CN114875155A - Gene mutation and application thereof in diagnosis of pancreatic and biliary tract cancer - Google Patents

Abstract

The invention belongs to the field of biological medicine, and particularly relates to a group of gene mutations and application thereof in diagnosis of pancreatic and biliary tract cancer. Specifically, the invention provides a group of gene mutations for detecting pancreatic and biliary tract cancer, wherein the gene mutations comprise one or more of AKT1, KRAS, APC, NRAS, ARID1A, PIK3CA, AXIN1, PPP2R1A, BAP1, PTEN, BRAF, SMAD4, CDKN2A, TERT, TP53, EGFR, FBXW7, FGFR2, HRAS, IDH1 and IDH 2.

Description

Gene mutation and application thereof in diagnosis of pancreatic and biliary tract cancer

Technical Field

The invention belongs to the field of biological medicine, and particularly relates to a group of gene mutations and application thereof in diagnosis of pancreatic and biliary tract cancer.

Background

Pancreatic biliary cancer (Pancreatobiliary cancer) includes biliary cancer (BTC) and pancreatic cancer (pancreatic cancer).

Biliary tract cancers originate in biliary epithelial cells at different anatomical locations, such as intrahepatic, extrahepatic and gallbladder, or may originate directly from hepatocytes (hepatocytes). Biliary tract cancers include biliary duct cancer (CCA), gallbladder cancer (GBC) and ampulla cancer (amplary cancer). Cholangiocarcinoma is the second most common primary liver cancer, accounting for approximately 3% of all gastrointestinal tumors. Cholangiocarcinoma is further classified as Intrahepatic (iCCA), perihepatic (pCCA) or distal (dCCA) cholangiocarcinoma. Although biliary tract cancer is relatively uncommon worldwide, its incidence is rapidly increasing worldwide in recent years, with the highest incidence in east and south asia (e.g., thailand and china) and parts of south america. Risk factors for biliary tract cancer include Primary Sclerosing Cholangitis (PSC), liver fluke, fibropolycystic liver disease (e.g., cholangioadenoma and cholangiopapillomatosis), biliary and gall bladder stones, viral hepatitis, and chemical carcinogen exposure, among others. Pancreatic cancer is one of the cancers with the highest global mortality, and is the seventh leading cause of cancer death worldwide due to poor prognosis, specifically including head cancer, tail cancer, and diffuse cancer.

Diagnosis of pancreatic biliary cancer is challenging. Most patients have been diagnosed in the late stage because early symptoms are nonspecific or even asymptomatic. Advanced diagnosis, at least, can lead to poor prognosis in BTC patients, with a 5-year overall survival rate of below 20%. Patients with biliary stenosis and jaundice may have biliary, gall bladder or pancreatic cancer, and it is difficult to distinguish between malignant and benign strictures (iatrogenic bile duct injury, Primary Sclerosing Cholangitis (PSC) and choledocholithiasis). Cholangiopancreaticocarcinoma is routinely diagnosed in a number of ways including clinical examination, imaging by imaging, endoscopic procedures, pathological evaluation, and biochemical examination (e.g., CA 19-9). However, these methods have some limitations, such as that CA19-9 is not suitable for Lewis antigen-negative patients (7% of the general population), and the sensitivity and specificity of the above methods are not satisfactory. It is reported that about 15-24% of patients who have undergone surgery for malignant biliary stricture are ultimately diagnosed as benign.

Therefore, there is an urgent need to develop a better detection method for diagnosing pancreatic and biliary tract cancer with high sensitivity, specificity and safety.

Disclosure of Invention

Patients with pancreaticobiliary cancer often have a poor clinical prognosis with an overall 5-year survival rate of less than 20%. This is mainly related to late diagnosis. In addition, the method can accurately distinguish malignant cancers from benign diseases before operation, and can avoid unnecessary trauma. Therefore, there is an urgent need to develop a detection method for diagnosing malignant pancreaticobiliary cancer, which has high sensitivity, strong specificity, and high safety.

In order to achieve the technical purpose, the invention provides the following technical scheme:

in a first aspect, the invention provides a set of genetic mutations for detecting pancreatic biliary cancer, the genetic mutations including one or more of AKT1, KRAS, APC, NRAS, ARID1A, PIK3CA, AXIN1, PPP2R1A, BAP1, PTEN, BRAF, SMAD4, CDKN2A, TERT, TP53, EGFR, FBXW7, FGFR2, HRAS, IDH1, IDH 2.

More specifically, as demonstrated in the specific examples of the present invention, diagnosis of pancreatic biliary tract cancer based on the presence of a mutation in at least one of the following genes can more sensitively distinguish patients with pancreatic biliary tract cancer from non-cancer patients: AKT1, KRAS, APC, NRAS, ARID1A, PIK3CA, AXIN1, PPP2R1A, BAP1, PTEN, BRAF, SMAD4, CDKN2A, TERT, TP53, EGFR, FBXW7, FGFR2, HRAS, IDH1, IDH 2.

The term "pancreatic biliary tract cancer" according to the present invention may also be referred to as Pancreatobiliary tract cancer (Pancreatobiliary tract cancer), which includes biliary tract cancer (BTC, also referred to as bile duct cancer) and pancreatic cancer (pancreatic cancer); the biliary duct cancer includes biliary duct cancer (CCA), gallbladder cancer (GBC), and ampulla cancer (amplary cancer); the pancreatic cancer comprises head cancer, tail cancer and diffuse cancer.

Preferably, the non-cancerous patient in the present invention is a subject that has not been diagnosed with cancer for at least 12 months, and optionally, may have symptoms of the following non-malignant tumors: gallstone, biliary obstruction, biliary stricture, pancreatic occupation, pancreatic cyst, pancreatitis.

In another aspect, the invention provides an application of the reagent for detecting the gene mutation in the preparation of a product for diagnosing pancreatic and biliary tract cancer.

More specifically, the diagnosis of pancreatic biliary tract cancer refers to distinguishing between patients with malignant tumor (pancreatic biliary tract cancer) and patients without malignant tumor, which may suffer from benign diseases such as gallstone, biliary obstruction, biliary stenosis, pancreatic occupancy, pancreatic cyst, pancreatitis, and the like.

Preferably, the product comprises a kit, a chip, a diagnostic system, etc.

In an alternative embodiment, the reagent for detecting gene mutation comprises a reagent used in any of the following methods: TaqMan probe method, sequencing method, chip method, flight mass spectrometer (MALDI-TOFMS) detection, restriction fragment length polymorphism (PCR-RFLP), single strand conformation polymorphism (PCR-SSCP), allele-specific PCR (AS-PCR), SNaPshot method, SNPlex typing system, SNPStream analysis system, Sequenom typing system, Denaturing High Performance Liquid Chromatography (DHPLC), Denaturing Gradient Gel Electrophoresis (DGGE).

Preferably, the gene mutation of the present invention is found by detecting a sample from a subject.

Preferably, the sample is taken from the biliary tract.

Specifically, the sample includes bile, exfoliated cells in biliary tract, and tissue sample.

More specifically, the exfoliated cell, tissue sample in the biliary tract may be a sample taken by ERCP biopsy/brush.

The term "biliary tract" is a generic term for the ducts that carry bile from the liver to the duodenum. It is divided into two parts, intrahepatic and extrahepatic bile ducts.

The term "Endoscopic Retrograde Cholangiopancreatography (ERCP)" refers to a technique in which a duodenoscope is inserted into the descending part of the duodenum, the papilla of the duodenum is found, a contrast catheter is inserted into the opening of the papilla from a biopsy channel, and a contrast medium is injected into the opening of the duodenum, followed by x-ray radiography to visualize the cholangiopancreatography.

Preferably, the bile collection method includes, but is not limited to, duodenal drainage, cholecystectomy, and direct surgical collection.

More preferably, the sample needs to be subjected to a treatment comprising a step of DNA extraction.

Preferably, the treatment may further comprise steps of purification, quality inspection, and the like.

Preferably, the subject comprises a patient suspected of having pancreatic biliary cancer.

Preferably, the gene mutation of the invention can also be used together with other types of markers, wherein the other types of markers comprise an expression level marker and a methylation marker.

Preferably, the methylation markers include any one or more of: 3-OST-2, EBF, RASSF, APC, EYA, RUNX, BNIP, FHIT, SALL, CCND, FOXE, SEPT, CD1, GSTP, SFRP, CDH, hMLH, SLIT, CDH, KCNK, SLIT, CDKN2, MGMT, SOX, CDKN2, NDRG, TERT, CDO, NPTX, TFPI, CLEC, NXPH, TIMP, CNRIP, PENK, TMEFF (HPP), DAPK, PRKCB VIM, DCLK, PTCHD, ZSCAN, DLC, RAR β 2 (RARB).

Preferably, the methylation markers include one or more of SOX17, 3-OST-2, NXPH1, SEPT9, and TERT.

Preferably, the methylation marker can be detected by methods known in the art, such as in particular: pyrosequencing, bisulfite conversion sequencing, methylation chip methods, qPCR methods, digital PCR methods, second generation sequencing, third generation sequencing, whole genome methylation sequencing, DNA enrichment detection methods, simplified bisulfite sequencing techniques, HPLC methods, MassArray, methylation specific PCR, or combinations thereof.

In another aspect, the present invention also provides a diagnostic system for diagnosing pancreatic and biliary tract cancer, which reports a calculation means for obtaining a diagnostic conclusion based on whether a subject has at least one of the genetic mutations provided in the present invention.

More specifically, the diagnosis criteria is that patients with pancreaticobiliary cancer are diagnosed with at least one mutation provided by the present invention. More specifically, patients without any of the genetic mutations described in the present invention are non-cancer patients (who may have other non-malignant neoplastic diseases).

Preferably, the system comprises:

(1) a sample collection and processing device for performing the steps of: collecting a sample from a subject, processing the sample;

(2) a nucleic acid sequence determination device;

(3) a computing device for obtaining a diagnostic conclusion based on whether the subject has at least one of the genetic mutations provided herein.

Preferably, the sample comprises bile, exfoliated cells in the biliary tract, a tissue sample.

Preferably, the treatment comprises the steps of purification, quality inspection, DNA extraction, and the like.

Preferably, the nucleic acid sequence determination device can detect whether the subject has any of the gene mutations provided by the present invention by implementing any one of the following methods: TaqMan probe method, sequencing method, chip method, flight mass spectrometer (MALDI-TOFMS) detection, restriction fragment length polymorphism (PCR-RFLP), single strand conformation polymorphism (PCR-SSCP), allele-specific PCR (AS-PCR), SNaPshot method, SNPlex typing system, SNPStream analysis system, Sequenom typing system, Denaturing High Performance Liquid Chromatography (DHPLC), Denaturing Gradient Gel Electrophoresis (DGGE).

Preferably, a methylation detection device can also be included in the system for detecting a methylation marker.

In another aspect, the present invention also provides a method for diagnosing pancreatic biliary tract cancer, which determines whether a subject has pancreatic biliary tract cancer based on whether the subject has at least one of the genetic mutations provided herein.

Preferably, the methods provided by the present invention can also be used in combination with other diagnostic methods, such as: abdominal ultrasound examination, clinical examination, endoscopic surgery, biochemical testing, radiological imaging (CT, magnetic resonance imaging MRI, magnetic resonance pancreaticocholangiography MRCP), etc.

The invention has the following beneficial effects:

the technical scheme provided by the invention can obtain bile as a sample in a non-invasive sampling mode for detection, and has the characteristics of high specificity and high sensitivity; the disease is accurately diagnosed in an early stage of the disease, and the patient can be treated in a targeted manner in advance, so that the cure possibility is improved, and the survival period is prolonged; meanwhile, unnecessary surgical trauma is avoided for non-cancer patients.

Drawings

Figure 1 is a flow chart of subject inclusion criteria and study design of the present invention.

FIG. 2 is a statistical chart of the basic information of a subject according to the present invention.

FIG. 3 is a validation of diagnostic efficacy of each diagnostic model in different data sets.

Figure 4 is a test result statistic for subjects in the training cohort and the validation cohort.

FIG. 5 is a validation of the diagnostic efficacy of methylation markers.

FIG. 6 is a comparison of the diagnostic efficacy of each diagnostic model in different datasets with that of CA 19-9.

FIG. 7 is a statistical result of the consistency of the gene mutation detection results in the brushing sample and the biopsy sample.

Detailed Description

The present invention will be further described with reference to the following examples, which are intended to be illustrative only and not to be limiting of the invention in any way, and any person skilled in the art can modify the present invention by applying the teachings disclosed above and applying them to equivalent embodiments with equivalent modifications. Any simple modification or equivalent changes made to the following embodiments according to the technical essence of the present invention, without departing from the technical spirit of the present invention, fall within the scope of the present invention.

Example 1 screening, identification and verification of mutant and methylated genes

1. Research population and experimental design

The study population is selected from patients with pancreatic and biliary diseases accepted by five hospitals from 11 months in 2018 to 10 months in 2020, and the total number is 338. The five hospitals are respectively: tumor hospital of the Chinese medical academy of sciences, central hospital of Sichuan Dazhou city, subsidiary Beijing Chaoyang hospital of the university of capital medical science, eastern hospital of the Beijing traditional Chinese medicine university, and civil hospital of the valley city of the Xiangyang city of Hebei province. 79 patients with various causes such as non-biliary tract cancer or bile DNA deficiency were excluded, and 259 patients were finally selected for molecular testing.

Of these 259 patients, 209 patients diagnosed as either malignant or benign were selected as the training group (n-104) and the validation group (n-105), with 116 cases of malignant tumors and 93 cases of benign disease. The malignant tumor was confirmed as a biliary tract malignant tumor (pancreatic bile duct cancer) after diagnosis by ERCP (retrograde cholangiopancreatography) biopsy/brush (ERCP-associated biopies/brushings). The benign disease patients included 78 patients with cholelithiasis, and the 78 patients had no malignant lesions in the surgically removed specimens, but had chronic cholangitis; in 15 cases, after more than 12 months of follow-up visit, gallstones are removed by ERCP, and no malignant lesions are found.

In addition, considering that some patients with Biliary Tract Cancer (BTC) have low sensitivity to ERCP pathology, 50 patients with ERCP biopsy/brush negative or suspicious diagnostic results were classified as independent test cohorts. In the test cohort, 40 malignant patients were confirmed during the follow-up by pathology assessment (biopsy/brush from surgically excised specimens, percutaneous needle or ERCP, n ═ 21), radiographic (n ═ 2) or clinical criteria (n ═ 17), while 10 benign diseases were confirmed by surgical pathology (n ═ 4), radiographic (n ═ 1) or no malignant tumors found at least 12 months after follow-up (n ═ 5).

Patient enrollment and study design is shown in figure 1. The study was approved by the ethical review committee of the five hospitals (ID: NCC2018 JJJ-001).

2. Sample preparation

Bile samples were obtained from all patients, 181 patients before treatment by ERCP and 78 patients with cholelithiasis during cholecystectomy.

The resulting bile samples were centrifuged at 12000 rpm for 10 minutes and the supernatant and particles were separated. DNA was extracted from bile samples using a TIANAMP genomic DNA kit (Tiangen Biotech, Beijing, China). RQ-PCR detection of human GAPDH gene was performed with Taqman probe to determine DNA quality.

Paired biopsies or brush tissues obtained during ERCP of 34 and 9 patients were subjected to NGS (Next-generation high-throughput sequencing technology) detection sequencing, with the exception of bile samples, and genomic DNA was extracted using the QIAamp DNA Mini Kit (Qiagen, usa).

The sera of most patients were further tested for CA19-9 by electrochemiluminescence (electrochemiluminescence) technique using Roche E601 system (Roche Diagnostics, Switzerland).

3. Analysis of Gene mutation and Gene methylation Using BileScreen

TABLE 1 mutated genes discovered by sequencing of the invention and genes with methylation modifications

400ng of DNA was disrupted by ultrasonication, and then subjected to end repair. Then, the DNA fragment was digested with the methylation-sensitive restriction enzyme HHAI (R0139S, New England Biolabs, MA, USA) and subjected to amplicon-based targeted capture technology-based targeted gene sequencing by Mutation Capsule technology (see document Qu, C.et al.Detection of early-stage macromolecular in apoptosis HBsAg-serositive peptides by liquid biology. proceedings of the National Academy of science of the United States America.116,6308-6312 (2019)).

Briefly, fragments of restriction endonuclease HHA i digested DNA were treated with the KAPA Hyper Prep kit (switzerland, roche) to obtain a sequencing library by a series of steps including end repair, a tail addition with adenylate a, custom linker ligation, and three rounds of PCR amplification (first round using common sequence primers and last two rounds using primers containing target specific and common sequences). 23 mutant genes and 44 genes with methylation modifications were sequenced (Table 1).

4. Data processing and mutation/methylation detection

Gene sequencing was performed using a digital (UID) high throughput sequencing platform. Briefly, before PCR amplification, a unique UID label is added to each fragment in a sample, then library amplification is carried out, after sequencing is completed, by comparing sequences of the fragments, repeated fragments marked by the same UID are combined, natural repetition of different UID marks is kept, and the ending coordinate of reads is calculated according to the starting coordinate and the cigar information; cutting a reference sequence corresponding to reads from a reference genome according to the start coordinate and the end coordinate of the reads; the reads were re-aligned to the hg19 genome, respectively, to obtain the start and end positions of the mutation. The valid UID (Effective UID) family is defined as a UID family (UID) that contains at least two reads and at least 80% of the reads are of the same type. The frequency of each mutation was calculated by dividing the number of alternative EUID families by the sum of the alternative and reference families. We further examined the mutations manually (in IGV) and annotated the candidate Variant genes with VEP (Ensembl Variant Effect predictor).

The mutations detected had at least four EUID families. For the hot-spot mutated oncogenes including KRAS (G12, G13, Q61 and a146), the limit of detection (LOD) was set to 0.5%. While for other mutant genes, including common non-hotspot cancer suppressor genes, such as TP53, Smad4, and rare mutations, the LOD was set at 1% in order to reduce the occurrence of false positives. Because there are no matching leukocytes to exclude germline mutations, the mutations detected in the sample are screened against the germline and somatic mutation databases to determine the highest likelihood of germline mutation. Mutations found in the germline mutation database (1000AF, ESP6500 AA/EA, Exac AF) with a frequency of 0.1% or more were germline mutations and were first excluded. The passed mutations were further screened, and for those genes with higher frequency (. gtoreq.40%), if they appeared in the COSMIC database in fewer than 10 samples, they were likely germline mutations and were therefore further excluded.

In methylation analysis, clusters with HHAI restriction sites at the ends are unmethylated sequences, and molecules with at least one HHAI restriction site and not at the end are methylated sequences. The methylation ratio per base is the ratio of the number of methylated molecules to the sum of the number of methylated and unmethylated molecules.

5. Construction of BileScreen diagnostic model

Malignant tumors appear when AKT1, KRAS, APC, NRAS, ARID1A, PIK3CA, AXIN1, PPP2R1A, BAP1, PTEN, BRAF, SMAD4, CDKN2A, TERT, TP53, EGFR, FBXW7, FGFR2, HRAS, IDH1 and IDH2 are mutated (as shown in the following table 2).

TABLE 2 detection results of mutations

Among the 44 methylation modifying genes, 5 methylation modifying genes SOX17, 3-OST-2, NXPH1, SEPT9 and TERT are screened out by adopting a stepwise penalty Logistic regression method by using a Training set (Training set) for constructing a diagnosis model. Punishment Logistic regression is carried out on the training queue by using the 5 methylation modifying gene markers, and the performance of the model is evaluated by adopting leave-one-out cross validation and through the area under the working characteristic curve (ROC curve), the sensitivity and the specificity index of a subject. The cut-off for methylation was determined from the Youden index of ROC analysis.

In the BileScreen model, when mutation and methylation are integrated, the positive result is positive if one of the two is positive. The performance of the BileScreen model was further evaluated in a separate validation queue and test queue.

In addition, since in the training cohort and the Validation cohort (Validation set), the benign cases selected are mostly young women with gallstones, there is a certain tendency in the age and sex of the malignant and benign patients. To exclude the effect of this artificial sample selection on the diagnostic prediction, 52 age and gender matched malignant patients and 52 benign patients were assigned to the training cohort. Thus, the age and gender distribution in the validation cohort was not uniform (fig. 2). However, all mutations and methylation were not clearly correlated with age, sex (correlation coefficient/correlation coefficient <0.5, or Wilcoxon test P > 0.05).

6. Statistical analysis

The role of individual mutant genes or methylation-modified genes in predicting disease states was evaluated using ROC analysis (pROC package) and the Wilcoxon test. Genetic markers for diagnostic models were screened using a penalized Logistic regression method (glmnet package). In the training cohort, the ROC curve is input as raw score and the Youden index alone is used to determine the optimal cut-off point for methylation. In addition, ROC analysis is used to compare the performance of different methods with a "0 or 1" value determined by the corresponding cut-off point as input. Sensitivity and specificity were calculated using a standard 2X 2 cascade (continingness tables). All R-package correlation analyses were based on R software (v.3.6.3).

7. Results

1) BileScreen model establishment based on gene mutation and methylation modification

104 patients in the training cohort were sequenced and analyzed for data, including 52 ERCP-pathologically confirmed patients with malignant tumors and 52 benign patients, one of the 52 patients with surgical pathology indicating no cancerous lesions in the tissue region and another with bile duct stones, followed at least 12 months for a clinical profile of benign disease as summarized in fig. 2.

The DNA of the bile samples was analyzed using Mutation Capsule technology (Mutation Capsule technology) and 23 mutant genes and 44 methylation-modifying genes were detected. The most common mutant genes in cancer are TP53 (50%) and KRAS (46%). Both CTNNB1 and GNAS mutations were detected in cancer and benign disease patients, and therefore the genes were not significantly correlated with malignant status, with CTNNB1 and GN AS mutations excluded from the bilesen model.

TABLE 3 detection accuracy of each data set

Genetic mutations are used to distinguish patients with pancreaticobiliary cancer from non-cancerous (benign disease) subjects:

mutations of AKT1, KRAS, APC, NRAS, ARID1A, PIK3CA, AXIN1, PPP2R1A, BAP1, PTEN, BRAF, SMAD4, CDKN2A, TERT, TP53, EGFR, FBXW7, FGFR2, HRAS, IDH1, IDH2, wherein at least one mutation detected is considered positive; the Sensitivity (Sensitivity) was 81%, Specificity (Specificity) was 100%, and AUC was 0.90 when pancreatic cholangiocarcinoma patients and non-cancer subjects were distinguished by mutation alone (table 3, fig. 3A).

Methylation markers were used to distinguish patients with pancreaticobiliary cancer from non-cancerous (benign disease) subjects:

for methylation markers, diagnostic models were constructed by stepwise penalizing Logistic regression methods, selecting 5 markers, SOX17, 3-OST-2, NXPH1, SEPT9, and TERT (fig. 3, table 4). By leave-one-out method, patients with pancreaticobiliary cancer could be well identified from non-cancer cases only by the methylation markers with sensitivity of 88%, specificity of 98%, and AUC of 0.93 (table 3, fig. 3). The cut-off value for methylation scores was 0.422, resulting in the maximum Youden index (fig. 5).

TABLE 4 construction of diagnostic models based on 5 methylation markers

Finally, when the gene mutation and methylation marker are combined, i.e., bilesescreen:

positivity was defined as a positive in either case with further increased performance, 94% sensitivity, 98% specificity, and 0.96 AUC (table 3, fig. 3). BileScreen was validated against 105 additional cases (validation cohort), 64 of which were malignant and 41 of which were benign (FIG. 4). BileScreen accurately predicted the disease status of 59 cases of malignancy and 40 cases of non-cancer. BileScreen showed 92% sensitivity and 98% specificity in the validation cohort, with an AUC of 0.95 (Table 3, FIG. 3). If only gene mutation is used, the sensitivity and specificity are 78% and 100%, respectively. The sensitivity and specificity of the methylation marker only assay were 81% and 98%, respectively (table 3).

Use of the BileScreen model for the detection of suspected malignancies

We further performed bilesence validation on 50 patients with ambiguous ERCP (Test cohort) results, and therefore 50 patients had ERCP diagnosis as "suspicious malignant tumor" or "unable to exclude cancer". These cases were followed up for at least 12 months, with 40 out of 50 cases found to be malignant. The remaining 10 cases found no cancer during the follow-up period and were diagnosed as benign. Of the 40 malignant lesions, 36 were positive, and of the 10 benign lesions, 2 were positive, with a sensitivity of 90% and a specificity of 80% (FIG. 3). For those patients who could not be diagnosed by ERCP, the bileseren results were significantly correlated with clinical results (P <0.001, continuos correction chi-square test).

Mutation or methylation alone distinguished cancer from benign patients with sensitivity of 75% and 80%, specificity of 90% and 80%, respectively, and AUC of 0.83 and 0.8, respectively (table 3, fig. 3).

Comparison of the results of detection of CA19-9 with the BileScreen model in each group

In the training cohort and validation cohort, we screened 85 and 74 patients, respectively, for whom serum CA19-9 data were available (FIG. 2, Table 5), and a direct comparison was made between serum CA19-9 and BileScreen. The AUC for serum CA19-9 to identify benign and malignant in 2 cohorts was 0.78 and 0.81, respectively (FIG. 6), with a cutoff of 27U/mL or more, the sensitivity of serum CA19-9 was 88% and 91%, respectively, and the specificity was 67% and 70%, respectively (Table 5).

TABLE 5, validation results of each model and CA19-9 in different datasets

In contrast, the sensitivity of BileScreen was 93% and 94%, respectively, and the specificity 98% and 96%, respectively. Sensitivity and specificity of CA19-9 were 90% and 68%, respectively, which were less than 93% and 97% of BileScreen throughout the training and validation cohort. Therefore, BileScreen is superior to the serum CA19-9 in detecting pancreatic and biliary tract cancer, especially in detecting specificity.

In addition, the results of the 38 patients' serum CA19-9 in the test cohort are shown in FIG. 6A, with very low specificity (14%) for serum CA19-9, 0.51 AUC, and 84% sensitivity (Table 4, FIG. 6). CA19-9 is less accurate in predicting patients with ERCP diagnoses as suspicious malignancies compared to the training and validation cohort. In contrast, the sensitivity and specificity of BileScreen in this population were 87% and 86%, respectively.

4. Comparison of Gene mutation results in bile and ERCP biopsy/swipe samples

In the test cohort, 34 patients obtained biopsy samples by ERCP and 9 patients obtained swipe samples. We performed head-to-head comparison studies on gene and tissue samples. Of the 43 cases, 70 mutations were present in both sample types, 5 mutations were detected only in bile (brush samples) and 9 were detected only in tissue (biopsy samples) (fig. 7). Thus, 93% (70/75) mutations in bile could also be detected in tissues, others were found only in bile, and 89% (70/79) tissue-derived mutations could be detected in bile. In addition, 36 of the 43 samples detected mutations in at least one type of sample, of which 34 (94%) detected at least one common mutation between the two sample types. Thus, the patient's mutational status as measured by bile was 95% matched to the mutational status as measured by tissue (41/43).

Claims (10)

1. A set of gene mutations for detecting pancreatic biliary cancer, the gene mutations comprising one or more of AKT1, KRAS, APC, NRAS, ARID1A, PIK3CA, AXIN1, PPP2R1A, BAP1, PTEN, BRAF, SMAD4, CDKN2A, TERT, TP53, EGFR, FBXW7, FGFR2, HRAS, IDH1, IDH 2;

preferably, the genetic mutation consists of AKT1, KRAS, APC, NRAS, ARID1A, PIK3CA, AXIN1, PPP2R1A, BAP1, PTEN, BRAF, SMAD4, CDKN2A, TERT, TP53, EGFR, FBXW7, FGFR2, HRAS, IDH1, IDH 2.

2. Use of a reagent for detecting mutation of the gene according to claim 1 in the preparation of a product for diagnosing pancreatic and biliary tract cancer.

3. The use of claim 2, wherein the pancreatic biliary tract cancer comprises biliary tract cancer and pancreatic cancer;

preferably, the cholangiocarcinoma comprises cholangiocarcinoma, gallbladder carcinoma, and ampulla;

preferably, the pancreatic cancer comprises head cancer, tail cancer, diffuse cancer.

4. The use according to claim 2, wherein the reagent for detecting gene mutation comprises a reagent used in any one or more of the following methods: TaqMan probe method, sequencing method, chip method, flight mass spectrometer detection, restriction fragment length polymorphism method, single-strand conformation polymorphism method, allele specific PCR, SNaPshot method, SNPlex typing system, SNPStream analysis system, Sequenom typing system, denaturing high performance liquid chromatography, denaturing gradient gel electrophoresis method.

5. The use of claim 2, wherein the genetic mutation is detected in a sample from the subject;

preferably, the sample is taken from the biliary tract;

specifically, the sample comprises bile, exfoliated cells in biliary tracts, and a tissue sample;

more specifically, the exfoliated cell, tissue sample in the biliary tract is a sample taken from an ERCP biopsy/brush.

6. The use of claim 2, wherein the genetic mutation of claim 1 is further used in combination with a methylation marker comprising one or more of SOX17, 3-OST-2, NXPH1, SEPT9, and TERT;

preferably, the methylation marker further comprises any one or more of EBF3, RASSF1, APC, EYA4, RUNX3, BNIP3, FHIT, SALL3, CCND2, FOXE1, CD1D, GSTP1, SFRP1, CDH1, hMLH1, SLIT2, CDH13, KCNK12, SLIT3, CDKN2A, MGMT, CDKN2B, NDRG4, CDO1, NPTX2, TFPI2, CLEC11, TIMP3, CNRIP1, PENK, TMEFF2, DAPK1, PRKCB, VIM, DCLK1, PTCHD2, ZSCAN18, DLC1, RAR β 2.

7. A diagnostic system for diagnosing pancreatic biliary tract cancer, or a use thereof, the system reporting a computing device that obtains a diagnostic conclusion based on whether a subject has at least one of the genetic mutations of claim 1.

8. The diagnostic system of claim 7, the system comprising:

(1) a sample collection and processing device for performing the steps of: collecting a sample from a subject, processing the sample;

(2) a nucleic acid sequence determination device;

(3) a computing device for obtaining a diagnostic conclusion based on whether a subject has at least one of the genetic mutations of claim 1.

9. The diagnostic system of claim 8, wherein the pancreatic biliary cancer comprises biliary cancer and pancreatic cancer;

preferably, the cholangiocarcinoma comprises cholangiocarcinoma, gallbladder carcinoma, and ampulla;

preferably, the pancreatic cancer comprises head cancer, tail cancer, diffuse cancer;

preferably, the detection is performed on a sample derived from a subject;

preferably, the sample comprises bile, cells, tissue, peripheral blood, serum, plasma, urine, saliva, tears;

preferably, the sample comprises bile or cells, tissues taken from the biliary tract;

more preferably, the exfoliated cells, tissue sample in the biliary tract is a sample taken from an ERCP biopsy/brush;

preferably, the nucleic acid sequence determination apparatus can detect whether the subject has at least one of the gene mutations of claim 1 by implementing any one of the following methods: TaqMan probe method, sequencing method, chip method, flight mass spectrometer detection, restriction fragment length polymorphism method, single-strand conformation polymorphism method, allele specific PCR, SNaPshot method, SNPlex typing system, SNPStream analysis system, Sequenom typing system, denaturing high performance liquid chromatography, denaturing gradient gel electrophoresis method.

10. The diagnostic system of claim 8 or 9, further comprising a methylation detection means for detecting a methylation marker;

the methylation markers include one or more of SOX17, 3-OST-2, NXPH1, SEPT9, and TERT;

preferably, the methylation marker further comprises any one or more of EBF3, RASSF1, APC, EYA4, RUNX3, BNIP3, FHIT, SALL3, CCND2, FOXE1, CD1D, GSTP1, SFRP1, CDH1, hMLH1, SLIT2, CDH13, KCNK12, SLIT3, CDKN2A, MGMT, CDKN2B, NDRG4, CDO1, NPTX2, TFPI2, CLEC11, TIMP3, CNRIP1, PENK, TMEFF2, DAPK1, PRKCB, VIM, DCLK1, PTCHD2, ZSCAN18, DLC1, RAR β 2.

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