Immune combination chemotherapy efficacy prediction model based on lung adenocarcinoma plasma extracellular vesicle-derived cd160

Abstract

The application discloses a screening method of cancer plasma extracellular vesicle long-chain RNA (exLRs) markers, which comprises the steps of separation of subject plasma, extraction of extracellular vesicle RNA, library construction, high-throughput sequencing and bioinformatics analysis. The application also discloses application of CD160 from extracellular vesicles as a marker in lung cancer immune combined chemotherapy efficacy prediction or dynamic treatment effect evaluation.

Description

Technical Field

[0001] This invention relates to the field of molecular biology detection, specifically to a predictive model for the efficacy of immunotherapy combined with chemotherapy based on CD160 derived from extracellular vesicles in lung adenocarcinoma plasma, and its construction method. Background Technology

[0002] Lung cancer is currently the leading cause of cancer-related deaths worldwide, and lung adenocarcinoma is the most common histological subtype, accounting for approximately 40% of all cases. In recent years, immune checkpoint inhibitors (ICIs) targeting programmed cell death 1 (PD-1) and its ligand (PD-L1) have opened a new chapter in lung cancer treatment. Whether used as monotherapy in patients with a PD-L1 tumor proportion score (TPS) ≥50%, or in combination with platinum-based chemotherapy in patients regardless of PD-L1 expression levels, PD-1 inhibitors have significantly improved the efficacy of first-line treatment for patients with advanced lung adenocarcinoma.

[0003] Biomarkers for predicting immunotherapy response in lung cancer include PD-L1 expression, tumor mutational burden (TMB), and microsatellite instability (MSI) / mismatch repair deficiency (DMMR). However, NSCLC patients with low PD-L1 expression or low TMB may still benefit from PD-1 inhibitors combined with chemotherapy. Furthermore, MSI / dMMR is rare in lung cancer, with an incidence of less than 1%. Due to intratumoral spatial heterogeneity, a single biopsy specimen cannot adequately assess the entire tumor microenvironment (TME) and systemic antitumor immune response. Moreover, studies have shown that the predictive effectiveness of known ICI-related biomarkers, such as PD-L1 and TMB, is significantly diminished in lung adenocarcinoma when chemotherapy is added to intratumoral chemotherapy (ICI). Therefore, better predictive biomarkers are needed to predict the efficacy of immunotherapy combined with chemotherapy in cancer patients.

[0004] Extracellular vesicles (EVs), mainly including exosomes and microvesicles, are spherical, nanoscale lipid bilayer structures. EVs carry parent cell-specific nucleic acids (double-stranded DNA and various RNA subtypes), proteins, and lipids, which can act as signaling molecules. Under physiological and pathological conditions, they can be secreted by various cells, including immune cells, tumor cells, and stem cells, participating in processes such as antigen presentation in immunity, tumor growth and metastasis, and tissue repair. In recent years, EV-based liquid biopsies have received increasing attention for early cancer diagnosis, disease monitoring, prognostic prediction, and efficacy evaluation. Jin et al. reported that plasma EV-derived miRNAs can be used to differentiate between lung adenocarcinoma and squamous cell carcinoma in the early diagnosis of NSCLC. Diego et al. reported that dynamic changes in EV-derived PD-L1 can predict the efficacy of ICIs in NSCLC patients. EV-derived long RNAs (exLRs) include messenger RNA (mRNA), circular RNA (circRNA), and long non-coding RNA (lncRNA). The inventors’ previous research has demonstrated that exLRs can serve as biomarkers for diagnosis and prognosis in pancreatic ductal adenocarcinoma and breast cancer.

[0005] Currently, research on extracellular vesicles in the field of lung cancer mainly focuses on microRNAs and the diagnosis and prognostic prediction of lung cancer. There is currently no exploration of efficacy biomarkers for immunotherapy combined with chemotherapy for lung adenocarcinoma based on plasma exLRs. Summary of the Invention

[0006] To address the aforementioned issues, this invention employs high-throughput sequencing and bioinformatics analysis of plasma exLRs in patients with advanced lung adenocarcinoma before and after immunotherapy combined with chemotherapy. This identifies plasma EV-specific transcriptional profiles in patients with advanced lung adenocarcinoma, explores the application value of plasma exLRs in predicting the efficacy of immunotherapy combined with chemotherapy in lung adenocarcinoma, and verifies the results using real-time quantitative PCR (RT-qPCR). This enables the screening of potential beneficiaries of immunotherapy combined with chemotherapy in lung adenocarcinoma at the level of extracellular vesicles in peripheral blood cells.

[0007] Specifically, the first aspect of the present invention provides a method for screening extracellular vesicle long RNA (exLRs) markers in cancer plasma, the method comprising the steps of separating plasma from a subject, extracting extracellular vesicle RNA, constructing a library, high-throughput sequencing, and bioinformatics analysis.

[0008] In some embodiments, the biomarkers include those used for cancer diagnosis, treatment, efficacy evaluation of therapy, and / or prognostic assessment; preferably, the biomarkers are used for efficacy evaluation of therapy.

[0009] In some embodiments, the therapy includes chemotherapy, radiotherapy, immunotherapy, or combined immunotherapy and chemotherapy; preferably, the therapy is combined immunotherapy and chemotherapy.

[0010] In some embodiments, the immunotherapy in the combined immunotherapy and chemotherapy includes PD-1 inhibitor therapy, and the chemotherapy includes pemetrexed and / or platinum-based chemotherapy; preferably, the PD-1 inhibitor is selected from pembrolizumab or camrelizumab.

[0011] In some embodiments, the cancer is lung cancer; preferably, the cancer is lung adenocarcinoma.

[0012] In some implementations, biomarkers for specific purposes are screened by combining clinical characteristics of the subjects, high-throughput sequencing results, and bioinformatics analysis; preferably, the biomarkers for specific purposes are exLRs for evaluating the efficacy of immunotherapy combined with chemotherapy for lung adenocarcinoma.

[0013] A second aspect of the present invention provides exLRs markers obtained by screening according to the method of the first aspect of the present invention.

[0014] In some embodiments, the marker is CD160 derived from extracellular vesicles.

[0015] A third aspect of the present invention provides biomarkers for predicting the efficacy of combined immunotherapy and chemotherapy for lung cancer or for evaluating the dynamic treatment effect, said biomarkers including CD160 derived from extracellular vesicles.

[0016] In some embodiments, the immunotherapy in the combined immunotherapy and chemotherapy includes PD-1 inhibitor therapy, and the chemotherapy includes pemetrexed and / or platinum-based chemotherapy; preferably, the PD-1 inhibitor is selected from pembrolizumab or camrelizumab.

[0017] In some embodiments, the lung cancer is lung adenocarcinoma.

[0018] In some embodiments, CD160 derived from extracellular vesicles is used as a standalone biomarker for prediction or in combination with a second biomarker for prediction; preferably, the second biomarker includes the neutrophil / lymphocyte ratio (NLR level) and bone metastasis status.

[0019] The fourth aspect of this invention provides the use of a reagent for detecting the expression level of CD160 derived from extracellular vesicles in the preparation of a drug for predicting the efficacy of combined immunotherapy and chemotherapy for lung cancer or for evaluating the dynamic treatment effect.

[0020] In some embodiments, the immunotherapy in the combined immunotherapy and chemotherapy includes PD-1 inhibitor therapy, and the chemotherapy includes pemetrexed and / or platinum-based chemotherapy; preferably, the PD-1 inhibitor is selected from pembrolizumab or camrelizumab.

[0021] In some embodiments, the lung cancer is lung adenocarcinoma.

[0022] In some embodiments, the detection reagents include reagents for high-throughput sequencing of plasma extracellular vesicle transcriptomes and reagents for RT-qPCR.

[0023] In some embodiments, the reagent for RT-qPCR includes primers; preferably, the primers include CD160 primers as shown in SEQ ID NO: 1-2; more preferably, the primers further include β-actin internal reference primers as shown in SEQ ID NO: 3-4.

[0024] In some implementations, high baseline levels of CD160 are associated with longer progression-free survival (PFS) and overall survival (OS); preferably, the AUC value of the ROC curve is used as a criterion to distinguish whether the treatment is effective.

[0025] In some implementations, a significant decrease in CD160 in early-stage extracellular vesicles indicates the effectiveness of immunotherapy combined with chemotherapy.

[0026] The fifth aspect of the present invention provides a method for constructing a predictive model for the efficacy of immunotherapy combined with chemotherapy in lung cancer. The method uses the screening method described in the first aspect of the present invention to screen exLRs for predicting the efficacy of immunotherapy combined with chemotherapy in lung cancer, uses a logistic regression algorithm to construct a predictive model, and uses clinical samples to validate the evaluation model.

[0027] The sixth aspect of the present invention provides a prediction model constructed according to the method described in the fifth aspect of the present invention.

[0028] In some implementations, the model uses baseline peripheral blood EV-CD160 levels to predict the efficacy of immunotherapy combined with chemotherapy in patients with lung adenocarcinoma.

[0029] In some embodiments, the model combines peripheral blood EV-CD160 levels, NLR levels, and bone metastasis status to predict the efficacy of immunotherapy combined with chemotherapy in patients with lung adenocarcinoma.

[0030] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0031] 1. In the field of lung cancer, current research on extracellular vesicles (exLRs) mainly focuses on microRNAs and the diagnosis and prognostic prediction of lung cancer. There is currently no exploration of efficacy biomarkers for immunotherapy combined with chemotherapy in lung adenocarcinoma based on plasma exLRs. This invention employs an optimized strategy for plasma extracellular vesicle long RNA sequencing (exLR-seq). This method encompasses a complete standard procedure for capturing, detecting, and analyzing plasma exLRs, including plasma isolation from lung cancer patients, extraction of exLR RNA, library construction, high-throughput sequencing, and bioinformatics analysis.

[0032] 2. This invention, based on high-throughput sequencing results, revealed that the exLR characteristics of patients with advanced lung adenocarcinoma differed significantly from those of healthy individuals. Baseline plasma exLR in patients responding to immunotherapy combined with chemotherapy was significantly enriched in T-cell activation-related pathways. Among T-cell activation-related exLRs, CD160 showed the highest correlation with survival time. High baseline levels of CD160 were associated with longer progression-free survival and overall survival.

[0033] 3. This invention validated the predictive efficacy of CD160 using RT-qPCR. High baseline levels of qPCR-CD160 were associated with longer PFS and OS. The qPCR validation results were similar in predictive power to EV-CD160, further confirming the predictive ability of CD160 for the efficacy of immunotherapy combined with chemotherapy in patients with lung adenocarcinoma. Considering the detection cost and high sensitivity, RT-qPCR detection of plasma extracellular vesicle CD160 has greater clinical benefits, and its application in screening for patients with a high risk of immunotherapy combined with chemotherapy in lung adenocarcinoma shows broad promise.

[0034] 4. This invention also found that dynamic changes in EV-derived CD160 levels can be used to monitor treatment response. Elevated baseline CD160 reflects a greater abundance of NK cells and CD8+ immature T cells in the peripheral blood, suggesting a more active anti-tumor host immune status. Furthermore, elevated tissue-level CD160 is associated with a favorable prognosis in patients with lung adenocarcinoma.

[0035] 5. Based on baseline peripheral blood EV-CD160 levels, this invention establishes a predictive model that combines baseline peripheral blood EV-CD160 levels, NLR levels, and bone metastasis status for predicting the efficacy of immunotherapy combined with chemotherapy in patients with lung adenocarcinoma. Attached Figure Description

[0036] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0037] Figure 1(A) EV extraction procedure and exLR-seq. (B) Electron micrographs of isolated EVs. (C) Particle size analysis of isolated EVs. (D) Immunoblot analysis of EVs isolated from samples from two patients and exosome-related markers in peripheral blood mononuclear cells (PBMCs).

[0038] Figure 2 (A) Flowchart of the selection and validation of the predictive biomarker CD160. (B) The top 15 significantly enriched GO-BP pathways analyzed from differentially expressed exLRs between effective and ineffective patients in the retrospective cohort; T-cell activation-related pathways are underlined. (C) Summary of log-rank P-values ​​and median PFS differences associated with identified T-cell activation-related genes; expression levels of each gene are categorized as high or low based on the median. (D) PFS in lung adenocarcinoma patients with high and low baseline EV-CD160 (using the median CD160 expression level in the retrospective cohort as the cutoff).

[0039] Figure 3 (A) In the retrospective cohort, KM survival curves assessed the difference in PFS between groups with the optimal cutoff value of baseline CD160 expression. (B) In the retrospective cohort, KM survival curves assessed the difference in OS between groups with the optimal cutoff value of baseline CD160 expression. (C) In the retrospective cohort, CD160 predicted the ROC curve for efficacy. (D) In ​​the prospective cohort, KM survival curves assessed the difference in PFS between groups with the optimal cutoff value of baseline CD160 expression. (E) In the prospective cohort, KM survival curves assessed the difference in OS between groups with the optimal cutoff value of baseline CD160 expression. (F) In the prospective cohort, CD160 predicted the ROC curve for efficacy. (G) Box plots showing baseline EV-CD160 levels between responders and non-responders in the pooled cohort. (H) The proportion of responders and non-responders at different baseline EV-CD160 levels.

[0040] Figure 4 (A) Correlation analysis between relative RT-qPCR-CD160 values ​​and EV-CD160 values. (B) ROC curve for predicting efficacy using relative RT-qPCR-CD160 values. (C) KM survival curve assessment of PFS differences grouped by median baseline relative RT-qPCR-CD160 values. (D) KM survival curve assessment of OS differences grouped by median baseline relative RT-qPCR-CD160 values.

[0041] Figure 5(A) Dynamic changes in EV-CD160 after treatment in responders and non-responders. (B) Relationship between EV-CD160 changes and PFS in lung adenocarcinoma patients in a retrospective cohort. (C) Relationship between EV-CD160 changes and OS in lung adenocarcinoma patients in a retrospective cohort. (D) Typical case studies showing the relationship between EV-CD160 levels and the volume of left lobe lung tumors shown on CT imaging from initial response to eventual resistance.

[0042] Figure 6 Predictive performance of models based on EV-CD160 levels and other predictive indices. (A) Objective response rate (ORR) grouped by different predictive indices, with neutrophil / lymphocyte ratio (NLR) levels defined according to the optimal cutoff value for PFS (4.64). (B) Proportion of patients with PFS > 6 months in different predictive indices, with NLR levels defined according to the optimal cutoff value for PFS (4.64). (C) Normograph of 6-month PFS predicted by combining bone metastasis, NLR levels, and CD160 expression in all enrolled lung adenocarcinoma patients.

[0043] Figure 7 (A) Violin plots show that high baseline expression of EV-CD160 is significantly associated with high abundance of circulating NK cells. (B) Violin plots show that high baseline expression of EV-CD160 is significantly associated with high abundance of circulating CD8+ naive T cells. (C) In the TCGA-lung adenocarcinoma dataset, CD160 expression in cancerous tissue was significantly lower than in adjacent normal tissue. (D) Overall survival (OS) of TCGA-lung adenocarcinoma patients without targeted mutations in the high (maximum 25%) and low (minimum 25%) CD160 groups. Detailed Implementation

[0044] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the described embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0045] Unless otherwise defined, the technical or scientific terms used herein shall have the ordinary meaning as understood by one of ordinary skill in the art to which this invention pertains.

[0046] This study included 74 patients with locally advanced / metastatic lung adenocarcinoma without target mutations who received first-line anti-PD-1 immunotherapy combined with chemotherapy. Plasma EV transcriptome sequencing was used to analyze their exLRs, identifying the exLR expression profile of advanced lung adenocarcinoma patients for the first time. By analyzing samples from a retrospective cohort (N=36) and a prospective cohort (N=38) of lung adenocarcinoma patients before and after treatment, combined with treatment response and survival analyses, efficacy biomarkers were identified and evaluated. It was found that EV-derived CD160 can predict the efficacy of anti-PD-1 immunotherapy combined with chemotherapy in lung adenocarcinoma, and this was validated at the RT-qPCR level. A predictive model based on peripheral blood EV-CD160 levels, NLR levels, and bone metastasis status was established for predicting the efficacy of immunotherapy combined with chemotherapy in lung adenocarcinoma patients.

[0047] Example 1 Experimental Method

[0048] 1.1 Research Group

[0049] This study included 74 patients with lung adenocarcinoma at Fudan University Cancer Hospital. PD-L1 expression in tumor tissues was measured using the DAKO IHC 22C3 method. Thirty-six patients were assigned to a retrospective cohort for predictive biomarker identification. To validate the predictive efficacy of candidate biomarkers, 38 patients with lung adenocarcinoma served as a prospective validation cohort. All patients received first-line PD-1 inhibitors (pembrolizumab or camrelizumab) combined with pemetrexed plus platinum-based chemotherapy, repeated every 3 weeks for 4–6 cycles. Subsequent maintenance therapy with PD-1 inhibitors and pemetrexed was administered, repeated every 3 weeks, until disease progression or intolerable toxicity.

[0050] 1.2 Efficacy Assessment

[0051] Efficacy of each treatment cycle was evaluated according to the RECIST version 1.1 criteria for evaluating the efficacy of treatment in solid tumors. Progression-free survival (PFS) was defined as the time from the start of immunotherapy combined with chemotherapy to disease progression or death from any cause. Overall survival (OS) was defined as the time from the start of immunotherapy combined with chemotherapy to death from any cause. Objective response rate (ORR) was defined as the proportion of patients who achieved a complete response (CR) or partial response (PR) as their best response. Patients were divided into treatment-responsive and treatment-ineffective groups based on their best response assessment during immunotherapy combined with chemotherapy and disease progression. The treatment-responsive group was defined as having a best response assessment of complete response (CR) / partial response (PR) and PFS ≥ 6 months. The treatment-ineffective group was defined as having a best response assessment of stable disease (SD) / progressive disease (PD) or PFS < 6 months.

[0052] 1.3 Plasma Collection

[0053] Plasma samples were collected from all lung adenocarcinoma patients prior to their first immunotherapy combined with chemotherapy (baseline, N=74) and from a retrospective cohort of lung adenocarcinoma patients (post-treatment dynamics, N=46). Regarding the 46 post-treatment plasma samples in the retrospective cohort, 36 samples were collected after two cycles of immunotherapy combined with chemotherapy (including 5 patients whose disease had progressed at the time of initial efficacy evaluation), and the remaining 10 samples were collected at four cycles of immunotherapy combined with chemotherapy (N=4) and at disease progression (N=6). In this case, approximately 6-8 mL of whole blood was drawn into an EDTA anticoagulant blood collection tube, and the whole blood was immediately centrifuged at 3000 rpm at room temperature for 10 minutes, followed by plasma separation. The separated plasma was then immediately centrifuged at 13,000 rpm at 4°C for 10 minutes to remove debris and stored at -80°C until use.

[0054] Purification of 1.4 EV and separation of exLR

[0055] For each sample, use 1 mL of plasma. Purify EVs using the exoRNeasySerum / PlasmaKit (Qiagen, Hilden, Germany) according to the manufacturer's protocol. Simply put, mix plasma with an equal volume of binding buffer XBP and add to an ExoEasy membrane affinity spinning column. After centrifugation, wash the bound EVs with wash buffer XWP.

[0056] For transmission electron microscopy (TEM) observation, particle size distribution measurement, and Western blotting, 400 μL of elution buffer XE (Qiagen, Cat. No. 76214) was spread onto the membrane-bound EVS and eluted by centrifugation at 5000 × g for 5 minutes. The elution volume was reduced to 50 μL by ultrafiltration, and then the buffer was exchanged with phosphate-buffered saline (PBS) using Amicon Ultra-0.5 Centrifugal Filter 10 kDa (Merck Millipore, Germany).

[0057] For RNA isolation, EVs were lysed on the column by incubation in QIAzol (Qiagen) for 5 minutes at room temperature. Chloroform was then added to the QIAzol elution buffer, followed by centrifugation at 12,000 × g for 15 minutes at 4°C. The supernatant was transferred to a new collection tube and thoroughly mixed with 2 volumes of ethanol. The mixture was then transferred to an RNeasy MinElutespin column and centrifuged to discard the elution buffer. After washing sequentially with RWT and RPE buffers, the EV RNA was eluted with ribonuclease-free water. RNA sequencing (RNA-seq) library preparation was performed immediately on the EV RNA. The remaining EV RNA was stored at -80°C for use within two weeks.

[0058] 1.5 ExLR sequencing analysis

[0059] EV RNA isolated from plasma was treated with DNase I (NEB, Ipswich, Massachusetts, USA) to remove DNA. Strand-specific RNA-seq libraries were then prepared using the SMARTer Stranded Total RNA-seq kit (Clontech, Palo Alto, CA, USA). Library quality was analyzed using a Qubit fluorometer (Thermo Fisher Scientific, Waltham, Massachusetts, USA) and a Qsep100 (BiOptic, New Taipei City, Taiwan, China). Paired-end sequencing of 2 × 150 bp was performed on an Illumina sequencing platform (San Diego, California, USA). Raw sequencing reads were filtered using FastQC (version 0.11.8) and aligned to the human genome (GRCh38) using Read Aligner STAR (version 2.7.1a). Gene expression levels were subsequently quantified using featureCounts (version 1.6.3) and converted to kilobase million transcripts per mille (TPM). Gene annotation information was retrieved from the GENCODE database (Human, Version 29). CircRNAs were identified and quantified using Assembling Splice Junctions Analysis (ASJA) software.

[0060] 1.6 Real-time quantitative PCR reaction

[0061] EV RNA was synthesized using SMART cDNA synthesis technology (Clontech, USA) to prepare specific RNA-seq libraries. RT-qPCR was performed using the SYBR Green Pro Taq HS (Accurate Biology) kit. The CD160 primer sequences used were as follows: CD160-F: 5'-TCTGGGTAATGCTGGTCAC-3', SEQ ID NO:1; CD160-R: 5'-AAGCCATAGTCAGACTCATC-3', SEQ ID NO:2. β-actin was used as an internal control, with the following primer sequences: ACTB-qF: 5'-TTGTTACAGGAAGTCCCTTGCC-3', SEQ ID NO:3; ACTB-qR: 5'-ATGCTATCACCTCCCCTGTGTG-3', SEQ ID NO:4. The RT-qPCR sample concentration was 0.1 ng / mL. Based on the obtained CT values ​​and amplification curves, the calculation method was CT = CT experimental group - CT internal control group, and finally, the final data was calculated using formula 2 - ΔCT.

[0062] 1.7 Data Analysis and Statistics

[0063] RNA-Seq read counts were converted to TPM values ​​to assess all comparable exLR genes in the samples. Genes with low overall frequency (expressed in less than 30% of all analyzed samples) were removed, and the remaining exLRs were used for subsequent analyses. Differences in exLR expression between responding and non-responding patients were assessed using fold change (FC) and compared using the Mann-Whitney U test. Wilcoxon signed-rank test was performed on paired samples from the same patient before and after treatment. ExLRs with Fc > 1.5 and P < 0.05 were defined as differentially expressed genes. Gene ontology (GO), biological process (BP) enrichment analyses, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed on differentially expressed exLRs to identify significantly enriched pathways. Benjamini-Hochberg correction was used to control for false discovery rate (FDR).

[0064] The clinical characteristics of patients were summarized using the median and interquartile range (IQR) of continuous variables, and the frequency and percentage of categorical variables. For clinical characteristics in both retrospective and prospective cohorts, t-tests were performed on normally distributed continuous variables, and chi-square or Fisher's exact tests were performed on categorical variables.

[0065] Clinical evaluation employed the Kaplan-Meier method to assess overall survival (OS) and progression-free survival (PFS) curves, with log-rank tests used for intergroup comparisons. Receiver operating characteristic (ROC) curves were used to evaluate the predictive ability of EV-derived CD160 levels to distinguish between treatment-responsive and treatment-ineffective patients. In the retrospective cohort, the optimal cutoff value for CD160 expression was determined using the 'Maxstat' R package to assess patient PFS. Univariate and multivariate Cox analyses were performed using a Cox proportional hazards regression model to identify prognostic factors associated with PFS and OS. Variables with p-values ​​<0.05 in the univariate analyses were included in subsequent multivariate analyses. The proportional hazards model was used to estimate the hazard ratio (HR) and its 95% confidence interval (CI).

[0066] Statistical analysis used Statistics (version 26) and R (version 4.0.2) tools were used. All statistical tests were two-tailed, and P < 0.05 was considered statistically significant. R packages included 'limma', 'clusterProfiler', 'survminer', 'Survival', 'proc', 'ggplot2', 'rms', 'Maxstat', 'reshape2', and 'tidyverse'.

[0067] Example 2 Experimental Results

[0068] 2.1 Patient population, grouping criteria, and sample collection

[0069] A total of 36 patients were assigned to the retrospective cohort for exLR marker identification, and 38 patients with lung adenocarcinoma served as a prospective validation cohort to validate the predictive power of the markers. At the data cutoff, the median follow-up time in the retrospective cohort was 11.75 months (interquartile range [IQR], 9.30 to 18.15 months), while the median follow-up time in the prospective cohort was 7.73 months (IQR, 6.52 to 10.35 months). The objective response rate (ORR, the proportion of patients with the best efficacy assessment of complete response [CR] or partial response [PR], was 52.8% in the retrospective cohort and 52.6% in the prospective cohort. In the retrospective cohort, 41.7% (15 patients) of patients were classified as responders to immunotherapy combined with chemotherapy, while in the prospective cohort, 50.0% (19 patients) of patients were classified as responders to immunotherapy combined with chemotherapy.

[0070] 2.2 Identification of plasma exLR and screening of predictive biomarkers for therapeutic efficacy

[0071] RNA was extracted from EVs in the plasma of lung adenocarcinoma patients, and exLR sequencing was performed on each plasma sample. Figure 1A). Next, the extracted plasma EVs were validated for morphology, particle size, and characteristic proteins. For example... Figure 1 As shown in Figure B, transmission electron microscopy (TEM) imaging revealed that the isolated vesicles exhibited spherical, cup-shaped, and double-membrane structures. Particle size analysis of the isolated vesicles showed a heterogeneous population of spherical nanoparticles with an average diameter of 100.2 ± 37.1 nm. Figure 1 C). Western blot analysis confirmed that the EV markers CD63 and TSG101 were abundantly expressed in isolated vesicles but not in peripheral blood mononuclear cells (PBMCs). Meanwhile, Calnexin, an endoplasmic reticulum marker expected to be absent in EVs, was detected in PBMCs but not in isolated vesicles. Figure 1 (D) Compared with exLR sequencing data from healthy donors in our previous studies, approximately 15,000 and 16,000 annotated exLR genes, including mRNAs, lncRNAs, pseudogenes, and circRNAs, were consistently detected in each sample from healthy donors and lung adenocarcinoma patients, respectively. The majority of the detected exLRs were mRNAs. The abundance of mRNAs, pseudogenes, and circRNAs was higher in lung adenocarcinoma patients than in healthy donors. 496 and 378 exLR genes were significantly upregulated and downregulated, respectively, in lung adenocarcinoma patients (FDR < 0.05, fold change [FC] > 2). Kyoto Encyclopedia of Genetics and Genomes (KEGG) pathway analysis showed that differentially expressed exLRs were significantly enriched in cancer-related pathways.

[0072] Selection of exLR predictive biomarkers in a lung adenocarcinoma cohort. A schematic diagram illustrating the selection and validation of the predictive biomarker CD160 is shown below. Figure 2 As shown in Figure A. By comparing the baseline exLR expression profiles of the treatment-responsive and ineffective groups, 498 differentially expressed genes (DEGs, P < 0.05, FC > 1.5) were selected. Gene Ontological Biology Processes (GO-BP) enrichment analysis showed that T cell activation-related pathways were significantly enriched in the DEGs. Figure 2 B) indicates that T cell activation plays an important role in the response to anti-PD-1 agent immunotherapy. Therefore, 17 DEGs (degenerative genes) in the T cell activation-related pathway were selected. Figure 2 C), and explored the relationship between the expression levels of these genes and patient PFS. Patients were divided into high and low groups based on the median expression of the corresponding genes. Among the 17 DEGs, CD160 showed the greatest difference between responders and non-responders, with the largest difference in median PFS (C). Figure 2C). Further survival analysis showed that patients with high baseline EV-CD160 values ​​had a median PFS of 19.80 months (95% confidence interval [CI] 9.00–30.60 months), while patients with low EV-CD160 values ​​had a median survival of 5.00 months (95% CI 2.80–7.20 months) (HR = 0.26, P = 0.001). Figure 2 D).

[0073] 2.3 Baseline EV-CD160 levels are associated with the response to immunotherapy combined with chemotherapy in patients with lung adenocarcinoma.

[0074] Based on the PFS information of the retrospective group, patients were divided into high and low baseline CD160 expression groups using the 'MAXSTAT'R package, and 9.779 was determined as the optimal cutoff value. The median PFS in the high CD160 group was 19.82 months (95% CI, 13.10–26.54 months), and the median PFS in the low CD160 group was 7.46 months (95% CI, 4.94–5.00 months) (P<0.001). The incidence of disease progression and death was 5 (33.3%) and 18 (85.7%), respectively. Figure 3 A). Compared with the low CD160 group, the high CD160 group had a longer overall survival (median, not reached vs. 13.20 months [95% CI 6.95–19.45 months]; P = 0.005), with 1 death (6.7%) and 11 deaths (52.4%), respectively. Figure 3 B). To evaluate the predictive performance of baseline CD160 expression levels, ROC curve analysis was performed, yielding an area under the curve of 0.784 (95% CI, 0.619–0.949), a sensitivity of 0.952, and a specificity of 0.600, indicating strong predictive ability. Figure 3 C). To further evaluate the predictive performance of baseline EV-CD160 on response to immunotherapy combined with chemotherapy, an additional 38 patients with lung adenocarcinoma were included in this prospective cohort. Survival analysis was performed on this prospective cohort using an optimal cutoff value of 9.779. Although the median survival was not reached in the prospective cohort due to the short follow-up time, patients with high CD160 expression still had significantly longer PFS (P = 0.003) and OS (P = 0.014). Figure 3 The AUC value of the ROC curve was 0.648 (95% CI, 0.467–0.829), the sensitivity was 0.526, and the specificity was 0.789 (D and 3E). Figure 3 F). Subsequent retrospective and prospective cohort analyses showed that baseline CD160 levels in effective participants were significantly higher than in ineffective participants (median, 13.73 vs. 6.70; P = 0.0025). Figure 3G). Furthermore, baseline CD160 levels were positively correlated with treatment efficacy. The effective rate was 65.6% in the high CD160 expression group and 31.0% in the low expression group (P = 0.0063). Figure 3 H).

[0075] To validate the predictive power of baseline EV-CD160, CD160 RNA from the exLR sequencing library was used as a template for RT-qPCR validation, with β-actin as an internal control. -ΔCT The final data were calculated. In 41 baseline samples where measurements were available, the results showed a high correlation between the relative values ​​of qPCR-CD160 and EV-CD160 sequencing values ​​(r = 0.63, P < 0.001). Figure 4 A), and the relative value of qPCR-CD160 has good efficacy in predicting whether a patient responds to or does not respond to treatment. Figure 4 B), the AUC value of the ROC curve was 0.656 (95% CI, 0.482–0.829). Using the median relative qPCR-CD160 value as the cutoff, patients with high baseline qPCR-CD160 levels had significantly longer survival than patients with low baseline qPCR-CD160 levels. Figure 4 CD, median PFS: not reached vs. 11.8 months, HR = 0.37, P = 0.035; median OS: not reached vs. 13.3 months, HR = 0.22, P = 0.039). The predictive performance of the above RT-qPCR results is consistent with that of the exLR-seq results.

[0076] 2.4 Monitoring the dynamic changes of EV-CD160 can assess the dynamic efficacy of immunotherapy combined with chemotherapy.

[0077] Paired exLR analysis was performed on blood samples from lung adenocarcinoma patients before (TX) and after (TX) treatment in a retrospective cohort. It was found that the expression level of EV-CD160 in the treatment-responsive group was significantly decreased in the early stage of treatment (the time point of the first imaging assessment, approximately 4-6 weeks after the first treatment) (P = 0.002). Figure 5 A). However, this change in CD160 expression was not observed in the null group (P = 0.56, Figure 5 A). Compared with the group with elevated CD160 after treatment, the group with decreased CD160 had significantly prolonged PFS (P=0.009) and OS (P=0.007). Figure 5Therefore, changes in plasma EV-CD160 levels in early-stage patients may predict treatment outcomes in lung adenocarcinoma patients receiving anti-PD-1 immunotherapy combined with chemotherapy. To further evaluate the response of EV-CD160 expression level changes to targeted lesion size during anti-PD-1 immunotherapy combined with chemotherapy, longitudinal dynamic tracking of CD160 expression and CT imaging was performed on a representative patient who initially received a partial response (PR) but developed progressive disease (PD) after 13 months of treatment. Figure 5 (D) CD160 expression levels began to decline at the time of the patient's first imaging assessment showing partial response (PR) and continued to decline as the tumor shrank. Thirteen months after treatment, tumor progression occurred, and CD160 expression levels increased accordingly. The changes in EV-CD160 levels in this lung adenocarcinoma patient who received anti-PD-1 immunotherapy combined with chemotherapy may reflect the clinical response during treatment.

[0078] Model construction for predicting efficacy using 2.5EV-CD160 in combination with other biomarkers

[0079] Univariate and multivariate Cox regression analyses were performed on the characteristics of all enrolled lung adenocarcinoma patients. Potential associations of age, sex, smoking history, stage, thoracic metastasis, adrenal metastasis, liver metastasis, brain metastasis, bone metastasis, baseline circulating neutrophil / lymphocyte ratio (NLR), platelet / lymphocyte ratio (PLR), lactate dehydrogenase (LDH), and EV-CD160 levels were assessed using progression-free survival (PFS) and overall survival (OS) (Table 1). Among these variables, high NLR, high PLR, and high LDH are known immune-related biomarkers associated with poorer prognosis in NSCLC patients receiving immunotherapy. Univariate analysis showed that bone metastasis, high NLR levels, and low baseline EV-CD160 expression were significantly associated with shorter PFS and OS. Multivariate analysis showed that, in addition to the presence or absence of bone metastasis and NLR, CD160 value was also an independent prognostic factor affecting PFS (P < 0.001) and OS (P = 0.018).

[0080] Table 1. Univariate and multivariate Cox analyses of PFS and OS in patients with lung adenocarcinoma.

[0081] The predictive efficacy of the above indicators was assessed based on baseline protective factors (high EV-CD160 level, low NLR level, and no bone metastasis) identified by multivariate Cox regression. Objective response was achieved when EV-CD160 expression level was used alone or in combination with other predictive indicators. Figure 6 A) and

[0082] The percentage of patients with pre-existing conditions (PFS) ≥ 6 months ( Figure 6 B) All are at a relatively high level.

[0083] The inventors constructed a predictive model, Normograph, based on peripheral blood EV-CD160 levels, NLR levels, and bone metastasis status. This model was used to predict 6-month progression-free survival (PFS) in all enrolled lung adenocarcinoma patients via multivariate Cox regression. Figure 5 C) The results confirmed the discriminative power, consistency, and clinical applicability of the nomogram in patient risk stratification. In conclusion, the results suggest that EV-CD160 is a potential prognostic factor that can predict clinical outcomes in patients with advanced lung adenocarcinoma.

[0084] 2.6 Relationship between baseline EV-CD160 levels and prognosis in patients with lung adenocarcinoma

[0085] This study aimed to understand the potential mechanisms underlying the prognostic predictive role of EV-CD160. In previous studies, an EV deconvolution method called EV-Origin was developed to resolve cell origin from exLR-seq gene expression data. Compared to the low CD160 level subset, the high CD160 level subset showed a significant enrichment of natural killer (NK) cells and CD8+ naive T cells. Figure 7 (AB) This means that there are higher abundances of innate and adaptive immune components in people with high CD160 levels.

[0086] Further reference was made to the Cancer Genome Atlas (TCGA)-Lung Adenocarcinoma dataset to assess the concordance between CD160 expression and clinical outcomes in EVs and lung adenocarcinoma tissues. Analysis showed that CD160 expression in lung adenocarcinoma tissues was significantly lower than that in non-cancerous tissues. Figure 7 C). Notably, patients with high baseline tissue CD160 levels (above 75%) showed a better prognosis than patients with low baseline tissue CD160 levels (below 25%). Figure 7 D) Similar to lung adenocarcinoma patients with higher baseline EV-CD160 levels, who respond better to immunotherapy combined with chemotherapy.

[0087] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered illustrative and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the scope of the invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

[0088] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This description is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. The use of a reagent for detecting the expression level of CD160 derived from plasma extracellular vesicles in the preparation of a product for predicting the efficacy of combined immunotherapy and chemotherapy for lung cancer; wherein the CD160 expression level is at the RNA level, the chemotherapy is pemetrexed and platinum-based chemotherapy; the immunotherapy is PD-1 inhibitor therapy, wherein the PD-1 inhibitor is pembrolizumab or camrelizumab, and the lung cancer is lung adenocarcinoma.

2. The use according to claim 1, characterized in that, The detection reagents include reagents for high-throughput sequencing of plasma extracellular vesicle transcriptomes and reagents for RT-qPCR.

3. The use according to claim 2, characterized in that, The reagents used for RT-qPCR include primers.

4. The use according to claim 3, characterized in that, The primers include CD160 primers as shown in SEQ ID NO: 1-2.

5. The use according to claim 4, characterized in that, The primers further include β-actin internal reference primers as shown in SEQ ID NO: 3-4.

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