New application of LINC01409 in colorectal cancer diagnosis and prognosis prediction

Abstract

The invention discloses a novel application of LINC01409 in diagnosis and prognosis prediction of colorectal cancer, finds that the LINC01409 has obvious differential expression in patients with colorectal cancer for the first time, can be used as a biomarker for diagnosis and prognosis prediction of colorectal cancer, and has the advantages of high accuracy, good specificity, high sensitivity and the like. A brand-new thought and strategy are provided for early diagnosis and prognosis prediction of colorectal cancer in the field, and good clinical application value is achieved.

Description

Technical Field

[0001] The present invention belongs to the field of biotechnology, and specifically, the present invention relates to a new use of LINC01409 in the diagnosis and prognosis prediction of colorectal cancer. Background Art

[0002] The global cancer statistics report shows that colorectal cancer (CRC) has become the third most common malignant tumor in the world and ranks second among the causes of tumor-related deaths, bringing a heavy burden to global health and economy. Early diagnosis and screening of colorectal cancer are crucial to reducing the morbidity and mortality of colorectal cancer. At present, the widely used colorectal cancer screening methods in clinical practice include fecal occult blood test and serum tumor marker detection such as carcinoembryonic antigen (CEA). However, its sensitivity and specificity are low. With the popularity of colonoscopy, colonoscopy has become an effective tool for early screening of colorectal cancer, but it is an invasive operation and is accompanied by complications such as bleeding, infection and perforation. Patients have poor compliance and there is a certain rate of missed diagnosis. Therefore, exploring a non-invasive, simple, effective, sensitive and specific biomarker is crucial for the diagnosis and prognosis of colorectal cancer patients and has important clinical significance.

[0003] In recent years, with the development of whole genome and transcriptome sequencing technologies, lncRNA has received increasing attention. A large number of research results have shown that lncRNA is associated with the occurrence and development of cancer, and it is abnormally expressed in many cancers. Long non-coding RNA (lncRNA) refers to a type of RNA with a length greater than 200 nucleotides, widely present in the nucleus and cytoplasm, which cannot encode proteins but has the function of regulating gene expression. Relevant studies have shown that colorectal cancer-related lncRNA can regulate genes through a variety of mechanisms, including epigenetic modification, lncRNA-miRNA and lncRNA-protein interactions, and as miRNA precursors. Because some lncRNAs can be detected in body fluids and have good specificity and sensitivity, they have been considered to be new potential biomarkers for the diagnosis and prognosis of colorectal cancer and for predicting responsiveness to treatment.

[0004] To date, there has been no research or report on the application of LINC01409 in the diagnosis and prognosis prediction of colorectal cancer. Summary of the invention

[0005] In view of this, the purpose of the present invention is to provide a new use of LINC01409 in the diagnosis and prognosis prediction of colorectal cancer.

[0006] The biomarker LINC01409 (long intergenic non-protein coding RNA 1409) described in the present invention has a Gene ID of 105378580 in NCBI (https: / / www.ncbi.nlm.nih.gov / ), and a specific location of 1p36.33.

[0007] In order to achieve the above object, the present invention adopts the following technical solutions:

[0008] In a first aspect, the present invention provides the use of a reagent for detecting the expression level of the biomarker LINC01409 in the preparation of a product for diagnosing or assisting in the diagnosis of colorectal cancer.

[0009] Further, the reagent includes a probe that specifically recognizes LINC01409 and / or a primer that specifically amplifies LINC01409;

[0010] Preferably, the reagent includes a reagent for detecting the expression level of LINC01409 using transcriptome sequencing technology, reverse transcription-polymerase chain reaction, real-time fluorescence quantitative PCR technology, Northern blot, in situ hybridization technology, gene chip technology, Nanopore sequencing technology or PacBio sequencing technology.

[0011] Furthermore, the reagent described in the first aspect of the present invention is used to detect the expression level of the biomarker LINC01409 in a test sample derived from a subject, so as to further diagnose or assist in diagnosing whether the subject has colorectal cancer or the risk of colorectal cancer.

[0012] In some embodiments, the sample includes, but is not limited to, tissue samples, primary or cultured cells or cell lines, cell supernatants, cell lysates, platelets, serum, plasma, vitreous fluid, lymph fluid, synovial fluid, follicular fluid, semen, amniotic fluid, milk, whole blood, blood-derived cells, urine, cerebrospinal fluid, saliva, sputum, tears, sweat, mucus, tumor lysates, tissue culture fluid, tissue extracts, homogenized tissues, tumor tissues, cell extracts, and combinations thereof. In a preferred embodiment, the sample is a tissue sample derived from a subject.

[0013] In some embodiments, the subject refers to any animal, including humans and non-human animals. Non-human animals include all vertebrates, for example, mammals, such as non-human primates (particularly higher primates), sheep, dogs, rodents (such as mice or rats), guinea pigs, goats, pigs, cats, rabbits, cattle, and any livestock or pets; and non-mammals, such as chickens, amphibians, reptiles, etc. In a preferred embodiment, the subject is a human.

[0014] In some embodiments, the primer refers to an oligonucleotide that can be used in an amplification method such as a polymerase chain reaction (PCR) to amplify a nucleotide sequence based on a polynucleotide sequence corresponding to a target gene (e.g., a sequence of LINC01409 or a portion thereof). Typically, at least one PCR primer used to amplify a polynucleotide sequence is sequence-specific for the polynucleotide sequence. The exact length of the primer depends on a variety of factors, including temperature, primer source, and the method used. For example, for diagnostic applications, depending on the complexity of the target sequence, the oligonucleotide primer typically contains at least 10, or 15, or 20, or 25 or more nucleotides, and it may also contain fewer nucleotides or more nucleotides. The factors involved in determining the appropriate length of the primer are well known to those skilled in the art.

[0015] In some embodiments, the probe refers to any molecule that can selectively bind to a specific intended target biomolecule. The probe can be any molecule that can be indirectly or directly, covalently or non-covalently bound to any substrate and / or reaction product disclosed herein (especially LINC01409 in the present invention), and its binding can be detected using methods known to those skilled in the art. In some embodiments, the probe is a fluorescent probe, an antibody, or an absorbance-based probe. If it is an absorbance-based probe, the chromophore pNA (p-nitroaniline) can be used as a probe for detecting and / or quantifying target nucleic acid sequences disclosed herein. In some embodiments, the probe can be a nucleic acid sequence comprising a fluorescent molecule or substrate that fluoresces when exposed to an enzyme.

[0016] In some embodiments, the sequencing technology described in the present invention includes but is not limited to: first-generation sequencing, second-generation sequencing, and third-generation sequencing. Among them, first-generation sequencing, also known as Sanger sequencing, is a sequencing technology that utilizes DNA polymerase synthesis reaction. First-generation sequencing is a sequencing technology based on the Sanger method; second-generation sequencing is based on massively parallel sequencing technology (Massive parallel analysis, MPS), which can simultaneously complete the synthesis of complementary chains of sequencing templates and the acquisition of sequence data; third-generation sequencing is based on single-molecule sequencing and massively parallel sequencing technology.

[0017] In a second aspect, the present invention provides a product for diagnosing or assisting in the diagnosis of colorectal cancer.

[0018] Further, the product comprises a reagent for detecting the expression level of the biomarker LINC01409;

[0019] Preferably, the reagent includes a probe that specifically recognizes LINC01409 and / or a primer that specifically amplifies LINC01409;

[0020] More preferably, the reagent includes a reagent for detecting the expression level of LINC01409 using transcriptome sequencing technology, reverse transcription-polymerase chain reaction, real-time fluorescence quantitative PCR technology, Northern blot, in situ hybridization technology, gene chip technology, Nanopore sequencing technology or PacBio sequencing technology;

[0021] Most preferably, the product comprises a kit, a chip and / or a test strip.

[0022] In some embodiments, the kit also includes instructions for use or labels, positive controls, negative controls, buffers, adjuvants or solvents, and one or more containers for containing the compositions contained in the kit. The composition may be in liquid form or may be lyophilized. Suitable containers for the composition include, for example, bottles, vials, syringes and test tubes. The container may be formed of a variety of materials, including glass or plastic. The instructions or labels describe in detail how to use the kit to detect samples from a subject's source and that the kit is used for the purpose of diagnosing or assisting in the diagnosis of colorectal cancer.

[0023] In some embodiments, the kit may also include a variety of different reagents suitable for practical use (such as for different detection methods), and is not limited to the reagents currently listed in the present invention. As long as the reagent is based on the detection of the biomarker LINC01409 to diagnose or assist in the diagnosis of colorectal cancer, it is included in the protection scope of the present invention.

[0024] In some embodiments, the chip can be prepared by conventional methods for preparing biochips known to those skilled in the art, including but not limited to: using a solid phase carrier of a modified glass slide or silicon wafer, the 5' end of the probe contains an amino-modified poly dT string, the oligonucleotide probe is prepared into a solution, and then it is spotted on the modified glass slide or silicon wafer using a spotter, arranged into a predetermined sequence or array, and then fixed by leaving it overnight to obtain the chip described in the present invention.

[0025] In some embodiments, the primers for specific amplification of LINC01409 and the probes for specific recognition of LINC01409 described in the present invention can be prepared by chemical synthesis. After being appropriately designed by a preparation method well known to those skilled in the art with reference to known information, primers and probes that can be used to specifically detect the biomarker LINC01409 described in the present invention are prepared by chemical synthesis.

[0026] In a third aspect, the present invention provides the use of a reagent for detecting the expression level of the biomarker LINC01409 in the preparation of a colorectal cancer prognosis prediction product.

[0027] Further, the reagent includes a probe that specifically recognizes LINC01409 and / or a primer that specifically amplifies LINC01409;

[0028] Preferably, the reagent includes a reagent for detecting the expression level of LINC01409 using transcriptome sequencing technology, reverse transcription-polymerase chain reaction, real-time fluorescence quantitative PCR technology, Northern blot, in situ hybridization technology, gene chip technology, Nanopore sequencing technology or PacBio sequencing technology.

[0029] In a fourth aspect, the present invention provides a product for predicting the prognosis of colorectal cancer.

[0030] Further, the product comprises a reagent for detecting the expression level of the biomarker LINC01409;

[0031] Preferably, the reagent includes a probe that specifically recognizes LINC01409 and / or a primer that specifically amplifies LINC01409;

[0032] More preferably, the reagent includes a reagent for detecting the expression level of LINC01409 using transcriptome sequencing technology, reverse transcription-polymerase chain reaction, real-time fluorescence quantitative PCR technology, Northern blot, in situ hybridization technology, gene chip technology, Nanopore sequencing technology or PacBio sequencing technology;

[0033] Most preferably, the product comprises a kit, a chip and / or a test strip.

[0034] In a fifth aspect, the present invention provides a risk assessment model for predicting the prognosis of colorectal cancer.

[0035] Furthermore, the risk assessment model includes the biomarker LINC01409;

[0036] Preferably, the risk prediction and assessment model also includes the following indicators: the growth of the tumor itself (T), the degree of metastasis of the regional lymph nodes (N), and the presence or absence of blood circulation in distant organs (M).

[0037] In a sixth aspect, the present invention provides a device / system for predicting the prognosis of colorectal cancer.

[0038] Further, the device / system comprises:

[0039] (1) Data acquisition module, used to obtain the expression level of the biomarker LINC01409 in the sample of the test subject, as well as the growth of the tumor itself (T), the degree of metastasis of the regional lymph nodes (N), and the presence of blood circulation in distant organs (M);

[0040] (2) a prediction module, used to provide the data obtained by the data acquisition module as input data to the risk assessment model described in the fifth aspect of the present invention, wherein the risk assessment model predicts the prognosis of the subject based on the data obtained by the data acquisition module;

[0041] (3) A prediction result acquisition module, which is used to obtain the output result of the risk assessment model in the prediction module to obtain the prognosis prediction result of the subject.

[0042] In a seventh aspect, the present invention provides the use of a reagent for detecting the expression level of the biomarker LINC01409 in the preparation of a device / system for predicting the prognosis of colorectal cancer.

[0043] In an eighth aspect, the present invention provides the use of the biomarker LINC01409 in the preparation of a drug for treating and / or preventing colorectal cancer.

[0044] Furthermore, the pharmaceutical composition further comprises a pharmaceutically acceptable carrier and / or excipient.

[0045] Furthermore, the pharmaceutical composition also contains other drugs for treating and / or preventing colorectal cancer, including but not limited to: oxaliplatin, capecitabine, 5-fluorouracil, folinic acid, S-1, irinotecan, bevacizumab, cetuximab, tramadol, celecoxib, and pethidine hydrochloride.

[0046] In addition, the present invention also provides a device / system for diagnosing or assisting in the diagnosis of colorectal cancer, the device / system comprising:

[0047] (1) A colorectal cancer assessment device: comprising a control unit and a storage unit, used to assess whether a subject has colorectal cancer or the risk of having colorectal cancer;

[0048] (2) information communication terminal devices that are communicatively connected to each other: for providing data on the expression level of the biomarker LINC01409 in a sample from a subject;

[0049] The control unit of the colorectal cancer assessment device includes the following four units:

[0050] 1) A data receiving unit: used to receive data on the expression level of the biomarker LINC01409 in the sample from the subject transmitted from the information communication terminal device;

[0051] 2) a discriminant value calculation unit: which calculates a discriminant value based on the discrimination of the expression level of the biomarker LINC01409 in the sample derived from the subject received by the data receiving unit and the expression level of the biomarker LINC01409 stored in the storage unit as an explanatory variable;

[0052] 3) a discriminant value reference evaluation unit: which evaluates the colorectal cancer risk of the subject based on the discriminant value calculated by the discriminant value calculation unit;

[0053] 4) An evaluation result transmitting unit which transmits the evaluation result of the subject obtained by the discriminant value reference evaluating unit to the information communication terminal device.

[0054] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0055] The present invention discovered for the first time that LINC01409 is significantly differentially expressed in patients with colorectal cancer, and can be used as a biomarker for the diagnosis and prognosis prediction of colorectal cancer, and has the advantages of high accuracy, good specificity, and high sensitivity. It provides a new idea and strategy for the early diagnosis and prognosis prediction of colorectal cancer in the field, and has good clinical application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 This is a graph showing the differential expression of LINC01409 between colorectal cancer tissues and normal tissues in the screening set (TCGA dataset);

[0057] Figure 2 This is a graph showing the differential expression of LINC01409 between colorectal cancer tissues and normal tissues in the validation set (clinical sample dataset);

[0058] Figure 3 This is the ROC curve result diagram of LINC01409 for diagnosing colorectal cancer in the screening set (GTEx-TCGA dataset), where the ordinate is sensitivity and the abscissa is specificity;

[0059] Figure 4 This is the ROC curve result of LINC01409 for diagnosing colorectal cancer in the validation set (clinical sample data set), where the ordinate is sensitivity and the abscissa is specificity;

[0060] Figure 5 This is the ROC curve of the M+N+T+LINC01409 model for colorectal cancer prognosis prediction, where T represents the growth of the cancer tumor itself, including the size of the tumor and its infiltration range; N represents the degree of metastasis of the regional lymph nodes; M represents whether the distant organs have blood circulation;

[0061] Figure 6 This is the survival curve obtained by using LINC01409 to predict the prognosis of colorectal cancer. DETAILED DESCRIPTION

[0062] Unless otherwise defined, all technical and scientific terms used in the context of the present invention have the same meanings as understood by those of ordinary skill in the art. The terms used in the specification of the present invention are only for describing specific embodiments and are not intended to limit the present invention. In addition, in order to further promote the understanding of the present invention, some of the terms involved in the present invention are explained as follows:

[0063] As used herein, the term "or" refers to a single element of the listed alternative elements unless the context clearly indicates otherwise.

[0064] As used herein, the term "and / or" refers to any combination of a single element or a plurality of elements among the listed optional elements, unless the context clearly indicates otherwise.

[0065] The term "comprising" as used herein means including stated elements or components but not excluding other elements or components.

[0066] As used herein, the term "biomarker" refers to any gene or protein whose expression level in a tissue or cell is altered compared to the expression level in a normal or healthy tissue or cell. The biomarker may be differentially present at any level, but is generally present at a level that is increased by at least 5%, at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 35%, at least 40%, at least 45%, at least 50%, at least 55%, at least 60%, at least 65%, at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 100%, at least 110%, at least 120%, at least 130%, at least 140%, at least 150%, at least 160%, at least 170%, at least 180%, at least 190%, at least 200%, at least 210%, at least 220%, at least 230%, at least 240%, at least 250%, at least 260%, at least 270%, at least 280%, at least 290%, at least 30 ... %, at least 130%, at least 140%, at least 150%, or more; or generally present at a level that is reduced by at least 5%, at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 35%, at least 40%, at least 45%, at least 50%, at least 55%, at least 60%, at least 65%, at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, or 100% (i.e., absent). In a specific embodiment of the invention, the biomarker is LINC01409.

[0067] The term "differential expression" as used herein refers to the difference in the expression level of one or more splice variants of a biomarker in one sample, as compared to the expression level of the same biomarker in a second sample, by measuring the amount or level of the biomarker. Differential expression can be determined as described herein and by methods understood by those skilled in the art. The term "differential expression" means that the increase or decrease in the measurable expression level of a given biomarker in a sample can be measured by measuring the amount of RNA compared to the measurable expression level of a given biomarker in a second sample. "Differential expression" as used herein can be measured by p-values, and when the p-value is less than 0.1, the biomarker is identified as differentially expressed between the first and second samples. More preferably, the p-value is less than 0.05. Even more preferably, the p-value is less than 0.01. Still more preferably, the p-value is less than 0.005. Most preferably, the p-value is less than 0.001. In a specific embodiment of the present invention, the biomarker is LINC01409.

[0068] The term "expression level" as used herein refers to the amount of polynucleotides, mRNA or amino acid products or proteins in a biological sample. "Expression" generally refers to the process by which the information encoded by a gene is converted into a structure that exists and operates in a cell. Therefore, according to the present invention, the "expression" of a gene can refer to transcription into polynucleotides, translation into proteins, or even post-translational modification of proteins. Fragments of transcribed polynucleotides, translated proteins, or post-translationally modified proteins should also be considered expressed, whether they are derived from transcripts generated by alternative splicing or degraded transcripts, or from post-translational processing of proteins (e.g., by proteolysis). "Expressed genes" include genes that are transcribed into polynucleotides (e.g., mRNA) and then translated into proteins, as well as genes that are transcribed into RNA but not translated into proteins (e.g., lncRNA, miRNA).

[0069] The term "diagnosis or auxiliary diagnosis" as used herein refers to any type of procedure intended to: obtain information that is helpful in assessing whether a patient has suffered from or is likely to suffer from, or is more likely to suffer from a certain disease (especially colorectal cancer in the present invention) or condition (especially colorectal cancer-related conditions in the present invention) in the past, at the time of diagnosis, or in the future; discover how the disease is progressing or may progress in the future.

[0070] The term "prognosis prediction" used herein refers to the prediction of the probability of the outcome of a disease, that is, a pre-estimation of the future course of the disease after the onset of the disease. The prognosis of a disease is not only a simple cure or death, but also includes complications, disability, deterioration, recurrence, remission, prolongation, survival period (such as five-year survival rate) and quality of life, etc., and the situation where the disease condition has changed or reached a new stable state. In a specific embodiment of the present invention, the prognosis prediction includes predicting the prognosis of patients with colorectal cancer.

[0071] For the purpose of the present invention, prognosis prediction can be understood as predicting the disease-free survival rate or survival rate of a cancer patient by predicting the disease course of the cancer patient and whether the cancer patient is cured. For example, a prediction of "good prognosis" indicates that the disease-free survival rate or survival rate of the cancer patient is at a high level, which means that the cancer patient is more likely to be treated; while a prediction of "poor prognosis" indicates that the disease-free survival rate or survival rate of the cancer patient is at a low level, which means that the cancer of the cancer patient is likely to recur or the cancer patient is likely to die from cancer.

[0072] The term "AUC" as used herein, same as "area under the curve", refers to the area under the receiver operating characteristic curve (ROC) well known to those skilled in the art. The determination of the area under the curve (AUC) helps to compare the accuracy of the classifier via the overall data range. A classifier with a larger area under the curve has a higher ability to accurately distinguish between two groups of interest (e.g., a group of colorectal cancer patients and a healthy control group). In the differential diagnosis of two populations (e.g., colorectal cancer patients and healthy controls), the receiver operating characteristic curve (ROC curve) is useful for representing the performance of a specific feature (e.g., any item of biomarkers and / or additional biomedical information described in the present invention) in a graphical form. The receiver operating characteristic curve refers to a graphical curve showing the performance of a binary classifier system as its discrimination threshold changes. The curve is created by plotting a curve of the true positive rate against the false positive rate at various threshold settings. The true positive rate is also referred to as sensitivity. The false positive rate is calculated as 1-specificity. Therefore, the ROC curve is a graphical display of the true positive rate versus the false positive rate (sensitivity vs (1-specificity)) over a range of cutoff values ​​and a means of selecting the best cutoff value for clinical use. Accuracy, expressed as the area under the ROC curve (AUC), provides a useful parameter for comparing test performance. An AUC close to 1 indicates that the test is highly sensitive and has a high specificity.

[0073] The term "kit" used herein includes not only primers, probes, etc. for specific detection of the biomarker, but also one or more other component compositions, solutions or devices suitable for analytical methods. In a specific embodiment of the present invention, the kit containing primers specific to the biomarker can be a kit containing basic elements for amplification reactions such as PCR. For example, a kit for PCR can include a test tube or other suitable container, a reaction buffer, triphosphate deoxynucleotides (dNTPs), an enzyme (such as Taq polymerase and reverse transcriptase), a deoxyribonuclease (DNase), a ribonuclease (RNAse) inhibitor, DEPC-water, or sterile water, etc.

[0074] The term "risk assessment model" used herein refers to a mathematical model in computational science that can study the behavior of complex systems through computer simulation. In a specific embodiment of the present invention, it refers to a mathematical model that associates the expression level of the biomarker LINC01409 with the risk or possibility of colorectal cancer in a subject. The biomarker LINC01409 can be associated with colorectal cancer using any suitable mathematical method described in the prior art. The logarithmic function used to associate the biomarker with the disease preferably uses an algorithm developed and obtained by applying statistical methods, for example, suitable statistical methods are discriminant analysis (DA) (i.e., linear, quadratic, regular DA), Kernel method (i.e., SVM), non-parametric method (i.e., k-nearest neighbor classifier), PLS (partial least squares), tree-based methods (i.e., logistic regression, CART, random forest method, boosting / bagging method), generalized linear model (i.e., logarithmic regression), principal component-based method (i.e., SIMCA), generalized superposition model, fuzzy logic-based method, neural network-based method and genetic algorithm-based method. Those skilled in the art are able to skillfully select appropriate statistical methods to evaluate the biomarkers described in the present invention and thereby obtain appropriate mathematical algorithms.

[0075] The term "device / system" used in this article can be embodied in programming, and various aspects of the technology can be considered to be a product in the form of a machine (or processor) executable code and / or related data that is usually executed or embodied in a machine-readable medium. The machine executable code can be stored in an electronic storage unit such as a memory (e.g., read-only memory, random access memory, flash memory) or a hard disk. Storage-type media can include any or all tangible memories of a computer, a processor, etc., or its related modules, such as various semiconductor memories, tape drives, disk drives, etc., which can provide non-temporary storage for software programming at any time. All or part of the software can sometimes communicate through the Internet or various other communication networks. For example, such communication can enable software to be loaded from one computer or processor to another computer or processor, for example, from a management server or host to a computer platform of an application server. Therefore, another type of medium capable of carrying software elements includes optical waves, electric waves, and electromagnetic waves such as physical interfaces between local devices, through wired and optical fiber landline networks, and used on various air links. Physical elements that carry such waves, such as wired or wireless links, optical links, etc.

[0076] The term "pharmaceutical composition" as used herein refers to a pharmaceutical composition for treating and / or preventing colorectal cancer. In some embodiments, the pharmaceutical composition provided by the present invention can also be used in combination with other drugs for treating colorectal cancer, and other therapeutic compounds can be administered simultaneously with the main active ingredients contained in the pharmaceutical composition of the present invention, or even administered simultaneously in the same composition. Other therapeutic compounds can also be administered separately as a separate drug or in a dosage form different from the main active ingredient.

[0077] The pharmaceutical composition of the present invention can be in a dosage form suitable for injection, a dosage form suitable for oral ingestion (such as capsules, tablets, caplets, elixirs), an ointment, cream or lotion form suitable for topical administration, a delivery form suitable for use as eye drops, an aerosol form suitable for administration by inhalation (such as through nasal inhalation or oral inhalation), a dosage form suitable for parenteral administration, i.e., subcutaneous, intramuscular or intravenous injection.

[0078] The present invention is further described below in conjunction with specific embodiments, which are only used to explain the present invention and are not to be construed as limiting the present invention. It will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to these embodiments without departing from the principles and purposes of the present invention, and that the scope of the present invention is defined by the claims and their equivalents. The experimental methods for which specific conditions are not specified in the following examples are usually tested under conventional conditions or under conditions recommended by the manufacturer.

[0079] Example Screening and validation of biomarker LINC01409 associated with diagnosis and prognosis of colorectal cancer 1. Experimental subjects

[0080] (1) Filter set

[0081] The lncRNA sequencing data and clinical information of the TCGA colorectal cancer cohort used for testing in this experiment were downloaded from the GDC website, and the gene expression data of the normal colon cohort in the GTEx database were downloaded from the UCSC xene website. After de-batch processing of the TCGA database and the GTEx database, a total of 741 samples were used for differential expression and colorectal cancer diagnosis analysis, including 359 normal tissues and 382 colorectal cancer tissues; in addition, after removing normal, duplicated, and deleted samples in the TCGA database, a total of 619 samples were used for prognostic analysis.

[0082] (2) Validation set

[0083] The validation set used to validate the biomarkers related to colorectal cancer diagnosis and prognosis obtained through screening in this embodiment comes from 29 colorectal cancer patients collected by the present invention, including 29 cases of colorectal cancer tissues and 29 cases of paracancerous tissues. The inclusion criteria of the colorectal cancer patients are as follows:

[0084] Inclusion criteria: ① All patients were diagnosed with colorectal cancer for the first time, and the pathological diagnosis and staging of colorectal cancer were completed according to the World Health Organization's Digestive System Tumors (Fourth Edition) classification and the American Joint Committee on Cancer staging system, and the films were independently read and diagnosed by two pathologists; ② All patients underwent radical resection of colorectal cancer, with no less than 10 lymph nodes removed; ③ No anti-tumor treatment was performed before surgical treatment, including neoadjuvant chemotherapy, radiotherapy, targeted therapy or biological therapy.

[0085] Exclusion criteria: ① incomplete clinical case data; ② no systematic lymph node dissection or palliative surgery; ③ previous history of tumor or concurrent tumors in other parts of the body; ④ death of patients not due to tumor or within 1 month after surgery; ⑤ severe perioperative heart, lung, liver, or kidney dysfunction.

[0086] The information of 29 patients with colorectal cancer collected in this example is shown in Table 1.

[0087] Table 1 Information of 29 patients with colorectal cancer

[0088] serial number gender Age (years) diagnosis Tumor diameter (cm) T N C4 female 74 Sigmoid Colon Cancer 3.8×2.8(raised type) 2 1 C5 male 61 Rectal cancer 6.0×5.5(ulcer type) 3 2 C6 female 74 Right colon cancer 5.0×4.5(ulcer type) 3 0 C8 male 66 Sigmoid Colon Cancer 2.0×2.0(raised type) 2 1 C10 female 45 Sigmoid Colon Cancer 9.5×6.5(ulcer type) 3 1 C11 male 62 Transverse colon cancer 10×3.0(raised type) 3 0 C13 female 81 Right colon cancer 4.5×4.0(raised type) 3 0 C14 male 67 Right colon cancer 5.0×3.0 (ulcer type) 3 1 C15 female 58 Sigmoid Colon Cancer 4.0×2.0 (ulcer type) 3 1 C17 male 71 Right colon cancer 5.5×3.5(ulcer type) 3 0 C18 male 67 Sigmoid Colon Cancer 3.0×3.0 (ulcer type) 3 0 C19 female 71 Ascending colon cancer 7.0×4.0(ulcer type) 3 0 C21 female 39 Sigmoid Colon Cancer 5.5×3.0(raised type) 3 0 C23 female 65 Sigmoid Colon Cancer 3.0×1.5(ulcer type) 3 0 C25 female 43 Sigmoid Colon Cancer 6.5×5.5(ulcer type) 3 1 R1 male 64 Rectal cancer 3.5×3.0 (ulcer type) 2 0 R2 male 55 Rectal cancer 1.5×1.5(raised type) 3 0 R4 male 77 Rectal cancer 7.0×5.5(raised type) 2 0 R6 male 66 Rectal cancer 3.0×3.0(raised type) 2 0 R7 male 72 Rectal cancer 5.0×4.0 (ulcer type) 3 1 R8 female 48 Rectal cancer 3.0×2.0 (ulcer type) 2 0 R9 male 43 Rectal cancer 4.5×3.0(raised type) 2 0 R11 female 76 Rectal cancer 4.0×4.0 (ulcer type) 2 0 R19 female 48 Rectal cancer 4.5×4.0 (ulcer type) 3 1 R20 male 53 Rectal cancer 4.0×3.0 (ulcer type) 3 2 R21 male 49 Low rectal cancer 2.0×1.5(raised type) 2 0 R22 female 55 Rectal cancer 3.0×3.0 (ulcer type) 3 1 R23 male 75 Rectal cancer 4.5×4.5(ulcer type) 2 0 R25 female 81 Rectal cancer 8.0×6.0(ulcer type) 3 1

[0089] 2. Analysis of differentially expressed lncRNA

[0090] (1) Screening and analysis of differentially expressed lncRNAs

[0091] SPSS software was used to perform differential expression analysis on the sequencing data of LINC01409 in the screening set, and the differential expression of genes between colorectal cancer tissues and adjacent tissues in the screening set was compared.

[0092] (2) Analysis of differentially expressed lncRNAs in the validation set

[0093] ① RNA extraction

[0094] Total RNA was extracted from tissues using the RNeasy kit (Beyotime, Shanghai, 456 China, R0027). The specific experimental steps are as follows:

[0095] a. Sample preparation: Take 20 mg of animal tissue, place it in a 1.5 mL centrifuge tube, add about 6 zirconium oxide beads, quickly add 600 μL of ice-cooled lysis solution, and homogenize with a micro-electric homogenizer. After grinding or homogenization, gently blow the homogenate 8-10 times and leave it at room temperature for 3-5 minutes. Then centrifuge at about 14,000g for 2 minutes and transfer the supernatant to a new centrifuge tube.

[0096] b. Add an equal volume of binding buffer to the lysate and gently invert 3-5 times to mix.

[0097] c. Transfer the mixture of lysate and binding solution into the purification column, centrifuge at 16,000g for 1 minute, and discard the lower layer of liquid.

[0098] d. Add 600 μL of washing solution I to the purification column, centrifuge at 16,000 g for 1 minute, and discard the lower layer of liquid. Add 600 μL of washing solution II to the purification column, centrifuge at 16,000 g for 1 minute, and discard the lower layer of liquid. Repeat this step twice.

[0099] e. Centrifuge at 16,000 g for 2 minutes to remove the residual liquid on the purification column.

[0100] f. Discard the collection tube, place the RNA purification column in the RNA elution tube, add 50 μL of elution solution to the center of the purification column, leave at room temperature for 3 minutes, and centrifuge at 16,000g for 30 seconds. Add the obtained eluate to the purification column again and repeat the elution, centrifuge at 16,000g for 30 seconds to obtain purified RNA.

[0101] ②Reverse transcription

[0102] a. Determine the concentration and quality of sample RNA: Perform reverse transcription on sample RNA with a concentration higher than 143 ng / μL and OD230 / 260 and OD280 / 260 that meet the standards.

[0103] b. Remove DNA from RNA: First, prepare a mixed solution of gDNA Eraser and 5×gDNA Eraser Buffer on ice and dispense into each reaction tube, then add 1 μg of total RNA and enzyme-free water. See Table 2 for the specific reaction system.

[0104] Table 2 Reaction system

[0105]

[0106] The above reaction system was heated at 42°C for two minutes to remove DNA.

[0107] c. Reverse transcription reaction: First prepare a mixed solution except the first step reaction solution on ice, and then add the first step reaction solution. The specific reaction system is shown in Table 3 below.

[0108] Table 3 Reaction system

[0109]

[0110] The above reaction system was heated at 37°C for 15 minutes and then at 85°C for 30 seconds. 180 μL RNase Freed HO was added to each tube. 2 O dilution.

[0111] ③PCR reaction

[0112] a. Primer design: The primers were synthesized by the company. The relevant primer sequences for LINC01409 are as follows:

[0113] F: 5'-CCCATCCTGCCACTAACAGA-3' (SEQ ID NO: 1);

[0114] R: 5'-GGAGGAAGCCCTTGGTAGAAG-3' (SEQ ID NO: 2).

[0115] b. Prepare the reaction system: TB Green Premix Ex Taq II reagent is protected from light, and the PCR forward and reverse primers are mixed in advance. First, prepare the mixed solution except cDNA on ice, divide it into eight strip tubes, and then add cDNA. The specific reaction system is shown in Table 4 below.

[0116] Table 4 Reaction system

[0117]

[0118]

[0119] c. Centrifuge eight rows and load onto the machine.

[0120] Real-time quantitative PCR detection and analysis used a two-step PCR standard amplification procedure. The reaction conditions were: cDNA as a template for qRT-PCR, and GAPDH as an internal reference for amplification. The reaction conditions were: first step pre-denaturation (98°C for 30 seconds) and second step PCR amplification (95°C for 5 seconds, 60°C for 30 seconds, 40 cycles).

[0121] The test data results were recorded and analyzed by the specific software program of the qRT-PCR instrument. According to the formula, multiple = 2 -ΔΔCt Calculate the relative expression level of each target gene.

[0122] 3. Analysis of the diagnostic efficacy of lncRNA for colorectal cancer

[0123] The R package "pROC" was used to draw the receiver operating curve (ROC) and analyze the AUC values, sensitivity, and specificity of the lncRNAs that were screened and showed significant differential expression between colorectal cancer tissues and normal tissues in the screening set and validation set, respectively, to determine their diagnostic efficacy for colorectal cancer.

[0124] The expression level of the lncRNA (Log 2 The expression level was evaluated and analyzed, and the point corresponding to the maximum Youden index was selected as its cutoff value, that is, the optimal division threshold was determined by the point with the largest Youden index.

[0125] 4. Survival analysis

[0126] In this example, the prognostic effect of the lncRNA on the overall survival (OS) of colorectal cancer patients was evaluated by Kaplan-Meier analysis in the TCGA dataset. The patients were divided into two groups according to the optimal cut-off point of the lncRNA expression.

[0127] 5. Analysis of the prognostic prediction efficacy of lncRNA for colorectal cancer

[0128] The R package “pROC” was used to draw the receiver operating curve (ROC) to analyze the efficacy of the lncRNA in predicting the prognosis of colorectal cancer in the TCGA dataset.

[0129] 6. Statistical analysis methods

[0130] The Wilcoxon signed rank test was used to evaluate the differential expression of the lncRNAs. The log-rank test was used for survival analysis. The remaining data were analyzed using the Student's t test (normally distributed variables) or the Wilcoxon rank sum test (non-normally distributed variables). All statistical tests were performed using R (version: 3.6.3), and the significance threshold was set at 0.05.

[0131] 7. Experimental results

[0132] (1) Differential expression analysis

[0133] The results of differential expression analysis in the screening set are as follows Figure 1 As shown in Figure 2, the results showed that the expression level of LINC01409 in colorectal cancer tissues was significantly downregulated compared with normal tissues. The analysis results of differential expression in the validation set are shown in Figure 2. Figure 2 As shown, the results showed that the expression level of LINC01409 in colorectal cancer tissues was also significantly downregulated compared with normal tissues.

[0134] (2) ROC curve analysis of biomarker LINC01409 in diagnosing colorectal cancer

[0135] The ROC curve analysis results of the screening set are as follows Figure 3 As shown in Figure 2, the AUC value in the colorectal cancer samples of the GTEx-TCGA database was 0.812 (sensitivity was 0.708, specificity was 0.822), and the ROC curve analysis results in the validation set were shown in Figure 2. Figure 4 As shown, the AUC value shown in clinical colorectal cancer patient samples was 0.806 (sensitivity was 0.828, specificity was 0.690). The above results indicate that the biomarker LINC01409 can be used for the accurate diagnosis of colorectal cancer.

[0136] (3) ROC curve and survival curve analysis of the biomarker LINC01409 in predicting the prognosis of colorectal cancer

[0137] The results of ROC curve analysis of the prognosis of patients with colorectal cancer are as follows Figure 5 As shown in the figure, the results showed that compared with the conventional prognostic prediction method using M+N+T (AUC value was 0.703, sensitivity was 0.661, and specificity was 0.648), the prediction method using M+N+T+LINC01409 was used to analyze the prognosis of colorectal cancer patients, and its AUC value was 0.724 (sensitivity was 0.569, specificity was 0.762), which was higher than the former, indicating that the biomarker LINC01409 can improve the accuracy of prognosis prediction for colorectal cancer patients. The results of survival curve analysis are shown in the figure. Figure 6 As shown, the results showed that the biomarker LINC01409 could effectively distinguish patients in the high overall survival (OS) group from those in the low OS group.

[0138] The description of the above embodiments is only used to understand the method and core idea of ​​the present invention. It should be pointed out that, for those skilled in the art, several improvements and modifications can be made to the present invention without departing from the principle of the present invention, and these improvements and modifications will also fall within the scope of protection of the claims of the present invention.

Claims

1. Application of reagents for detecting the expression level of biomarker LINC01409 in the preparation of products for diagnosis or auxiliary diagnosis of colorectal cancer.

2. The use according to claim 1, characterized in that: The reagents include a probe that specifically recognizes LINC01409 and / or a primer that specifically amplifies LINC01409; Preferably, the reagent includes a reagent for detecting the expression level of LINC01409 using transcriptome sequencing technology, reverse transcription-polymerase chain reaction, real-time fluorescence quantitative PCR technology, Northern blot, in situ hybridization technology, gene chip technology, Nanopore sequencing technology or PacBio sequencing technology.

3. A product for diagnosing or assisting in the diagnosis of colorectal cancer, characterized in that: The product comprises a reagent for detecting the expression level of the biomarker LINC01409; Preferably, the reagent includes a probe that specifically recognizes LINC01409 and / or a primer that specifically amplifies LINC01409; More preferably, the reagent includes a reagent for detecting the expression level of LINC01409 using transcriptome sequencing technology, reverse transcription-polymerase chain reaction, real-time fluorescence quantitative PCR technology, Northern blot, in situ hybridization technology, gene chip technology, Nanopore sequencing technology or PacBio sequencing technology; Most preferably, the product comprises a kit, a chip and / or a test strip.

4. Application of reagents for detecting the expression level of biomarker LINC01409 in the preparation of colorectal cancer prognosis prediction products.

5. The use according to claim 4, characterized in that: The reagents include a probe that specifically recognizes LINC01409 and / or a primer that specifically amplifies LINC01409; Preferably, the reagent includes a reagent for detecting the expression level of LINC01409 using transcriptome sequencing technology, reverse transcription-polymerase chain reaction, real-time fluorescence quantitative PCR technology, Northern blot, in situ hybridization technology, gene chip technology, Nanopore sequencing technology or PacBio sequencing technology.

6. A product for predicting the prognosis of colorectal cancer, characterized in that: The product comprises a reagent for detecting the expression level of the biomarker LINC01409; Preferably, the reagent includes a probe that specifically recognizes LINC01409 and / or a primer that specifically amplifies LINC01409; More preferably, the reagent includes a reagent for detecting the expression level of LINC01409 using transcriptome sequencing technology, reverse transcription-polymerase chain reaction, real-time fluorescence quantitative PCR technology, Northern blot, in situ hybridization technology, gene chip technology, Nanopore sequencing technology or PacBio sequencing technology; Most preferably, the product comprises a kit, a chip and / or a test strip.

7. A risk assessment model for colorectal cancer prognosis prediction, characterized in that: The risk assessment model includes the biomarker LINC01409; Preferably, the risk prediction and assessment model also includes the following indicators: the growth of the tumor itself (T), the degree of metastasis of the regional lymph nodes (N), and the presence or absence of blood circulation in distant organs (M).

8. A device / system for predicting the prognosis of colorectal cancer, characterized in that: The device / system comprises: (1) Data acquisition module, used to obtain the expression level of the biomarker LINC01409 in the sample of the test subject, as well as the growth of the tumor itself (T), the degree of metastasis of the regional lymph nodes (N), and the presence of blood circulation in distant organs (M); (2) a prediction module, configured to provide the data obtained by the data acquisition module as input data to the risk assessment model of claim 7, wherein the risk assessment model predicts the prognosis of the subject based on the data obtained by the data acquisition module; (3) A prediction result acquisition module, which is used to obtain the output result of the risk assessment model in the prediction module to obtain the prognosis prediction result of the subject.

9. Use of a reagent for detecting the expression level of the biomarker LINC01409 in the preparation of a device / system for predicting the prognosis of colorectal cancer.

10. Use of the biomarker LINC01409 in the preparation of a drug for treating and / or preventing colorectal cancer.

Images