouping, and dosing regimen

[0310] This invention uses BALB / c nude mice (6–8 weeks old) to establish an in vivo model of gemcitabine-resistant pancreatic cancer and conduct drug administration and recovery experiments. The animals were housed in an SPF environment, and both modeling and drug administration were carried out by random grouping and numbering. The model establishment steps are as follows: (1) Subcutaneous xenograft model: AsPC-1-GEM cells in the logarithmic growth phase were taken, washed twice with PBS, and a cell suspension was prepared. The cell concentration was adjusted to 5×10⁻⁶. 5 (1) Cells / 100μL, 100μL of cell suspension was subcutaneously injected into the right side of each mouse; (2) Orthotopic pancreatic cancer model: After anesthesia, a small incision was made in the left abdomen to expose the pancreas, and the tumor cell suspension was slowly injected into the pancreatic parenchyma (the specifics are the same as before), the pancreas was repositioned and the incision was sutured; (3) Lung metastasis model: The cell concentration was adjusted to 1×10 6 cells / mL, 1×10 cells / mL, injected via tail vein 5 An experimental lung metastasis model was established using cells / 100 μL. Subcutaneous tumors were allowed to form and reach a measurable volume (approximately 100 mm²). 3 ) or enter the treatment group after the formation of in situ tumor. The dosing regimen is as follows: (4) Gemcitabine (Gem): intraperitoneal injection 50 mg / kg, twice a week; (5) c-Lip@siKRT6A: tail vein injection (dose volume and frequency as before; preparation method as before); (6) combination group: the same animal receives Gem and c-Lip@siKRT6A at the same time during the treatment cycle (e.g. Figure 65(7) Recovery experiment: On the basis of “Gem + c-Lip@siKRT6A” combined treatment, add the recovery factor - cytidine (100 mg / kg) intraperitoneally, and inject 30 min in advance on the day of Gem administration; or recover TAM-M2 cells: obtain M2 macrophages according to the induction method (PMA 50 ng / mL induction, IL-4 and IL-13 20 ng / mL each segmented treatment, and confirm M2 status by CD206 upregulation), inject 2×10 pertumoral injections each time. 5 One cell, once a week (e.g.) Figure 66 (As shown).

[0311] 2. Evaluation of the in vivo antitumor effect of c-Lip@siKRT6A in combination with gemcitabine

[0312] To evaluate the in vivo efficacy of the combined therapy, this invention established a subcutaneous xenograft model using AsPC-1-GEM cells and randomly divided the patients into a control group, a Gem monotherapy group, a c-Lip@siKRT6A monotherapy group, and a combined therapy group, and treated them according to the first-stage dosing regimen. The efficacy evaluation steps are as follows: (1) Dynamic monitoring of tumor volume: From the start of drug administration, the long diameter (L) and short diameter (W) of the tumor were measured at fixed time intervals using calipers, and the volume L*W2 / 2 was calculated; (2) Plotting the tumor growth curve: The volume data at each time point were plotted as a tumor growth curve over time; (3) Endpoint sampling and weighing: Mice were sacrificed at the experimental endpoint, the tumor was dissected, photographed and recorded, and the tumor weight was weighed using an electronic balance; (4) Statistical processing: n=6 for each group, and the results were expressed as mean ± standard deviation and inter-group comparisons were performed. Figure 67 Image A shows representative appearance images of subcutaneous xenograft tumors at the endpoint in different treatment groups. Figure 67 B represents the weight statistics (n=6). Figure 67 In the middle C, the growth curve of the subcutaneous xenograft tumor volume changes over time (n=6). Figure 68 This study compared the tumor growth trends of subcutaneous xenografts in different treatment groups (n=6). The results showed that the combination therapy significantly inhibited tumor growth and reduced the endpoint tumor weight compared to Gem alone or c-Lip@siKRT6A alone, indicating that c-Lip@siKRT6A can significantly enhance the in vivo therapeutic effect of gemcitabine in a drug-resistant pancreatic cancer model.

[0313] 3. The in vivo remodeling effect of c-Lip@siKRT6A on the tumor microenvironment

[0314] To verify whether combination therapy improves drug resistance by reshaping the tumor microenvironment, this invention performs multiplex immunofluorescence (IF) analysis on transplanted tumor tissue and quantifies TAM-M2 infiltration. The experimental steps are as follows: (1) Tissue fixation and sectioning: After the endpoint, tumor tissue is taken, fixed, paraffin-embedded and sectioned; (2) Multiplex immunofluorescence staining: The same procedure as before is followed (dewaxing and hydration → antigen retrieval → blocking → primary antibody incubation → HRP secondary antibody → TSA fluorescence signal deposition → thermal peeling → repeated cycles → DAPI counterstaining → mounting and imaging), KRT6A, MIF and ENT1 are detected and the spatial colocalization / mutual exclusion characteristics are observed by combining channels; (3) Imaging and quantification: Images are acquired under uniform exposure parameters, and the changes in KRT6A and MIF signal intensity and the recovery of ENT1 in each group are compared; (4) Quantification of M2 macrophages: Based on immunofluorescence markers (CD206 is used as the M2 marker for TAM-M2; CD68 is used for total TAM), the number or proportion of M2 positive macrophages is counted under the same field standard, and inter-group comparisons are performed. Figure 69 , Figure 70 The results showed that c-Lip@siKRT6A treatment significantly reduced the expression of KRT6A and MIF in tumor tissue and restored ENT1 expression, while significantly reducing the TAM-M2 infiltration rate, suggesting that this nano-formulation can improve the response to gemcitabine treatment by inhibiting the formation of an immunosuppressive microenvironment.

[0315] 4. Verification of the effect of TAM-M2 and cytidine replenishment on the combined therapeutic effect

[0316] To verify the key dependence of "c-Lip@siKRT6A enhancing gemcitabine efficacy", this invention performs TAM-M2 complementation or cytidine complementation on the basis of "Gem + c-Lip@siKRT6A" combined therapy, and evaluates tumor growth and microenvironment changes. The steps are as follows: (1) Grouping: In the subcutaneous xenograft tumor model, a basic group of “Gem + c-Lip@siKRT6A” is set up, and “TAM-M2 replenishment” or “cytidine replenishment” treatment is added respectively (the grouping and administration rhythm are the same as the recovery scheme in the first paragraph); (2) Efficacy evaluation: Tumor volume monitoring, endpoint dissection photography and weighing are performed in the same way as in the second paragraph, growth curves are plotted and differences are compared; (3) Immunofluorescence verification of replenishment effect: After the endpoint, tumor tissue sections are taken and immunofluorescence staining is performed to detect KRT6A and total TAM markers (for observing the overall TAM level) and KRT6A and M2 markers (for observing M2 infiltration recovery). The staining and imaging process is the same as in the third paragraph (the TSA multiple immunofluorescence steps are the same as above); (4) Result judgment: If the tumor growth inhibition effect of the replenishment group is weakened, and the immunofluorescence shows that the TAM or M2 infiltration level recovers, it supports the mechanism chain that “the combined efficacy depends on the inhibition of TAM-M2 and nucleoside enrichment microenvironment”. Figure 71Image A in the diagram represents representative morphological images of subcutaneous xenografts at the endpoint of the recovery experiment in different treatment groups. Figure 71 B represents the weight statistics (n=6) and Figure 71 In the middle C, the tumor growth curve of the subcutaneous xenograft is shown (n=6). Figure 72 To retrieve the results of the comparison of tumor growth trends in subcutaneous xenografts in different treatment groups (n=6); Figure 73 To reproduce representative images of KRT6A and total TAM immunofluorescence staining in experimental xenograft tissue; Figure 74 Representative images of KRT6A and M2 macrophages in the experimental xenograft tissue were obtained using immunofluorescence staining. Results showed that both TAM-M2 complementation and cytidine supplementation weakened the inhibitory effect of combined therapy on tumor growth to varying degrees. Immunofluorescence further demonstrated that complementation treatment restored macrophage infiltration and M2 ratio levels, indicating that c-Lip@siKRT6A primarily enhances the in vivo antitumor efficacy of gemcitabine by inhibiting TAM-M2 polarization and pyrimidine enrichment.

[0317] (x) Evaluation of in vitro and in vivo biocompatibility of c-Lip@siKRT6A

[0318] To evaluate the blood compatibility and in vivo safety of c-Lip@siKRT6A, this invention underwent hemolysis experiments, in vivo weight monitoring, major organ pathological examinations, and hematological / liver and kidney function tests. The specific implementation steps are as follows:

[0319] 1. Hemolysis test

[0320] Fresh anticoagulated blood from mice was collected, centrifuged to obtain red blood cells (RBCs), and washed with physiological saline / PBS until the supernatant was clear. The RBCs were resuspended to form a homogeneous red blood cell suspension, which was then incubated with the test sample c-Lip@siKRT6A (37℃, 1h). ddH2O was used as a positive control (complete hemolysis), and PBS was used as a negative control (no hemolysis). After incubation, the supernatant was collected by centrifugation, and the hemolysis phenomenon was observed visually and the absorbance of the supernatant at 540 nm was measured. The hemolysis rate was calculated by normalizing the sample group and the positive / negative control according to the hemolysis rate calculation formula. Figure 75 The results of the c-Lip@siKRT6A hemolysis assay are shown (including hemolysis appearance image; (+) positive control ddH2O, (-) negative control PBS). The results show that the overall hemolysis rate of c-Lip@siKRT6A is less than 5%, indicating that it has excellent blood compatibility and does not cause significant damage to red blood cells.

[0321] 2. Mouse weight monitoring

[0322] Healthy mice were selected and randomly divided into PBS group, Lip@siKRT6A group and c-Lip@siKRT6A group. The corresponding samples were injected via tail vein (injection method as before). Weight was recorded every 3 days from the injection date and monitored for 15 consecutive days. Weight change curves were plotted. Figure 76 The results showed that the body weight of mice increased steadily within 15 days after tail vein injection of PBS, Lip@siKRT6A, or c-Lip@siKRT6A. There was no significant difference in body weight between the c-Lip@siKRT6A group and the PBS group, suggesting that the nano-formulation did not cause observable systemic toxicity or growth inhibition.

[0323] 3. HE pathological evaluation of major organs

[0324] Mice were sacrificed 15 days after tail vein injection, and major organs such as heart, liver, spleen, lungs and kidneys were dissected and collected. The organs were fixed in 10% neutral buffered formalin, routinely dehydrated, embedded in paraffin and sectioned (about 5 μm). After hematoxylin-eosin (H&E) staining, the morphological characteristics of the tissues were observed under an optical microscope, and the presence of toxicity-related changes such as inflammatory cell infiltration, necrosis, hemorrhage and structural disorder was assessed. Figure 77 The results of H&E staining of major organs (heart, liver, spleen, lung, and kidney) 15 days after tail vein injection (scale bar 100 μm) show that no obvious inflammation, necrosis, or tissue damage was observed in the major organs of the c-Lip@siKRT6A group, which is consistent with the morphological characteristics of the PBS control group.

[0325] 4. Hematological, liver function, and kidney function tests

[0326] Peripheral blood was collected from mice on day 15 post-injection. The blood samples were used for complete blood count (CBC) and blood biochemistry tests: (i) CBC was used to assess white blood cell count, red blood cell count, hemoglobin, and platelet count; (ii) Liver function tests were used to assess indicators related to liver injury (such as ALT and AST); (iii) Kidney function tests were used to assess indicators related to kidney injury (such as creatinine and blood urea nitrogen). The results of the c-Lip@siKRT6A group were compared with those of the PBS control group. Figure 78 , Figure 79 and Figure 80 The results showed that the complete blood count, liver function-related biochemical indicators, and kidney function-related biochemical indicators of mice were measured 15 days after tail vein injection. The results showed that all hematological, liver function, and kidney function indicators in the c-Lip@siKRT6A group were within the normal range and consistent with those in the PBS group, further demonstrating its good biocompatibility in vivo.

[0327] In summary, hemolysis experiments, weight monitoring, HE pathology of major organs, and hematological / hepatic and renal function evaluations all indicate that c-Lip@siKRT6A has excellent in vitro blood compatibility and in vivo biocompatibility, providing a safety basis for its biomedical application as a nucleic acid delivery nanoparticle formulation.

[0328] (xi) Mechanism of KRT6A promoting gemcitabine resistance in pancreatic cancer and the therapeutic effect of c-Lip@siKRT6A

[0329] Figure 81 The mechanism of action diagram illustrates a working model elucidating the molecular process by which KRT6A upregulation in pancreatic cancer promotes gemcitabine resistance through two synergistic mechanisms. On one hand, KRT6A inhibits the expression of the nucleoside transporter ENT1, reducing the efficiency of gemcitabine transport and uptake into tumor cells, thereby directly reducing the intracellular effective drug concentration and weakening the drug's killing effect. On the other hand, KRT6A-positive pancreatic cancer cells secrete macrophage migration inhibitory factor (MIF), activating the CD74 / CD44 receptor complex on the surface of tumor-associated macrophages (TAMs), driving TAM polarization towards the M2 phenotype. M2 TAMs further release pyrimidine nucleosides (such as cytidine), which can be taken up by tumor cells via ENT1 and enhance the nucleoside salvage pathway, thereby reducing tumor cells' dependence on gemcitabine, a cytidine analogue, and thus decreasing their therapeutic sensitivity. The synergistic effect of these two effects—limited drug uptake and enhanced metabolic compensation—ultimately promotes gemcitabine resistance in pancreatic cancer.

[0330] The schematic diagram further illustrates that the cRGD-modified nanodelivery system c-Lip@siKRT6A can target pancreatic cancer cells and specifically silence KRT6A gene expression, thereby restoring ENT1 levels, inhibiting MIF-mediated TAM-M2 polarization, reversing the immunosuppressive and pyrimidine-enriched tumor microenvironment, and ultimately enhancing the therapeutic sensitivity of pancreatic cancer to gemcitabine.

[0331] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

Claims

1. A KRT6A gene expression inhibitor, characterized by, KRT6A siRNA comprising a nucleotide sequence as shown in SEQ ID NO.

1.

2. Use of the KRT6A gene expression inhibitor of claim 1 in the preparation of a medicament for treating gemcitabine-resistant pancreatic cancer.

3. A pancreatic cancer targeting liposomal nanofonnulation, characterized in that, The surface of the pancreatic cancer-targeting liposome nano-preparation is modified with arginine-citrulline-aspartic acid, and the inside is wrapped with KRT6A siRNA comprising a nucleotide sequence as shown in SEQ ID NO. 1, and the preparation method comprises the following steps: The pancreatic cancer-targeting liposome nano-preparation is prepared by the film hydration method using 1,2-dioleoyl-3-trimethylammonium propane, 1,2-distearoyl-sn-glycero-3-phosphocholine, cholesterol, 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[methoxy(polyethylene glycol)-2000], and 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[methoxy(polyethylene glycol)-2000]-arginine-citrulline-aspartic acid as the lipid components and the KRT6A siRNA as the drug component.

4. The pancreatic cancer targeting nanoformulation according to claim 3, wherein, The molar ratio of the 1,2-dioleoyl-3-trimethylammonium propane, 1,2-distearoyl-sn-glycero-3-phosphocholine, cholesterol, 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[methoxy(polyethylene glycol)-2000], and 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[methoxy(polyethylene glycol)-2000]-arginine-citrulline-aspartic acid is (12-16):(45-60):(25-35):(2-5):

1.

5. The pancreatic cancer targeting nanoformulation as claimed in claim 4, wherein, The molar ratio of the 1,2-dioleoyl-3-trimethylammonium propane, 1,2-distearoyl-sn-glycero-3-phosphocholine, cholesterol, 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[methoxy(polyethylene glycol)-2000], and 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[methoxy(polyethylene glycol)-2000]-arginine-citrulline-aspartic acid is 15:50:30:4:

1.

6. A pharmaceutical composition for treating pancreatic cancer, characterized by, comprising the following (a) and (b): (a) gemcitabine; (b) the KRT6A gene expression inhibitor of claim 1 or the pancreatic cancer-targeting liposome nano-preparation of any one of claims 3-5.

7. The pharmaceutical composition of claim 6, wherein, The pharmaceutical composition further comprises a pharmaceutically acceptable excipient.

8. The pharmaceutical composition of claim 6, wherein, The dosage form of the pharmaceutical composition is an injection. The dosage form of the pharmaceutical composition is an injection.

Images