KR20170037715A - Novel composition for prognosing lung cancer using transcriptome - Google Patents

Abstract

The present invention relates to a composition for predicting a prognosis of lung cancer, which includes a unit for detecting a transcriptome specifically expressed in lung cancer tissues. The present invention further relates to a kit for predicting a prognosis of lung cancer containing the composition, and a method for providing information for predicting the prognosis of lung cancer using the composition or the kit. The composition for predicting the prognosis of lung cancer can be used in the prediction of the prognosis after undergoing lung cancer treatment, by detecting transcriptome specifically expressed only in a tissue where cancer cell exists among lung tissues in a patient in which lung cancer is progressed at a certain level. Accordingly, the composition of the present invention can be widely applied to lung cancer treatment.

Description

TECHNICAL FIELD The present invention relates to a composition for predicting the prognosis of lung cancer using a transgene,

The present invention relates to a composition for predicting the prognosis of lung cancer using transcripts, and more particularly, the present invention relates to a composition for predicting the prognosis of lung cancer, comprising means for detecting a transcript specifically expressed in lung cancer tissue, And a method for providing information for predicting the prognosis of lung cancer using the composition or kit.

Lung cancer, a malignant tumor originating from the lung, is divided into small cell lung cancer and non-small cell lung cancer according to its tissue type. Although the small cell lung cancer is classified as a part of lung cancer by the location of the onset tissue, it is distinguished from the other lung cancer in terms of clinical course, treatment method and prognosis. In addition, non-small cell lung cancer is divided into adenocarcinoma, squamous cell carcinoma and large cell carcinoma according to the histological type.

In particular, small-cell lung cancer is a large mass, grayish white, and is known to proliferate along the bronchial wall. In many cases, surgical resection is difficult at the time of diagnosis, and malignancy is rapidly growing. It is known that chemotherapy or radiotherapy has a remarkable therapeutic effect while it is easily transferred to whole body through blood circulation. The brain, liver, bone, lung, adrenal gland, kidney, etc. have been reported as the main organs in which the small cell lung cancer is metastasized.

On the other hand, non-small cell lung cancer is classified into adenocarcinoma, squamous cell acinoma, and large-cell carcinoma as described above. First, adenocarcinomas occur mainly in the lungs, and they occur frequently in women or non-smokers. In many cases, the adenocarcinoma is metastasized even if the size is small, and the incidence of the adenocarcinoma is increasing recently. Next, squamous cell carcinoma is found mainly in the central lung, and it is known to grow up to the lumen of the bronchial tree, blocking the airway, is common to men, and is closely related to smoking. Finally, large cell carcinomas arise mainly in the vicinity of the lung surface (the distal end of the lung), about half in large bronchi, accounting for 4 to 10% of all lung cancers, and generally large cell size, It is known that prognosis is worse than other non - small cell lung cancer because it tends to proliferate and metastasize rapidly.

In particular, in the case of non-small cell lung cancer, the survival rate in the last 10 years is only about 10%. One of the main reasons for such a low survival rate is that the success rate of diagnosis of lung cancer is very low. As a method for improving the success rate of such lung cancer, a method for detecting a lung cancer-specific gene abnormality has been proposed, and various studies on lung cancer-specific gene mutation have been reported. However, There is a disadvantage that the criterion for judging whether or not an abnormality is present is ambiguous. In other words, the correlation between the level of mutation of a specific gene and the likelihood of lung cancer is unclear, and the clear criteria for the suspicion of lung cancer is ambiguous when a variety of lung cancer-associated genes are mutated. It is also common to all other cancer diagnoses.

Therefore, studies are being actively conducted to determine the criteria for determining whether a gene is abnormal, which can clearly determine whether or not a cancer has occurred. For example, Korean Patent No. 709633 discloses a technique for diagnosing the risk of lung cancer using XPG polymorphism markers for risk diagnosis of lung cancer. Korean Patent No. 884565 discloses a technique for diagnosing lung cancer-specific methylation marker genes (CDO1, CREM, FABP4, GOS2, HYAL1, LPXN, NFKBIA, RRAD, THBD, TNNC1 or TOM1).

However, the study on the diagnosis and treatment of lung cancer has been actively studied, but the method of predicting the prognosis of lung cancer has not been studied sufficiently. At present, postoperative clinical symptoms such as weight loss, loss of appetite, local symptoms, pathologic tumor stage, abdominal and inguinal examination, rectal examination, occult blood test, The prognosis is judged. However, this method has disadvantages such that the criterion is not objective, has a complicated procedure, and the result is not accurate.

Recently, as a diagnostic method for various cancers including lung cancer, a method of using a transcript specifically expressed in cancer cells has been developed. These transcripts are used for the early diagnosis of various cancers including lung cancer because they can clearly determine the onset of cancer according to their occurrence, but they are not used for prediction of cancer prognosis. It is expected that specific transcripts will be specifically expressed due to the continuous generation of genetic mutations as the cancer cells proliferate and it is expected that it will be possible to use a specific transcript for predicting the prognosis of cancer, In addition, a large number of transcripts are expressed in normal tissues, and transcripts that can be specifically used for predicting the prognosis of cancer selected from these transcripts have not been reported yet.

Under these circumstances, the present inventors have conducted intensive research to discover transcripts that can be used specifically for predicting the prognosis of lung cancer. As a result, three types of transcripts whose expression levels are increased in lung cancer tissues are used to predict the prognosis of lung cancer The present invention has been completed based on this finding.

One object of the present invention is to provide a composition for predicting the prognosis of lung cancer, which comprises at least one agent for measuring the expression level of a transcript for prediction of lung cancer prognosis selected from the group consisting of TCONS_00075018, TCONS_00004993 and TCONS_00184955.

Another object of the present invention is to provide a kit for predicting the prognosis of lung cancer, which comprises the composition for predicting the prognosis of lung cancer.

Another object of the present invention is to provide a method for predicting the prognosis of lung cancer by treating the normal lung tissue sample and the lung cancer tissue sample of a subject to be predicted of the prognosis of lung cancer and measuring the expression level of the transcript for predicting the prognosis of lung cancer from each sample And a method for providing information for predicting the prognosis of lung cancer.

The present inventors obtained a tissue sample of a normal region present in the lung tissue of lung cancer patients and a tissue sample of a cancer-producing region, respectively, in order to identify transcripts that can be specifically used for predicting the prognosis of lung cancer, Sequence data of each of these RNAs was obtained from the lung tissue, and the obtained RNA-sequence data was analyzed and compared with that of the normal region of the transcripts, As a result, transcripts with 26 transcripts were found to be increased in cancer tissues. Three transcripts (TCONS_00075018, TCONS_00004993 and TCONS_00184955) identified as statistically significant among the 26 transcripts identified were finally selected as lung cancer-specific transcripts.

The present inventors investigated whether the above-mentioned three types of transcripts can be used in predicting the prognosis of lung cancer. In the case of lung cancer tissues obtained from about 100 patients who were treated after lung cancer incidence but were not yet treated, Expression levels in lung cancer tissues were increased compared to the normal tissues. As a result, it was confirmed that the expression level of the above three transcripts was increased in the lung cancer tissue as compared with the normal tissue of the patient at a detection rate of 40 to 66%.

Since the transcript is specifically elevated in the lung cancer tissue of a patient who has not been treated even after receiving the treatment for lung cancer, the expression level of the gene measured in the lung cancer tissue sample of the patient is expressed in the expression , It was predicted that the symptom of the patient would be further deteriorated. This prediction could be confirmed from the progress of the pathology of each patient.

That is, when the expression level of the above-mentioned three transcripts measured in the patient's lung cancer tissue is significantly increased compared to the level measured in the normal tissues of the patient, it is possible to predict the prognosis of the patient's lung cancer On the other hand, if the expression level of the transcript measured in the lung cancer tissue of the patient is not significantly changed compared with the level measured in the normal tissue of the patient, the prognosis of the patient is being treated.

Thus, it can be seen that the transcript can be used as a marker for predicting the prognosis of lung cancer. In addition, since the transcripts are detected at different levels depending on the patient, these transcripts can be used as markers for predicting the prognosis of lung cancer, either alone or in combination. If these transcripts are used in combination, It can be used as a marker for prediction. As described above, the technique of using three kinds of transcripts as markers for predicting the prognosis of lung cancer has not been reported at all and has been developed for the first time by the inventors of the present invention.

.

In one embodiment, the present invention provides a transcription product comprising a transcript TCONS_00075018 for the nucleotide sequence of SEQ ID NO: 1, TCONS_00004993 for the nucleotide sequence of SEQ ID NO: 2, and TCONS_00184955 for the nucleotide sequence of SEQ ID NO: 3 And at least one agent for measuring the expression level of a transcript for predicting the prognosis of lung cancer selected from the group consisting of the prognosis of lung cancer.

The term "transcriptome " of the present invention is a term encompassing the entire transcription product of a genome, and refers to the total RNA expressed in a desired cell or tissue. The transcript also includes noncoding RNA (ncRNA) such as snRNA (small nuclear RNA), snoRNA (small nucleolar RNA) and miRNA (microRNA) as well as mRNA, tRNA and rRNA related to protein transcription and translation can do.

The term " transcript for predicting lung cancer prognosis "of the present invention refers to a transcript that has been known up to now but whose function is not known. In the lung tissue derived from lung cancer patients, Means an increasing transcript.

For example, in the present invention, the transcript that is an object of measurement of the expression level is not particularly limited. However, the transcription product TCONS_00075018, which is a transcription sequence for the nucleotide sequence of SEQ ID NO: 1, TCONS_00004993 which is a transcription sequence for the nucleotide sequence of SEQ ID NO: 3 < / RTI > sequence TCONS_00184955.

The transcript may be used as a marker for predicting the prognosis of lung cancer, since the expression level is specifically increased in cancer tissues in which the lung cancer progresses continuously and the disease progresses. That is, when the expression level of the transcript measured in cancer tissue is significantly increased compared to the expression level of normal tissue, it can be predicted that the prognosis of lung cancer is poor, and the expression level of the transcript measured in cancer tissue is normal If the level of expression is not significantly increased compared with the expression level of the tissue, its prognosis can be predicted to be good.

The term " prognostic prediction "of the present invention is used in the same sense as" prognosis ", which means an act of predicting the progress and result of a disease in advance. More specifically, the prognosis prediction means that the progress of the disease after the treatment depends on the physiological or environmental condition of the patient, and it means all actions that predict the course of the disease after treatment considering the condition of the patient in a comprehensive manner .

For the purpose of the present invention, the prognosis prediction can be interpreted as predicting the disease-free survival rate or the survival rate of patients with lung cancer by anticipating the progress of the disease and the cure after the treatment of lung cancer. For example, predicting a "good prognosis" indicates a high level of disease-free survival or survival rate after treatment for lung cancer, suggesting that patients with lung cancer are more likely to be treated, and predictions of "poor prognosis" The disease-free survival rate or survival rate of patients after treatment is low, meaning that cancer is likely to recur from lung cancer patients or die from lung cancer.

The term " disease free survival "of the present invention means the possibility that a patient can survive without recurrence of cancer after treatment of lung cancer.

The term "survival rate" of the present invention means the possibility that, after treatment of lung cancer, the patient can survive regardless of recurrence of cancer.

On the other hand, the lung cancer which can predict the prognosis by the transcription agent is not particularly limited, but examples thereof include small cell lung cancer; Or non-small cell lung cancer such as adenocarcinoma, squamous cell carcinoma, and large cell carcinoma.

The term "agent for detecting a transcript" of the present invention means a preparation used for measuring the level of the transcript in order to confirm the expression of the transcript contained in the sample, and is not particularly limited thereto For example, RT-PCR, quantitative real-time PCR, competitive RT-PCR, real-time quantitative RT-PCR, and RNase- a primer base pair capable of specifically binding to a target gene used in methods such as protection assay, Northern blotting and DNA chip analysis, and a probe.

The term "primer" of the present invention refers to a nucleic acid sequence having a short free 3 'hydroxyl group, capable of forming base pairs with a complementary template and having a starting point for template strand copying Refers to a short nucleic acid sequence that serves to initiate DNA synthesis in the presence of a reagent for polymerization (i. E., DNA polymerase or reverse transcriptase) and a different four nucleoside triphosphate at a suitable buffer solution and temperature .

For the purpose of the present invention, PCR amplification can be performed on the transcript using the composition containing the primer, and the prognosis of lung cancer can be predicted by detecting the transcript. The PCR conditions, the lengths of the sense and antisense primers can be modified based on what is known in the art. For example, the present inventors measured the expression levels of transcripts comprising the nucleotide sequences of SEQ ID NOS: 1 to 3 by PCR using primers consisting of the polynucleotides of SEQ ID NOS: 4 to 9, The prognosis was predictable.

When a primer base pair consisting of the polynucleotides of SEQ ID NOS: 4 to 9 is used as a component for predicting the prognosis of lung cancer as a preparation for detecting the transcript, each primer base pair for detecting each transcript alone In addition, when a composition containing each primer base pair alone is used, the cost and time required for predicting the prognosis of lung cancer can be saved, and the complexity of each primer base pair can be reduced. , The success rate of prediction of prognosis of lung cancer can be improved.

For example, a primer capable of amplifying TCONS_00075018, one of the transcripts for predicting prognosis of lung cancer, can be a primer base pair consisting of SEQ ID NOS: 4 and 5; Primers capable of amplifying TCONS_00004993 can be primer base pairs consisting of SEQ ID NOS: 6 and 7; Primers capable of amplifying TCONS_00184955 can be primer base pairs consisting of SEQ ID NOS: 8 and 9.

The term "probe" of the present invention means a nucleic acid fragment such as RNA or DNA corresponding to a few bases or a few hundred bases, which can be specifically bound to the transcript. The probe may be labeled with a labeling substance to detect a specific transcript. The probe may be an oligonucleotide probe, a single stranded DNA probe, a double stranded DNA probe, an RNA probe And the like.

For the purpose of the present invention, the prognosis of lung cancer can be predicted by confirming whether the probe is complementarily hybridized with the transcript. Selection of suitable probes and hybridization conditions can be modified based on what is known in the art.

The term "labeling substance" of the present invention refers to a substance that assists in visually confirming the presence or absence of the probe. It generally includes enzymes, minerals, ligands, emitters, microparticles, redox molecules, Isotopes, and the like, but is not particularly limited thereto. For example, enzymes that can be used include? -Glucuronidase,? -D-glucosidase,? -D-galactosidase, urease, peroxidase or alkaline phosphatase, acetylcholinesterase, Glucosoxidase, hexokinase, GDPase, RNase, glucose oxidase and luciferase, phosphofructokinase, phosphoenolpyruvate carboxylase, aspartate aminotransferase, phosphoenolpyruvate decarboxylase, beta -lactamase, and the like, and examples of the usable minerals include fluorescein, isothiocyanate, rhodamine, picoeriterine, picocyanin, allophycocyanin, o-phthaldehyde, And examples of ligands that can be used include biotin derivatives and the like, and available luminescent materials include acridinium ester, luciferin, luciferase, etc., and available microparticles Colloidal gold, colored latex, etc. The available redox molecules include ferrocene, ruthenium complex, viologen, quinone, Ti ion, Cs ion, diimide, 1,4-benzoquinone, hydroquinone and the like number, and a radioactive isotope available will include ^{3 H, 14 C, 32 P} , 35 S, 36 Cl, 51 Cr, 57 Co, 58 Co, 59 Fe, 90 Y, 125 I, 131 I, 186 Re But is not limited thereto.

The primers or probes of the present invention can be chemically synthesized using the phosphoramidite solid support method, or other well-known methods. Such nucleic acid sequences may also be modified using many means known in the art. Non-limiting examples of such modifications include, but are not limited to, methylation, "capping ", substitution of one or more natural nucleotides with one or more homologues, and modifications between nucleotides such as uncharged linkers (e.g., methylphosphonate, Phosphoamidates, carbamates, etc.) or charged linkages (e.g., phosphorothioates, phosphorodithioates, etc.).

In another aspect, the present invention provides a lung cancer prognostic prediction kit comprising the composition for predicting the prognosis of lung cancer.

The kit of the present invention can predict the prognosis of lung cancer by measuring the expression level of a lung cancer-specific transcript. The lung cancer prognosis prediction kit of the present invention may include one or more other component compositions, solutions or devices suitable for the analysis method as well as primers or probes for measuring the expression level of a lung cancer-specific transcript.

As a specific example, the kit of the present invention may be a kit containing necessary elements necessary for carrying out RT-PCR. The RT-PCR kit includes a test tube or other appropriate container, reaction buffer (pH and magnesium concentrations vary), deoxynucleotides (dNTPs), Taq-polymerase Enzymes such as enzyme and reverse transcriptase, DNase, RNAse inhibitor, DEPC-water, sterile water, and the like. In addition, it may contain a primer pair specific to a gene used as a quantitative control.

As another example, the kit of the present invention may be a prognosis prediction kit containing essential elements necessary for performing a DNA chip. The DNA chip kit may include a substrate on which a cDNA corresponding to the transcript or the fragment thereof is attached as a probe, and a reagent, a preparation, an enzyme, and the like for producing a fluorescent-labeled probe. In addition, the substrate may contain a cDNA corresponding to a quantitative control gene or a fragment thereof.

In another aspect of the present invention, there is provided a method for predicting the prognosis of lung cancer, comprising the steps of treating a normal lung tissue sample and a lung cancer tissue sample of a subject to predict the prognosis of lung cancer, A method for providing information for predicting the prognosis of lung cancer, comprising the step of measuring.

The term "individual" of the present invention means an object to which the prognosis of lung cancer is to be predicted, and generally refers to an individual who has undergone lung cancer treatment after the onset of lung cancer. At this time, the above-mentioned individual may include, without limitation, humans and any animals that can cause lung cancer such as dogs, horses, cows, rats, goats, rabbits, chickens, ducks and geese.

Through the above method, the expression level of the transcript is measured in a sample of lung cancer tissue of a subject to be predicted of the prognosis of lung cancer, and the expression level of the transcript is compared with the expression level of normal tissue to predict whether the prognosis of the patient is good or bad Can be provided. That is, when the expression level of the transcript measured in the lung cancer tissue is increased more than twice as compared with the expression level in the normal lung tissue, it can be determined that the prognosis of the individual is poor. On the other hand, The prognosis of the subject can be judged to be good if the expression level of the transcript does not show a large difference (for example, to less than 2-fold) in comparison with the expression level in normal lung tissue.

In order to detect the transcript, RT-PCR, competitive RT-PCR, real-time quantitative RT-PCR, RNase protection Analysis methods such as RNase protection method, Northern blotting and DNA chip technology can be used, but the present invention is not particularly limited thereto.

The composition for predicting the prognosis of lung cancer of the present invention can be used for predicting the prognosis after the treatment of lung cancer by detecting a transcript that is specifically expressed only in the tissue of the cancerous area in the lung tissue of the patient whose lung cancer has progressed to a certain level. It can be widely used to effectively treat lung cancer.

Hereinafter, the present invention will be described in more detail with reference to examples. However, these examples are for illustrative purposes only, and the scope of the present invention is not limited to these examples.

Example  1: lung cancer-specific Transpositional  excavation

Each lung tissue was obtained from 71 lung cancer patients obtained from NCBI Gene Expression Omnibus (GEO) and 10 lung cancer patients collected through clinical pathways, and lung tissues from the lung tissues obtained from the obtained lung tissues, Of lung tissue, respectively. Sequence data of each of these RNAs was obtained from each of the lung tissues obtained from the above-obtained separated tissues, and RNA-sequence data obtained was analyzed to determine whether or not the lung tissue of the cancer- 26 transcripts were identified that increased expression levels more than twice (Table 1)

Lung cancer-specific transcript Transcript p-value q-value T / N Log2FC N_avg FPKM T_avg FPKM TCONS_00060951
TCONS_00297480
TCONS_00153072
TCONS_00177744
TCONS_00026376
TCONS_00216641
TCONS_00075482
TCONS_00075498
TCONS_00278129
TCONS_00026744
TCONS_00026666
TCONS_00055498
TCONS_00230072
TCONS_00070806
TCONS_00171491
TCONS_00288419
TCONS_00263220
TCONS_00130910
TCONS_00204891
TCONS_00278219
TCONS_00184955
TCONS_00204842
TCONS_00004993
TCONS_00075018
TCONS_00289456
TCONS_00036224 0.00005
0.00005
0.00005
0.00005
0.00005
0.00005
0.00005
0.00005
0.00005
0.00005
0.00005
0.00005
0.00005
0.00005
0.00005
0.00005
0.00005
0.00005
0.00005
0.00005
0.00005
0.00005
0.00005
0.00005
0.00005
0.00005 0.030504
0.030504
0.030504
0.030504
0.030504
0.030504
0.030504
0.030504
0.030504
0.030504
0.030504
0.030504
0.030504
0.030504
0.030504
0.030504
0.030504
0.030504
0.030504
0.030504
0.030504
0.030504
0.030504
0.030504
0.030504
0.030504 12.830380520
12.549197500
11.191830300
11.033663890
10.519302070
10.286754110
10.268389900
10.146568680
9.649087284
9.609247080
9.493004790
9.424739470
9.318194800
9.163855940
9.058099988
8.847774599
8.785596322
8.657768607
8.592673800
8.545497380
8.230870000
8.173542230
4.338530000
2.583163720
2.323318300
2.019470000 0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2.32643
0
0.359426
1.29644
20.1218
0.203013 7.282320
5.992560
2.338250
2.095350
1.466660
1.248170
1.232370
1.132500
0.801906
0.780037
0.719575
0.686273
0.637346
0.572582
0.532040
0.459729
0.440294
0.402876
0.385058
0.372638
4.501210
0.287723
5.385970
7.773940
100.7100
1.622830

Of the 26 transcripts with increased expression levels in the cancer tissues, three transcripts detected in two or more tissue samples and identified as statistically significant were finally selected as lung cancer-specific transcripts. At this time, it was confirmed that the three selected transcripts were TCONS_00075018, TCONS_00004993, and TCONS_00184955, respectively, which are transcripts for the nucleotide sequence of SEQ ID NO: 1, SEQ ID NO: 2 and SEQ ID NO: 3, respectively .

Example  2: lung cancer-specific Transpositional  Verification

To confirm whether the three transcripts finally selected in Example 1 (TCONS_00075018, TCONS_00004993 and TCONS_00184955) can be used to predict the prognosis of lung cancer patients.

First, a primer capable of amplifying the above three transcripts was designed and synthesized.

TCONS_00075018 F: 5'-CCAAAGTGCTGGGATTATAGGCG-3 '(SEQ ID NO: 4)

TCONS_00075018 R: 5'-CCCGAGAATCCGAAGTTCCAGA-3 '(SEQ ID NO: 5)

TCONS_00004993 F: 5'-GGTGGGTTCGTGGTCTCGC-3 '(SEQ ID NO: 6)

TCONS_00004993 R: 5'-TGGACGTAGTTCCTCTCTTGCCC-3 '(SEQ ID NO: 7)

TCONS_00184955 F: 5'-GGATGCGATGGCTTGGCTT-3 '(SEQ ID NO: 8)

TCONS_00184955 R: 5'-CAGGACTTTGGGCATTACTGGG-3 '(SEQ ID NO: 9)

Next, total RNA was obtained from cancer tissues of 104 lung cancer patients who had undergone therapeutic treatment after lung cancer but were not yet treated, and each cDNA was synthesized from the obtained total RNA. At this time, clinical information on 104 patients who provided tissue samples is as shown in Table 2.

Clinical information of patients with lung cancer Check item division Measured value gender male
female
Unknown 74
19
11 Progression of lung cancer Ia
IB
IIa
IIb
IIIa
IIIb
IV
Unknown 16
27
18
7
8
One
2
25 Smoking Over smoking
Smoking
Non-smoking
Unknown 21
41
21
21 case history SQ (squamous carcinoma)
AD (adenocarcinoma)
Large
Unknown 45
54
3
2 age 65 years or older
Under 65
The 47
46
11

Using the synthesized cDNA as a template, qPCR using each of the synthesized primers was performed. Then, a sample whose expression level was more than 2 times higher than that of normal lung tissue was detected from the cancerous lung tissue, and the detection rate thereof was calculated (Table 3).

Detection of samples with more than two-fold changes in the expression level of transcripts in lung cancer tissues Transcript Detection rate (%) TCONS_00075018
TCONS_00004993
TCONS_00184955 40
66
40

As shown in Table 3, it was confirmed that the expression level of each transcript was increased in lung cancer tissues compared with normal lung tissues at a detection rate of 40 to 66%.

Since the expression level of the gene is specifically increased in lung cancer tissues of a patient who has not been treated even after the treatment of lung cancer, the expression level of the gene measured in lung cancer tissue samples of the 104 patients was measured in normal tissues It was predicted that the symptom of the patient would be further deteriorated from the fact that it was confirmed to be increased more than twice the expression level. Such prediction could be confirmed from the progress of the pathology of each patient.

Thus, it was found that the gene could be used as a marker for predicting the prognosis of lung cancer. In addition, since these genes are detected at different levels depending on the patients, these genes can be used as markers for predicting the prognosis of lung cancer, either alone or in combination. If these genes are used in combination, prediction of prognosis for more effective lung cancer It can be used as a marker.

<110> Dankook University Cheonan Campus Industry Academic Cooperation Foundation <120> Novel composition for prognosing lung cancer using transcriptome <130> KPA151045-KR <160> 9 <170> Kopatentin 2.0 <210> 1 <211> 3285 <212> DNA <213> Artificial Sequence <220> <223> TCONS_00075018 <400> 1 gctggagtgc actggtacaa tcttggttca ctgcaacctc cgcctcctgg cttgaagatt 60 ttcctgcctc agcttcctga gtagctggga tcacaggcac gtgccaccat gtttggctaa 120 ttttcgtatt ttttgtagag ctggggtttc accatgtcgg ccaggctggt ctcaaactcc 180 tgacatcagg tgatctgccc acctcggcct tataaactgc tgtgattata ggcataagct 240 actgtgtctg gcctaattgt cctctactaa tactgtatta ggctgggaag actaactgct 300 ctagcaatcc tcaaatctca atggtgtaag aaaataaaaa ctttattttt tgctcatgtc 360 acagttcggt gcaggatagt gagaaggatc tgctctcctt tgctactgga gacccaggct 420 gcttctgtgt agtgcctaga aaagtctcag cagctgagag gtgaaaaggt gtggaggatt 480 gcatggaagg ttttataagc caagcccagg ggctgttgaa tttcatgtcc tctcatattt 540 tattggccag aaatcaggta tagtaccaca tcgaactgga aaggaggcca ggatatgctg 600 cccaatagga tgctccgagc agtgcactca gaagaatgaa caggtttgga gacagtccaa 660 gtctgctgtg tcctcaactt ccttgggggt attttcctta caatctataa cttttttttt 720 tttttttttg agatggagtc ttggtctgtc gcccaggctg gagtgcaatg gtgcagtctc 780 agctcactga aacctctgcc tcccgggttc aagtgattct cctgcctcag cctaccgagt 840 agctgggatt acaggggcct accaccatgc ctggctaatg tttgtatttt tagtagagat 900 ggggcttcac catgttggcc atgctggtct cgaagtgctg acctcgtgat ctgtccgcct 960 cggcctccca aagtgctggg attataggcg tgagccactg ctcccggcca caatctacaa 1020 cttcaaatgg aaaaggcaaa gataaatatt agtcctctat cagtaaggac acacatgtag 1080 ctgctgtaac aaaggcaaaa caaaaaaaca caatgcaata acttaaacaa gatacagtat 1140 ttttcttgct tgcataaaaa tctgaacaaa gcactccagg gttgacgtgg cggctccaca 1200 gaatcaggca ctaaaggctc ctggtatatt gttttgtctc cccgatcacc taacttcctt 1260 cttatcatct gagatgacaa ctttacctcc actgtagtgt ccacattctg gcaaactgga 1320 aagaggagaa gggcaagtgg aaagcaagcc tttcccttta aaggtataac ccaaaagttg 1380 tctatgtcac ttgtgcttat gtcccattgg ccaaaactta gtaaccaaat cttggtaagc 1440 acccttgctg cagtgggagt tgggaaatgt agatctttgt ttaggtaaga aagaagaggg 1500 catggagggc acagtcctta cattccagac cttagtcatg gcgctacacc tcgttgtaag 1560 ggaggctagc tattgcagcc tttcgctggg tggccatgta cccagctaga tctcaggggc 1620 actcttacta aagtaatgca tggagaatgg atagcatgag aagcagtttc tgctacaagt 1680 gcctttcata aaaagaactc ctataagaaa aacaaacagg gcctaaggaa aactaatcca 1740 aagggtaaaa catggggaaa agacaaaaaa caaaagaaaa aagaaaagca agtttcccag 1800 gtagaaaatg aatgaagact gaggtacata agtgagaagt cctgtaaaat tgataatcct 1860 tttcattttg tcacaaaagt ccctacttac attctaaaat tccattaaat gtcacctttc 1920 tgatatcccc attttatttc tctctctttg ggcatttacc atgctgtagt gtactctagg 1980 ccattcctag ctttgtaact ctctcaaggt gactctgcag gagatgcaaa gtagttaaga 2040 ggagaacccc caatactgat gtgtttatag gtgaggtggt ctgatgtctt agatttgctt 2100 taaaatattc ctgcacaaaa taaaaagggg aatagatgaa acaagattga caaaatgttg 2160 attcattgac gcggtgtaat gggtatctgg gtgatcatag tacaatttta tctcttttgt 2220 atatatttta aaatttccat aatatagcaa aacatgagcc cagtccctca aggcagccag 2280 atttgggttc aaaccctagt ttgacctttt actcgctgag tgactttacc ctgctacagc 2340 ttcagtttct ccaaatggaa ataatatata ctccattaag gttcttgtaa actctcaagt 2400 aagagggaat ctgaggctct agcacacggc ccggccctta atagttgtac taatttttat 2460 tttatttttc gaaacggagt ttgctctgtc acccaggctg gagtgtagtg gcatgatccg 2520 gctcactgca acctccacct ccagggttca agcaattctc ctgcctcagc ctcctcccga 2580 gtaactggga ttacaggagt gcgccaccac gcccagctaa tttttgtatt ttttagtaga 2640 gcggggttt cggcatgttg tccaggctgg tctccaactc ctgacctcag gttatcctcc 2700 cgcctcggcc tcccagagtg ctgggattac aggcgtgagc cactgcgcct ggccagtagt 2760 tgtactaaca agggtttctg cttgcgagca acaaagactg actctagttg tggctaattt 2820 ctttcacaca cacatattaa gtgccagagg taggacttga gctcggatct ctgatttcca 2880 gacctagaac tttttatgtg ttattacagt cgttaaaaac cttacctgga tttgtgcttt 2940 gcaatttacg ctttcgaaca tgcaggaatg tagtttgggc atttgtctgg aacttcggat 3000 tctcgggact ccagggtggc caaggcgcgg aggtgactca atgacattga ccggcctgga 3060 tgcacgtggg ttgctgagcc gatgctggga aggtacgggg tttgcccggt gcaggccgcc 3120 ggaactcacg cacgcccctg tctctctcac tcctggggtc ggctctggcc ggtggcctcc 3180 agctcagcta gcggccggac gcgcagcccg ccgactagcc ctccaggtcc tagcgcgact 3240 cccggatccc ggatccggcg gatctggccg accactcacc ctccc 3285 <210> 2 <211> 23120 <212> DNA <213> Artificial Sequence <220> <223> TCONS_00004993 <400> 2 tccccacctc ctcacccagc ctctggtagc catcattcta ctctctactt ctgtgagtac 60 aactttttta gattccgcat aaaagtgaga tcatgcagta tttgcttttc tgtgcctagc 120 ttatttaact ttgcacaata ttctccacgt tcatccacat tgtcacaaat gacaagattt 180 tcttcttttt taagactgaa tagtattcca ttgtctacat gtaccacatt ttctttatct 240 attcatctgt tgatggacac aagttgattc cacatcttgg ctattgtgga cagcactgcc 300 atgaacatag gagtccagat atcctttgga catattgatt tcaattcttt tggactaata 360 cccagaagag ggtttgactg acatatgata gttctatttt tagttttttg aggaacttcc 420 attcagtttc ccataatggc tgtgagtctg gagtttgttc ctgccggtgg gttcgtggtc 480 tcgctgactt caagaatgaa gctgcagacg ttcgtggtaa gtgttacagc ttttaaaggt 540 gacacggacc caaagagtga ggagcagcaa gatttattgt gaacagcgaa aaacagagct 600 tccacagcat gtaaagggac ccaagaaggt tgccactgct ggctgggatg accagctttt 660 attcccttat ttgtcccctc ccatgttcca tttctgtcat atcagagtgc ccttttttca 720 atcctccctg tgattggcta cttttaggct cctgctgatt ggtgcatttt acagagctct 780 gattggtgca ttttacagag tgctgattgg tgcattttac agagtgctga ttggtgcatt 840 ttacaacccc cttgctatct acagagcact gattggtgca ttttacaatc ctagctacag 900 agtgctgatt ggtgcatttt acaatcctct tgtaagacag aaaattctcc aagtccccaa 960 tcaacccaag aagtccagct ggctttacct ctcaatcccc cctctaaaca ggacactcca 1020 actgctgctg ggaattgggc gatgaccact ctagctactt cctgatggat aggggtgaag 1080 aaggggccct gcaattgtag tgtcctccag aggggaactc tctaggccag tcaaagggcc 1140 actgggtcag tccaggggtc ctcggtagaa gttgtgagtt gagctcattt ggggttccat 1200 ttgtaagacc atctgtagct tgatggcctc aatcctggag gtaacaaatt tgacaagcag 1260 gtaaaaaata cagggcctga aggcgagtaa tagcaaaatg gctgtcacag gacctagaaa 1320 agggagaagc catgtcaccc aactccagag gttggtataa gagtctgaaa ggcattgtct 1380 gatttcagaa gccttttcct gtaaatgcca ggcagcgtct catactctcc ctgactggtt 1440 agtgtaaaaa caacactctt cacctaaaaa ggtgcagagt cctcctttct cagccatgag 1500 gaagtctagg cctcagcagt tttggagagt caaagagtct gctgccaaag agtctatttg 1560 ggattgtaga gtaaggatag atttagttat ttcttgcaaa ctgtctgaga aatcctttga 1620 gaatgtgtgg tagtaggata gcgaagtgga caaacctgct actctggttc ctgtagtagt 1680 ggccatccct aaacctataa gtaggggtat tacttgtatg gccctgcact gacagacttg 1740 agctttgagg ggcactgata ggttctgatt tcctggggca ttgtgaatgt tgggacttag 1800 gaagattaag gtacaagtgc ctgtccagtt ggtggggagg cagatatagg ttgaagttcc 1860 atgtaagaag aatatgcctt ggctgggtag acagaacagg ttgtgtatgt tgaaaaggtg 1920 tgtgagtttg ttgttttcat tttcccatac tcctagagta cttgccaagg tagctccaga 1980 gcagctgaaa aggggtgttg ggagcaaatt gagtggctcc ctgtgttcta ttttcccatt 2040 ggagaaaaaa accattttgt atctactagg aaccattcaa gggagtgatt gaaagagggg 2100 atgagaaggc attcattagt ggtgggagcg ctgctgcagg gggtccaggg tgaatggtca 2160 tgcagggagt atgtttgcca ttaaaaaacc tggactgttt attaagcagg gaggaggtga 2220 taatttttgg aggccctgag aagaaggcaa gctgtctgaa tggagctgtt tgggtgactc 2280 ggaagttact atgatcagat ggggcttgaa gttgtagaat gtaattacac tgatgggata 2340 gtagatgccc caggggcagg cctaataaca ggtcgcattg gatgcataaa agggcttgga 2400 aagttaagat ggtatttgta gttgcagggc tgtgtatggg cttttcattg ctcatgtaat 2460 aggtgaggtt ggaaatgtaa gagtgtaaaa gttggattgt gcatcctgtt agggtattct 2520 aggtcctatc agagatgggg aagttggcta atgattgcat atttggaatt tggaaagggt 2580 cttttccttc ataagaggga tggtaggtta agttggtaaa gacccagttt tttgcaggaa 2640 caggagtggc aacgtaagca tgcctgatag agagatgcaa agccaacagt catttgccag 2700 ggaaggactg gactggttta acagagagtg ggttaagttt agagtcttgt agaggtaact 2760 aggagctagt ggaaggggag gggcaactat gtggggtatc caagtaggca ggagggatag 2820 ataggcaaag agtaagtagg aaggtaaaga gggtgccctg aaagatgaga tcattttatc 2880 cagtctgagt taatggtagg agtaaattgc tgtcagaagg aaggatgata gaagaaaggt 2940 tgatgtgatt aggatttcat cctggagcta cagtatatag tcctactgca aagagtacag 3000 ctagtatcct ggttaataat gtgatgaaac agtaaaagga ttccattaaa ggggcaagga 3060 gaggtgttaa agattatgta ggttttcact tatctttttt aagtaggaag gggtttttct 3120 tcaggatcgg ctgtaggagt ctttttagtc tgggattttt ctttccaaaa tagaagacac 3180 aagtcctcca atggctcaca ggtgtatcga ggctggtctg gctgataatg ggactcctga 3240 gctctcggtc ccgcaggttc ttcagggggt gtccaaagct taaatcggtg tggtgaatcc 3300 aagattccac tcctgccacc ttaactgcag tgggggtaga gaggattacc gagtatggtc 3360 cttcccacaa agaatccata gatagggaga tagaggggag ggattcaaac aacactagat 3420 ctcctggttg aaataacacc gtttcctgtt ctctgtgaca tccttcacat aggatttaag 3480 ttttgttgat attttgccaa agaagttata tctttgacca agttggccat tttctgatca 3540 agtaggaggt catttgtgag aaaaggtcat ccatacagca tttcatgtgg actgaacccc 3600 atttcttgag gagaatttcg gattctcaac aaggccatgg ggaaaagaat aggccatggg 3660 agatgagttt cttgagttag tttccttagg tgcctcttga tgtttcattt gccttctcaa 3720 ccttccctga ggattgtggc ctccaggtgc agtgaacgtg atattgtatc cctagcaccc 3780 tggaaattcc ctgggttatt gtggctttaa aagctggact gttgttgctt cgtaagcttt 3840 agggaagttc aaatctagaa attatttcat aaattaggac tctaaccact tcctgagact 3900 tctctgtctt gcaggggaag gcttctatcc aatttgtaaa ggtatcaaca cagatcaaca 3960 agtattgaaa tccccttgac ttaggcatat gggtgaagtc taactgccag tcctctccgg 4020 gatagtgccc tattctttgt tttcccagag gggccttaag atagaccaag ggattattcc 4080 tttgacacct cacaggcttt gactacttgt cggatggtcc agaggagatt tggccctgta 4140 aacagggatt tagccatttg atgagtgttc tcaataccca tatgaatagt ttggtggagg 4200 ggcttaagta ttttccactg gctgacttcg ggtatgagta cctttccctc ttctgtcatt 4260 aaccaccctg aggggagaaa actatgcccc cgtgaaagtc cccatttttt ttcaattggg 4320 gaatactggg gcttaatctc ttggagaggg ttgttccata ccaagtgtcc ttccataggt 4380 atttctaatg ggaagttctg cttggcagca attttggcct cagcgtctgc ccgatggttt 4440 ccttctgcct tttctccttc acctttctga tggctttggc agtgtaagac tgctacctcc 4500 ttgggttttt gcactgcatg caataactcc atgatttcca tgtggtattt aatgggggtt 4560 cccccagagg ttaggaactc cctttctttc cacattgcag catgagcatg taggattaga 4620 taagcataca tgctatctgt atacacattt attctttttc cctttcccag ttctaaggct 4680 caggtaagca ctactagttc tgctaactgg gcactggtcc ctgggggaag aggcttactt 4740 tcaagtactg ttacatcact aactacggca taacctgccc tttgtttccc attctccaca 4800 aatgaacttc catcaatata taggttaaag tcaggattaa ctaaggggac ttctaaaaga 4860 tcctctcagg tggcataagt ctgggctaca atttgttggc agtcatgctc gattggttcc 4920 ccatcctctg ggaaaaaagt ggcagggttg agggctgcac acatgcgtat ttgaagcact 4980 agtccctcaa ggagtagtgc ctggtatcta agcaggccat tgtctgatag ccataaactt 5040 cctttggcac ctagtatgcc atttacgtca tgagtagtcc agacagttag atcctttcct 5100 tgtattattt tgatagcctc tgatactaaa atggccacca ctgcaactac tcataaacag 5160 tgaggccagc cttttgctac tacatcaatt tccttactta aggcctgacc atctcactgt 5220 atcgggggat ctatagtagg caaaagccag tgattccaag gaacccccac aaatgtttta 5280 atgtcttagg gcaaggataa gccagtatag gctgtattcc ttccttgctg aaggccctgg 5340 ctcctctggc taagattatg cctagatatt tgacttgttg taggcagagc tgggcctttg 5400 attgagacct cttgtaccct tcattagcta gaaagttcaa gagatctaga gtagcctgct 5460 ggtatgaggc ttctgaactg gtagacaaaa gtaaatcatc cacataccga agcatcagaa 5520 tgcctggact tgagaagtgg cctagatctt aggccagtgc ctgaccaaac ggatgagggc 5580 tatccctaaa cccttgaggc aagaccgtcc atgtaagttt ggatgggtgt tctgcgggat 5640 cctcaaaggc aaagagaaac tgggagtcag agtgcaagac actgcagaag aaggtatcct 5700 tgagatccag aacagtgaac cattctgctt cctctgatat ttgagagggc agggtatagg 5760 ggttgggtac agctggatat agaggaatta ctgcctcatt gatgagtcta agatcttgca 5820 ctagtctcca ctgaccattc agtttttgta ctcctagaat tggggtgttg cagtgactgt 5880 tgcattttct tactaagact tgagctttta aatgtctaat aatatcctgt aatcctttat 5940 aagcttcagg ccttaaggga tattgccttt gataaggaaa agtggtgggg tcttttagcc 6000 tgatttggac tgggtggaca ttttttgccc ttcaaaattg tcctttcaat gcccagactt 6060 cagggttgat tccctcctca aataggggac aacaaatggg tatcttgtcc cccatattca 6120 tgtagataat agctccagct ttggctaata tgtccctccc taataagggt gtgagacttt 6180 caggcataac aagaaaggca tgtgaaaaga gcaaagtctc ccaattacaa ctgaggaggt 6240 gggagaaaca cctggttaca ggctgtccca ggatccctca gatggtaatg gaccttgaag 6300 acagtcgtcc ggggtaggag attaacactg agaaggctgc accagtgtcc aggaggacat 6360 caatttcctg gccctcaatg attaaacata cacagggctc agtgagggtg atgacatgag 6420 ctggagcttg ccctgggcac cctcagtcat attgttggat catctggccc acagaacctt 6480 tgtactctgc agtgtgcctt ccagtgattg ccttggcata gtggacttgg gtgagggggc 6540 agctcgtttt tcatcggaca atctttttta aggtgtcctt gcaaaccaca ctgataacca 6600 gccctaccaa gtgattggcc tgctccattt ctgtcctctc tgaaccacca tggtttgttt 6660 gtctgagggc cacgactaag gctgtggcct ttctctgaac tcacttttcc ttttcagcct 6720 gttcctcttg gtccctgtta cagaacaccg aggttgccag gtttaataat gcttccagat 6780 tttgttcagg gccagggctc tttgaggatc aattgaccct tgacaaagtc gggtgacagg 6840 gaagtttatt ttcttaaggc ctcccatagc cactcaagga aggcagaagg attttcttgc 6900 tttccctgag ttatggtgga catcactgaa taattcatgg gttttttttt ctaattctcc 6960 ttagtccttc taggacacaa gtcaacagat gtttttcact ctagtcccca tgatctgagt 7020 ctaggtccca gctggaatcc atactgggga caacttgcta actagtaggg aatttgtccc 7080 tttcttcagc tgtcattcta tcatttactt gactaagata caaggtatct ccaaactcgg 7140 gctggagcta aagtcacatt cttttcatta aaggccaggg tttgatctaa caatagcatg 7200 acatctctcc aaatgaggcc gaaggttttc cctagaccct ttaggacatc tgtataccta 7260 tcaggataat ctgaaaatgt ccccaggtct accttgatct gctttaaatc agagaaggag 7320 aaggggacat gtacctgggt tgggccaaat taccctcccc ctacagcttg aagggcacat 7380 aagtgatagc ctggggggtt ttgtgatccc ttggagattt ctttgcttgt tcccttctgg 7440 gtgggggaga ttagaggaag tttatcatta ataggatggg gagctgtagg gaggcaagga 7500 tatggaagta agctgagagg tcctcctgta ggatataaat tgcaagcttt gcatagttgt 7560 ggattctcct tcatagtacc taatttatgc ttccctgagg tggccatttt tccccatcag 7620 agaatactgg ggccaggctg tagtgcagaa aaaaaataag ctgcttattt ttcagggttt 7680 gtggatcaaa ttgatcccaa aggcttagga tgcatttcaa gggtgagcct gttgatgcct 7740 gagtgtttcc catctgaaag aaaaaactgc ctacagtttt ggtttgcttg tttgtttttc 7800 cccctgccca agaacctgca atggtccctg gaccctgctg ttcggaacag ttgcactcac 7860 tgaagcagca gaggaaacac tagttttcct cagagaccac aaagaggacc aaggaatgtc 7920 ggatttagtg gcccttatca atgcattctc gaaaatctgc acccttgcct ttcctcttag 7980 gacacaaaga ggacaaagaa aaatcggatt tagtggccat taccattgca ttctcaaaaa 8040 cctgttagag tcctaacaat tctcctgtta gtaatgggac cttacccttg tcctatgaag 8100 atgatatgcc tcaaaatgga gtggagggcc ataccctgag ggagggaagg gataactaag 8160 gttggaagag tgaggccttt tgttctcact tctcatcata tcaatgggaa ggttaaaatt 8220 tctgaggctc tcaatatcct agcttcagga atagcctttg ttaggccttc tgtaggggtg 8280 ggttgcccct ctacacctgt gggtgtttct cgtaaggtgg gatgagagat ttggaaaaga 8340 aaaagacaca gagacaaagt atagagaaag aaataagggg acccggggaa ccagcgttca 8400 gcatatggag gatcccgcca gcctctgagt tcccttagta tttattgatc atttgtgggt 8460 gtttctcgaa gagggggatg tgtcagggtc acaagacaat tgtggggaga gggtcagcag 8520 acaaacacat gaacaaaggt ctttgcatca tagacaatgt aaaggattaa gtgctgtgct 8580 tttagatatg catacacata aacatctcaa tgctttacaa agcagcattg ctgcccgcag 8640 gtcccacctc cagccctaag gcggtttttc cctatctcag tagatggacc atacaatcgg 8700 gttttatacg gagacattcc attgcccagg gacaggcagg agacagatgc cttcctcttg 8760 tctcaactgc aagaggcatt ccttcctctt ttactaatcc tcctcagcac agacccttta 8820 cggatgtcgg gctgggggac ggtcaggtct ttcccttccc atgaggccat atttcagact 8880 atcacatggg gagaaacctt ggacaatacc tggctttcct aggcagaggt ccctgcggcc 8940 ttctgcagtt tttgtgtccc tgggtacttg agattaggga gtagtgatga ctcttaagga 9000 gcatgctgcc ttcaagcatc tgtttaacaa agcacatctt gcaccgccct taatccattc 9060 aactctgagt tgacacagca catgtttcag agagcacggg gttgggggta aggtcacaga 9120 atctcaaggc agaagaattt ttcttagtac ataacaaaat ggagtctcct atgtctactt 9180 ctttctacac agacacagta acaatctgat ctctcttgct tttccccaca ccttctagtc 9240 taaggagaga tcctgaaatt ccagatagtc ccccaccaac ggggttttgg gcaaaaatta 9300 cgtcctttag attggtgagc ccaggtgcct aaagaaggga acagagtccc aaaatttata 9360 ctagaaatca ttcttatagg agaaactaga agagcaccag ggacagggag tggtttttta 9420 gaagtgggac tagcctctga gaagagaggt gggaggaatt ttgtctgaca ggcattagga 9480 cccaggaggc aagagtcagg gtagatagga aagatgggtg agtctcactt agacaacgta 9540 actttgagag ttctgctcat ggctgcaggg tcaactaact ttttgttggg accctggagc 9600 tgaatggctt tcctctctgt tgacccttgg ctcagcccag aagtgcagga aaagtggaag 9660 ctggttccac acaaaccaac gcttctgact ccaaagagtt aaaggttgtt agagagccct 9720 ttcccagaaa gcctgacacc cgtgtcttta gtccggcagc tgacaggtgc ctagtgttta 9780 gcccttgaat tctaaagaaa aataggacag aatagcaagt gaaagcatat cactgtgtgg 9840 tgatatcgtg gacaagaccc caagatgaca atgctgccct ggggagtgac agacatctgg 9900 caacctgctc aggttccctt ccacactgtg gaagctttgt tctttcactc ttcacaataa 9960 atcttgctgc tgctcactct ttgggtccgt gccatcttta agagctgtaa cactcaccac 10020 aaaggtctgt ggctccattc ttgaagttaa caagaccatg aacccaccag aaggaaccaa 10080 ctccagacac agctgtacta atttacattc ccaccaagat tgtctctttt ctccacatcc 10140 ttggtaacac ttgtctttca tcttcttgat aaaagtcatt ctcattggtg tgaggcaata 10200 tctcattctg gttttaattt gaatttcccc aaatgattag tgatgctgag cattttttca 10260 caaacctgcc agccatttgt atgtcttctt ttgaaaagtg tctgttcaag tcctttgccc 10320 attgttaaat caggctattt gttttcttcc tattgagttg tttgagttct tcacatattt 10380 tggatattaa ccccttatca gatgtatgat ttgtaaatat ttttcccact ctgtgggctg 10440 tctcttcagt tttattaatt gtttcttttt tttttttttt tttttttttt gagacggagt 10500 ctcgctctgt cgcccaggct ggagtgcagt ggcgggatct cggctcactg caagctccgc 10560 ctcccgggtt cacgccattc tcctgcctca gcctcccaag tagctgggac tacaggcgcc 10620 caccaccatg cccagctaat tttttttttt tttttttttt ttaagtagag atggggtttc 10680 actgtgttag ccaggatggt ctcgatctcc tgacctcatg atccgccctc ctcggcctcc 10740 caaagtgctg ggattacagg cgtgagccac cgcgcccggc ctaattgttt cttttgctgt 10800 gcagaagttt gatgtaatct cttgtctatc tttgctttca ttgcctgtgc ttttggatcc 10860 atatccaaaa atcattaccc agacaatgtt gcagagcttt tcccatatgt tttcttctag 10920 tagttttata gtttcaggtc tcaaagtgtg gatgtcaatg gataaagctg tgcttcacca 10980 agcaatctct tgttctttga tcaggaagag agcagtgcga tgatgcaggc accctaggga 11040 ctccaatttt aacaaaggag atttccagtt ttggggtata gtattggctg agattcaggc 11100 ttccctggtc tagcatcatt ggtatgagct gaggtatttg tttccagcag tggcagtggt 11160 gtggacacct cctccacaag gggattttga gcctgaatct ttggccgtcc ttggaattcc 11220 atgcacttcc taagatcctt attaaatttc ttttctgttt aacctagtaa gggtggattc 11280 tgtgttttca gctaagaaca caggtgacat atggatcatc tgagctatga aatggtttag 11340 gtcagtatcc ttgacctata caagcccctc atcagtaacc aacatagtgg tctttcacca 11400 acatatgtct ttcacctcct tggttagata gattcctagg tattttattt ttttaaacta 11460 ttataaaagt gtttgagttt atttgattct cagcttggtt gctgttggtg tatagcagag 11520 ctactgattt gtatacatta attttgtatt ctgaaacttt gctgaattca ttaatcagct 11580 ctaggagctg ttgggagtag tctttagagt tttctaggaa tatgatcata tcatcagcaa 11640 acagcgacag tttaacttcc tctttatcaa ctcagatgcc cttatttctt tctcttgtct 11700 tattactctg gctaggattt ccagtactat gttgaataga aatggtgaga gtgggcatct 11760 ttggttccag ttctcagggg aaatggtttc aacttttccc cattcagtgt aattttggct 11820 gtgggtttgt catagatggc ttttattacc ttaaggtatg tacctttgat gtaggttttg 11880 ctgagggttt taaccataaa gggatgctag ataatgtcaa atgctttttc tgcatctatt 11940 gagatgatca tgtaattttt gtttttaatt ctgtttatgt ggtgtatcac atttattgac 12000 ttgcatatgt taaaccatcc ctgtatccct ggtatgaaac ccacttgatc atggtggatt 12060 atctttctga tatgctgttg gattcagtta gctagtattt tgttaaggat ttttgcatct 12120 atgttcatca gtgatattgg tctgttattt tcttttttgt catgtttttt cctggttttg 12180 gtattaaggt gatcctggct tcatagaatt atttaggaag gattctttct ctgtcttgtg 12240 gaatagtgtc aataagattg gtatcaatgg ttctttggat acctgtcaga attcagctgt 12300 gaatctgcct ggtcctgaac tttttttttg ttggcaattt ttaaaattac catttcagta 12360 ttgctgcttg ttataggtct gttcagagtt tctatttctt cctggtttaa tacaggagag 12420 ttgtatattt ccaggaattt atccatctcc tctaggtttt ctagtttatg tgcataaagg 12480 tgttcatagt agtcttgaat catcttttgt atttctgtgg catcagttat aatagctccc 12540 atttcatttc taattacatt tatttggatc ttctctcttc ttttcttggt taatcttgct 12600 aatggtctat caattttatt tatcttttcc aagaaccaga tttttgtttc atttgccttt 12660 ggtatttttt ttgtttcaat tttatttagt tctgctctga tctttattat ttattttctt 12720 ctgctgggtt tgggtttggt ttgttcttgc ttctcttgtt ccttaaggta tgaccttaga 12780 ttgcctattt gtgctctttc agactttcct ctcagcacca cctttgtggt atcccagagg 12840 ttttgatagg ttgtgcttcc attatcattc aattaaaaga atttgttaat ttccatcttg 12900 atttcattgt tgatccaatg atcattcaag agcaggttat ttaatttcca tgtatttgca 12960 tggttttgag gtttcttttt ggagttcatt tccagttgta ttccactgtg atctgagtga 13020 ggacttgata taatttcaat tttcttaaat gtattgagac ttgttttgtg gcctaccata 13080 tggtctatct tggagaatgt tccatgtgct gatgaataga atgtgtattc tgcagttgtt 13140 gggtagaatg ttctgtaaat atctgttaag tccatttgtt ctagggtata tttaaattca 13200 ttgtttcttt gtgttgactt ctgtcttgat tacctatcta gtgttgtcag agtattaaag 13260 tcccccacta ttattgtgtt gctgtctatc ttatttctta ggtctagtgg taattgtttt 13320 ataaatgtgg cagctccagt attaggtgta tgtatattta ggattgcgat attttcctgt 13380 tgggcaagtt catttatcat tatatataat gcccttcttt gttttttcta actgctgttg 13440 ctttaaagtt tgtttttatc tgatataaga atagctattc ctcctcactt ttggtgtcca 13500 tttgcatgga atatcttttt ccatcccttt tccttaagtt tatgtgagtc cttatgtgtt 13560 aggtgagtct tgtaaagaca gcagatactt ggttagtgaa ttcttatcca ttctgccatt 13620 ctgtaccttt taagtgcagc atttaggcca tttatattca atgttcatat tgagatgtga 13680 ggtactattc tattcatcat gccatttttg cctgaatacc ttgggttttt taaaatttat 13740 tatatttttg ttttattggt cctgtgagat ttatgcttta aggagtttct attctggtgt 13800 gtttggaaga ttagtttcaa gatttagagc tccttttagc agttgtggta gtgctggctt 13860 ggtagaggca aattctctca gcatttgttt gtctgaagaa gactttatct ttccttcatt 13920 tatgaagcat agttttgctg gatacaaaat ttttggctga taattatttt gtttaaggag 13980 gctaaagata ggaccccaat ccctcctagc ttgtagagtt attgctgaga aatcttctgt 14040 taatctcata ggttttcctt tgtagattac ctgatgcttt tgcctcacag ttcttaagat 14100 tctttacttt gtcttgactt tacataactt gatgactatg tgcctaggta atgatctttt 14160 gtgataaatt tcccaggtgt cctttgagct tcttgtattt ggaagtctag atctctagca 14220 aggctggaga ggtttccctc aattattatc tcaaatatat tttccaaact tttagattta 14280 tcttcttcct tggaaacatc aattattctt aggtttcatc atttaacata atcccaaact 14340 tcttggaggc tttgttcatt ttcttttatt cttttttctt tatctttgtt ggattgagtt 14400 aatttgaaag ccttgtcttt gagctctgaa gttctttctt ctacttattt gattctattg 14460 ctgagacttt ctagtgtatt ttgcatttct ctaagtgtgt ccttcatttc cagaagttgt 14520 gattgttttt taattatgct atttcactga agatttttcc cttcatgtat tgtattatta 14580 ttatttttta gttccttaac tgggacttca aatttctctg gtgcctcctt gattagctta 14640 ataattgacc ttttgaattc tttttctggc gattcagaga tttcttcttg gtttgaatct 14700 gttgctggtg agctagtgtg gtcttttggg ggtgttaata aaacattttt gtcatatgtc 14760 caggattgtt tttctgtttt ttttttgttt tgttttgttt tgtttttctc atttgggtag 14820 actatgtcag agggaagagc tggggctcaa gagttgctgt cagactcttt tcatcccaca 14880 gggttctccc ttgatatggt gctctccccc ttcctgtaga gatatagctc cctgagagct 14940 gaactatagt gattgttatt tctcccctgg atctagccac ccagtggggc taccagcctt 15000 ctggctctta tgaggggctg tctgcacagg gccctgtgaa tcatcttcag gtctctcagc 15060 cactgatatc agcatctgtt ctgatggagg tggtagggga gtaaagtgga ctctgtgagg 15120 gtccttggtt gtagatttgt ttattgaatt agttttgtgt tggttgggct ccagccagga 15180 gatggtgttt tcaagaaagc atcagctgca gtagtataga aaggatcagg tggtgggtgg 15240 gatcatagag ctcccaagag attatgtcct ttgtctttgg ctaccagggc aggtagagaa 15300 agaccatcag gtgtgggcag ggttaagcat gtctgtctga gctcagactc tctttgttca 15360 gggcttgctg cagctgctgt gagggatggg gttgttattc tcaggccaat ggatttatgt 15420 ttccagggag attatggctg cctctgctgc atcatgcaag tcaccaggca agtgggggaa 15480 agccagcagt tagttgcagt cctcacgcag ctcccatgca gcccaaaagg ctggtctcac 15540 tctcaccatg ccccctagta acaccaagtt tatttccagg cagctggtaa gcagggctgg 15600 gaacttaccc caggctgcca gcctccttgc tgagaaagca agtagggctt tcaggttttg 15660 tgcctccctg cctgtggcag tttctgtgct gagtctgcac tccaatttcc gcctccccca 15720 gggttctgtt caggaaaact tcacattcag tcaaaattgt tatgcacttc agctagaagt 15780 ttccttctcc ctgtagtctt ttcccagttc ctctggcagc cctccccaag gacccctgtg 15840 agataaagtt agaaatggct tccctgggga ctgagagcac ccacagtgct cttcccgctg 15900 tttcttctac ccctatattt cacttggctc tctaaatttg tctcagtacc aggtaaggtc 15960 aaattcctct tccacgattt ggaccttcag gttccccagt gaaggtgcat gtttgggggc 16020 agaagaactc cattgcaaac tttgggcact cacagttctt caggtgtctc ttggagcatg 16080 cagtggcaac ccacttcctt caaagggtcc gtggattcac ttggctttcc tggtatgttc 16140 ctgcagtagt tcttggagca aaagttcatg atgtgagtct ccatatgctg ctctgtccat 16200 ccaagtggga gctgcaagtt agtcctgcct cctatctgcc tttttttcca accctgccat 16260 tggtctctct taacagcagg agaggctccc ttcatcctct gccttttata ttttttgtgg 16320 tgcttattag cccttgttac agttacctag ctcaaggctt attgtagttt ctttcattct 16380 tattttccct ttctgtctgc attcctttag ctttcattga ccacctactc tgtgccagac 16440 actaaagaca tattagaaaa gaattataca taattctttt ctaattatga cacaaattct 16500 ttatgtctaa ttagacataa agaaaatata ttatactccc ttccaaagaa ctgacagaat 16560 tctcaaatga ccagcaagca agcaacaact aaaaggctgt atgatgttaa gtcatctaca 16620 gcaaagtaaa ataatgcaat aactaaatgc ataggctttg gagtcagaat cacctacaca 16680 cagattcagg ctctgaggct agctggtgat ttttactaaa ttatttaatc ccttaagctt 16740 caatttcccc atctataaaa taaggttaat aatgagttat gcatagggtg gttgtgaaca 16800 tgaaataaaa tagtgtacac taagtactta atagagtgcc caattttttg taatattcaa 16860 taaatattat tgctaaaaac aagtttgtct gaggatgtca ggaaatccct cacagaggga 16920 aaataacatt attacttaaa ggaagcattc ttaatctaag caggcagatg cacctgtgca 16980 ttttgtttct tagtcaacaa ttattcattt taaaagactg tttcttgaaa catcctggga 17040 tgaggagtat cctgttttga ttcttctatt ttgcaaacag agaaaatgtc agaagctaat 17100 cagctcatcc aagtgcatac cagttttgtt atttaaccag taaaggcttt ctgtgagaaa 17160 agattatgca gttaatctac attaaatact tactctgtac aaagccttgt gggggatata 17220 gaaatgtaaa accactaaga gacaccatgt gatgtcactg ggagttaatg ttgattccaa 17280 gatgagcact ccacaaaggc agaaaagttg aaactgtcat tctgtatgcc agactacagt 17340 gataggtata aagaagagat catggtcaag aggaatgatc agaaaagact gtcacaaagg 17400 aagtgaactt gaaaagctgg gcttaaaaaa agaatggaat ttagacaatg ggtagagaag 17460 ggtatgggga gtgtattagg aaaaacagaa tttgagcaaa gggcatggta gtgaagacac 17520 acaacactca ggagaaatca agccggcaaa ttctctttgt gcagttaaga ggtcaaatga 17580 ctttcccaag atcacacaat tatttaggac taggatgggg tcttctaatt tgcagtttga 17640 cttgttctgc catgtgcaag atttataact gatgattggg tgttgcaaga agggcaacat 17700 ttcatcatcc tcaaagaaat gagacaaaaa gactgtctct aaggcttatt ggatgcagat 17760 gtggttgcct taaaattcca gcagactcgt gtttaccttc tgtggctgag caggaccatc 17820 ctgtaggaag gctgctactg ccgacctggt actcccacca catcctgaca ctcagactct 17880 gagtatgtag ctttatggga atatccaagg ccataggact tcctcaggac agccctggca 17940 catggcccag aaaggtgttt gggccacata gtctatcatg gctcttcaga gggacagcag 18000 tgcagggagc atttctggac tttatttccc tggattgaac aaaatttgtg agtttccagt 18060 tagagttagc tcttcttagt gttgtccttt tttttttttt tttttttttt tttttgagat 18120 ggagtttcgc tcctgttgcc caggctggag ggcaatggtg taatggtata ctcttggctt 18180 actgcaacct ctgcctccca agttcaagcg attctcctgc ctcagcctcc caagtagctg 18240 ggattacagg cgcctgccac cacactcagc taatttttgt atttttagta gagacagggt 18300 tttaccacat tggccaggct ggtcttgaac tcctgacctc aggtgatcca cccaccttgg 18360 cctcccaaag tgctgggatt acaggcgtga gccgccatgc ccagctgtgt tgtccttctt 18420 gataagcagt gccatttaga agattatatg ctggagaaag aagatctggg ttcaagtcct 18480 tttctagctt tgtgatttgg aacaagttga ttatgatatc ttgttaccat gagattggtt 18540 atgccaatct ccttatttta tgggttaaaa aaaccccaga agctcagaag agtttaataa 18600 cctgttcaaa gttatatgat atgttaaata tataaatctc cattgaataa tatcacctct 18660 atcttcctta caaagctttt atgaggctca aataagaaaa taaatatgaa tattcaccac 18720 agtacttgac atggatgcta ggaaccctta atgttccctt ttcccagtag taaagcagta 18780 gtaatcagtc acacacacac acatgacacac acacacagac accccacata tacagcatag 18840 tgcgtaacac acatacatat aagatttatt taaaacgacc ttgagaagaa aattattaac 18900 tctgggtcag atgtgtttat aagcccattt ctgggaccac attctgggct ctaccatatt 18960 gtatcttggg gtcatggctc tctcacaact ggagagaggt gctccaagca tcaattcata 19020 aaagctgtta ctagcacact atctctatcc tgtttttttt aaaataatac tatctacctt 19080 gccttttatg aggtgcagag cctagcacaa atgtgtctaa tcaggctgat caaaacaagg 19140 ggaattgcac tggtatttgg gcctggggtg cacagcaaaa ggtcaaagac ttacacgacc 19200 aggaaagctt gtgacttggt tattccactt atgatgtggt ttttatataa atggcctgca 19260 ttcatttaag gacaaacata agacagccct tctcctagct tcagaataga ctgaaagtgg 19320 aggagaagag cagagagaaa ttttgttttt ttttttggtt tggttttagg aaataattta 19380 caatatttat attctaggaa ttgccctaga gaaattagaa ttttttaatt aaaaaattta 19440 ttttcctctt agcttcttgc aatgtccaca ttatacggtg cattaaagct ataaggtctt 19500 attcctattt cagcaattct caatcagata atctcagaat gcttgttaaa acacagatct 19560 gtgggctttg atccagatca actgatttat aattacttgt ataagtaagt caaataagtt 19620 cttggtgaaa ttctcatgtc cactagaatt tagaaaccac tgcacactcc cttctagcat 19680 ctgaaatcac ttctattttt atagataaaa tagcctgctt ttcaaactct tccatatttg 19740 tagctttggg tttctagatc tcttttaagc tcaccaagat ctagtattca gcctagtact 19800 cagccagcga aattagatgg agtagaatgg aaattctact tgtgcttccc ataataaagc 19860 ttcactcttc cctcttcctg cttcaacttt ctccacaaac acacagcagt taaatataca 19920 tatttttaaa gttctattct tatgcaccac agagcttaag aaacactgct ccccttgtgg 19980 taggtgctgg accagccaat gtttttgatt agtaggtgag gcacatgagg agtttgtggt 20040 gaatgcatca gtgggaggaa gaaaggcatg aaatgaagaa tcgacatgat tgtggtgcct 20100 ggagccagag agttagctgc tggttccagc tctggtatta actgagggtg tgatctgagg 20160 tgagtcatgc ctctctttgg gccacagggt gccttagggc taggcagaat tctttaaggc 20220 agagcttcct agcttatatg tagtatcaca ctggtgtgcc acaaacggat tataggtgtg 20280 ctatgaatta ctgcgttcct cagctctcag aatgtgcctc tagccaagag aagcctcatc 20340 agagtcttct tggggactgg tctgagcagt gtaggagtcc aaggaccacc ctcatagtcc 20400 ctagaggagg cagtgggcac catgagtcac atttaccatg catttctcca ctataatgcc 20460 ctgaatgcac acagccaaga aggtaggtgt tctactgcat gggcatctca gcagccatcc 20520 atcctagcag ttagcaccgc agaccattct aggtaaggcc tgaggatcag taggtagttt 20580 gtgtccagct gcccagaagc ttagagctta gcccaagatg tggccagtgg ggatgagtga 20640 gtgcagaaac atggtgggga tttctggtct gcccagcaac acgtgatagc ccagaatctg 20700 ttttcacata tatcagatac tcctgttcat cttcagcaga tggacaaaaa agtccattta 20760 gtggtttcca tgctagctgt agggcaactg ctcttacaat gcatatgcaa tatacaaatt 20820 agaccttcgt tattattttg gaatgctaga tagcataaaa gtctgaattt aaagtacctt 20880 tgctctatca taaaaaatta aacattaact tgtcagtata agaaaaggat aagctattag 20940 gttctttaat ttcaaatgtt gcaaatcttc aaatagttgt aaacaatggt tttaattttt 21000 taaattatct tattgtggga atgaaggttc ttgttgatac acaccactag gaatttgaaa 21060 caatcatcat taagaagtct tactcagagt tttgcatagc tattttgaat atggtatctg 21120 ttggtaaaaa gatatgtcaa tggtaataag ttcaaatttc taatttttta aaattatttt 21180 atttggaacc tttatataaa tttaatattt gatatttttc taaacatctt gtattttatt 21240 tttcctataa ggatataaat ataaagagtg acaatttttt tcactgaact ttgttgagct 21300 attcccagat caccctccag gttttgtaga gaaaacattt gtacaaaaca aaaagttttt 21360 ctatgtgtgg aagatgtgac aaagattgcc tacagtgttt tagggcagtg gttctcaact 21420 ggggatgatt ttgcttccca aagggcattt gacaatattt gaagacatct tctgtttgtc 21480 accattgggg agctacttat ggtgtttaac aggcagaggc caggaatgct gctaaatacc 21540 ctacaatgca caggaaaatt ctccataaaa agaattatca gacccaaaat gtcaatagtg 21600 ccaaagatag aaactgtgtt ctagagcctg tctcattctt atatcctgat tcagaattat 21660 aaatgttctc atagtggttg gcaataacgg atgtggccag aaatggccag ctctaatctc 21720 ctaactgcat ctataatagc agaccctgta ggcaagcaaa atgtggggca ggacttccta 21780 taggcctcct tgagatggta tgcatttcaa agcagcagtt gtgtaacttt tatggctaca 21840 aagttagtac acccaggtga gcatcttctt ctcccatttt atttttttta aatatcatat 21900 tctagaaatg acatttttgt tccattggat tgtgactcat gttatttttc aacaacgccc 21960 cttcctctag ccccaactct ggatctcacc atgactagcc tggctggg gggtggccca 22020 aaaggcagag atttgcactg aaaatctttt caaatcattc ccttctcctt cccgttcgaa 22080 ttcgaaaggg gaattcaaat tccttcaaat ttatttcgga gtcgaagtca tcctattgtt 22140 tggcattaat gtgctacttc taagactaaa caaatcttcc atatccttcc tctctgatgc 22200 actcatcctc ttggttgttt tgttttgttt tttaacacgt caggatgatt caagtgacta 22260 gggattaaac cagtctggac agccatactc ctttatcaat acgactccta ccactccttc 22320 agtcaatttt tacaacaggt tcacatctac catctggtac caagagcagg tttaatggag 22380 catcagacac ttttatttgt cctaggactt aacagaggat tggcaattct attaataaat 22440 gtacctggat agaagaaaga tcaatagatc tagggtcttt gttatataaa attaagcaag 22500 ttattcagtc attagagcct cattttgctc atataaaaga gtagtagtga cgagagggct 22560 gctgattttt ccccaactta aaatgaaaga aaaagcactg agaaattttg aaaagcatgt 22620 cagtattagg aaatgcacac tttcatggta ttgactcatt gttaatgtat catttatact 22680 gaaatgagga agttgggttt tacagttgga atcaggaact agtttacatc ctttgcaggg 22740 tttagaggcc ctggaagatt atggtcatca gcgtgacctg gatagcgctt taatgctggc 22800 aaaaacaaac catcaattta tttaagaaat acatattaga aacctagtat gctctttgta 22860 aacaaatagt acaaagtttt ttttctattt tgcagaggag aaagctgaag caccagatgg 22920 ttaaaaggac tgttcaagac agccttgcaa ttttgaccaa ggaagaaagc tgaagagtgc 22980 tagggcaaga gaggaactac gtccagaaca attcataatt ccaaattctc acttccatga 23040 tttcaatgct gaatgtgtac ttctctagct aaaaatacaa ttgcttaagt aaaatcatca 23100 ttatttacag tcttgctgaa 23120 <210> 3 <211> 4938 <212> DNA <213> Artificial Sequence <220> <223> TCONS_00184955 <400> 3 tgtgagcaac atggctgttt atttcacctg ggtgcagacg ggctgagtcc gaaaagagag 60 tcagccaagg gagataagtt tggggccgtt ttataggatt tgggtaggta aaggaaaatt 120 acagtcaaag ggggtttgtt ctctggcggg caggagtggg ggttgcaagg tgctcggtgg 180 gggtgctttt tgagccagga tgagccagga aaaggacttt cacaaggtaa tgtcatcagt 240 taaggcaagg gccggccatt tgcacttctt ttgtggtgga atgtcatcag ttaaggtggg 300 gcagggcata gtcacttctt ttgtgattct tcagttactt caggccttct gggcgtatac 360 gtgcaagtca caggggatgc gatggcttgg cttgggctca gaggcctgac actaaccaac 420 ctcccaaatc attgagctgt ttgttaaaaa gaaaaaaaag gaaaaggaaa aagcatgaca 480 ttgtgtatcg atttttttgt tgttgaccaa aatcacacac atggaaacat gtaattcaac 540 agagtgggat agcgatcaga ttcttggctt agtattacta atgggcagga ttttacaacg 600 agcaactatc agattattcc tttcagtgat tcttatggca tctaaattac tgaataaatt 660 attaatcagt gaatcaaatt gattaaaatt attaaatgaa tgctcagcat tagttgaaaa 720 ctgttgtgtg aaacatgtct acccagaaaa gtaacattct ataaatacta ttaaacaact 780 tagctatatt atttttaggt attaagttat atgtcaagca gttaaagtga atttcagagt 840 aaaagtaagg catgtttctg agcaacattg ataattcctt aatttgcaaa tttcttcttt 900 cttacttgga tgcttggaat atagtgtgag attttttatt tctaaatttt gttgtatctt 960 ctattacata actgcattgt ttgacaatta taaaatgcaa gtgttttttg aatgatttta 1020 agaatttggc ttaaaaactg attgatacaa tgtattattt gtactaagaa gtaacttgac 1080 ccaaaacacc ctttatgttt gcttagggta tttttcttca atgcctgaaa gttaaaggta 1140 ttcctgtcac aactgtaaac aaacttaccc taaatgtgtt aaaacatatt cttgggtact 1200 ctatttgtgt atctttcgtg ccttgaaaat ctgaaggtta atccaaactc acatgtttta 1260 gcgtatttga gaaaaaaaaa ctacttttaa tatcagcctt ttaaatttca tgaagatttt 1320 ggtgaggaat aatagtatat actttattga caaaacttgg aaagtttctt tctataaaat 1380 gggaaatact caatatctaa acccaggtca gtcatgggag atcagtattt atttaacgtt 1440 ggatgttttg tgttttatat ttataatgtt caaaaatgca agcataacat ttaatctttg 1500 tccacatggt tttacaaaag taaatcttaa attacctcgc ttttctcata tgttctcata 1560 ctttctcaaa tcactataaa gaattacttg ttatctatta aaaatcccct tcactcaagt 1620 ctgtattatg gtttcaccaa atattctgtg atgtagccca gaaaatccac accttttgta 1680 ctttttaatt tgaataatca tgtgcttagt cccttggatt gctgccacat cagtttaaca 1740 tgaagcacat tcccatgtca tcaaggtgtt ggctcagatt tattcttaat tggatggtta 1800 aagcatacac taccttgtta cagttggttt agtgtagtgg attattgaca tgacaccatg 1860 agaacatgtg gaattttata ccacatttat aaaacatgat tttgttttct acccttcaag 1920 gtaaacatga aaagtaaggt ggtatctgtg tacttgtaca taaatccaaa attatagttg 1980 ggaaaaaaat ttatatatga aaatgtcaaa aaaattactt tgttgcaaga aagaaggtta 2040 attgattatt aggacttttg ataagttagc aaatcggata ctgttttcaa atcttagatt 2100 cagtattggg ctaacaatag ttctgtttta aggtttctat gaggactaaa tgagagaact 2160 tactaaaaaa tgcattcaat atgtgtttat tatgtcatta tctcgttact ccctttttag 2220 ggtttatgat tcaagtctca tagaagttta aatcacttgt caaatgtaac ctatttcaga 2280 atcaccaagg acttaacgct ttttattcta aaaactgttt tgtaaaatgt ggaataaatg 2340 accagtgcca ttattcagtc caatttgttt attttacatc aaagaaatct gagtcacaga 2400 aggcttactg tatcagccca tggccaggcc attaggtttt gagtaggacg gaaattgtga 2460 tgatacatac tttcatattt tgagatgtat tgatattgtg agtacaaaaa tgatgatttg 2520 ataacagcat agagtgtggt aatccagcaa aatacattat attttgaaat gtgaagaata 2580 ttactgattt tgagtttgtg ttttgtttta atctatgaga aatattgcat ctcacatttg 2640 acatgtttaa aaatgtacgc atatctcgct gggtgcagtg actcaggcct gtaatcccag 2700 cactttggga ggctgaggcg ggcagatcac gaggtcagga gatcgagacc atcctgacta 2760 acatggtgaa accccgtctc tactaaaaaat acaaaaaaaa caaattagct tggtgtcctc 2820 catgcaaagc ctgtggtggg tcttgctctg ggactagttg agcagcattg cactcgtgtt 2880 gt; cttgacttga gaatgattga gaagtgtact tttcagtttc ccaagtacat atttttgggg 3000 gagaggactg tgttgcattt ggccagagaa tatgtgacct ttcggttgtt gagggactgg 3060 tgtgtacccc tgggggctcg gtatccactt ggaggttggg tgtccgtgtg gaacctgatg 3120 tacctgtgga cctggttgcc cacatgggtc ctggtgtcca cctggagcct gatgtttccc 3180 aggggcctgg gtatccactg gggtcccgat gttcatctag gagctggtgt tcacctaggc 3240 cctgatagtc acctgggggc tgggtatgta cctgaggcct catgtccacc tgtgctgtag 3300 gtatctatgc atgggctgtg tgccaacctg gtgcctcatg tcctcctatg gattagatac 3360 ccaactaggg tttggtgttt acctggaacc tgatatccaa tggggcccaa attctccacc 3420 tggggactgg tgtctggatg gagtcttaca gctaccctgg ggtgtggtgt cctcttgagg 3480 tgtggctgtg aacatggggc ctaaagtcta cttagagttc agtgtctacc tggagcctaa 3540 tgtgacctgg ggccctatgt caacctgggg cttggtattt aggtcgggtt cgggcgacca 3600 cccagggatt gatctcagct ggggcctgat gttttcttag cgcctggtgt tcacctgagg 3660 cctgggtgtc aacttgggac tggatagcca actgaggcct gagtgtttct tggtgactga 3720 ggacttcctg ggacccatat ttcctggacc cggattttca catggagcct gatgtctgga 3780 gttctgagtt ctaggtgttt acttgggacc cagatgtgca ccttggcaga gcctccgtaa 3840 caaaggccta gggccaccag gaggctgtga aaaagaagca gggcgtctct ttccccggac 3900 acttgagagt ttgtcagagc cttcagcgac agagcaggtg ccctggacat aggaacccag 3960 gcacctgggc actgacatca cctcaagggc cacttgtgcc ccaggctata gagtctcctg 4020 agccaccagg gggtgcgcgg agtggggagg gcatttgttc acgtgcagcg gcctcttgcc 4080 actgccatct gtctccacag ctaagttgcg ggacctgtgg gaaggagggg gagggcaaag 4140 gtcattgtca caccacctgg gccgcaggtg acaggcaagc tcccactgag gctgcatgga 4200 agtccccaca accctggtgg agggtaggtt ccaaggtgca gccccagccc tacccctagc 4260 ctggggtgaa cacctgggcc tgggaggggc agcagtttat ggcgctgctg tgtcccaagg 4320 tctcaggaag cctggggctc cttgtaggtg gagaaatcaa aacgatatgc ttgagttttc 4380 agaatagccc agggcttgcc ccaagttctc gaataaaggt agttaccccg ttccaagaca 4440 gagctaatca gggctgagag gaatggaggc gggaaggcac cagcacgcag aggcccccaa 4500 atccccagca aggccccctt actcaggcct ctgccccaga gccagggtct cccagccacc 4560 tccgatgtaa gcgcaggctc ctgacccagc gcaggctcct gccctcgccc tgcagtccca 4620 ccccgtcctc caggccggcc ctcctgcacc attcttgccc ctgacatttc ttttccaagc 4680 aacaaccaga aatattcctt taaagtgaaa gcagatctta ccatctcatc ttgtttcacg 4740 ccacctcacc ctgggttccc atcatttccc agtaatgccc aaagtcctgg gcccctggct 4800 tgggcacctc gagaccagtg agtgtaggat gctggctgcc ctcggctagg ctggccatgc 4860 tctgctcagc caagcccctg tccttcctgc aggtgccagt ccgtccctgc ctggccagca 4920 cccccgtgcc cacgggcc 4938 <210> 4 <211> 23 <212> DNA <213> Artificial Sequence <220> <223> primer <400> 4 ccaaagtgct gggattatag gcg 23 <210> 5 <211> 22 <212> DNA <213> Artificial Sequence <220> <223> primer <400> 5 cccgagaatc cgaagttcca ga 22 <210> 6 <211> 19 <212> DNA <213> Artificial Sequence <220> <223> primer <400> 6 ggtgggttcg tggtctcgc 19 <210> 7 <211> 23 <212> DNA <213> Artificial Sequence <220> <223> primer <400> 7 tggacgtagt tcctctcttg ccc 23 <210> 8 <211> 19 <212> DNA <213> Artificial Sequence <220> <223> primer <400> 8 ggatgcgatg gcttggctt 19 <210> 9 <211> 22 <212> DNA <213> Artificial Sequence <220> <223> primer <400> 9 caggactttg ggcattactg gg 22

Claims (9)

Expression levels of transcripts for prediction of lung cancer prognosis, selected from the group consisting of transcripts TCONS_00075018 for the nucleotide sequence of SEQ ID NO: 1, TCONS_00004993 for the nucleotide sequence of SEQ ID NO: 2 and TCONS_00184955 for the nucleotide sequence of SEQ ID NO: Wherein the composition comprises at least one agent for measuring the prognosis of lung cancer.
The method according to claim 1,
Wherein the agent is a primer pair or probe that specifically binds to the transcript.
3. The method of claim 2,
Wherein the primer base pair consists of a polynucleotide selected from the group consisting of SEQ ID NOS: 4-9.
A kit for predicting the prognosis of lung cancer, comprising the composition for predicting lung cancer prognosis according to any one of claims 1 to 3.
5. The method of claim 4,
Wherein the kit is an RT-PCR kit or a DNA chip kit.
A composition for predicting the prognosis of lung cancer according to any one of claims 1 to 3 is applied to normal lung tissue samples and lung cancer tissue samples isolated from individuals to be predicted for prognosis of lung cancer, Wherein the method comprises the step of determining the level of expression of the cancer.
The method according to claim 6,
Wherein said subject is an individual who has undergone a lung cancer treatment procedure after the onset of lung cancer.
The method according to claim 6,
The detection of the transcript is accomplished by RT-PCR, competitive RT-PCR, real-time quantitative RT-PCR, RNase protection assay (RNase protection method, Northern blotting or DNA chip technology.
The method according to claim 6,
Wherein the prognosis of lung cancer is determined to be poor when the expression level of the progenitor for predicting the prognosis of lung cancer measured from the lung cancer tissue sample is increased more than two times as compared with the expression level measured from the normal lung tissue sample.