Design method and application of cancer-specific core probe set for MRD detection

Abstract

The purpose of the present invention is to provide a design method and application of a cancer-specific core probe group for MRD detection. The design method of the cancer-specific core probe group of the present invention incorporates drug mutations with high evidence levels of target cancers and high-frequency mutation sites of target cancers, which can be used for MRD monitoring to monitor tumor evolution and overcome the temporal and spatial heterogeneity of tumors to a certain extent; and after verification by multiple databases, comprehensive coverage of multiple solid tumors has been achieved; after verification by clinical samples, the probe combination of the present invention has excellent capture efficiency and good uniformity.

Description

Technical Field

[0001] The present invention belongs to the field of nucleic acid sequencing, and in particular, relates to a design method of a cancer-specific core probe group and its application. Background Art

[0002] Surgical resection is the primary treatment for subjects with early-stage solid tumors, but a considerable number of subjects still experience local recurrence or distant metastasis after surgery. At present, the prognostic stratification of cancer is mainly based on clinical pathological parameters, such as TNM staging, pathological subtype, tumor grade, etc. However, the sensitivity and specificity of prognostic stratification by these indicators are limited, and more effective methods are urgently needed to identify subjects with high risk of recurrence and / or who may benefit from adjuvant therapy. Studies have shown that tumor cells and DNA can be released into the peripheral blood during the tumor progression stage to form circulating tumor DNA (ctDNA), which carries free genomic fragments with tumor-specific genetic changes and is associated with tumor development, resistance, recurrence and metastasis. It is of great value for the diagnosis, treatment and prognosis of tumors. Detection of ctDNA in the blood of tumor subjects can provide a rapid, efficient and relatively non-invasive "liquid biopsy".

[0003] Molecular / Minimal Residue Disease (MRD) refers to the situation where a cancer patient achieves complete radiographic remission after radical treatment, but there are still residual tumor cells or tiny lesions in the body that cannot be detected by imaging methods. The cancer-derived molecular abnormalities that can be discovered through liquid biopsy represent the continued existence of cancer and the possibility of clinical progression. The number of residual tumor cells at this stage may be very small, not reaching the level observable by imaging. It belongs to the latent stage of tumor progression and may not cause any signs or symptoms for the time being, but it is a potential hidden danger for tumor recurrence or metastasis. The detection of molecular / minimal residual lesions has good prognostic value. MRD detection based on circulating tumor DNA (ctDNA) can detect this molecular abnormality, which can be used for recurrence risk stratification, treatment response assessment and disease monitoring, and provide an important reference for clinical treatment decisions.

[0004] MRD detection methods based on high-throughput sequencing are mainly divided into group customization strategies and personalized customization strategies. The personalized customization strategy MRD detection method has the advantages of high sensitivity, high specificity and high cost performance, but it cannot monitor drug-resistant mutations generated by tumor evolution. This field urgently needs a cancer-specific core probe set that covers medication and high-incidence mutations in the population. Summary of the invention

[0005] The present invention provides a design method of a cancer-specific core probe set for MRD detection and its application.

[0006] According to the first aspect of the present invention, the present invention provides a method for designing a cancer-specific core probe group, wherein the cancer-specific core probe group is designed based on one or more of the following genes and / or mutations: guideline or expert consensus-level drug mutations; non-guideline / non-consensus-level genes and mutations with clear clinical value and strong biomarker predictive value; driver gene mutations in target cancers; hotspots and high-frequency mutation genes / regions in target cancers.

[0007] In some embodiments, the cancer-specific core probe group selects the genes and / or mutations according to the following priority order: Level 1 includes guideline or expert consensus-level drug mutations; Level 2 includes non-guideline / non-consensus-level genes and mutations with clear clinical value and strong biomarker predictive value; Level 3 includes driver gene mutations in the target cancer; Level 4 includes genes / regions with high population incidence in the target cancer.

[0008] In some embodiments, the method for calculating genes / regions with high population incidence is performed according to the following steps:

[0009] (1) Obtain mutation information of each patient / sample from the target cancer database, and annotate the corresponding transcript and exon information based on the mutation information;

[0010] (2) Calculate the mutation density coefficient of the probe covering the target exon:

[0011] Target exon probe mutation density coefficient = (a / m) / length,

[0012] a: The total number of mutations in the target exon in the population,

[0013] m: the number of all mutations in the population,

[0014] length: The length of the probe covering the target exon, estimated by the length of the exon:

[0015] Exon ≤ 40bp, probe length: 120bp, extension length at both ends of the exon ≥ 40bp,

[0016] Exon>40bp, probe length: exon length + 80bp, with 40bp extension at both ends of the exon;

[0017] (3) Calculation of the incidence of exon populations carrying mutations:

[0018] The incidence of exon population carrying mutations = b / n,

[0019] b: Number of patients carrying mutations in the target exon,

[0020] n: total number of patients;

[0021] (4) First, sort in descending order according to the mutation density coefficient of the target exon probe, and then sort in descending order according to the prevalence of the exon population carrying the mutation. The genes / regions ranked higher have a higher priority.

[0022] In some embodiments, the target cancer database used in the high population incidence calculation method includes, but is not limited to, commonly used cancer genome databases such as the TCGA database and the MSK database.

[0023] In some embodiments, the guideline or expert consensus-level drug mutation is a Class I drug mutation recommended by the NCCN guidelines for the target cancer, and / or a Class I drug mutation recommended by the CSCO guidelines, and / or a drug mutation approved by the FDA or NMPA in the target cancer, or a drug target recommended by domestic and foreign expert consensus.

[0024] In some embodiments, the number of probes in the lung cancer, colorectal cancer, breast cancer or pan-cancer probe group in the cancer-specific fixed core probe group in step 3 ranges from 40 to 100, preferably 40, 50, 60, 70, 80, 90, or 100.

[0025] In some embodiments, the probe length of the cancer-specific fixed core probe set in step 3 is 80-160 base pairs, preferably 80, 90, 100, 110, 120, 130, 140, 150, 160 base pairs in length.

[0026] In some embodiments, the target cancer is lung cancer, and the monitoring sites of the cancer-specific core probe group include the following genes: EGFR, ERBB2, MET, BRAF, KRAS, ALK, PIK3CA, TP53.

[0027] In some embodiments, the target cancer is colorectal cancer, and the monitoring sites of the cancer-specific core probe group include the following genes: BRAF, KRAS, NRAS, TP53, PIK3CA, APC.

[0028] In some embodiments, the target cancer is breast cancer, and the monitoring sites of the cancer-specific core probe group include the following genes: PIK3CA, AKT1, ESR1, ERBB2, TP53, PTEN, and GATA3.

[0029] In some embodiments, the target cancer is a pan-solid tumor other than lung cancer, colorectal cancer, and breast cancer, and the monitoring sites of the cancer-specific core probe group include the following genes: BRAF, KRAS, PIK3CA, CDKN2A, and TP53.

[0030] In some embodiments, the cancer-specific core probe set can be used to detect MRD in a biological sample of a subject. Preferably, the MRD detection in a subject also includes any combination of the cancer-specific core probe set and other probe sets.

[0031] According to a second aspect of the present invention, the present invention provides a screening system for cancer-specific core probe group monitoring sites using the above method, wherein the system comprises the following modules:

[0032] A sorting module, used to sort mutations or genes;

[0033] The cancer-type-specific core probe group monitoring site determination module is used to determine the monitoring sites of the cancer-type-specific core probe group of the target cancer.

[0034] In some embodiments, the screening system is used to perform the screening method described above.

[0035] According to a third aspect of the present invention, the present invention provides a storage medium recording a method for running the above-mentioned method or the above-mentioned system.

[0036] According to a fourth aspect of the present invention, the present invention provides a cancer-type specific core probe set obtained by the method described above. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 The capture efficiency of different sized panels of the present disclosure is shown.

[0038] Figure 2 The population coverage of the cancer-specific core probe set disclosed in the present invention for each cancer type is shown.

[0039] Figure 3 The figure shows the distribution of the number of mutations detected by the cancer-specific core probe set disclosed in the present invention in patients with different cancer types.

[0040] Figure 4 The capture efficiency of the cancer-specific core probe set of the present disclosure is shown.

[0041] Figure 5A The proportion of probes with a sequencing depth of ≥ 0.2 times the average in the cancer-specific core probe set disclosed in the present invention is shown.

[0042] Figure 5B The proportion of probes with a sequencing depth of ≥ 0.5 times the average in the cancer-specific core probe set disclosed in the present invention is shown.

[0043] Figure 6 The probe depth coefficients of the cancer-specific core probe sets disclosed herein are shown. DETAILED DESCRIPTION

[0044] In this application, the term "MRD" may be an abbreviation of three terms, namely, molecular residual disease, measurable residual disease, and minimal residual disease. MRD reflects the residual status of tumor lesions. After treatment, a small amount of tumor cells may remain in the body of the tumor subject, and the number of these tumor cells may be so small that they do not cause any symptoms or signs. They are usually not detected by traditional means such as cytological microscopy or serological examinations. Detection requires the use of highly sensitive modern cutting-edge technologies such as flow cytometry, PCR, NGS, etc.

[0045] In this application, the term "Panel" is a term used after the development of high-throughput gene detection and gene sequencing. It means that in the detection, not only one site or one gene is detected. Instead, multiple genes and multiple sites are detected at the same time. These sites and genes need to be selected and combined according to a standard to form a detection panel. Therefore, the gene detection panel can be understood as a gene combination, a gene set or a probe combination.

[0046] In this application, the term "deep sequencing" refers to the general concept of a large number of repeated reads for each region of a sequence.

[0047] In this application, "sequencing data" refers to any sequence information about nucleic acid molecules known to the skilled person. Sequence data may include information about DNA or RNA sequences, modified nucleic acids, single-stranded or double-stranded sequences, or alternatively amino acid sequences that must be converted into nucleic acid sequences. Sequence data may additionally include information about sequencing equipment, acquisition date, read length, sequencing direction, source of sequenced entities, adjacent sequences or reads, presence of repetitions, or any other suitable parameter known to those skilled in the art. Sequence data may be presented in any suitable format, archive, encoding, or document known to those skilled in the art.

[0048] In this application, the term "tumor" refers to a mass or neoplasm, which itself is defined as an abnormal new growth of cells that usually grow faster than normal cells and will continue to grow if not treated, sometimes causing damage to adjacent structures. Tumors can vary greatly in size. Tumors can be solid or fluid-filled. Tumors can refer to benign (non-malignant, usually harmless) or malignant (capable of metastasizing) growths. Some tumors may contain benign neoplastic cells (e.g., carcinoma in situ) while also containing malignant cancer cells (e.g., adenocarcinoma). It should be understood to include neoplasms located in multiple locations throughout the body. Therefore, for the purposes of this disclosure, tumors include primary tumors, lymph nodes, lymphatic tissue, and metastatic tumors.

[0049] In the present application, non-limiting examples of the cancer include biliary tract cancer, bladder cancer, transitional cell carcinoma, urothelial carcinoma, breast cancer, cervical cancer, cervical squamous cell carcinoma, rectal cancer, colorectal cancer, colon cancer, hereditary nonpolyposis colorectal cancer, colorectal adenocarcinoma, gastrointestinal stromal tumor (GIST), endometrial cancer, endometrial stromal sarcoma, esophageal cancer, esophageal squamous cell carcinoma, esophageal adenocarcinoma, ocular melanoma, uveal melanoma, gallbladder cancer, gallbladder adenocarcinoma, renal cell carcinoma, clear cell renal cell carcinoma, transitional cell carcinoma, urothelial carcinoma, Wilms' tumor, liver cancer, hepatoepithelial carcinoma, hepatocellular carcinoma, bile duct carcinoma, hepatoblastoma, lung cancer, non-small cell lung cancer (NSCLC), nasopharyngeal carcinoma (NPC), neuroblastoma, oral cancer, oral squamous cell carcinoma, ovarian cancer, pancreatic cancer, pancreatic ductal adenocarcinoma, pseudopapillary neoplasm, acinar cell carcinoma, prostate cancer, skin cancer, melanoma, malignant melanoma, cutaneous melanoma, small intestine cancer, stomach cancer, gastric epithelial carcinoma, uterine cancer, or uterine sarcoma.

[0050] In some embodiments, the sequencing technology includes but is not limited to Illumina, MGI, and Geneplus.

[0051] In this application, the term "subject" refers to any animal, mammal or human. The subject has, may have or is suspected of having one or more diseases. The subject may have cancer, the subject may show symptoms associated with cancer, the subject may not show symptoms associated with cancer, or the subject may not have been diagnosed with cancer. In some embodiments, the subject is a human.

[0052] In this application, the term "CSCO guidelines" refers to various clinical practice guidelines for malignant tumors issued by the Chinese Society of Clinical Oncology.

[0053] In this application, the term "TCGA database" refers to the Cancer Genome Atlas Program, which currently contains data from 20,000 patients and 33 types of cancer. It includes genome, transcriptome, epigenetic, proteome and other omics data, as well as clinical sample information.

[0054] In this application, the term "MSK Database" is a data directory provided by the Memorial Sloan Kettering Cancer Center (MSKCC) in the United States, which includes various biomedical data generated by the center's researchers and partners, including genome, transcriptome, proteome, metabolome, clinical trials and other data.

[0055] The design method of the cancer-specific core probe group of the present invention incorporates drug mutations with high evidence levels in the target cancer and high-frequency mutation sites in the target cancer, which can be superimposed with the personalized probe group for MRD monitoring, play a role in monitoring tumor evolution, and overcome the temporal and spatial heterogeneity of tumors to a certain extent.

[0056] The cancer-specific core probe set of the present invention has been verified by the TCGA database and the Genenjia database, and has achieved comprehensive coverage of various solid tumors. In the Genenjia database that conforms to the tumor mutation characteristics of the Chinese population, the coverage of colorectal cancer, lung cancer and breast cancer is 98.22%, 89.95% and 85.96%, respectively. The median number of mutations detected in colorectal cancer and ovarian cancer is 2, and the median number of mutations detected in lung cancer, breast cancer, esophageal cancer and other cancers is 1. According to clinical sample verification, the probe combination of the present invention has excellent capture efficiency (median> 40%) and good uniformity.

[0057] The following are preferred embodiments of the present invention, and the present invention is not limited to the following preferred embodiments. It should be noted that for those skilled in the art, several modifications and improvements made on the basis of this invention and creation concept all belong to the protection scope of the present invention. The reagents used without indicating the manufacturer are all conventional products that can be obtained through commercial purchase.

[0058] Example

[0059] Example 1: Core probe screening and performance testing

[0060] Core probes for monitoring tumor evolution.

[0061] 1.1. Determination of the size of cancer-specific core probe sets

[0062] After statistical analysis of the capture efficiency of probe sets of different sizes, it was found that as the probe set increased, the capture efficiency gradually increased and then tended to stabilize ( Figure 1 ). When the probe set size reaches 5kb, the capture efficiency is basically stable at more than 30%, which can meet the detection requirements. Smaller probe sets will lead to lower capture efficiency, which will eventually affect the detection performance. In summary, the size of the cancer-specific core probe set is set to 5kb.

[0063] 1.2. Screen the core probe region according to the following rules

[0064] 1. Screening level 1: Class I drug mutations recommended by the NCCN guidelines for target cancers, and Class I drug mutations recommended by the CSCO guidelines; drug mutations approved by the FDA or NMPA in target cancers; drug targets recommended by consensus of domestic and foreign experts for target cancers.

[0065] Individual core probes were designed for lung cancer, colorectal cancer, and breast cancer, and pan-cancer core probes were designed for other cancers. See Table 1.

[0066] Table 1: Probe design for lung cancer, colorectal cancer, breast cancer, and pan-cancer

[0067]

[0068]

[0069] 2. Screening level 2: non-guideline / non-consensus-level genes and mutations with clear clinical value and strong biomarker predictive value in target cancers reported in the literature; Level 3: driver gene mutations in target cancers reported in the literature; Level 4: genes / regions with high population incidence in target cancers in the TCGA database, MSK database, and Cosmic database. See Table 2.

[0070] Select the non-guideline-level genes / mutations with high priority from the priority-ranked genes / mutations above, and merge these mutations with the mutations selected in 1 until the expected panel size (5 kb) is reached.

[0071] Table 2: Screened mutations that meet the level 2-level 4 rules

[0072]

[0073]

[0074] 1.3. Coverage evaluation of core probes

[0075] In order to evaluate the coverage of core probes in the population, the single-point coverage (≥1 site) of core probes in the Genealogy database and TCGA database was counted.

[0076] (1) Core probe coverage of a single cancer type

[0077] The core probes for lung cancer have a coverage of 89.95% and 80.20% in the Giyinga database and TCGA database, respectively; the core probes for colorectal cancer have a coverage of 98.22% in the Giyinga database and 92.53% in the TCGA database; the core probes for breast cancer have a coverage of 85.96% and 71.93%, respectively. Figure 2 ).

[0078] The difference in coverage between the Genetic Alzheimer's and TCGA databases may be related to factors such as race and region. The population in the Genetic Alzheimer's database is mainly Chinese. In general, the core probe population coverage is excellent.

[0079] (2) Coverage of core probes for pan-solid tumors

[0080] The pan-solid tumor core probe detection range includes 11 types of cancer, including esophageal cancer, pancreatic cancer, ovarian cancer, endometrial cancer, gastric cancer, and urothelial cancer. The coverage rate of the pan-cancer core probes in the esophageal cancer population in the TCGA database is 95.33%, and the coverage rate in the esophageal cancer population in the Jiyinga database is 88.65%; the coverage rate in the pancreatic cancer population in the TCGA database is 93.79%, and the coverage rate in the pancreatic cancer population in the Jiyinga database is 80.54%; the coverage rate in the ovarian cancer population in the TCGA database is 90.68%, and the coverage rate in the ovarian cancer population in the Jiyinga database is 88.86%; the coverage rate in the endometrial cancer population in the TCGA database is 76.79%, and the coverage rate in the endometrial cancer population in the Jiyinga database is 77.8%; the coverage rate in the gastric cancer population in the TCGA database is 75.95%, and the coverage rate in the gastric cancer population in the Jiyinga database is 66.82%; the coverage rate in the urothelial carcinoma population in the TCGA database is 71.52%, and the coverage rate in the ovarian cancer population in the Jiyinga database is 61.34% ( Figure 2 ).

[0081] 1.4. Evaluation of the number of mutations detected by core probes

[0082] The number of mutations detected by the core probes in the TCGA and Genenjia databases was counted: the median number of mutations in colorectal cancer sites was 2, the median number of mutations in lung cancer was 1, and the median number of mutations in breast cancer was 1; in other solid tumors, the median number of mutations in esophageal cancer and pancreatic cancer was 1, and the median number of mutations in ovarian cancer was 2 ( Figure 3 ). In the same cancer type, the median number of mutations detected in the Genentech database and the TCGA database is the same, indicating that the genes included in the core probes have achieved good coverage in different populations.

[0083] 1.5. Evaluation of capture efficiency and uniformity of core probes for clinical samples

[0084] The performance of the four core probes designed above was tested using clinical samples, including 4 samples each of lung cancer, colorectal cancer, breast cancer, and pan-solid tumors, and each sample was tested twice.

[0085] (1) Probe capture efficiency

[0086] The capture efficiency of cancer-specific core probes was sorted out based on clinical sample information. The median capture efficiency of colorectal cancer core probes was 44.5% (30.12%-56.62%), the median capture efficiency of lung cancer core probes was 43.4% (34.88%-48.99%), the median capture efficiency of breast cancer core probes was 41.51% (38.62%-49.04%), and the median capture efficiency of pan-solid tumor core probes was 40.08% (36.23%-43.66%). The probe capture performance was good ( Figure 4 ).

[0087] (2) Probe uniformity

[0088] According to the clinical sample information, the proportion of samples with ≥0.2 times the average depth was summarized ( Figure 5A ), ≥0.5 times the average depth sample ratio ( Figure 5B ). In the sample proportion results of ≥0.2 times the average depth, except for the colorectal cancer core probe with a median of 99.98%, the medians of the other three probes were all 100%; in the sample proportion results of ≥0.5 times the average depth, the medians of the four cancer-specific core probes were all above 97%. The results show that the four cancer-specific core probes have high uniformity and perform well.

[0089] (3) Probe depth factor

[0090] The depth coefficients of the four core probes ranged from 0.2 to 2. The coefficients of the colorectal cancer probes ranged from 0.28 to 1.47, with a median of 1.03; the coefficients of the lung cancer probes ranged from 0.56 to 1.87, with a median of 1.22; the coefficients of the breast cancer probes ranged from 0.4 to 1.78, with a median of 1.04; the coefficients of the pan-cancer probes ranged from 0.37 to 1.83, with a median of 1.10 ( Figure 6 ). The overall probe depth factor is good.

Claims

1. A method for designing a cancer-specific core probe set for MRD detection, wherein the cancer-specific core probe set is designed based on the following genes and mutations: guideline or expert consensus-level drug mutations; non-guideline / non-consensus-level genes and mutations with clear clinical value and strong biomarker predictive value; driver gene mutations in target cancers; genes / regions with high population incidence of target cancers; The cancer-specific core probe set selects the genes and / or mutations according to the following priority order: Level 1 includes guideline or expert consensus-level drug mutations; Level 2 includes non-guideline / non-consensus-level genes and mutations with clear clinical value and strong biomarker predictive value; Level 3 includes driver gene mutations in target cancers; Level 4 includes genes / regions with high population incidence in target cancers; The genes / regions with high population incidence are calculated according to the following steps: (1) Obtain mutation information of each patient / sample from the target cancer database, and annotate the corresponding transcript and exon information based on the mutation information; (2) Calculate the mutation density coefficient of the probe covering the target exon: Target exon probe mutation density coefficient = (a / m) / length, a: The total number of mutations in the target exon in the population, m: the number of all mutations in the population, length: The length of the probe covering the target exon, estimated by the length of the exon: Exon ≤ 40bp, probe length: 120bp, extension length at both ends of the exon ≥ 40bp, Exon>40bp, probe length: exon length + 80bp, with 40bp extension at both ends of the exon; (3) Calculation of the prevalence of exon populations carrying mutations: Prevalence of exon populations carrying mutations = b / n, b: Number of patients carrying mutations in the target exon, n: total number of patients; (4) First, sort in descending order according to the mutation density coefficient of the target exon probe, and then sort in descending order according to the prevalence of the exon population carrying the mutation. The genes / regions with higher rankings have higher priority; The guideline or expert consensus-level medication mutations include Class I medication mutations recommended by the NCCN guidelines for target cancers and Class I medication mutations recommended by the CSCO guidelines; FDA or NMPA-approved drug mutations in target cancers; Drug targets recommended by domestic and international expert consensus for target cancer types.

2. The method according to claim 1, characterized in that The guideline or expert consensus-level drug mutations are Class I drug mutations recommended by the NCCN guidelines for the target cancer, and / or Class I drug mutations recommended by the CSCO guidelines, and / or drug mutations approved by the FDA or NMPA in the target cancer, and drug targets recommended by domestic and foreign expert consensus.

3. The method according to claim 1, characterized in that The target cancer is lung cancer, and the monitoring sites of the cancer-specific core probe group are located at the following genes: EGFR, ERBB2, MET, BRAF, KRAS, ALK, PIK3CA, and TP53.

4. The method according to claim 1, characterized in that: The target cancer is colorectal cancer, and the monitoring sites of the cancer-specific core probe group are located at the following genes: BRAF, KRAS, NRAS, TP53, PIK3CA, and APC.

5. The method according to claim 1, characterized in that The target cancer is breast cancer, and the monitoring sites of the cancer-specific core probe group are located at the following genes: PIK3CA, AKT1, ESR1, ERBB2, TP53, PTEN, and GATA3.

6. The method according to claim 1, characterized in that The target cancers are other solid tumors except lung cancer, colorectal cancer, and breast cancer. The monitoring sites of the cancer-specific core probe group are located at the following genes: BRAF, KRAS, PIK3CA, CDKN2A, and TP53.

7. The method according to claim 1, characterized in that The cancer-specific core probe set can be used to detect MRD in biological samples of subjects.

8. The method according to claim 7, characterized in that The MRD detection of the subject's biological sample also includes any combination of cancer-specific core probe groups and other probe groups.

9. A system for designing cancer-type specific core probe sets according to any one of claims 1 to 8, characterized in that: Includes the following modules: A sorting module, used to sort mutations or genes; The cancer-type-specific core probe group monitoring site determination module is used to determine the monitoring sites of the cancer-type-specific core probe group of the target cancer.

10. The system according to claim 9, configured to perform the method according to any one of claims 1 to 8.

11. A storage medium recording a method for executing any one of claims 1 to 8 or a system according to any one of claims 9 to 10.

Images