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

A group of gene mutations and their application in the diagnosis of pancreaticobiliary tract cancer

technical field

The invention belongs to the field of biomedicine, and particularly relates to a group of gene mutations and its application in diagnosing pancreaticobiliary tract cancer.

Background technique

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

Biliary tract cancers arise from bile duct epithelial cells in different anatomical locations, such as intrahepatic, extrahepatic and gallbladder, or may originate directly from hepatocytes. Biliary tract cancer includes cholangiocarcinoma (CCA), gallbladder cancer (GBC) and ampullary cancer. Cholangiocarcinoma is the second most common primary liver cancer, accounting for approximately 3% of all gastrointestinal tumors. Cholangiocarcinomas are subdivided into intrahepatic (iCCA), perihilar (pCCA), or distal (dCCA) cholangiocarcinomas. Although biliary tract cancer is relatively uncommon worldwide, its global incidence has increased rapidly in recent years, with the highest incidence in East and South Asia (eg, Thailand and China) and parts of South America. Risk factors for biliary tract cancer include primary sclerosing cholangitis (PSC), liver flukes, fibrous polycystic liver disease (eg, cholangio adenoma and biliary papillomatosis), biliary and gallbladder stones, viral hepatitis, and exposure to chemical carcinogens Wait. Pancreatic cancer is one of the most lethal cancers in the world. Due to its poor prognosis, it is the seventh leading cause of cancer death in the world, including pancreatic head cancer, pancreatic tail cancer, and diffuse cancer.

Diagnosis of pancreaticobiliary tract cancer is challenging. Because early symptoms are nonspecific or even asymptomatic, most patients are diagnosed at an advanced stage. Late diagnosis will at least lead to poor prognosis in BTC patients, with a 5-year overall survival rate below 20%. Patients with bile duct strictures and jaundice may have cholangiocarcinoma, gallbladder cancer, or pancreatic cancer, while distinguishing malignant from benign strictures (iatrogenic bile duct injury, primary sclerosing cholangitis (PSC), and choledocholithiasis (choledocholithiasis)) is very difficult. Routinely, cholangiopancreatic cancer is diagnosed by a combination of modalities, including clinical examination, imaging imaging, endoscopic procedures, pathological evaluation, and biochemical examinations (eg, CA19-9). However, these methods have some limitations, such as 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 has been reported that approximately 15-24% of patients undergoing surgery for malignant bile duct strictures are ultimately diagnosed as benign.

Therefore, there is an urgent need to develop a better detection method for the diagnosis of pancreaticobiliary tract cancer with high sensitivity, specificity and safety.

SUMMARY OF THE INVENTION

Patients with pancreaticocholangiocarcinoma usually have a poor clinical prognosis, with a 5-year overall survival rate of less than 20%. This is mainly related to late diagnosis. In addition, accurate preoperative distinction between malignant cancer and benign disease can avoid unnecessary trauma. Therefore, there is an urgent need to develop a detection method with high sensitivity, specificity and safety for diagnosing malignant cholangiopancreatic carcinoma.

For realizing the above technical purpose, the present invention provides the following technical solutions:

In a first aspect, the present invention provides a set of gene mutations for detecting pancreaticobiliary tract cancer, the gene mutations include AKT1, KRAS, APC, NRAS, ARID1A, PIK3CA, AXIN1, PPP2R1A, BAP1, PTEN, BRAF, SMAD4, CDKN2A One or more of , TERT, TP53, EGFR, FBXW7, FGFR2, HRAS, IDH1, IDH2.

More specifically, as verified in the specific embodiments of the present invention, the presence of mutations in at least one of the following genes is used as a criterion for diagnosing pancreaticobiliary tract cancer, which can more sensitively distinguish patients with pancreaticobiliary 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, IDH2.

The term "pancreatobiliary tract cancer" described in the present invention may also be referred to as pancreatobiliary tractcance, which includes bile tract cancer (BTC, also known as cholangiocarcinoma) and pancreatic cancer (pancreatic cancer); the cholangiocarcinoma Including bile duct cancer (cholangiocarcinoma, CCA), gallbladder cancer (gallbladder cancer, GBC) and ampullary cancer (ampullary cancer); the pancreatic cancer includes pancreatic head cancer, pancreatic tail cancer, diffuse cancer.

Preferably, the non-cancer patient in the present invention is a subject who has not been diagnosed with cancer for at least 12 months. Optionally, the non-cancer patient may have the following symptoms of non-malignant tumors: gallstones, biliary tract Obstruction, biliary stricture, pancreatic mass, pancreatic cyst, pancreatitis.

In another aspect, the present invention provides the application of the reagent for detecting the aforementioned gene mutation in the preparation of a product for diagnosing pancreaticobiliary tract cancer.

More specifically, the diagnosis of pancreaticobiliary tract cancer refers to distinguishing patients with malignant tumors (pancreatobiliary tract cancer) from patients without malignant tumors, and the patients without malignant tumors may have gallstones, biliary obstruction , biliary stricture, pancreatic mass, pancreatic cyst, pancreatitis and other benign diseases.

Preferably, the products include kits, chips, diagnostic systems, and the like.

In an optional embodiment, the reagents for detecting gene mutations include reagents used in any of the following methods: TaqMan probe method, sequencing method, chip method, detection by flight mass spectrometer (MALDI-TOFMS), 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 classification type system, denaturing high performance liquid chromatography (DHPLC), and denaturing gradient gel electrophoresis (DGGE).

Preferably, the genetic mutation of the present invention is found by testing a sample from a subject.

Preferably, the sample is taken from the biliary tract.

Specifically, the samples include bile, exfoliated cells in the biliary tract, and tissue samples.

More specifically, the exfoliated cells and tissue samples in the biliary tract may be samples obtained by ERCP biopsy/brushing.

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

The term "endoscopic retrograde cholangiopancreatography (ERCP)" refers to inserting a duodenoscope into the descending part of the duodenum, finding the duodenal papilla, and inserting a contrast catheter through the biopsy tube to the opening of the papilla , the technique of taking x-rays after injection of contrast agent to show the pancreaticobiliary duct.

Preferably, the bile collection method includes but is not limited to duodenal drainage method, gallbladder puncture method and direct operation method.

More preferably, the sample needs to be processed, and the processing includes the step of DNA extraction.

Preferably, the treatment may further include purification, quality inspection and other steps.

Preferably, the subject includes a patient suspected of pancreaticobiliary tract cancer.

Preferably, the gene mutation of the present invention can also be used simultaneously with other types of markers, and the other types of markers include expression markers and methylation markers.

Preferably, the methylation markers include any one or more of the following: 3-OST-2, EBF3, RASSF1, APC, EYA4, RUNX3, BNIP3, FHIT, SALL3, CCND2, FOXE1, SEPT9, CD1D, GSTP1, SFRP1, CDH1, hMLH1, SLIT2, CDH13, KCNK12, SLIT3, CDKN2A, MGMT, SOX17, CDKN2B, NDRG4, TERT, CDO1, NPTX2, TFPI2, CLEC11, NXPH1, TIMP3, CNRIP1, PENK, TMEFF2(HPP1), DAPK1, PRKCB VIM, DCLK1, PTCHD2, ZSCAN18, DLC1, RARβ2 (RARB).

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

Preferably, the methylation markers can be detected by methods known in the art, specifically for example: pyrosequencing method, bisulfite conversion sequencing method, methylation chip method, qPCR method, digital PCR method , next-generation sequencing, third-generation sequencing, whole-genome methylation sequencing, DNA enrichment detection, simplified bisulfite sequencing, HPLC, MassArray, methylation-specific PCR, or a combination thereof.

In another aspect, the present invention also provides a diagnostic system for diagnosing pancreaticobiliary tract cancer, the system reporting a computing device for obtaining a diagnosis conclusion according to whether a subject has at least one of the gene mutations provided by the present invention.

More specifically, the diagnostic criterion is that a patient with at least one mutation provided by the present invention is diagnosed as pancreatic cholangiocarcinoma. More specifically, patients who do not have any of the gene mutations described in the present invention are non-cancer patients (may suffer from other non-malignant tumors).

Preferably, the system includes:

(1) a sample collection and processing device, which is used to complete the following steps: collecting samples from subjects and processing the samples;

(2) a nucleic acid sequence determination device;

(3) A computing device for obtaining a diagnosis conclusion according to whether the subject has at least one of the gene mutations provided by the present invention.

Preferably, the sample includes bile, exfoliated cells in the biliary tract, tissue samples.

Preferably, the treatment includes purification, quality inspection, DNA extraction and other steps.

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, the system may further include a methylation detection device for detecting methylation markers.

In another aspect, the present invention also provides a method for diagnosing pancreaticobiliary tract cancer, the method judging whether the patient has pancreaticobiliary tract cancer according to whether the subject has at least one of the gene mutations provided by the present invention.

Preferably, the method provided by the present invention can also be used in combination with other diagnostic methods, such as abdominal ultrasonography, clinical examination, endoscopic surgery, biochemical tests, radiological imaging (CT, magnetic resonance imaging MRI, Magnetic Resonance Cholangiopancreatography (MRCP).

The present invention has the following beneficial effects:

The technical solution provided by the present invention can obtain bile as a sample for detection in a non-invasive sampling manner, which has the characteristics of high specificity and high sensitivity; the disease can be accurately diagnosed at an early stage of the disease, and the patient can be targeted for early diagnosis. Sexual treatment improves the possibility of cure and prolongs survival; at the same time, for non-cancer patients, unnecessary surgical trauma is avoided.

Description of drawings

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

Fig. 2 is a statistical chart of basic information of subjects involved in the present invention.

Figure 3 is the validation of the diagnostic performance of each diagnostic model in different datasets.

Figure 4 is the test result statistics of subjects in the training cohort and validation cohort.

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

Figure 6 shows the comparison results of the diagnostic performance of each diagnostic model in different data sets with the diagnostic performance of CA19-9.

Figure 7 is the result statistics of the consistency of the gene mutation detection results in the brushed samples and the biopsy samples.

Detailed ways

The present invention will be further described below in conjunction with the embodiments. The following descriptions are only preferred embodiments of the present invention, and are not intended to limit the present invention in other forms. Changes to equivalent embodiments with equivalent changes. Any simple modifications or equivalent changes made to the following embodiments according to the technical essence of the present invention without departing from the content of the solution of the present invention fall within the protection scope of the present invention.

Example 1. Screening, identification and verification of mutant genes and methylated genes

1. Study population and experimental design

The study population was selected from patients with pancreatic and biliary diseases admitted to the following five hospitals from November 2018 to October 2020, with a total of 338 cases. The five hospitals are: Cancer Hospital of Chinese Academy of Medical Sciences, Dazhou Central Hospital of Sichuan, Beijing Chaoyang Hospital Affiliated to Capital Medical University, Oriental Hospital of Beijing University of Traditional Chinese Medicine, and People's Hospital of Gucheng County, Xiangyang City, Hebei Province. Seventy-nine patients were excluded due to various reasons such as non-biliary tract cancer or insufficient bile DNA, and 259 patients were finally selected for molecular testing.

Of these 259 patients, 209 patients diagnosed as malignant or benign were selected for training (n=104) and validation (n=105), 116 with malignancy and 93 with benign disease. Malignant tumors were diagnosed as malignant tumors of the biliary tract (cancer of the pancreaticobiliary duct) after diagnosis by ERCP-obtained biopsies/brushings. Benign disease patients included 78 patients with cholelithiasis. In the 78 patients, no malignant lesions were found in the surgically resected specimens, but chronic cholangitis was found; 15 patients were followed up for more than 12 months, and no malignant lesions were found in the gallstones removed by ERCP. disease.

In addition, 50 patients with a negative or suspicious diagnosis by ERCP biopsy/brushing were classified into a separate testing cohort, considering that some patients with biliary tract cancer (BTC) have low sensitivity of ERCP pathology. In the testing cohort, 40 patients with malignancies were assessed by pathology (surgically resected specimen, biopsy/brushing obtained by 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 imaging (n=1) or no malignancy after at least 12 months of follow-up (n=5).

Patient enrollment and study design are shown in Figure 1. The study was approved by the ethics review committees of the five hospitals mentioned above (ID: NCC2018JJJ-001).

2. Sample preparation

Bile samples were obtained from all patients, including 181 patients who obtained bile samples by ERCP before receiving treatment, and 78 patients with cholelithiasis who obtained bile samples during gallbladder removal surgery.

The obtained bile sample was centrifuged at 12,000 rpm for 10 minutes, and the supernatant and pellet were separated. DNA was extracted from bile samples using TIANAMP Genomic DNA Kit (Tiangen Biotechnology, Beijing, China). Human GAPDH gene was detected by RQ-PCR with Taqman probes to determine DNA quality.

In addition to bile samples, NGS (Next-generation sequencing technology, next-generation high-throughput sequencing technology) was performed on paired biopsies or brushed tissues obtained during ERCP from 34 and 9 patients, using the QIAampDNA Mini Kit (Qiagen, USA). ) to extract genomic DNA.

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

3. Analysis of gene mutation and gene methylation using BileScreen

Table 1. Mutant genes and genes with methylation modification found by sequencing of the present invention

400ng of DNA was taken, disrupted by ultrasonic wave, and end repaired. Then, the DNA fragments were digested with the methylation-sensitive restriction enzyme HHAI (R0139S, New England Biolabs, MA, USA) and subjected to amplicon-targeted capture technology-based targeting by Mutation Capsule technology. For gene sequencing, please refer to Qu,C.et al.Detection of early-stage hepatocellular carcinoma in asymptomatic HBsAg-seropositive individuals by liquid biopsy.Proceedingsof the National Academy of Sciences of the United States of America.116,6308- 6312 (2019).

Briefly, fragments of restriction enzyme HHA I-digested DNA were processed using the KAPA Hyper Prep kit (Roche, Switzerland) through a series of steps including end repair, adenylate A tailing, custom-made adapter ligation and three rounds of PCR amplification (the first round using common sequence primers and the last two rounds using primers containing target specific and common sequences) to obtain sequencing libraries. 23 mutated genes and 44 genes with methylation modifications were sequenced (Table 1).

4. Data processing and mutation/methylation detection

Gene sequencing was performed using the Digital (UID) high-throughput sequencing platform. Simply put, add a unique UID tag to each fragment in the sample before PCR amplification, and then amplify the library. After the sequencing is completed, the repeat fragments marked with the same UID are merged by comparing the sequences of the fragments, while retaining Different UID markers are naturally repeated, and the end coordinates of the reads are calculated according to the start coordinates and cigar information; according to the start coordinates and end coordinates of the reads, the reference sequence corresponding to the reads is cut out from the reference genome; the reads are respectively and the hg19 genome is re-run again Alignment to obtain the start position and end position of the mutation. Effective UID (EUID, Effective UID) pedigrees are defined as UID pedigrees (Unique Identifier, UID) that contain at least two reads and at least 80% of the read types are the same. The frequency of each mutation was calculated by dividing the number of surrogate EUID families by the sum of the surrogate and reference families. We further manually checked for mutations (in IGV) and annotated candidate variant genes using VEP (Ensembl Variant Effect Predictor).

The detected mutations are in at least four EUID families. For oncogenes with hotspot mutations including KRAS (G12, G13, Q61, and A146), the limit of detection (LOD) was set at 0.5%. For other mutated genes, including common tumor suppressor genes without hotspots such as TP53, Smad4, and rare mutations, the LOD was set to 1% in order to reduce the occurrence of false positives. Since there were no matching leukocytes to rule out germline mutations, mutations detected in samples were screened with germline and somatic mutation databases to identify germline mutations with the highest probability. Mutations with a frequency of ≥ 0.1% found in germline mutation databases (1000AF, ESP6500 AA/EA, Exac AF) were germline mutations and were first excluded. Passing mutations were further screened, and for those genes with higher frequency (≥40%), if they appeared in less than 10 samples in the COSMIC database, they were likely to be germline mutations and were further excluded.

In terms of methylation analysis, clusters with HHA I restriction sites at the ends are unmethylated sequences, and molecules containing at least one HHA I restriction site and not at the ends 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 (see table below). 2).

Table 2. Mutation detection results

Among the 44 methylation-modified genes, five methylation-modified genes SOX17, 3-OST-2, NXPH1, SEPT9, and TERT were screened out by stepwise penalized logistic regression using the training set for constructing the diagnosis. Model. Penalized logistic regression was performed on the training cohort with the above 5 methylation-modified gene markers, and leave-one-out cross-validation was used to evaluate the performance of the model by the area under the receiver operating characteristic curve (ROC curve), sensitivity and specificity indicators . Cutoff values for methylation were determined according to the Youden index of ROC analysis.

In the BileScreen model, mutation and methylation are integrated when either is positive. The performance of the BileScreen model was further evaluated in separate validation cohorts and test cohorts.

In addition, because in the training cohort and the validation cohort (Validation set), the selected benign cases were mostly young women with gallstones, resulting in a certain predisposition between malignant and benign patients in terms of age and gender. To exclude the effect of this artificial sample selection on diagnostic prediction outcomes, 52 age- and sex-matched malignant patients and 52 benign patients were assigned to the training cohort. Therefore, the age and gender distribution in the validation cohort was uneven (Fig. 2). But all mutations and methylation had no significant correlation with age and gender (correlation coefficient/correlation coefficient<0.5, or Wilcoxon test P>0.05).

6. Statistical analysis

ROC analysis (pROC package) and Wilcoxon test were used to evaluate the role of individual mutated or methylated genes in predicting disease status. A penalized logistic regression method (glmnet package) was used to screen gene markers for diagnostic models. In the training cohort, ROC curves took raw scores as input and the Youden index alone was used to determine the optimal cut-off point for methylation. In addition, ROC analysis was used to compare the performance of different methods, taking as input a "0 or 1" value determined by the corresponding cutoff point. Sensitivity and specificity were calculated using standard 2x2 contingency tables. All R package correlation analyses were based on R software (V.3.6.3).

7. Results

1) Establishment of BileScreen model based on gene mutation and methylation modification

Sequencing and data analysis were performed on 104 patients in the training cohort, including 52 patients with pathologically confirmed malignancies diagnosed by ERCP and 52 patients with benign disease, some of whom were surgically and pathologically determined to have unidentified tissue sites. The patients with cancerous changes, and the other part with bile duct stones, were followed up for at least 12 months and were determined to be benign disease. The clinical characteristics are summarized in Figure 2.

Using Mutation Capsule technology, the DNA of bile samples was analyzed, and 23 mutant genes and 44 methylation modified genes were detected. The most frequently mutated genes in cancer were TP53 (50%) and KRAS (46%). Both CTNNB1 and GNAS mutations were detected in both cancer and benign disease patients, so the genes were not significantly associated with malignant status, and CTNNB1 and GN AS mutations were excluded from the BileScreen model.

Table 3. Detection accuracy of each dataset

Using genetic mutations to differentiate patients with cholangiopancreatocarcinoma from non-cancer (benign disease) subjects:

Mutations in AKT1, KRAS, APC, NRAS, ARID1A, PIK3CA, AXIN1, PPP2R1A, BAP1, PTEN, BRAF, SMAD4, CDKN2A, TERT, TP53, EGFR, FBXW7, FGFR2, HRAS, IDH1, IDH2, of which at least one mutation was detected Considered positive; mutation alone had a Sensitivity of 81%, a Specificity of 100%, and an AUC of 0.90 for distinguishing pancreatic cholangiocarcinoma patients from non-cancer subjects (Table 3, Figure 3A).

Using methylation markers to differentiate patients with cholangiopancreatic cancer from noncancerous (benign disease) subjects:

For methylation markers, five markers, SOX17, 3-OST-2, NXPH1, SEPT9, and TERT, were selected to construct a diagnostic model by stepwise penalized logistic regression method (Fig. 3, Table 4). By the leave-one-out method, methylated markers alone were able to identify pancreatic cholangiocarcinoma patients well from non-cancer cases with a sensitivity of 88%, a specificity of 98%, and an AUC of 0.93 (Table 3, Figure 3). The cutoff for methylation scores was 0.422, yielding the largest Youden index (Figure 5).

Table 4. Construction of diagnostic model based on 5 methylation markers

Finally, when genetic mutations and methylation markers are combined, BileScreen:

Positivity was defined as positive for either of the two, and the performance was further improved with a sensitivity of 94%, a specificity of 98%, and an AUC of 0.96 (Table 3, Figure 3). BileScreen was validated in an additional 105 cases (validation cohort), of which 64 were malignant and 41 were benign (Figure 4). BileScreen accurately predicted disease status in 59 malignant cases and 40 non-cancer cases. BileScreen showed 92% sensitivity and 98% specificity in the validation cohort with an AUC of 0.95 (Table 3, Figure 3). If only genetic mutations were used, the sensitivity and specificity were 78% and 100%, respectively. The sensitivity and specificity of the methylation marker analysis alone were 81% and 98%, respectively (Table 3).

2. The BileScreen model is used to detect suspicious malignant tumors

We further performed BileScreen validation on 50 patients with equivocal ERCP (Test cohort) results because of the ERCP diagnosis of "suspected malignancy" or "cancer cannot be ruled out". The cases were followed for at least 12 months, and 40 of the 50 were found to be malignant. The remaining 10 cases had no cancer found during the follow-up period and were diagnosed as benign. 36 of 40 malignant lesions and 2 of 10 benign lesions were positive, with a sensitivity of 90% and a specificity of 80% (Figure 3). For those patients who could not be diagnosed by ERCP, BileScreen results were significantly associated with clinical outcomes (P<0.001, continuity-adjusted chi-square test).

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

3. Comparison of detection results between CA19-9 and BileScreen model in each group

In the training and validation cohorts, we screened 85 and 74 patients, respectively, for which serum CA19-9 data were available (Fig. 2, Table 5), and performed a direct comparison between serum CA19-9 and BileScreen in these patients. Serum CA19-9 had AUCs of 0.78 and 0.81 to differentiate benign from malignant in the 2 cohorts (Fig. 6), with a cutoff value of ≥27 U/mL, serum CA19-9 sensitivity was 88% and 91%, respectively, specificity 67% and 70%, respectively (Table 5).

Table 5. Validation results of each model and CA19-9 in different datasets

In contrast, BileScreen had a sensitivity of 93% and 94%, and a specificity of 98% and 96%, respectively. In the entire training and validation cohorts, the sensitivity and specificity of CA19-9 were 90% and 68%, respectively, which were lower than 93% and 97% of BileScreen. Therefore, BileScreen is superior to serum CA19-9 in detection of pancreaticobiliary tract cancer, especially in detection specificity.

In addition, the serum CA19-9 results of 38 patients in the test cohort are shown in Figure 6A, the specificity of serum CA19-9 was extremely low (14%), the AUC was 0.51, and the sensitivity was 84% (Table 4, Figure 6) . Compared with the training and validation cohorts, CA19-9 was less accurate in predicting patients with suspected malignancy diagnosed by ERCP. 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/Brush Samples

In the testing cohort, 34 patients obtained biopsy samples by ERCP and 9 patients obtained brush samples. We analyze genetic and tissue samples for head-to-head comparison studies. In 43 cases, 70 mutations were present in both sample types, 5 mutations were detected only in bile (brush samples) and 9 only in tissue (biopsy samples) (Figure 7). Thus, 93% (70/75) of the mutations in bile were also detected in the tissue, some other mutations were only found in the bile, and 89% (70/79) of the tissue-derived mutations were detected in the bile. Additionally, 36 of the 43 samples had mutations detected in at least one type of sample, of which 34 (94%) had at least one common mutation detected between the two sample types. Thus, the patient's mutation status detected by bile was 95% (41/43) concordant with the mutation status detected by tissue.

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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