RELATED APPLICATIONS

This application is a National Phase of PCT Patent Application No. PCT/KR2018/004732 having International filing date of Apr. 24, 2018, which claims the benefit of priority of Korean Patent Application No. 10-2017-0052365 filed on Apr. 24, 2017. The contents of the above applications are all incorporated by reference as if fully set forth herein in their entirety.

FIELD AND BACKGROUND OF THE INVENTION

The present invention relates to a group classification and prognosis prediction system based on biological characteristics of gastric cancer.

Globally, gastric cancer is the third highest cause of cancer-related mortality and is the most common cancer particularly in Korea except for thyroid cancer, which is known to have a relatively good prognosis. In Korea, the survival rate of patients with gastric cancer has been increased due to early detection through national health examination, surgery standardization, and the discovery of anti-cancer therapeutic agents or the like, but despite the currently standardized treatment, about a half of patients with stage II and III advanced gastric cancer experience recurrence.

Cancer has been recognized as genomic disorder, and efforts have been made to classify cancer according to molecular and biological characteristics in line with the development of genetic testing technologies, such as next generation sequencing (NGS), instead of classifying cancer according to existing anatomical and pathological phenotypes. It has recently been reported in the Cancer Genome Atlas (TCGA) project that gastric cancer can be largely classified into four types according to various molecular characteristics thereof. This indicates that, even with the same clinical stage in an anatomical sense, prognoses and the degree of chemotherapy benefit may differ according to molecular and biological characteristics.

According to recently reported TCGA project results of 295 gastric cancer patients, gastric cancer is classified as four types: {circle around (1)} Epstein-Barr virus positive (EBV positive); {circle around (2)} microsatellite instability-high (MSI-H); {circle around (3)} chromosomal instability (CIN); and {circle around (4)} genomically stable (GS). Through this massive cancer genome sequencing, it can be seen that gastric cancer is divided into heterogeneous subgroups that are molecular-genetically distinguished, rather than having one cancer type. Thus, it suggests that to realize the personalized treatment of gastric cancer, it is necessary to identify subtypes based on molecular-genetic and pathological characteristics, discover corresponding target genes, and apply treatment accordingly. In addition, according to gastric cancer research results, it is reported that the prognosis of gastric cancer can be classified according to the subtype of gastric cancer.

If the prognosis of patients after chemotherapy treatment following gastric cancer surgery can be predicted, it will be a ground data capable of establishing a treatment strategy suitable for each prognosis. Currently, in standardized treatment practices, postoperative adjuvant chemotherapy treatment is used in all patients with stage II and III advanced gastric cancer. This, however, may be an undertreatment in groups with bad prognoses. Therefore, it may have a clinical significance for patient groups with poor prognoses if it were possible to develop strategies for other additional treatment methods in addition to the current standard treatment.

Since 2010, it has been discovered that in the case of stage II and III advanced gastric cancer, adjuvant chemotherapy treatment after standardized D2 gastrectomy increases the survival rate of gastric cancer patients, and currently, this corresponds to standard therapy. Traditionally, gastric cancer has been classified according to anatomic and pathologic phenotypes thereof, and cases of stage II or higher according to TNM stage classification receive chemotherapy treatments, but currently, there is no other method of predicting a prognosis according to chemotherapy treatment than TNM stage classification.

SUMMARY OF THE INVENTION

An object of the present invention is to provide a composition for predicting the prognosis of advanced gastric cancer, the composition based on a quantified value of an mRNA expression level of a target gene group, through which the postoperative prognosis of a patient with advanced gastric cancer (Stage II and III: based on AJCC 6thEdition) is predictable.

Another object of the present invention is to provide a method of providing information for predicting a prognosis in terms of the survival rate of patients, the method based on a quantified value of an mRNA expression level of a target gene group, through which the postoperative prognosis of an advanced gastric cancer patient is predictable.

Still another object of the present invention is to provide a method of predicting a prognosis in terms of the survival rate of patients, the method based on a quantified value of an mRNA expression level of a target gene group, through which the postoperative prognosis of an advanced gastric cancer patient is predictable.

According to an aspect of the present invention, provided is a composition for predicting a prognosis of stage II and III advanced gastric cancer, the composition including: an agent for measuring an mRNA expression level of a target gene group including TFF1, TFF2, VSIG1, CNN1, NEXN, SCRG1, SORBS1, SPARCL1, AURKA, BUB1, CDC20, CEP55, PTTG1, UBE2C, CD8A, GBP1, GBP5, GZMB, NKG7, WARS, ANTXR1, SFRP4, VCAN, CDH17, CDX1, and MYO1A; and an agent for measuring an mRNA expression level of a reference gene group including ACTB, ATP5E, GPX1, UBB, and HPRT1.

The present invention also provides a kit for predicting a prognosis of stage II and III advanced gastric cancer, the kit including the above-described composition.

The present invention also provides a method of providing information for predicting a prognosis of stage II and III gastric cancer or a method of predicting a prognosis of stage II and III gastric cancer, each of the methods including:in a sufficiently statistically significant number of reference samples and biological samples obtained from stage II and III advanced gastric cancer patients,measuring mRNA expression levels of a target gene group and a reference gene group, the target gene group including: a gastric signature consisting of TFF1, TFF2, and VSIG1; a mesenchymal signature consisting of CNN1, NEXN, SCRG1, SORBS1, and SPARCL1; a proliferative signature consisting of AURKA, BUB1, CDC20, CEP55, PTTG1, and UBE2C; an immune signature consisting of CD8A, GBP1, GBP5, GZMB, NKG7, and WARS; a stem-like signature consisting of ANTXR1, SFRP4, and VCAN; and an intestinal signature consisting of CDH17, CDX1, and MYO1A, and the reference gene group including ACTB, ATP5E, GPX1, UBB, and HPRT1;calculating ΔCq values of the target gene groups of the reference samples and the biological samples according to Equation 1 below and inputting the values to a computer program; andperforming non-negative matrix factorization (NMF) and NMF-based clustering on the values input to the computer program to be classified into a plurality of clusters, calculating a score value (SV) by applying a score (d′ik) of the target gene group in each cluster to Equation 2 below, classifying the clusters into an intestinal molecular subtype, an inflammatory molecular subtype, a mesenchymal molecular subtype, a mixed-stromal molecular subtype, and a gastric molecular subtype, and predicting a prognosis of the molecular subtype to which the biological sample belongs by analyzing the prognosis in terms of overall survival,wherein the molecular subtypes of gastric cancer are classified such that a cluster in which the SV of the gastric signature is a maximum value is determined as a gastric molecular subtype; among clusters except for the cluster determined as the gastric molecular subtype, a cluster in which the SV of the mesenchymal signature is a maximum value and the SV of the proliferative signature is a minimum value is determined as a mesenchymal molecular subtype; among clusters except for the cluster determined as the gastric molecular subtype and the cluster determined as the mesenchymal molecular subtype, a cluster in which the SV of the immune signature is a maximum value and the SV of the intestinal signature is a minimum value is determined as an inflammatory molecular subtype; among clusters except for the cluster determined as the gastric molecular subtype, the cluster determined as the mesenchymal molecular subtype, and the cluster determined as the inflammatory molecular subtype, a cluster in which the SV of the stem-like signature is a maximum value is determined as a mixed-stromal molecular subtype; and a last remaining cluster is determined as an intestinal molecular subtype, anda prognosis of gastric cancer is predicted, in terms of overall survival, such that one classified as the inflammatory molecular subtype is predicted as a good prognosis group; those classified as the intestinal molecular subtype and the gastric molecular subtype are predicted as intermediate prognosis group; and those classified as the mixed-stromal molecular subtype and the mesenchymal molecular subtype are predicted as bad prognosis group:
ΔCq=(Cqvalue of target gene)−(Cqmean of reference gene group)  [Equation 1]wherein the Cq mean of the reference gene group denotes a mean of Cq values of the reference gene group including ACTB, ATP5E, GPX1, UBB, and HPRT1,

SV⁢⁢(Score⁢⁢Value)=1t⁢∑i∈SNθ⁢⁢dik′[Equation⁢⁢2]wherein SV is an expression mean of each signature in the clusters obtained from NMF-based clustering, t is the number of genes (i) belonging to each signature, SNθis signature (θ=6), k denotes the number of clusters, which is an integer of 2 to 7, and d′ikdenotes a score based on a distance between the median of total gene and a mean of each cluster and is obtained according to Equation 3 below:
d′ik=sign(dik)(|dik|−Δ)+[Equation 3]wherein a critical value (Δ) is set at 0.1 so that genes with no specificity according to molecular subtype are converged to 0, sign(dik) denotes a sign of dik, and dikis obtained according to Equation 4 below:

dik=x_ik-x_imk⁡(si+s0),⁢si2=1n-k⁢∑k=15⁢⁢∑j∈Ck⁢⁢(xij-x_ik)2[Equation⁢⁢4]wherein

x_ik=∑j∈Ck⁢xijnk
is an expression mean of the (ith) gene in molecular subtype (k),

x_i=∑j=1n⁢xijn
is a total mean of the same (ith) gene, mkdenotes a degree of freedom

(mk=1nk+1n)
for correcting a standard error ofxik−xi, sidenotes a standard deviation of the entire sample of the (i) gene belonging to molecular subtype (k), and s0denotes a median of si.

According to the present invention, an algorithm capable of predicting the prognosis of advanced gastric cancer in terms of overall survival by using a quantified value of an mRNA expression level of a target gene group, through which the prognosis is predictable, has been developed and this can be used as auxiliary information for determining a treatment method of a gastric cancer patient.

