Non-coding RNA for cancer detection

Abstract

Providing non-coding RNA for cancer detection. The present disclosure generally relates to methods based on detecting or quantifying non-coding nucleic acid sequences in a sample. Detection of non-coding RNA molecules in a sample or diagnosis of a subject, particularly cancer, including breast cancer. The invention described relates to the identification and use of molecular biomarkers for cancer, such as breast cancer. and a biomarker that indicates the presence of and can be used to accurately diagnose breast cancer in a subject. The present invention provides novel small non-coding RNAs that function as a transcription factor.

Description

[Technical Field]

[0001] Related Applications This application is a continuation of U.S. Provisional Patent Application No. 62 / 584,899, filed November 12, 2017. No. 60 / 699,999, filed on May 1, 2003, the contents of which are incorporated herein by reference in their entirety.

[0002] The present disclosure generally relates to methods for detecting or quantifying non-coding nucleic acid sequences in a sample. Detection of non-coding RNA molecules or target diagnostics, particularly molecular biology of cancer, including breast cancer Marker identification and use. [Background technology]

[0003] Widespread reprogramming of gene expression is a hallmark of cancer development. Systematic identification of regulatory pathways that drive pathological gene expression patterns is crucial for understanding and improving cancer. Over the years, numerous regulatory mechanisms have been identified that regulate the function of cancer cells. It has been implicated in the oncogenic expression of genes involved in differentiation, survival, invasion, and metastasis. Although much research has focused on the transcriptional pathways underlying carcinogenesis, post-transcriptional regulatory pathways are also important. have emerged as key regulators of processes such as gene silencing. MicroRNAs (small non-coding RNAs), a subclass of small RNAs, function in A) was one of the first characterized post-transcriptional regulators of breast cancer progression (1). RBP-binding proteins (RBPs) are also important post-transcriptional regulators of gene expression, with several specific Several RBPs have been shown to affect carcinogenesis and cancer progression (e.g., 2-5). Recently, other classes of small non-coding RNAs, tRNAs (6) and tRNA fragments (7 ) has been demonstrated to play a fundamental role in breast cancer progression.

[0004] Although a diverse repertoire of regulatory mechanisms is involved in cancer, there are commonalities among them. Their distinctive feature is that they exploit or dysregulate existing pathways within the cell. In other words, cancer cells overactivate oncogenic pathways and cause tumors. To downregulate tumor suppressor pathways, somatic mutations (e.g., KRAS, 8), gene fusions, In cases of BCR-ABL, epigenetic modifications (e.g., promoter hypermetastasis) 10), and disruption of regulatory mechanisms (NFkB transcription factors, 10). (11, 12). These strategies may be used to investigate the pathology of pre-existing regulatory programs. While dependent on the node, cancer cells may develop specialized regulatory pathways that drive tumorigenesis. There is the often overlooked possibility that a new system can be created. Summary of the Invention [Means for solving the problem]

[0005] The described invention indicates the presence of cancer, such as breast cancer, and accurately diagnoses breast cancer in a subject. The present invention provides novel small non-coding RNAs that function as biomarkers that can be used to In some embodiments, the methods of the present invention involve measuring extracellular circulating small RNA molecules in a suitable sample. In some embodiments, the sample is a human serum sample. In an embodiment, the sample is a fractionated human exosome containing exosomes containing small non-coding mRNA. This is a serum sample.

[0006] The present invention also relates to detecting the presence of non-coding RNA in a blood or serum sample. In some embodiments, the present disclosure provides a method for detecting hyperproliferative cells in a subject. Method for detecting the absence, presence, or amount of non-coding nucleic acids in a serum or plasma sample In some embodiments, the method of the present invention comprises extracting total RNA from a sample. and detecting the presence of non-coding mRNA sequences, and Correlating the amount of RNA to the likelihood that the subject contains one or more hyperproliferative cells In some embodiments, the methods of the invention involve isolating total RNA from a sample. and detecting the presence of non-coding mRNA sequences, and the amount of non-coding mRNA. The method includes correlating the results of the analysis with the likelihood that the subject contains one or more cancer cells. In some embodiments, the methods of the invention involve isolating total RNA from a sample and extracting non-coding RNA. and detecting the presence of non-coding mRNA sequences and determining the amount of non-coding mRNA in a subject. In some embodiments, the method further comprises correlating the likelihood of the tumor containing a plurality of solid tumor cells with the likelihood of the tumor containing a plurality of solid tumor cells. In the present invention, the method involves isolating total RNA from a sample and extracting non-coding mRNA sequences. and detecting the presence of, and measuring the amount of, non-coding mRNA in one or more breast cancer cells. This includes relating the possibility of including or not including.

[0007] In some embodiments, the methods described herein are for determining a diagnosis, The non-coding nucleic acid fragments are extracted from a sample derived from a subject's plasma or serum sample by the methods described above. determining the presence of one or a combination of the non-coding nucleic acids; or providing a diagnosis based on the presence of a combination. The diagnosis determined is cancer, such as breast cancer.

[0008] In some embodiments, the computer-implemented method comprises: The method described above is used to determine the presence or absence of a combination of and from one or more samples containing one or a combination of non-coding nucleic acids. Quantifying the abundance of one or a combination of non-coding nucleic acids of the reference material; Normalized amounts of one or a combination of non-coding nucleic acids in a sample or samples determining by calculation, and determining one of the non-coding nucleic acids based on the normalized amount. In some embodiments, the question includes determining the presence or absence of one or a combination of the questions. Quantification involves sequencing a sample of total RNA isolated from the subject sample. In one embodiment, computational analysis is performed on sequence data obtained from whole blood or serum samples. In some embodiments, the result of the computer-implemented method described above is an output , an output that can be a diagnosis, for example, a diagnosis of a hyperproliferative disorder such as breast cancer. , additional sample-related information, e.g., information regarding the presence or absence of known tumor antigens in the sample. The output may be by various means as described herein, for example For example, the results may be output visually, for example on a computer monitor, or may be output may be hard copy, such as a printed paper report. The present invention provides, for example, the following items. (Item 1) 1. A method of diagnosing a subject having benign, pre-malignant, or malignant hyperproliferative cells, comprising: The presence, absence, and / or activity of at least one non-coding RNA or functional fragment thereof in a sample. and / or detecting the amount of. (Item 2) Item 1, wherein the subject is a human diagnosed with or suspected of having breast cancer. . (Item 3) Item 1, wherein the detecting step is performed after obtaining a sample from the subject. How to do it. (Item 4) A sample derived from a subject is subjected to a step of analyzing a non-coding RNA selected from SEQ ID NO: 1 to SEQ ID NO: 201. or any nucleic acid of Tables 1, 2, and / or 3. At least 70%, 80%, 85%, 90%, 95%, 96%, 97%, 98%, Complementary to one or a combination of non-coding nucleic acid sequences with 99% sequence identity 4. The method according to any one of items 1 to 3, further comprising exposing the method to at least one nucleic acid molecule. How to do it. (Item 5) Item 1, wherein the at least one non-coding RNA is T3p or a functional fragment thereof. A method according to any one of claims 1 to 4. (Item 6) The detecting step detects the presence, absence, and / or amount of BRCA gene expression. 6. The method according to any one of items 1 to 5, further comprising: (Item 7) The presence, absence, and / or homologous sequence of at least one non-coding RNA or its homologous sequence in the sample. and / or wherein said step of detecting the amount of said at least one non-coding RNA is or a functional fragment thereof, and Normalizing the amount in the sample to a measurement taken from a control sample. 10. The method according to any one of claims 1 to 9. (Item 8) relative to a measured amount of at least one non-coding RNA or its homologous sequence in a control sample. The amount of at least one non-coding RNA or a homologous sequence thereof in the sample is determined by the subject. further comprising correlating the probability or likelihood of having a benign, pre-malignant, or malignant tumor. The method according to any one of items 1 to 7. (Item 9) Items 1 to 8, wherein the benign, premalignant, or malignant hyperproliferative cells are derived from breast tissue. 10. The method according to any one of the preceding claims. (Item 10) 10. The method according to any one of items 1 to 9, wherein the sample is blood or serum from a subject. Law. (Item 11) The method further comprises treating the subject with cancer selected from one or more of: basal or luminal cancer. 10. Diagnose the presence of pre-malignant or malignant hyperproliferative cells. The method described. (Item 12) the sample is seeded with at least one cell from the subject, or a sample of seeded cells 12. The method according to any one of items 1 to 11, wherein the cell culture medium is harvested from a culture medium. (Item 13) At least one biopsy from the subject is cultured using a culture medium to culture a small amount of tissue from the subject's breast. further comprising culturing the culture under conditions and for a period of time sufficient to allow at least one cell to grow. 13. The method according to any one of items 1 to 12. (Item 14) The method for measuring the amount of at least one non-coding RNA or a functional fragment thereof in a sample. The steps include digitally imaging the sample, analyzing the sample for non-coding RNA or functional fragments thereof, and exposing the sample to a known amount of labeled antibody specific for an epitope of the non-coding RNA or or functional fragments thereof, exposing the sample to one or more dyes specific for said non-coated fragments. Exposing the DNA to at least one labeled probe complementary to the sequence of the DNA or a functional fragment thereof. subjecting the sample to chromatography; isolating total RNA from the sample; subjecting the total RNA to sequence analysis and / or subjecting the sample to mass spectrometry. 7. The method according to any one of items 1 to 6, comprising one or a combination of the following: (Item 15) 15. The method of claim 14, further comprising analyzing the morphology of cells from the sample. (Item 16) The sample is obtained from a subject's plasma, serum, or blood draw, brushing, biopsy, or surgical procedure. 16. A human tissue sample according to any one of items 1 to 15, comprising a tissue or fluid sample obtained by surgical resection. The method described in paragraph . (Item 17) The sample is freshly obtained, formalin-fixed, alcohol-fixed, and 17. The method according to any one of items 1 to 16, comprising / or paraffin-embedded cells. (Item 18) The presence, absence, and / or homologous sequence of at least one non-coding RNA or its homologous sequence in the sample. and / or the step of detecting the amount of a chemiluminescent probe, a fluorescent probe, and / or 18. The method according to any one of items 1 to 17, comprising using a fluorescent microscope or a fluorescent microscopy. (Item 19) The presence, absence, and The step of detecting the amount and / or type of total RNA of the sample is performed by detecting a small amount of a target gene complementary to T3p. 19. The method according to any one of items 1 to 18, comprising contacting the sample with at least one probe. method. (Item 20) The presence, absence, and and / or the amount of the total RNA of the sample is detected by detecting the amount of the total RNA of the sample according to Tables 1, 2, and and / or any one or combination of nucleic acid sequences comprising any of the sequences in 3. 20. The method of claim 19, further comprising contacting the nucleic acid sequence with at least one probe complementary to the nucleic acid sequence. How to do it. (Item 21) 1. A method for detecting cancer cells in a subject, comprising: The sample is subjected to a sequence of probes complementary to one or a combination of non-coding RNA sequences. The non-coding RNA is then contacted with an amount of one or a combination of the detecting the presence of the compound in a sample. (Item 22) Detecting the presence or quantifying the amount of a non-coding RNA or its homologous sequence 22. The method according to claim 21, wherein the step of obtaining a sample from the subject is followed by the step of obtaining a sample from the subject. method. (Item 23) The method comprises: Based on the presence, absence, or amount of one non-coding RNA and / or its homologous sequence calculating one or more scores based on the The amount of the non-coding RNA and / or functional fragment thereof is determined by the amount of the non-coding RNA in the control sample. or when the amount of said non-coding RNA and / or functional fragment thereof exceeds the amount of said non-coding RNA and and / or functional fragments thereof in a sample taken from a subject known to have cancer. the amount of non-coding RNA and / or functional fragment thereof is substantially equal to that of the subject and comparing the one or more scores to the non-coding RNA and the and / or a functional fragment thereof. 23. The method according to claim 21 or 22. (Item 24) Those nucleic acid sequences of Tables 1, 2, and / or 3 or Tables 1, 2, and / or At least 70%, 80%, 85%, 90%, 95% of any of the three sequences , 96%, 97%, 98%, 99% sequence identity. detecting or defining the presence of two or more non-coding RNAs selected from a set of 24. The method according to any one of items 21 to 23, further comprising quantification. (Item 25) The sample is obtained by subjecting serum or plasma or blood to a blood draw, brushing, biopsy, or 25. The method according to any one of items 21 to 24, wherein the tissue sample is a human tissue sample comprising tissue obtained by surgical resection. How to do it. (Item 26) The sample is freshly obtained, formalin-fixed, alcohol-fixed, and and / or any one of items 21-25, including total RNA from paraffin-embedded cells The method described in paragraph . (Item 27) Quantifying the amount of at least one of the non-coding RNAs and / or fragments thereof in the sample 27. Any of items 21 to 26, wherein the step of isolating total RNA from the sample. The method according to any one of claims 1 to 4. (Item 28) Items 21-2, in which the complementary probe is an RNA sequence that is either one or T3p 8. The method of any one of 7. (Item 29) 29. The method according to any one of items 21 to 28, wherein the sample is plasma, blood, or serum. Law. (Item 30) 1. A method of diagnosing breast cancer in a subject, comprising: (a) the presence of a non-coding RNA and / or a functional fragment thereof in a sample from said subject; or contacting the sample with a probe specific for the non-coding RNA and / or its homologous sequence; detecting or quantifying by causing (b) detecting or determining the presence or amount of said non-coding RNA and / or its homologous sequence. diagnosing the subject with breast cancer if the quantification is positive. (Item 31) Detecting the presence or quantifying the amount of non-coding RNA and / or its homologous sequences Item 30, wherein the step of performing the test is performed after the step of collecting a sample from the subject. How to do it. (Item 32) Step (a) Based on the presence, absence, or amount of non-coding RNA and / or its homologous sequences further comprising calculating one or more scores; Step (b) The amount of said non-coding RNA and / or its homologous sequence in the control sample is determined by A and / or its homologous sequences, or or the amount of a homologous sequence thereof in a sample taken from a subject known to have breast cancer. If the amount of the gene encoding the nucleotide sequence is substantially equal to the amount of the gene encoding the nucleotide sequence of ... The one or more scores may be compared to a non-coding RNA and / or a non-coding RNA to diagnose the patient as having the disorder. Item 30, or 31. The method according to claim 31. (Item 33) 30-3 further comprising detecting the presence or quantifying the amount of a cancer antigen. 3. The method of any one of claims 2 to 2. (Item 34) The sample may be obtained by subjecting plasma, serum or blood to a blood draw, brushing, biopsy, or surgical procedure. 34. A human tissue sample comprising cells or tissues obtained by resection, according to any one of items 30 to 33. The method described. (Item 35) The sample is freshly obtained, formalin-fixed, alcohol-fixed, and and / or any one of items 30-34, including total RNA from paraffin-embedded cells The method described in paragraph . (Item 36) The amount of at least one of the non-coding RNA and / or its homologous sequence in the sample is determined. The quantitation step may use fluorescent imaging and / or digital imaging. 36. The method according to any one of Items 30 to 35, comprising: (Item 37) The probe may comprise one or more nucleic acids complementary to T3p, optionally including a fluorophore. 37. The method according to any one of items 30 to 36, wherein the amino acid sequence is a sequence of amino acids. (Item 38) 38. The method according to any one of items 30 to 37, wherein the sample is human serum. (Item 39) 1. A method of treating a subject in need of treatment diagnosed with or suspected of having breast cancer, comprising: (a) specific for one or a combination of non-coding RNAs and / or their homologous sequences; contacting one or more differential probes with the sample; (b) the presence, absence, or both of the non-coding RNA and / or its homologous sequences in the sample; is the step of quantifying the amount; (c) determining whether a non-coding RNA and / or its homologous sequence is present, absent, or abundant; calculating one or more scores based on the (d) determining whether the amount of said non-coding RNA and / or its homologous sequence is higher than that of the non-coding RNA in the control sample; If the amount of NA and / or its homologous sequence exceeds the amount of the one or more scores of the non-coding sequence, and correlating the presence, absence, or amount of the RNA and / or its homologous sequence. wherein said associating step comprises diagnosing the subject with breast cancer; and to (e) administering to the subject a therapeutically effective amount of a treatment agent for breast cancer. Law. (Item 40) A method of treating a subject in need of treatment who has been diagnosed with or is suspected of having cancer. So, (a) one or more probes specific for the non-coding RNA and / or its homologous sequence; contacting the probe with the sample; (b) quantifying the amount of non-coding RNA and / or its homologous sequence in said sample; Top; (c) one or more scores based on the amount of said non-coding RNA and / or its homologous sequence. calculating the normalized value; (d) determining whether the amount of said non-coding RNA and / or its homologous sequence is higher than that of the non-coding RNA in the control sample; If the amount of NA and / or its homologous sequence exceeds the amount of the one or more scores of the non-coding sequence, a step of correlating the amount of the target RNA and / or its homologous sequence with the amount of the target RNA and / or its homologous sequence, wherein the step of diagnosing the subject with cancer; and (e) administering to the subject a therapeutically effective amount of a treatment agent for the cancer. Law. (Item 41) The probe may be one or a combination of the sequences of Table 1, Table 2, and / or Table 3. 41. The nucleic acid sequence of claim 40, wherein the nucleic acid sequence is one or more nucleic acid sequences complementary to a nucleic acid sequence selected from the group consisting of: How to do it. (Item 42) One in which the substrate contains a fluorophore, a chemiluminescent agent, and / or a quencher. 40. The method according to claim 40. (Item 43) 1. A system comprising: (a) a sample; (b) one or more non-coding RNAs that bind to at least one non-coding RNA and / or its homologous sequence; or a plurality of probes and / or stains; (c) at least one promoter that binds to said non-coding RNA and / or its homologous sequence; One that can quantify the presence, absence, and / or intensity of a lobe or stain A system including the above device. (Item 44) The sample is taken from a subject identified as having or suspected of having breast cancer. Item 44. The system according to item 43, (Item 45) 1. A method for characterizing a developmental stage or pathology of a sample containing hyperproliferative cells, comprising: (a) A sample is subjected to a plurality of probes specific for non-coding RNA and / or its homologous sequences. contacting; (b) quantifying the amount of non-coding RNA and / or its homologous sequence in said sample; Top; (c) based on the presence, absence, or amount of non-coding RNA and / or its homologous sequences; calculating one or more normalized scores based on the (d) determining whether the amount of said non-coding RNA and / or its homologous sequence is higher than that of the non-coding RNA in the control sample; the amount of NA and / or its homologous sequence exceeds the amount of said one or more scores and correlating the amount of said non-coding RNA and / or its homologous sequence. and wherein said correlating step includes characterizing said sample as containing hyperproliferative cells. A method comprising the steps of: (Item 46) 1. A method for determining whether a subject has a malignant tumor, comprising: the presence or absence of non-coding RNA and / or its homologous sequences in a sample from said subject; or the amount is determined by subjecting the sample to a probe specific for the non-coding RNA and / or its homologous sequence. contacting substrates specific for the RNA and / or non-coding RNA and / or its homologous sequence detecting the presence of a substance by causing the substance to react with the substance. (Item 47) The presence, absence, or presence of non-coding RNA and / or its homologous sequences in said sample from said subject The presence or amount of the non-coding RNA and / or its homologous sequence is determined by subjecting the sample to a probe specific for the non-coding RNA and / or its homologous sequence. contacting the lobe and / or the T3p or a functional fragment thereof with a substrate specific for the T3p or a functional fragment thereof; Item 47. The method of item 46, further comprising detecting by (Item 48) 1. A method for determining whether a subject has a BRCA-expressing cancer, comprising: the presence or absence of non-coding RNA and / or its homologous sequences in a sample from said subject; or the amount is determined by subjecting the sample to a probe specific for the non-coding RNA and / or its homologous sequence. contacting substrates specific for the RNA and / or non-coding RNA and / or its homologous sequence detecting the presence of a substance by causing the substance to react with the substance. [Brief explanation of the drawings]

[0009] [Figure 1A]We demonstrate the discovery, annotation, and validation of cancer-specific orphan noncoding RNAs in breast cancer. Figure 1A is a heat map depicting the relative abundance of 437 small noncoding RNAs significantly expressed in breast cancer lines but not in normal HUMEC. HUMEC were treated in triplicate, while all other cell lines were analyzed in duplicate. Figure 1B is a heat map showing that of the 437 small RNAs identified in (Figure 1A), 201 were significantly expressed in small RNA gene expression profiles of breast tumor biopsies collected as part of the Cancer Genome Atlas (TCGA-BRCA), and these 201 were largely absent in adjacent normal tissues collected from approximately 200 individuals in this dataset. Figure 1C is a heat map showing that these 201 cancer-specific small RNAs were classified as orphan noncoding RNAs or oncRNAs and independently validated in a third dataset comparing small RNA profiles from four normal epithelial samples and 10 patient-derived xenograft models. [Figure 1B] Same as above. [Figure 1C] Same as above. [Figure 2A]Orphan small RNAs are relatively abundant in cancer cells and rarely detected in normal tissues. In Figure 2A, to identify cancer-specific small RNAs, RNAs that are rarely present in normal cells / tissues but commonly expressed in cancer cells were searched for. Such RNA species were identified from two independent sources: (i) profiles of breast cancer cell lines compared with HUMEC, and (ii) The Cancer Genome Atlas dataset (TCGA-BRCA), which contains approximately 200 normal tissue biopsies and approximately 1,000 tumor samples. These two independent sets were then superimposed to identify orphan noncoding RNAs (oncRNAs). As shown in Figure 2A, strong overlap was observed between these two analyses (hypergeometric test, P value approximately 0). In Figure 2B, the total abundance of 201 oncRNAs was calculated for four normal epithelial samples and 10 PDX models. As shown in Figure 2B, total oncRNA expression can perfectly predict whether a sample is cancerous or normal (both AUC and AUPRC equal 1.0). [Figure 2B] Same as above. [Figure 3A]We demonstrate that oncRNA T3p is strongly associated with breast cancer progression. Figure 3A is a volcano plot comparing oncRNA expression in low-metastatic breast cancer cells versus their highly metastatic derivatives. Significantly upregulated oncRNA T3p in highly metastatic cells is highlighted. Figure 3B is a schematic diagram showing that T3p maps to the 3' end (CR7 domain) of TERC, the RNA component of telomerase. Figure 3C shows the expression of T3p (cpm) in breast tumor biopsies and their corresponding normal tissues from the TCGA-BRCA dataset. Association p values ​​were calculated using a paired Wilcoxon test. Figure 3D shows T3p expression across the entire TCGA-BRCA dataset. Figure 3E shows a survival analysis of the TCGA-BRCA dataset for patients stratified based on T3p expression in their tumors. Samples from the top and bottom thirds were included in this analysis (log-rank test). Figure 3F shows the expression of T3p among normal samples, stage I, and stage II or III samples in the TCGA-BRCA dataset (*: P<0.05; ***, P:<0.001; using the Mann-Whitney test). [Figure 3B] Same as above. [Figure 3C] Same as above. [Figure 3D] Same as above. [Figure 3E] Same as above. [Figure 3F] Same as above. [Figure 4A]We demonstrate that oncRNA T3p is associated with aggressive breast cancer. Figure 4A shows a summary of the number of samples in the TCGA-BRCA dataset based on sample type (normal vs. breast cancer). Each contingency table also includes an accompanying Fisher's exact chi-square test. Figure 4B shows stratification of patients in the TCGA-BRCA dataset based on whether T3p was detected in their tumor biopsies. Even minimal detection of T3p in biopsies is associated with poor survival in breast cancer (p calculated based on the log-rank test). Figure 4C shows a comparison of T3p expression levels in TCGA-BRCA samples divided based on ER, PR, or HER2 status. Figure 4D shows that T3p is significantly expressed in breast cancer PDX models (***: P<0.001; Mann-Whitney test). [Figure 4B] Same as above. [Figure 4C] Same as above. [Figure 4D] Same as above. [Figure 5] We show that T3p promotes metastatic progression. The gene expression changes induced by anti-T3p LNAs are nearly equivalent regardless of whether (i) scrambled LNA or (ii) anti-TERC (but not T3p) LNA controls are used. Pearson correlation coefficients and associated P values ​​are included. [Figure 6A]T3p is shown as a regulator of gene expression and a driver of metastatic progression. Figure 6A shows a comparison of gene expression changes induced by anti-T3p LNA in MDA-LM2 cells to T3p mimics in MDA-MB-231 cells. The accompanying Pearson correlation (P value approximately 0) is reported. Figure 6B shows bioluminescence imaging plots of lung metastases from MDA-LM2 cells transfected with anti-T3p LNA (LNA-T3p) or scrambled LNA (LNA-Scr) (n = 4 or 5 in each cohort). Statistical significance was determined using two-way ANOVA. The area under the curve for each mouse was also calculated (change in normalized lung photon flux multiplied by the number of days elapsed). Error bars indicate the standard error of the mean. **: P < 0.01 by one-sided Mann-Whitney test. Figure 6C visually illustrates the number of visible metastatic nodules counted in three mice from each cohort. The right panel shows representative lung sections stained with hematoxylin and eosin (H&E) from each cohort, along with median counts. Error bars indicate the standard error of the mean. *: P<0.05 by one-sided Mann-Whitney test. [Figure 6B] Same as above. [Figure 6C] Same as above. [Figure 7A] Systematic profiling of oncRNAs in the exosomal compartment is shown. Figure 7A shows that the majority of oncRNAs were detected in exosomal small RNA data collected from MDA-MB-231 cells but not in normal HUVEC cells. Figure 7B shows small RNA profiling of exosomal RNA collected from breast cancer cell lines and normal HUVECs. A heat map showing oncRNA detection among extracellular populations is shown. Figure 7C shows oncRNA detection in serum samples collected from breast cancer patients with stage II and III disease. As a baseline for evaluation, data from 11 healthy individuals from an independent study were used as a reference. [Figure 7B] Same as above. [Figure 7C] Same as above. [Figure 8A]We demonstrate that T3p can be detected in exosomes and circulating compartments. Figure 8A shows the results of previously published small RNA-seq data (7) and quantitative RT-PCR validation of T3p upregulation in highly metastatic MDA-LM2 cells compared to their low-metastatic parental cells (n = 6 for each sample, **: P < 0.01; two-tailed Mann-Whitney test). Figure 8B demonstrates that T3p can be detected at high levels in the vast majority of serum samples collected from patients, while it is present at very low levels (or undetectable) in serum samples collected from healthy individuals. [Figure 8B] Same as above. [Figure 9A] We demonstrate that oncRNA T3p is associated with aggressive breast cancer. Figure 9A shows normalized T3p expression by small RNA sequencing for the indicated cell lines on the x-axis. All cancer lines were prepared and processed in biological triplicates, and HMECs in biological duplicates. Cell lines are grouped by subtype: HMEC (circles on the left side of the panel), triple-negative breast cancer (TNBC; squares, triangles, and diamonds in the center of the panel), HER2-positive (circles and squares on the right side of the panel), and luminal (triangles on the right side of the panel). Figure 9B shows a comparison of T3p expression levels in TCGA-BRCA samples divided based on ER, PR, or HER2 status (n = 1033, 1030, and 715, respectively). Mean values ​​± standard deviations are shown for each cohort. Figure 9C shows relative T3p expression measured by qRT-PCR in two low-metastatic and two highly metastatic breast cancer PDX models. [Figure 9B] Same as above. [Figure 9C] Same as above. [Figure 10A]We demonstrate that T3p can be detected in both the extracellular and circulating compartments. Figure 10A shows that T3p was present in sequenced small RNAs isolated from extracellular vesicles (EVs) from 7 / 8 breast cancer cell lines but not in HMEC EVs. Samples were processed and prepared in biological replicates and aggregated before calculating counts per million reads. Cell lines are categorized by subtype: HMEC (first column from the left on the x-axis), triple-negative breast cancer (TNBC; four columns to the right of HMEC), HER2-positive (two columns to the right of the HER2 set of samples), and luminal (last two columns on the far right of the graph). Figure 10B shows the Pearson correlation coefficients for oncRNA expression levels between the total intracellular (IC) and total extracellular (CM) compartments, and between the IC and extracellular vesicle (EV) compartments. n = 2 biologically independent experiments per cell line. Figure 10C shows ten bootstrap-based receiver operating characteristic (ROC) curves demonstrating the classification performance of a gradient-boosting classifier trained on oncRNA expression levels from the TCGA-BRCA dataset and tested on serum samples from healthy volunteers or breast cancer patients (GSE49035). Figure 10D shows that T3p can be detected at high levels in the vast majority of sera collected from patients, but is present at very low levels (or undetectable) in serum samples collected from healthy individuals. The right panel shows T3p levels in serum collected from individual breast cancer patients (n = 40 biologically independent samples). Mean ± standard error of the mean is shown. P values ​​were calculated using a two-tailed Mann-Whitney test. Figure 10E shows that T3p can be detected at high levels in the vast majority of sera collected from patients, but is present at very low levels (or undetectable) in serum samples collected from healthy individuals. The right panel shows T3p levels in serum collected from individual breast cancer patients (n = 40 biologically independent samples). Mean values ​​± standard error of the mean are shown. P values ​​were calculated using a two-tailed Mann-Whitney test.Bootstrapped ROC curves (10 times) were generated for gradient-boosting classifiers trained on miRNA expression in the TCGA-BRCA dataset and tested on serum samples from healthy volunteers or breast cancer patients (data not shown). [Figure 10B] Same as above. [Figure 10C] Same as above. [Figure 10D] Same as above. [Figure 10E] Same as above. [Figure 10F] Same as above. DETAILED DESCRIPTION OF THE INVENTION

[0010] The present disclosure provides a method for detecting breast cancer that indicates the presence of breast cancer and can be used to accurately diagnose or stage breast cancer in a subject. We provide novel small non-coding RNAs that can function as biomarkers. In one embodiment, the method of the present invention involves the detection of extracellular circulating small RNAs in a suitable sample. .

[0011] definition Before describing the present invention in detail, definitions of certain terms used herein are provided. do.

[0012] Unless otherwise defined, technical and scientific terms used herein refer to the present invention. has the same meaning as commonly understood by a person skilled in the art. For example, Singleton et al.,Dictionary of Microbiol ogy and Molecular Biology 2nd ed., J. Wile Y & Sons (New York, NY 1994) is used in this application. A general introduction to many of the terms is provided to those skilled in the art. Furthermore, practice of the invention is readily apparent to those skilled in the art, unless otherwise specified. Unless otherwise specified, the invention is based on molecular biology (including recombinant techniques), microbiology, cell biology, and the like, all of which are within the skill of those in the art. Such techniques are well known in the art, including "Molecular Cl oning:A Laboratory Manual”,2nd edition(S ambrook et al., 1989), “Oligonucleotide Sy “Animal Cell” (MJ Gait, ed., 1984), “Animal Cell Culture” (RIFreshney, ed., 1987), “Method s in Enzymology” (Academic Press, Inc.), “H andbook of Experimental Immunology”,4th edition(DMWeir & CCBlackwell, eds.,Bl ackwell Science Inc., 1987), “Gene Transfe. r Vectors for Mammalian Cells”(JMMille r & MP Calos, eds., 1987), “Current Protoc. ols in Molecular Biology”(FMAusubel et al., eds., 1987), and “PCR: The Polymerase C "Hain Reaction", (Mullis et al., eds., 1994) This is explained in detail in the literature.

[0013] As used in this disclosure and claims, the singular forms "a," "one," "one "An" and "the" include the plural unless expressly stated otherwise. do.

[0014] Where an embodiment is described herein using the term "comprising," it is also understood to include "consisting of" and and / or other similar embodiments described with the words "consisting essentially of" are also It will be understood that embodiments are provided herein using the term "consisting essentially of" If stated in the specification, the term "consisting of" is used to refer to a different, similar embodiment. It will be understood that embodiments are also provided.

[0015] When used herein in phrases such as "A and / or B," the term "and" " / or" means including A and B; A or B; A alone; and B alone. Similarly, the term "and" when used in phrases such as "A, B and / or C" "and / or" is intended to encompass each of the following specific expressions: A, B, and C; A, B or C;A or C;A or B;B or C;A and C;A and B;B and and C; A (alone); B (alone); and C (alone).

[0016] As used herein, the terms "about" or "approximately" mean within 5% or more of a given value or range. This means within 4%, within 3%, within 2%, or within 1%.

[0017] As used herein, the term "antibody" refers to a molecule that binds to at least one antigen-binding site. Proteins, polypeptides, peptides, carbohydrates, polynucleotides, lipids, or any of the foregoing The term "immunoglobulin molecule" refers to an immunoglobulin molecule that recognizes and specifically binds to a target, such as a combination of antibodies. When used herein, the term refers to an antibody that binds to an intact antibody, so long as the antibody exhibits the desired biological binding activity. Reclonal antibodies, intact monoclonal antibodies, single-chain antibodies, antibody fragments (e.g., Fa b, Fab', F(ab')2, and Fv fragments), single-chain Fv (scFv) antibodies, bispecific Multispecific antibodies such as heterologous antibodies, monospecific antibodies, monovalent antibodies, chimeric antibodies, humanized antibodies, Antibodies, fusion proteins containing the antigen-binding site of an antibody, and any other protein containing an antigen-binding site. The antibodies include modified immunoglobulin molecules of α, δ, ε, γ, and The following five immunoglobulins are classified based on the identity of their heavy chain constant domains, designated μ: It can be one of three major classes: IgA, IgD, IgE, IgG, and Ig M or its subclass (isotype) (e.g., IgG1, IgG2, IgG3, I The different classes of immunoglobulins have different and well-defined functions. They have known subunit structures and three-dimensional configurations. Antibodies can be naked or toxin-containing. and may be conjugated to other molecules including, but not limited to, radioisotopes.

[0018] The term "antibody fragment" refers to a portion of an intact antibody that retains the antigenicity of the intact antibody. Examples of antibody fragments include Fab, Fab', F(ab')2, and Fv. These include antibody fragments, linear antibodies, single-chain antibodies, and multispecific antibodies formed from antibody fragments. As used herein, an "antibody fragment" includes, but is not limited to, at least The term "variable region" of an antibody contains one antigen- or epitope-binding site. The term "variable region" refers to the variable region of an antibody light chain or the variable region of an antibody heavy chain, either alone or in combination. The variable region of the light or dark chain generally consists of three complementarity-determining regions (CDRs), also known as "hypervariable regions": Each chain consists of four framework regions (FRs) linked by CDRs. are held together in close proximity by framework regions and contribute to the formation of the antigen-binding site of antibodies There are at least two techniques for determining CDRs: (1) cross-species Sequence diversity-based methods (i.e., Kabat et al., 1991, Seq uences of Proteins of Immunological Inte rest,5th Edition,National Institutes of Health, Bethesda, MD) and (2) for crystallographic studies of antigen-antibody complexes. Based on the method (Al-Lazikani et al., 1997, J. Mol. Biol. l.,273:927-948). In addition, the combination of these two methods is is sometimes used in the art to determine

[0019] As used herein, the term "biomarker" refers to a marker that is present in individuals at different concentrations, Biomarkers are biomolecules that are useful in predicting the cancer status of an individual. These may include, but are not limited to, proteins and variants, and fragments thereof. A biomarker is not limited to a nucleic acid sequence that encodes the biomarker in whole or in part. The biomarkers useful in the present invention may be DNA comprising the sequence or the complement of such a sequence. Car nucleic acids include DNA containing any whole or partial sequence of a nucleic acid sequence of interest and It is believed that both RNA and

[0020] As used herein, the term "body fluid" refers to blood (or blood components such as plasma or serum). fraction), lymph, mucus, tears, saliva, sputum, urine, semen, feces, CSF (cerebrospinal fluid), breast milk It refers to bodily fluids containing non-coding RNA (ncRNA), including ascites fluid. In some embodiments, the bodily fluid is urine. In some embodiments, the bodily fluid is a fractionated exosome-containing fluid. It is serum.

[0021] As used herein, the terms "cancer" and "cancerous" refer to a condition in which a population of cells is in an unregulated state. Refers to or describes the physiological condition in mammals that is characterized by proliferation. In some embodiments, the cancer is breast cancer.

[0022] As used herein, the terms "associate" or "associating" refer to two things: Refers to statistical associations between events, where events can include numbers, data sets, etc. For example, if an event involves a numerical value, a direct correlation (also referred to herein as a "direct correlation") may be used. A negative correlation (as defined herein) means that as one increases, the other also increases. (sometimes called "inverse correlation") means that as one increases, the other decreases. The present invention provides small non-coding RNAs, the levels of which can be measured by small non-coding RNAs. Correlations exist between certain outcome measures, such as between levels of α-glucan and the likelihood of developing breast cancer. Increased levels of molecular non-coding RNAs may negatively correlate with the likelihood of a favorable clinical outcome in patients. In this case, for example, the patient's chances of long-term survival without recurrence of cancer and / or Such a negative correlation may lead to a patient having a poor prognosis. These findings suggest that chemotherapeutic strategies may result in a poor response to chemotherapy, which may be explained in a variety of ways. This can be demonstrated statistically, for example, by a high hazard ratio.

[0023] As used herein, the term "high stringency" refers to the following conditions: ) 15 mM sodium chloride / conditions using 1.5 mM sodium citrate / 0.1% sodium dodecyl sulfate; (2) Denaturing agents such as formamide during hybridization, e.g., 5x at 42°C 50% (v / v) in SSC (0.75 M NaCl, 75 mM sodium citrate) Formamide and 0.1% bovine serum albumin / 0.1% Ficoll / 0.1% poly Conditions using vinylpyrrolidone / 50 mM sodium phosphate buffer (pH 6.5); or (3) 50% formamide in 5xSSC at 42°C during hybridization. , 50 mM sodium phosphate (pH 6.8), 0.1% sodium pyrophosphate, 5x Denhardt's solution, sonicated salmon sperm DNA (50 μg / ml), 0.1% SDS, and and 10% dextran sulfate, in 0.2x SSC and 50% formamide. After washing at 42°C, a wash consisting of 0.1xSSC containing EDTA was performed at 55°C. Conditions.

[0024] The term "hyperproliferative disorder" refers to abnormal proliferation, growth, aging, or abnormal cell proliferation in an organism. Refers to diseases or disorders characterized by quiescence, abnormal elimination, and all forms of hyperplasia and neoplasia In some embodiments, the hyperproliferative disease is a disease of the gastrointestinal or urinary system. In some embodiments, the hyperproliferative disease is a cancer of the adrenal gland, bladder, bone, bone marrow, Brain, spine, chest, neck, gallbladder, ganglia, digestive tract, stomach, large intestine, heart, kidneys, liver, lungs, muscles , ovaries, pancreas, parathyroid glands, penis, prostate, salivary glands, skin, spleen, testes, thymus, thyroid gland, In some embodiments, the term hyperproliferative disease is selected from the following: Cancers of choice: lung cancer, bone cancer, CMML, pancreatic cancer, skin cancer, head and neck cancer, cutaneous melanoma Intraocular melanoma, uterine cancer, ovarian cancer, rectal cancer, anal cancer, stomach cancer, colon cancer, breast cancer, and testicular cancer uterine sarcoma, fallopian tube cancer, endometrial cancer, cervical cancer, vaginal cancer, or vulvar cancer cancer), Hodgkin's disease, cancer of the esophagus, cancer of the small intestine, cancer of the endocrine system (e.g., thyroid, parathyroid gland or adrenal gland cancer), soft tissue sarcoma, urethral cancer, penile cancer, prostate cancer, chronic or or acute leukemia, childhood solid tumors, lymphocytic lymphoma, cancer of the bladder, kidney, or urinary cancer of the duct (e.g., renal cell carcinoma, renal pelvic carcinoma), or central nervous system tumors (e.g., central nervous system primary lymphoma, spinal axis tumor, brainstem glioma, or pituitary adenoma).

[0025] As used herein, the terms "identical" or "identical" in the context of two or more nucleic acids "Percent identity" or "homology" refers to the degree of identity or any conservative amino acid substitutions. Compare and align (if necessary) for maximum matches without considering the A specific percentage of nucleotides or amino acids that are identical when the The percent identity refers to two or more sequences or subsequences that share the same amino acid residue. This can be measured using software or algorithms or by visual inspection. Various algorithms can be used to obtain alignments of amino acid or nucleotide sequences. The algorithms and software are well known in the art. These include BLAS, T, ALIGN, Megalign, BestFit, GCG Wisconsin P package, and variations thereof. In some embodiments, two nucleic acids of the invention are substantially identical, meaning that they are The best match, as determined using a sequence comparison algorithm or by visual inspection, at least about 70%, at least about 75%, when compared and aligned %, at least about 80%, at least about 85%, at least about 90%, and some In embodiments, at least about 95%, 96%, 97%, 98%, 99% or more of the nucleotides means having amino acid residue sequence identity. In some embodiments, identity is At least about 10, at least about 20, at least about 40-60 nucleotides, at least over a region of the sequence that is at most about 60 to 80 nucleotides, or any integer value therebetween. In some embodiments, the identity is at least about 80-100 nucleotides. In some embodiments, the nucleotide sequence is present over a region longer than 60-80 nucleotides, such as , the sequences are substantially identical over the entire length of the sequence being compared.

[0026] As used herein, the term "level" refers to the determination of the copy number of a non-coding RNA transcript. refers to the quantitative or qualitative determination of the level of RNA transcripts in a first sample, e.g., a clinically relevant In a related subpopulation of patients (e.g., patients with cancer), a second sample, e.g., If the RNA transcript is higher in a subpopulation (e.g., patients without cancer) than in a subpopulation (e.g., patients without cancer), "Increased levels" are shown. In the context of the analysis of the bell, the level of RNA transcripts in a subject is clinically relevant. If the RNA transcripts tend to trend or more closely approach levels characteristic of a patient subpopulation, indicates "increased levels."

[0027] As used herein, the term "metastasis" refers to the development of a similar cancerous lesion at a new location. "Metastasis" refers to the process by which cancer spreads or moves from its site of origin to other areas of the body. "Metastatic" or "metastasizing" cells lack adhesive contacts with neighboring cells and are the primary site of disease. a substance that travels (e.g., via the bloodstream or lymph) from one site to a second site.

[0028] As used herein, the term "monoclonal antibody" refers to an antibody that is directed against a single antigenic determinant or enzyme. It refers to a homogeneous population of antibodies that are involved in highly specific recognition and binding of a specific target. Usually, polyclonal antibodies contain a mixture of different antibodies directed against a variety of different antigenic determinants. The term "monoclonal antibody" refers to an intact, full-length monoclonal antibody. Monoclonal antibodies, as well as antibody fragments (e.g., Fab, Fab', F(ab'), F v), single chain (scFv) antibodies, fusion proteins containing antibody moieties, and antibodies containing antigen-binding sites Furthermore, "monoclonal antibodies" encompass any other modified immunoglobulin molecule containing " Hybridoma production, phage selection, recombinant expression, and transgenic animals The term "antibody" refers to such antibodies made by any number of techniques, including but not limited to:

[0029] As used herein, the term "normalized" with respect to non-coding RNA transcripts refers to Refers to the level of an RNA transcript relative to the average level of that transcript in a set of control RNA transcripts. Reference RNA transcripts were selected based on their minimal variability across patients, tissues, or treatments. Alternatively, the non-coding RNA transcript may be a transcript of the tested RNA or a transcript of such a test. The results can be normalized to the entire subset of RNA transcripts.

[0030] "Patient response" includes, but is not limited to, (1) slowing and complete cessation of growth; (2) a reduction in the number of tumor cells; and (3) a reduction in tumor size. (4) inhibition of (i.e., reduction of) tumor cell invasion into adjacent peripheral organs and / or tissues; (5) inhibition of metastasis (i.e., reduction, slowing, or complete cessation); (6) anti-tumor immunity, which may or may not result in tumor regression or rejection (7) a reduction to some extent in one or more symptoms associated with cancer; (8) a reduction in the immune response after treatment. (9) an increase in the length of survival, and / or a decrease in mortality at a given time point after treatment, Any endpoint that indicates benefit to the patient may be used for evaluation.

[0031] The terms "polynucleotide" and "nucleic acid" and "nucleic acid molecule" are used herein to refer to Used interchangeably, refers to nucleotide polymers of any length, including DNA and RNA Polynucleotides are made up of deoxyribonucleotides, ribonucleotides, and modified nucleotides. nucleotides or bases, and / or their analogs, or DNA or RNA polymerases The substrate may be any substrate that can be incorporated into a polymer by a polymerase.

[0032] The terms "polypeptide" and "peptide" and "protein" are used herein to refer to Used interchangeably, refers to a polymer of amino acids of any length. A polymer can be linear or branched. It may be branched, it may comprise modified amino acids, and it may be interrupted by non-amino acids. Naturally modified or intervened, e.g., disulfide bond formation, glycosylation, lipidation , acetylation, phosphorylation, or any other manipulation or modification, such as conjugation with a labeling component. Also included are amino acid polymers modified by, for example, amylases of one or more amino acids. modifications (e.g., containing unnatural amino acids) and other modifications known in the art. Polypeptides are also included within the definition. The polypeptides of the invention may be incorporated into antibodies or fusion proteins. In certain embodiments, polypeptides may be single chains or associated chains (e.g., It will be understood that the hydroxyl group may occur as a dimer.

[0033] As used herein, the term "prognosis" refers to the risk of recurrence, metastatic spread, or progression of a neoplastic disease such as breast cancer. and predicting the likelihood of death or progression attributable to cancer, including drug resistance.

[0034] As used herein, the term "reference" RNA transcript refers to a transcript whose level is compared to the R The term "RNA transcript" refers to an RNA transcript that can be used to compare the level of a specific RNA transcript. In this embodiment, the reference RNA transcripts include β-globin, alcohol dehydrogenase These include housekeeping genes such as ribosomal enzymes, or any other RNA transcripts, the levels of which can be The level or expression does not vary depending on the disease state of the cell containing the RNA transcript. In an embodiment, all of the assayed RNA transcripts or a subset thereof are compared with a reference RNA transcript. It can function as a photograph.

[0035] As used herein, the term "small non-coding RNA" (ncRNA) refers to a molecule that encodes a protein. It refers to RNA that is not translated into proteins, and includes transfer RNA (tRNA), ribosomal RNA (ribosomal RNA), and microRNA, snoRNA, microRNA (miRNA), siRNA, small nuclear molecules ( snRNA), Y RNA, vault RNA, antisense RNA, tiRNA (transcription Initiator RNA), TSSa-RNA (transcription start site-associated RNA), and piwiRNA ( Small ncRNAs include piRNAs. Small ncRNAs are less than 200 nucleotides in length. Preferably, as used herein, a small ncRNA is a molecule having a length of 50-100 nucleotides. ncRNAs can be of endogenous origin (e.g., human small non-coding RNAs) or exogenous origin. Can be of any origin (e.g., viral, bacterial, parasitic). "Canonical" ncRN A refers to the sequence of the RNA as predicted from the genome sequence and is identified for a particular RNA. The "trimmed" ncRNAs are the most abundant sequences found in exonuclease-dependent RNAs. The 5' and / or 6' ends of the molecule are removed by enzyme-mediated nucleotide trimming. "Extended ncRNA" refers to ncRNA with one or more nucleotides removed from the 3' end. "cRNA" refers to small non-coding RNAs that are longer than the canonical small non-coding RNA sequences. and is a term understood in the art. The nucleotides that make up the extension are , corresponding to a nucleotide in the precursor sequence, and therefore non-templated nucleotide addition In some embodiments, the nucleic acid sequences disclosed herein are encoded by the genome as opposed to the human genome. Any of the methods shown may detect any or a combination of the above disclosed RNAs. This includes:

[0036] As used herein, the term "subject" refers to a human, non-human primate, dog, cat, rodent, or The term "animal" refers to any animal (e.g., a mammal), including, but not limited to, animals such as mammals. Alternatively, the subject is a human subject. The terms "subject," "individual," and "patient" are used herein. The terms "subject," "individual," and "patient" are used interchangeably throughout this document. includes individuals with cancer (e.g., breast cancer) who have undergone resection (surgery) to remove cancerous tissue. ) or is a candidate for such.

[0037] The term "therapeutically effective amount" refers to an amount sufficient to achieve a desired therapeutic effect, e.g., Predicting symptoms associated with a disease, such as cancer growth or disorders associated with a hyperproliferative disorder The amount of compound administered to a subject is the amount that results in prevention or amelioration or reduction of the disease. type and severity of the disease and individual characteristics, such as health status, age, sex, weight, and It also depends on the extent, severity, and type of disease. The skilled artisan will be able to determine appropriate dosages depending on these and other factors. The dosing regimen may affect what constitutes an effective amount. The staggered doses may be administered daily or sequentially, or the doses may be administered as a continuous infusion. Furthermore, the dose of the compound of the present invention may be administered either as a single dose or as a bolus injection. may be increased or decreased proportionately as indicated by the urgency of the preventive situation. An effective amount of a compound of the present invention sufficient to achieve a therapeutic effect is about 100 mg / kg body weight per day. Range: approximately 0.000001 mg to approximately 10,000 mg per kilogram of body weight per day Preferably, the dose range is about 0.0001 mg per kilogram of body weight per day. ~ about 100 mg per kilogram of body weight per day. The compounds may be administered in combination with each other or with one or more additional therapeutic compounds. obtain.

[0038] The term "salt" includes acid salts formed with inorganic and / or organic acids as well as inorganic and Examples of these acids and bases are known in the art. Such acid addition salts are usually pharmaceutically acceptable, but pharmaceutically unacceptable salts may also be used. Salts of the acid may be useful in the preparation and purification of the compounds of the invention in question. Acid addition salts of the compounds are most suitably formed from pharmaceutically acceptable acids, for example inorganic acids, e.g. hydrochloric, hydrobromic, sulfuric, or phosphoric acid) and organic acids (e.g., succinic, maleic Other pharmaceutically unacceptable acids include those formed with acetic acid, acetic acid, or fumaric acid. Salts (e.g., oxalates) may be used, for example, for isolating the compounds of the invention, for experimental purposes, or for subsequent The solvates of the present invention and the compounds thereof can be used for conversion to pharmaceutically acceptable acid addition salts. Hydrates are also included within the scope of the present invention. Suitable esters or amides are those compounds having free hydroxy or amino functionality. The compound is reacted with the desired amine in the presence of a base in an inert solvent (e.g., dichloromethane or chloroform). Suitable bases include triethyl esters of methyl methyl esters, which may be formed by treating the acid chloride of the ester with triethyl esters of methyl methyl esters. Conversely, compounds of the invention having a free carboxy group include amines or pyridines. , standard conditions which may include activation followed by treatment with the desired alcohol in the presence of a suitable base. Examples of pharmaceutically acceptable addition salts include non-toxic inorganic salts. and organic acid addition salts, such as hydrochlorides derived from hydrochloric acid, bromides derived from hydrobromic acid, hydrochlorides, nitrates derived from nitric acid, perchlorates derived from perchloric acid, phosphates phosphate derived from acetic acid, sulfate derived from sulfuric acid, formate derived from formic acid, Acetate derived from acetone, aconitate derived from aconitic acid, and ascorbic acid Ascorbate derived from benzenesulfonic acid, benzenesulfonate derived from benzenesulfonic acid , benzoates derived from benzoic acid, cinnamates derived from cinnamic acid, citric acid citrate derived from embonic acid, embonic acid derived from enanthic acid, enanthate, derived from hydroxybenzoates; fumarate, derived from fumaric acid; and glutamic acid. Glutamate, glycolate derived from glycolic acid, lactate derived from lactic acid salts, maleates derived from maleic acid, malonates derived from malonic acid, mannose Mandelates derived from delic acid, methanesulfonic acid derived from methanesulfonic acid Salts, naphthalene-2-sulfonates derived from naphthalene-2-sulfonic acid, phthalates Phthalates derived from acids, salicylates derived from salicylic acid, and sorbic acid sorbates derived from stearic acid, stearates derived from succinic acid, succinate derived from tartaric acid, tartrate derived from p-toluenesulfonic acid Examples of suitable toluene-p-sulfonates include, but are not limited to, toluene-p-sulfonates, which are particularly preferred. Preferred salts are the sodium, lysine, and arginine salts of the compounds of the present invention. Salts may be formed by procedures well known and described in the art.

[0039] Other acids, such as oxalic acid, which cannot be considered pharmaceutically acceptable, may be used in the preparation of the compounds of the present invention. and salts useful as intermediates in obtaining pharmaceutically acceptable acid addition salts thereof. Metal salts of the compounds of the present invention include alkali metal salts, for example, salts of compounds having a carboxy group. The present invention also includes the sodium salts of the compounds of the present invention containing the isomers. The compounds can be separated into the individual isomers in a manner known per se, and the diastereoisomers can be For example, partitioning between multiphase solvent mixtures, recrystallization and / or cleavage, e.g., on silica gel. by chromatographic separation, or, for example, by medium pressure liquid chromatography on a reversed phase column. The racemic forms can be separated, for example, by salt formation with an optically pure salt-forming agent and the like. by separation of the resulting mixture of diastereoisomers, for example by fractional crystallization, Alternatively, they may be separated by chromatography on an optically active column material.

[0040] As used herein, the term "sample" refers to a sample of interest, as described herein. refers to a biological sample obtained or derived from a source. In some embodiments, Sources of interest include living organisms, such as animals or humans. In some embodiments, Biological samples include biological tissues or biological fluids. In some embodiments, the biological sample is bone marrow; blood; blood cells; ascites; tissue or fine needle biopsy sample; body fluid containing cells; floating Sexual nucleic acid; sputum; saliva; urine; cerebrospinal fluid, peritoneal fluid; pleural fluid; feces; lymphatic fluid; gynecological fluid; Skin swabs; vaginal swabs; oral swabs; nasal swabs; nasal or bronchoalveolar lavage fluids Any washings or lavage fluids; aspirates; scrapings; bone marrow specimens; tissue biopsy specimens; surgical specimens; stool, etc. and / or cells derived therefrom. In some embodiments, the biological sample is obtained from an individual. In some embodiments, the sample is or comprises a cell. A "primary sample" is a sample obtained directly from the source of interest. For example, in some implementations In form, primary biological samples may be obtained by biopsy (e.g., fine needle aspiration or tissue biopsy), surgery, or bodily fluids. collection of samples (e.g., blood, lymph, feces, etc.) In some embodiments, as will be clear from the context, the term "sample" refers to By treating the primary sample (e.g., by removing one or more components of the primary sample), and / or by adding one or more agents), the preparation obtained For example, filtration using a semipermeable membrane. Such a "processed sample" includes, for example, or by subjecting a primary sample to, for example, amplification or reverse transcription of mRNA, certain components, Nucleic acids or proteins obtained by subjecting them to techniques such as isolation and / or purification of Proteins may be included.

[0041] As used herein, the terms "treating" or "treatment" or "treat" mean 1) Treat, delay, reduce the symptoms of, and / or slow the progression of, a diagnosed condition or disorder; and 2) prognostic measures to prevent or delay the onset of the targeted condition or disorder. It refers to both preventative and prophylactic measures. Therefore, those who need treatment are those who are already those who have been diagnosed with a disability; those who are prone to having a disability; and those whose disabilities should be prevented. In some embodiments, the subject is a patient who exhibits one or more of the following: A person is successfully "treated" by the methods of the invention if: the number of cancer cells is reduced and / or Complete absence of cancer cells; reduction in tumor size; inhibition of tumor growth; Inhibition and / or absence of cancer cell invasion of peripheral organs, including spread to tissue and bone the presence of tumors or cancer cells; the inhibition and / or absence of metastasis of tumors or cancer cells; the inhibition of cancer growth and and / or absence; reduction of one or more symptoms associated with a particular specific cancer; incidence and Reduced mortality; improved quality of life; reduced tumorigenicity; reduced number or frequency of cancer stem cells or some combination of such effects.

[0042] As used herein, the term "tumor" refers to any tumor cell, whether malignant or benign. refers to the growth and proliferation of cells and tissues, as well as all precancerous and cancerous cells and tissues.

[0043] The term "T3p" refers to the protein encoded by or produced by the human TERC nucleotide sequence. The term refers to the last 45 nucleotides (5' to 3' direction) of a non-coding RNA that is expressed as a nucleotide sequence. The sequences are set forth in PCT No. PCT / US2008 / 055709 and the associated sequence listing. , the contents of which are incorporated herein by reference in their entirety.

[0044] As used herein, the term "tumor sample" includes tumor material obtained from a cancer patient. The term also refers to a tumor tissue sample, e.g., tissue obtained by surgical resection. and includes tissue obtained by biopsy, e.g., core biopsy or fine needle biopsy. In certain embodiments, the tumor sample is a fixed, wax-embedded tissue sample, e.g., formalin. Furthermore, the term "tumor sample" refers to a tissue sample that has been fixed and embedded in paraffin. Also included are samples containing tumor cells obtained from sites other than the tumor, such as circulating tumor cells. The term refers to cells that are the progeny of a patient's tumor cells, e.g., primary tumor cells or circulating tumor cells. The term also encompasses cell culture samples derived from cells excreted from tumor cells in vivo. Samples that may contain modified protein or nucleic acid material, such as bone marrow, blood, plasma, serum, etc. The term also encompasses tumor cells in which tumor cells have been enriched or otherwise manipulated after their acquisition. The polynucleotides and / or polynucleotides obtained from the prepared sample and the patient's tumor material Also encompassed are samples containing polypeptides.

[0045] Small RNA biomarkers for cancer The human genome contains a vast array of small non-protein-coding RNA (ncRNA) transcripts. Highly abundant transfer RNA (tRNA), ribosomal RNA (rRNA), and nuclear Small non-coding RNAs (snoRNAs), microRNAs (miRNAs), and small interfering RNAs ( siRNA), small nuclear RNA (snRNA), and Piwi-binding RNA (piRNP) Several ncRNA classes have been described, including Amaral et al., 2014 008, Martens-Uzunova et al., 2013). RNA initiates translation by binding to target mRNA at sites with appropriate sequence complementarity. acts as a lesser (Ameres et al., 2007), but is highly abundant in the cytoplasm Y RNA regulates RNA quality by influencing the subcellular location of Ro proteins. It functions in the regulation of mRNA translation (Sim et al., 2009). The repression activity of molecular non-coding RNAs silences retrotransposons at defined subcellular locations. In addition to signaling piRNAs, other classes of siRNAs, including endogenous siRNAs, It is shared with ncRNA (Chuma and Pillai, 2009). The activity of the code RNA is abundant at sufficient levels in the cytoplasm and localized to endosomal membranes. Depends on interaction with the RNA-induced silencing complex (RISC) (Gibbing s et al., 2009, Lee et al., 2009a), but a small amount of low-molecular-weight Non-coding RNAs have a smaller effect on translational repression. Even subtle changes in the levels of small non-coding RNAs can already affect cellular processes. However, strong perturbations can cause disease. Interaction with non-coding RNA partners and correct subcellular localization are essential for small non-coding RNAs These are interrelated factors that control the physiological functions of the .,2012, Wee et al.,2012).

[0046] Small RNAs can be secreted into cell-derived extracellular vesicles such as exosomes. Both A and small non-coding RNA species have been found to be contained in exosomes. Therefore, exosomes are a key component in the transport of RNA content and protecting it from degradation in the environment. This may provide a means for protection and provide a stable and reliable detection of RNA biomarkers. Make the selected source available.

[0047] The present disclosure provides a method for determining the risk of breast cancer in subjects with breast cancer compared to subjects who are "normal," i.e., subjects who do not have breast cancer. Small non-coding RNAs known to be differentially present in biological samples from subjects A. Biomarkers. Small non-coding RNA biomarkers or small non-coding The set of RNA biomarkers is comprised of small non-coding RNA biomarkers or or a set of small non-coding RNA biomarkers, the differences between which are statistically significant If a difference is determined to be significant, it is differentially present between samples. t-test, ANOVA, Kruskal-Wallis, Wilcoxon, Mann-Whitney These include, but are not limited to, odds ratios, and odds ratios. Molecular non-coding RNA biomarkers can be used to predict the relative risk of a subject having or not having cancer. can be used to provide a measure of

[0048] Small non-coding RNA biomarkers for breast cancer are available for multiple breast cancer subtypes and human breast cancer. Sequencing of small RNAs from epithelial cells and their differential expression in breast cancer cells It was discovered through the identification of previously unknown small non-coding RNAs. 200 previously unknown small non-coding RNAs specifically expressed in the were identified in this way (see Table 1). Currently, these small non-coding RNAs Biomarkers can be used to identify subjects, e.g., subjects whose breast cancer status was previously unknown or subjects who are suffering from breast cancer. It can be used to determine the cancer status of a subject suspected of having cancer. of identified small non-coding RNAs or combinations thereof in a biological sample derived from a subject. This can be achieved by determining the level of one or more of these small non-coding the level of one or more of the RNA biomarkers in a biological sample from a normal subject A difference in comparison thereto is indicative that the subject has breast cancer.

[0049] A study in which the levels of one or more small non-coding RNA biomarkers differed compared to normal subjects Subjects with breast cancer include those with early, moderate or intermediate stage, or advanced or late stage breast cancer. In one embodiment, the level of one or more small non-coding RNA biomarkers is The bell can be used to diagnose breast cancer in subjects with symptoms characteristic of early-stage cancer.

[0050] In one embodiment, the level of one or more small non-coding RNA biomarkers is determined in a subject. The present invention can be used to monitor the progression of cancer in humans, for example, the progression of breast cancer. The condition of a subject's cancer may change over time. For example, the cancer may worsen or Such deterioration or improvement may be accompanied by the development of one or more small non-coding RNA biomarkers. The level of the protein is altered in a statistically significant manner as detected in samples derived from the subject. For example, the levels of one or more of the small non-coding RNA biomarkers can be It may increase over time as breast cancer develops. Thus, it may be useful to monitor the progression of breast cancer in a subject. The method comprises: determining levels of one or more small non-coding RNA biomarkers in a first sample from a subject; determining a level of one or more small molecule non-coding Rs in a second sample from the subject; The level of a second NA biomarker can be monitored by determining the level of the second NA biomarker. The sample is obtained after the first sample. The second sample compared to the level in the first sample The level in Table 1, Table 2 from a first sample to a second sample indicates disease progression. or an increase in the level of one or more of the small non-coding RNA biomarkers in Table 3 This indicates that the subject has developed breast cancer or that the disease has progressed. of one or more small non-coding RNA biomarkers in Table 1, Table 2, or Table 3 to a sample A decrease in the levels of the above indicates that the disease has improved. The coding RNA biomarkers are those in Table 3 and combinations thereof.

[0051] The level of a small non-coding RNA biomarker in a biological sample from a test subject is positive Whether the levels of small non-coding RNA biomarkers present in normal subjects differ from those present in normal subjects will be investigated. Levels of small non-coding RNA biomarkers in samples from study subjects are compared with appropriate controls Those skilled in the art will be able to select appropriate controls for the assay in question. For example, a suitable control may be a known subject, e.g., a normal subject without cancer. A suitable control may be a biological sample from a subject known to be a normal subject. the level of a small non-coding RNA biomarker in a test subject, when obtained from A statistically significant difference compared to a suitable control indicates that the subject has breast cancer. The difference in the level of the small non-coding RNA biomarker is an increase. It can also be a reference standard. A reference standard is a standard by which a test sample is compared to estimate the breast cancer status of a subject. It serves as a reference level for comparison so that it can be compared with a standard. A subject, e.g., a subject known to be a normal subject or a subject known to have breast cancer. The level of one or more small non-coding RNA biomarkers in the A reference standard is a population of known subjects, e.g., a population of subjects known to be normal subjects or or one or more small non-coding RNA biomarkers in a population of subjects known to have breast cancer. A reference standard may represent the level of a marker, for example, by pooling samples from multiple individuals. and assessing the levels of small non-coding RNA biomarkers in the pooled samples. obtained by measuring, thereby providing an averaged population standard Such a reference standard can be used to measure the abundance of small non-coding RNA biomarkers in a population of individuals. A reference standard represents the average level of a marker, e.g., individual samples obtained from multiple individuals. The average levels of small non-coding RNA biomarkers determined to be present in the Such standards can also be obtained by analyzing small non-coding molecules in a population of individuals. It also represents the average level of the RNA biomarker. It can also be a collection of values ​​that represent the levels of small non-coding RNA biomarkers of interest. In certain embodiments, the test sample is used to measure such values ​​to predict breast cancer status in a subject. In certain embodiments, the reference standard is an absolute value. In such embodiments, the test sample is compared to an absolute value to estimate the subject's breast cancer status. In one embodiment, one or more small non-coding RNA biomarkers in a sample can be compared. Car-level comparison against appropriate controls is performed by running the software's classification algorithm. In some embodiments, one of Tables 1, 2, and / or 3 is used. or increased expression of a combination of non-coding RNAs in a normal sample. Approximately 10%, 20%, 30%, 40%, 50%, 60%, 70% compared to the expression of RNA. 80%, 90%, 95 percent, or about 100% or greater expression. In this case, one or a combination of non-coding RNAs in Tables 1, 2, and / or 3 Increased expression may be due to the expression of the same single or combination of non-coding RNAs in normal samples. Approximately 2X, 3X, 4X, 5X, 6X, 7X, 8X, 9X, or 10X or more development compared to the present In some embodiments, the nucleic acid sequences of Tables 1, 2, and / or 3 are about 7 0%, 80%, 81%, 82%, 83%, 84, 85%, 86%, 87%, 88%, 89 %, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, and One or more non-coding RNA or nucleic acid sequences with approximately 99% homology. In some embodiments, a single gene is used, with expression of one or more sequences of Tables 1, 2, or 3. The mere presence or expression of one or more non-coding RNAs, alone or in combination. In some embodiments, the nucleic acid sequences of Tables 1, 2, and / or 3 may be about 70%, 80%, 80%, 90%, 100%, 110%, 120%, 130%, 140%, 150%, 160%, 170%, 180%, 190%, 200%, 210%, 220%, 230%, 240%, 250%, 260%, 1%, 82%, 83%, 84, 85%, 86%, 87%, 88%, 89%, 90%, 91 %, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or approximately 99% homology The expression of one or more of the sequences having the same function, alone or in combination, corresponds to the The mere presence or expression of one or more non-coding RNAs. These homologous sequences are fragments of the nucleic acid sequences disclosed in Tables 1, 2, and / or 3. Contains one or more of:

[0052] Those skilled in the art will readily envision additional appropriate controls that may be appropriate depending on the assay in question. The above suitable controls are intended to be illustrative and not limiting. There is no.

[0053] In general, small non-coding RNA biomarkers in Table 1, Table 2, or Table 3 in normal subjects A biological sample derived from a test subject compared with an appropriate control that represents one or more levels of One or more of the small non-coding RNA biomarkers in Table 1, Table 2, or Table 3 in the sample An increase in the levels of the above would indicate that the test subject has breast cancer. In some instances where coding RNA biomarker levels are measured in a test subject, appropriate increased levels of one or more small non-coding RNA biomarkers compared to a control; Unchanged or increased levels of one or more additional small non-coding RNA biomarkers In such an example, the levels of one or more of the small non-coding RNA biomarkers may be increased. A suitable counter-representative of the levels of small non-coding RNA biomarkers in normal subjects was used. A difference compared to the control indicates that the test subject has breast cancer. Determining such a difference is performed by the method of the present specification. This may be aided by the implementation of a classification algorithm in software, as described in the document.

[0054] biological samples The expression levels of one or more small non-coding RNA biomarkers are analyzed in a biological sample derived from the subject. A subject-derived sample is one that originates from the subject. The sample may be further processed after it is obtained from the subject. For example, RNA may be extracted from the sample. In this example, the RNA isolated from the sample is also the sample from the subject. A biological test useful for determining the level of one or more small non-coding RNA biomarkers. Materials can be obtained from essentially any source, including cells, tissues, and fluids in the body. .

[0055] In some embodiments, the level of one or more small non-coding RNA biomarkers is determined. The biological sample used to determine the amount of circulating small non-coding RNA, e.g., extracellular small Extracellular small non-coding RNAs are collected from the circulatory system. A bodily fluid, such as a blood sample or lymph sample, or another bodily fluid, such as urine, They circulate freely in a wide range of biological materials, including saliva. In some cases, it is used to determine the levels of one or more small non-coding RNA biomarkers. The biological samples to be analyzed include body fluids, such as blood, its fractions, serum, plasma, urine, saliva, tears, sweat, semen, vaginal fluid, lymphatic fluid, bronchial secretions, CSF, whole blood, etc. In some embodiments, In some embodiments, the sample is a non-invasively obtained sample. The serum sample is

[0056] In some embodiments, any of the methods disclosed herein involve the use of small samples. In some embodiments, the disclosed methods include using about 20 microliters. The following samples: 40 microliter sample, 80 microliter sample, 100 microliter sample 100 microliter sample, 200 microliter sample, 300 microliter sample, 4 00 microliter sample, 500 microliter sample, 600 microliter 100µL sample, 700µL sample, 800µL sample, 900µL 100ml sample, 1ml sample, 1.1ml sample, 1.2ml 1.3 ml sample, 1.4 ml sample, 1.5 ml 1 ml sample, 1.6 ml sample, 1.7 ml sample, 1.8 ml The total RNase activity in the 1.9 ml sample, the 2.0 ml sample, and the 1.9 ml sample was Some embodiments include isolating A and / or amplifying non-coding RNA. In this state, the sample size is approximately 25 microliters to 100 microliters of the subject's plasma, whole blood, or serum form. It is a liquid sample of approximately 2 milliliters.

[0057] In some embodiments, the disclosed methods involve administering less than about 20 microliters of serum, 40 microliter serum, 80 microliter serum, 100 microliter serum , 200 microliters of serum, 300 microliters of serum, 400 microliters 100 microliters of serum, 500 microliters of serum, 600 microliters of serum, 700 microliters of serum Microliters of serum, 800 microliters of serum, 900 microliters of serum , 1 milliliter of serum, 1.1 milliliters of serum, 1.2 milliliters of serum, 1. 3 ml serum, 1.4 ml serum, 1.5 ml serum, 1.6 ml serum, 1.7 ml serum, 1.8 ml serum, 1.9 ml Isolating total RNA in 2.0 ml serum samples and and / or amplifying non-coding RNA.

[0058] Circulating small non-coding RNAs include small non-coding RNAs in cells and in microvesicles. , extracellular small non-coding RNAs in exosomes, and cells or microvesicles Examples of small extracellular non-coding RNAs that are not vesicular include non-vesicular extracellular small non-coding RNAs. In some embodiments, the levels of one or more small non-coding RNA biomarkers are The biological sample used to determine (e.g., a sample containing circulating small non-coding RNAs) ) may contain cells. In other embodiments, the biological sample may be cell-free or In some embodiments, the sample may be free of circulating low-molecular-weight proteins (e.g., serum samples). Samples containing small non-coding RNAs (e.g., extracellular small non-coding RNAs) are derived from blood. Exemplary blood-derived sample types include, for example, plasma samples, serum samples, In another embodiment, the sample containing circulating small non-coding RNA is The sample was lymphatic fluid. Circulating small non-coding RNAs were also found in urine and saliva. and biological samples derived from these sources may also contain one or more small non-coding RNAs. Suitable for determining biomarker levels.

[0059] In some embodiments, any of the methods of the present disclosure comprises the step of: The method includes isolating total RNA from the endothelial cells or microvesicles. For this purpose, methods for isolating RNA from blood, plasma, and / or serum (e.g., Tsui N See B et al. (2002) Clin. Chem. 48, 1647-53 (incorporated herein by reference in its entirety), as well as isolating RNA from urine. Methods (e.g., Boom R et al. (1990) J Clin Microbiol See Vol. 28, 495-503, which is incorporated herein by reference in its entirety. The following is stated:

[0060] Determining the levels of small RNA biomarkers in a sample The levels of one or more small non-coding RNA biomarkers in a biological sample can be determined by any suitable method. The level or amount of small non-coding RNA in a sample can be determined by various methods. Any reliable method for detecting small non-coding RNAs can be used. Generally, small non-coding RNAs are detected using methods such as For example, amplification-based methods (e.g., polymerase chain reaction (PCR), real-time polymerase chain reaction (RTC)) polymerase chain reaction (RT-PCR), quantitative polymerase chain reaction (qPCR), low-cost hybridization-based methods (e.g., hybridization Arrays (e.g., microarrays), NanoString analysis, Northern blot analysis, Lot analysis, branched DNA (bDNA) signal amplification, in situ hybridization tion), and sequencing-based methods (e.g., Illumina or IonT publicly available data for mRNA, including next-generation sequencing using current platforms Detection or detection of RNA from samples (including fractions thereof) such as RNA samples isolated by various known methods. Other exemplary techniques include ribonuclease protection assays (RPAs). A) and mass spectrometry.

[0061] In some embodiments, the RNA is converted to DNA (cDNA) before analysis. A can be produced by reverse transcription of isolated small non-coding RNA using conventional techniques. In some embodiments, the small non-coding RNA is amplified prior to measurement. In this example, the levels of small non-coding RNAs are measured during the amplification process. In embodiments, the level of small non-coding RNA is not amplified prior to measurement. Some exemplary methods suitable for determining levels of non-coding RNA are described in more detail below. These methods are provided by way of example only; other suitable methods may be used as well. It will be apparent to those skilled in the art that other methods may be used.

[0062] A. Amplification-Based Methods including but not limited to PCR, RT-PCR, qPCR, and rolling circle amplification Multiple amplification-based methods for detecting levels of unspecified small non-coding RNA nucleic acid sequences Other amplification-based techniques include, for example, ligase chain reaction, multi-site PCR, and Amplification using suitable ligatable probes (multiplex ligabl e probe amplification), in vitro transcription (IVT), strand displacement amplification amplification, transcription-mediated amplification, RNA (Eberwine) amplification, and other methods known to those skilled in the art. Examples include the law.

[0063] A typical PCR reaction involves multiple steps that selectively amplify a target nucleic acid species: Cycles include: a denaturation step in which the target nucleic acid is denatured; a set of PCR primers ( i.e., forward and reverse primers) anneal with complementary DNA strands. The annealing step involves the primer extension step, which is performed by a thermostable DNA polymerase. By repeating these steps multiple times, DNA fragments can be generated. The fragment is amplified to produce an amplicon corresponding to the target sequence. A typical PCR reaction consists of , which involves 20 or more cycles of denaturation, annealing, and extension. The ring and extension steps can be performed simultaneously, in which case the cycle consists of two steps. The reverse transcription reaction (the generation of cDNA sequences complementary to small non-coding RNAs) is the only step involved. A reverse transcription reaction (which produces a sequence) can be performed prior to PCR amplification. This involves the use of a DNA polymerase (reverse transcriptase) and primers.

[0064] Kits for quantitative real-time PCR of small non-coding RNAs are known and commercially available. Examples of suitable kits include the TaqMan miRNA Assay (Appli ed Biosystems) and mirVana.qRT-PCR miRNA detection Kits include, but are not limited to, the kit (Ambion). The molecular non-coding RNA is identified by a universal primer sequence, polyadenylation sequence, or adaptor. The primer is ligated to a single-stranded oligonucleotide containing a target sequence, Primers complementary to the mer sequence, poly(T) primers, or primers complementary to the adapter sequence The DNA can be amplified using primers containing the desired sequence.

[0065] In some cases, custom qRT-PCR is used to determine small non-coding RNA levels. Assays can be developed to measure small non-coding RNAs in biological samples (e.g., body fluids). For example, methods involving extended reverse transcription primers and locked nucleic acid modified PCR are used to Using the method, custom qRT-PCR assays can be developed. The code RNA assay uses a dilution system of chemically synthesized small non-coding RNA corresponding to a target sequence. This can be done by running an assay on the array. Furthermore, when used as a calibration curve, these These data allow for estimation of the absolute abundance of small non-coding RNAs measured in biological samples. To perform Noh.

[0066] Optionally, check the amplification curves to ensure that Ct values ​​are evaluated within the linear range of each amplification plot. Typically, the linear range spans several orders of magnitude. For small non-coding RNAs, obtain a chemically synthesized version of the small non-coding RNA. A dilution series can then be analyzed to determine the sensitivity limit and linear range of quantitation of the assay. Relative expression levels can be calculated using the method described, for example, in Livak et al., Methods (2001). ) December;25(4):402-8 do.

[0067] In some embodiments, two or more small non-coding RNAs are amplified in a single reaction volume. For example, multiplex q-PCR, such as qRT-PCR, uses two or more pairs of primers and / or By using two or more probes, you can mix at least two nucleotides of interest in one reaction volume. The primer pairs allow for simultaneous amplification and quantification of small non-coding RNAs of interest. The molecule comprises at least one amplification primer that specifically binds to non-coding RNA, The R&D units are labeled so that they can be distinguished from one another, allowing multiple small non-coding R&D units to be Simultaneous quantification of NA becomes possible.

[0068] Rolling circle amplification is the process of converting circularized oligonucleotide probes into linear or cyclic oligonucleotides under isothermal conditions. is a DNA polymerase-driven reaction that can replicate either by cleavage or geometric kinetics. (e.g., Lizardi et al., Nat. Gen. (1998) 19(3) :225-232;Gusev et al., Am. J. Pathol. (2001) 159(1):63-69, Nallur et al., Nucleic Acids Res. (2001) 29(23):E118). The presence of two primers In the presence of β-glucan, one hybridizes to the (+) strand of DNA and the other to the (-) strand. The complex pattern of strand displacement was observed in 10 of each DNA molecule within 90 minutes. 9Creating more than 100 copies By using a single primer, tandem sequences of closed circular DNA molecules can be linked. A bound copy can be formed. This process can be carried out using matrix-bound DNA. The template used for rolling circle amplification can also be reverse transcribed. This method can be used to identify small non-coding RNA sequences and very low small non-coding RNA sequences. A concentration can be used as a sensitive indicator of expression levels (e.g., Cheng et al.,Angew Chem.Int.Ed.Engl.(2009)48( 18):3268-72, Neubacher et al., Chembiochem (2009)10(8):1289-91).

[0069] B. Hybridization-Based Methods Small non-coding RNAs can be analyzed using hybridization arrays (e.g., microarrays) , NanoString analysis, Northern blot analysis, branched DNA (bDNA) signal amplification methods, and in situ hybridization. It can be detected using hybridization-based methods.

[0070] Microarrays are used to simultaneously measure the expression levels of multiple small non-coding RNAs. Printing onto glass slides using tapered pins, pre-fabricated masks, The photolithography and dynamic micromirror device used Photolithography using a micromirror device, inkjet using a variety of techniques, including jet printing, or electrochemistry using microelectrode arrays. Microarrays can be fabricated. Microarrays based on arrays of microfluidic qRT-PCR reactions can be fabricated. Chromofluidic TaqMan Low-Density Array and Associated qRT-P CR-based microfluidic methods are also useful.

[0071] Axon B-4000 scanner and Gene-Pix Pro 4.0 software The image can be scanned using software or other suitable software. Non-positive spots after background removal and outliers detected by the ESD procedure were removed. The resulting signal intensity values ​​are normalized to the median value per chip and then used to obtain the geometric mean and standard error for each small non-coding RNA. Each signal can be transformed into a logarithm base 2 and a one-sample t-test can be performed. To increase the robustness of the data, each small non-coding RNA was spotted multiple times. Independent hybridizations for the samples can be performed on the chip.

[0072] Microarrays for profiling the expression of individual small non-coding RNAs in disease For example, RNA can be extracted from the sample and, if desired, Small non-coding RNAs are size-selected from total RNA. Oligonucleotide linkers are added. The resulting ligation product can be attached to the 5' and 3' ends of small non-coding RNAs. The reaction product is used as a template for the RT-PCR reaction. The primers are designed to bind fluorophores to their 5' ends, allowing the detection of PCR products. The PCR products are denatured and then hybridized to a microarray. The corresponding small non-coding RNAs, called target nucleic acids, are captured on the array. PCR products complementary to the probe sequence base-pair at the spots where the capture probes are immobilized. The spots are then scanned using a microarray laser scanner. When excited using a

[0073] Several positive and negative controls and array data normalization methods were then used to analyze each sequence. The fluorescence intensity of the pot is evaluated in terms of the copy number of a specific small non-coding RNA. The result is an assessment of the expression levels of specific small non-coding RNAs.

[0074] Small non-coding RNAs extracted from body fluid samples without size selection Total RNA containing NA can also be used directly. For example, T4 RNA ligase and and 3'-end labeling of RNA using fluorophore-labeled short RNA linkers. The fluorescent probes are complementary to the corresponding small non-coding RNA capture probe sequences on the array. The proteophore-labeled small non-coding RNAs base-pair at the spots where the capture probes are immobilized. Then, several positive and negative controls and arrays are hybridized. Using data normalization methods, the fluorescence intensity of each spot was determined to be the proportion of copies of a specific small non-coding RNA. The expression levels of specific small non-coding RNAs are evaluated in terms of the number of is brought about.

[0075] Spotted oligonucleotide microarrays, prefabricated oligonucleotides These include microarrays or spotted long oligonucleotide arrays. Several types of microarrays can be used, including but not limited to:

[0076] Measured without amplification using the nCounter Analysis System (NanoStain) (Georg Technologies, Seattle, Wash.) This technique involves the detection of two nucleic acids that hybridize in solution. Use high-based probes (e.g., reporter probes and capture probes). After hybridization, excess probe was removed and the probe was purified according to the manufacturer's protocol. The nCounter miRNA Assay Kit analyzes the lobe / target complex. Available from anoString Technologies, highly similar low Molecular non-coding RNA can be identified with high specificity.

[0077] Detecting small non-coding RNAs using branched DNA (bDNA) signal amplification (See, for example, Urdea, Nature Biotechnology (1999) 94), 12:926-928). Coding RNA assays are commercially available. One such assay is QuantiGen e® 2.0 miRNA Assay (Affymetrix, Santa Clara, CA) Clara, Calif.).

[0078] Northern blot and in situ hybridization were used to identify small molecule non- Coding RNA may also be detected. Northern blots and in situ hybridization Suitable methods for performing the fusion are known in the art.

[0079] In some embodiments, biomarker expression is measured using a multi-analyte profile test, enzyme-linked Immunosorbent assay (ELISA), radioimmunoassay, Western blot assay, immunoassay Fluorescence assay, enzyme immunoassay, immunoprecipitation assay, chemiluminescence assay, immunohistochemistry assay assay, dot blot assay, or slot blot assay, The antibody is measured by assays known to those skilled in the art, including but not limited to: In some embodiments, the antibody used is detectably labeled. Antibody labels include: Immunofluorescence labeling, chemiluminescence labeling, phosphorescence labeling, enzyme labeling, radiolabeling, avidin / biotin These include, but are not limited to, colloidal gold particles, colored particles, and magnetic particles. In some embodiments, biomarker expression is measured by an IHC assay. do.

[0080] In some embodiments, expression of a biomarker is determined by specifically binding to the biomarker. Any molecular entity that exhibits specific binding to a biomarker is measured using a test agent. The method can be used to measure the level of the biomarker protein in a sample. Binding agents include antibodies, antibody fragments, antibody mimetics, and polynucleotides ( For example, aptamers) are included, but are not limited to these. The degree of specificity depends on the particular assay used to detect the biomarker protein. In some embodiments, the present disclosure provides a method for detecting a protein comprising administering a protein to a solid support (e.g., antibodies, antibody fragments, antibody mimetics, and the like capable of binding to T3p or salts thereof; and / or polynucleotide-containing ELISA plates, gels, beads, or columns. The present invention relates to a system including:

[0081] C. Sequencing-Based Methods When available, advanced sequencing methods can be used as well. For example, small non-coding R NAs are obtained using Illumina next-generation sequencing (e.g., HiSeq, HiScan, Ge) nomeAnalyzer, or MiSeq system (Illumina, Inc., For example, Sequencing-By Small molecules can be detected using the ELISA (Synthesis or TruSeq) Non-coding RNAs were analyzed using Ion Torrent Sequencing (Ion Torrent). ent Systems, Inc., Gulliford, Conn.) or other suitable Detection can also be performed using semiconductor sequencing techniques such as:

[0082] D. Additional Small Noncoding RNA Detection Tools Mass spectrometry to quantify small non-coding RNAs using RNase mapping The isolated RNA can be analyzed by MS or tandem MS (MS / MS) analysis. Before their analysis by this approach, highly specific RNA endonucleases (RNPs) were used. ase) (e.g., RNase T1, which cleaves 3' to all unmodified guanosine residues) The first method developed was for direct coupling to ESI-MS. On-line chromatography of endonuclease digests by reversed-phase HPLC. The mass shift from the expected mass based on the RNA sequence determined the transcript. The presence of post-modifications can then be revealed by tandemly sorting the ions with unusual mass / charge values. and isolate them for MS sequencing to determine the sequence arrangement of post-transcriptionally modified nucleosides. This can be done.

[0083] Matrix-assisted laser desorption / ionization mass spectrometry (MALDI-MS) has also been used to characterize post-transcriptional modifications. It is used as an analytical method to obtain information about nucleosides. MAL-based techniques can be distinguished from ESI-based techniques by a separation step. DI-MS uses a mass spectrometer to separate small non-coding RNAs.

[0084] Custom-fabricated nanotubes for analyzing limited amounts of intact small non-coding RNA Spray ion source, Nanovolume Valve (Valco Instrument nts), and a splitless nano HPLC system (DiNa, KYA Techn Linear ion trap-orbitrap hybrid mass spectrometer with Analyzer (LTQ Orbitrap XL, Thermo Fisher Scienti fic) or a tandem quadrupole time-of-flight mass spectrometer (QSTAR XL, Appli By using a fluorometric analysis system (Ed Biosystems), coupling with nano-ESI-MS was achieved. A capillary LC system with a built-in LC column can be used. The intact small molecule non-coated sample is loaded onto a C trap column, desalted, and then concentrated. The RNA is eluted from the trap column and injected directly into a Cl8 capillary column. Chromatographic separation was performed by RP-HPLC using a solvent gradient of increasing polarity. The ionization voltage is used to allow ions to be scanned in negative polarity mode. The chromatography eluate is sprayed from the tip of the sprayer attached to the column. can be.

[0085] Additional methods for detecting and measuring small non-coding RNAs include, for example, streptavidin. Strand invasion assay (Third Wave Technologies, Inc.), Surface plasmon resonance (SPR), cDNA, MTDNA (metallic DNA; Advanced nce Technologies, Saskatoon, SK), and U.S. Gen. Examples include single molecule methods such as those developed by nanocomics. Micro-imaging using a novel technique combined with particle-enhanced SPR imaging (SPRI) Multiple small non-coding RNAs can be detected in an array format. Surface reactions of the enzymes hybridized onto locked nucleic acid (LNA) microarrays Create a poly(A) tail on a small non-coding RNA. Then, DNA-modified nanoparticles are The molecules are adsorbed to the poly(A) tail and detected by SPRI. Using the PRI method for attomole-level small non-coding RNA profiling It is possible.

[0086] E. Detection of amplified and non-amplified small non-coding RNAs In certain embodiments, a label, dye, or labeled probe and / or primer used to detect amplified or unamplified small non-coding RNAs Those skilled in the art will be able to determine which detection method is appropriate based on the sensitivity of the detection method and the abundance of the target. Depending on the sensitivity of the detection method and the abundance of the target, amplification may be required prior to detection. Those skilled in the art will appreciate that it may or may not be necessary to amplify small non-coding RNAs. A suitable detection method will be found.

[0087] The probe or primer may contain standard bases (A, T or U, G, and C) or Modified bases may be included. Modified bases include those described, for example, in U.S. Patent No. 5,432,272; AEGIS bases described in Patents 5,965,364 and 6,001,983 (obtained from Eragen Biosciences), but are not limited to In certain embodiments, the bases are linked by natural phosphodiester bonds or by different chemical bonds. As a different chemical bond, for example, the bond described in U.S. Pat. No. 7,060,809 is used. Examples of such linkages include peptide bonds or locked nucleic acids (LNA) as described above. Not limited to these.

[0088] In a further aspect, the oligonucleotide probes or primers present in the amplification reaction The method is suitable for monitoring the amount of amplification product produced as a function of time. In some embodiments, probes having different single-stranded versus double-stranded characteristics are used to detect nucleic acids. The probe is used for 5'-exonuclease assays (e.g. , TAQMAN) probes (see U.S. Pat. No. 5,538,848), stem Group molecular beacons (see U.S. Patent Nos. 6,103,476 and 5,925,517) (see reference), stemless or linear beacons (WO9921881, U.S. Pat. No. 6,444,626). 85,901, and 6,649,349), peptide nucleic acids (PNA ) molecular beacons (see U.S. Patent Nos. 6,355,421 and 6,593,091) ), linear PNA beacons (see, e.g., U.S. Pat. No. 6,329,144) and ), non-FRET probes (see U.S. Pat. No. 6,150,097), Sunr ise™ / AmplifluorB™ probes (U.S. Patent No. 6,548,2 50), stem-loop and double-stranded SCORPION probes (see U.S. Pat. No. 6,429,493). No. 6,589,743), bulge loop probes (see U.S. Pat. No. 6,590 ,091), pseudoknot probes (see U.S. Pat. No. 6,548,250 (See U.S. Patent No. 6,383,752), MG B Eclipse™ probe (Epoch Biosciences), hairpin PNA Light-Up Probe (see U.S. Patent No. 6,596,490) probe, antiprimer quench probe (Li et al., Clin. Chem. 53:624-633(2006)), self-assembled nanoparticle probes, and e.g., rice Examples include ferrocene-modified probes described in Japanese Patent No. 6,485,901. Examples include, but are not limited to:

[0089] In certain embodiments, one or more of the primers in the amplification reaction comprises a label. In yet other embodiments, the different probes or primers have detectable sequences that are distinguishable from one another. In some embodiments, a nucleic acid such as a probe or primer comprises a label that can be detected by a detection method. It may be labeled with two or more distinguishable labels.

[0090] In some embodiments, a label is attached to one or more probes and has one of the following properties: (i) providing a detectable signal; (ii) interacting with a second label; and a detection signal provided by a second label, for example FRET (fluorescence resonance energy transfer). (iii) modifying the detectable signal; (iv) detecting hybridization (e.g., duplex formation) ); and (iv) stabilizing a binding complex or affinity set, e.g., an affinity complex. , antibody-antigen complexes, ionic complexes, hapten ligands (e.g., biotin-avidin In yet another embodiment, the use of labels provides members of known labels, bonds, linking groups, any of a number of known techniques using reagents, reaction conditions, and analytical and purification methods. This can be achieved using

[0100] Small non-coding RNAs can be detected by direct or indirect methods. In direct detection methods, one or more small non-coding RNAs are coupled to a detection molecule linked to a nucleic acid molecule. In such methods, the small non-coding RNA is detected by a label that can be detected by a probe. The binding can be performed by labeling the labeled antibody before binding to the probe. The probes are used to detect small non-coding RNAs. can be coupled to beads in the reaction volume by

[0091] In certain embodiments, nucleic acids are detected by direct binding to a labeled probe, In one embodiment of the present invention, the amplified small non-coding RNA is then detected. Nucleic acids such as A are complexed with probes to capture the desired nucleic acid. Detection is performed using a Luminex® fluorosphere. Detection of branched DNA (bDNA) by label-modified polynucleotide probes ) detection.

[0092] In some embodiments, the expression of the biomarkers is determined by a primer specific for each biomarker. The present invention is measured using a PCR-based assay that includes markers and / or probes. As used herein, the term "probe" refers to a molecule that selectively binds to a target biomolecule of particular interest. As used herein, in some embodiments, the term " "Probe" refers to the substrates and / or reaction products and / or It is indirectly or directly, covalently or non-covalently bound to one of the proteases. The term "binding" refers to any molecule capable of binding or associating with another molecule, and the binding or association is not limited to the molecules disclosed herein. In some embodiments, the probe is detectable using methods known in the art. probe, antibody, or absorbance-based probe. If it is an absorbance-based probe, The chromophore pNA (paranitroaniline) is used to detect the target nucleic acid disclosed herein. They can be used as probes for the detection and / or quantification of sequences. In this state, the probe contains a fluorogenic molecule or substrate that becomes fluorescent when exposed to the enzyme. The nucleic acid sequence may be any of the nucleic acid sequences in Tables 1, 2 and / or 3. 70%, 80%, 81%, 82%, 83%, 84, 85 for any or a combination %, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95 %, 96%, 97%, 98%, 99%, or about 100% sequence identity of nucleic acid sequences is complementary to the fragment.

[0093] The target molecule may be any of the nucleic acid sequences identified in Tables 1, 2, and / or 3 or In some embodiments, the target molecule is selected from the group consisting of those listed in Tables 1, 2 and / or 70%, 80%, 81%, 82% or any combination of the nucleic acid sequences in %, 83%, 84, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92% , 93%, 94%, 95%, 96%, 97%, 98%, or about 99% sequence identity. Probes may be synthesized by those skilled in the art using known techniques. Probes may be derived from RNA, DNA, proteins, or biological preparations. These include, but are not limited to, proteins, peptides, aptamers, antibodies, and organic molecules. The terms "primer" and "probe" refer to an oligonucleotide having a specific sequence. In some embodiments, the target includes a target gene or an oligonucleotide having a specific sequence. The target molecule may be any of the nucleic acid sequences or combinations identified in Tables 1, 2 and / or 3. any combination of the nucleic acid sequences in Tables 1, 2 and / or 3 70%, 80%, 81%, 82%, 83%, 84%, 85%, 86%, 8 7%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 9 Any or a combination of nucleic acid sequences containing 7%, 98%, or about 99% sequence identity. Any amplified fragment of the sequence.

[0094] In other embodiments, the nucleic acid is detected by an indirect detection method, e.g., biotinylation. The probe contains a dye conjugated to streptavidin to detect the bound nucleic acid. Streptavidin molecules can be combined with the binding sites on the amplified small non-coding RNA. The tin label is bound to the small non-coding RNA, which then binds to a streptavidin molecule. In one embodiment, the dye molecules are detected by detecting the dye molecules. Dye molecules conjugated to streptavidin include PHYCOLINK. R-Phycoerythrin (PROzyme). Other conjugated pigment molecules are It is well known to the trade.

[0095] Labels may produce or be capable of producing a detectable fluorescent, chemiluminescent, or bioluminescent signal. These include light-emitting compounds that emit or quench light, light-scattering compounds, and light-absorbing compounds. Non-limiting examples include (e.g., Kricka, L., Nonisotopic DNA Protease Activity). be Techniques,Academic Press,San Diego(1 992) and Garman A., Non-Radioactive Labeling (See, e.g., Academic Press (1997)). Dual-labeled fluorescent probes containing a fluorophore and a quencher fluorophore are used in some embodiments. Pairs of fluorophores with different emission spectra are used in It will be appreciated that they are chosen to be easily distinguishable.

[0096] In certain embodiments, the label enhances or stabilizes hybridization of the duplex. Hybridization stabilizing moieties, e.g., insertions, that allow or affect Intercalating dyes or intercalating dyes (ethidium bromide and SYBR-Green) are also available. (e.g., Blackburn, et al., eds. “DNA and RNA Structure” in N ucleic Acids in Chemistry and Biology(19 96).

[0097] In another embodiment, hybridization to quantify small non-coding RNAs is performed. and / or ligation-based methods may be used, including oligonucleotide Ligation (OLA) method and distinguishable hybridized to the target nucleic acid sequence Examples include methods that allow the probes to be separated from unbound probes. The HARP-like process disclosed in U.S. Patent Application Publication No. 2006 / 0078894 is A probe can be used to measure the amount of miRNA. After hybridization between the target nucleic acid and the hybridized probe, The probes are then modified to distinguish them from unmodified probes. can be amplified and / or detected. Generally, the probe inactivation region is Contains a subset of nucleotides within the target hybridization region. To reduce or prevent amplification or detection of unhybridized HARP probes, That is, to allow detection of the target nucleic acid, a target nucleic acid sequence is hybridized to the target nucleic acid sequence. Distinguish between hybridized and unhybridized HARP probes A post-hybridization probe inactivation step using an agent that can This agent prevents unhybridized HARP probes from amplifying. This can be inactivated or modified to prevent the probe ligation reaction from It can also be used to quantify small non-coding RNAs. Probe amplification (Schouten et al., Nucleic Acids Re search 30:e57(2002)), the target nucleic acid is immediately adjacent to each other. Hybridizing probe pairs are driven to ligate to one another by the presence of target nucleic acid. In some embodiments, the MLPA probe has flanking PCR primer binding sites. MLPA probes are specifically amplified when ligated, thereby identifying small non-coding Allows for the detection and quantification of RNA biomarkers.

[0098] Detection of small RNA biomarker levels The small non-coding RNA biomarkers described herein are useful for assessing breast cancer status in a subject. They can be used individually or in combination in diagnostic tests to assess the state of breast cancer. Status includes the presence or absence of breast cancer. Breast cancer status includes monitoring the progression of breast cancer. The method may also include monitoring the progression of the disease, for example, by monitoring the progression of the disease. Based on the condition, further treatment may be indicated, including, for example, additional diagnostic tests or therapeutic measures. do.

[0099] Generally, the ability of a diagnostic test to correctly predict disease status is determined by the accuracy of the assay, the sensitivity of the assay, specificity, or "area under the curve" (AUC), e.g., receiver operating characteristics Accuracy is measured in terms of the area under the receiver operating characteristic (ROC) curve. Accuracy is a measure of the proportion of samples that are classified correctly. Accuracy is, for example, the percentage of samples that are classified correctly divided by the total number of samples in the test population. Sensitivity can be calculated as the total number of correctly classified samples that are positive by the test. is a measure of predicted "true positives" and is the number of correctly identified breast cancers divided by the total number of breast cancer samples. Specificity can be calculated as the number of samples predicted to be negative by the test (true negatives). is a measure of "identification" and is calculated as the number of correctly identified normal samples divided by the total number of normal samples. AUC can be calculated using the receiver operating characteristic (ROC), which is a plot of sensitivity versus false positive rate (1 - specificity). It is a measure of the area under the curve. The larger the AUC, the higher the predictive value of the test. Another useful measure of efficacy is the "positive accuracy" which is the percentage of actual positives that test positive. and "negative predictive value," which is the percentage of actual negatives that test as negative. In a preferred embodiment, one or more of the samples from subjects with different breast cancer status are The levels of small non-coding RNA biomarkers above are measured relative to appropriate controls If the difference is at least p=0.05 compared to normal subjects, e.g., p=0.05, p=0 Statistically significant differences such as p=0.01, p=0.005, and p=0.001 are indicated. In embodiments, the small non-coding RNA biomarkers described herein, individually or in combination, are used in The diagnostic test used in combination should have an accuracy of at least about 75%, e.g., at least about 75%. %, approximately 80%, approximately 85%, approximately 90%, approximately 95%, approximately 97%, approximately 99%, or approximately 100% In other embodiments, the accuracy of the small non-coding RNA biomarkers described herein is shown. Diagnostic tests using these drugs individually or in combination have a specificity of at least about 75%, e.g. For example, at least about 75%, about 80%, about 85%, about 90%, about 95%, about 97%, about 9 In other embodiments, the small molecule non- Diagnostic tests using coding RNA biomarkers, individually or in combination, are at least At least about 75% sensitivity, e.g., at least about 75%, about 80%, about 85%, about 90%, about 9 In other embodiments, the method of the present invention exhibits a sensitivity of about 5%, about 97%, about 99%, or about 100%. Diagnostics using the small non-coding RNA biomarkers described in this document, individually or in combination The diagnostic test has a specificity and sensitivity of at least about 75%, respectively, e.g., at least about 75%. %, approximately 80%, approximately 85%, approximately 90%, approximately 95%, approximately 97%, approximately 99%, or approximately 100% exhibits a specificity and sensitivity of at least about 80% (e.g., at least about 80% specificity and at least about 8 0% sensitivity, or, for example, at least about 80% specificity and at least about 95% sensitivity. degrees).

[0100] Each biomarker listed in Tables 1, 2 and 3 is associated with breast cancer compared to normal subjects differentially present in biological samples from subjects, each of which facilitates the determination of breast cancer in a test subject. Such methods are each useful for facilitating the identification of biomolecules in a sample derived from a subject. Determining the level of a biomarker in a sample involves measuring the level of the biomarker. The method may be performed to detect biomarkers in a sample using any suitable method, for example, the methods described herein. The method may include measuring, detecting, or analyzing the level of a biomarker in a sample. Determining the level of a biomarker in a sample is performed by measuring, detecting, or assaying the level of the biomarker in the sample. The method may also include examining the results of the assay. This may involve comparing the biomarkers to an appropriate control. An alteration in the level of the marker relative to that of a normal subject is indicative of the breast cancer status of the subject. indicates the upper or lower limit of the amount of biomarkers at which a patient is classified as not having a particular breast cancer condition. A diagnostic amount of a biomarker can be used, for example, in a sample from an individual with breast cancer. In this case, if the biomarkers are upregulated compared to normal individuals, a diagnostic cutoff is established. A measured amount greater than 100 provides a diagnosis of breast cancer. Generally, the individual small molecule non-coding RNA biomarkers were significantly higher in breast cancer samples compared to samples obtained from normal individuals. As is well understood in the art, the amount of ATP used in the assay is Adjusting the specific diagnostic cutoff used can be used to adjust the sensitivity and The specificity and / or the specificity can be adjusted. Biomarkers in a statistically significant number of samples from subjects with different breast cancer status Measuring the amount and cutting at the desired level of accuracy, sensitivity, and / or specificity In certain embodiments, the diagnostic cutoff can be determined by As described herein, this can be determined with the aid of a classification algorithm.

[0101] Therefore, at least one of the circulating small non-coding RNAs in a sample from a subject is for diagnosing breast cancer in a subject by determining the level of small non-coding RNAs 10. A method for detecting a level of at least one small non-coding RNA from a normal subject, comprising: wherein a difference to (determined relative to a suitable control) indicates the presence of breast cancer in the subject. In one embodiment, the at least one small non-coding RNA preferably comprises includes one or more small non-coding RNAs from Table 1. In one embodiment, at least A small non-coding RNA preferably includes one or more small non-coding RNAs from Table 2. In one embodiment, the at least one small non-coding RNA preferably comprises The present invention provides a method for the production of a small non-coding RNA molecule comprising administering to a subject a small non-coding RNA comprising administering to a subject a small non-coding RNA molecule ... At least one small non-coding RNA in a sample containing circulating small non-coding RNAs A method for determining the level of NA, comprising measuring the level of at least one small non-coding RNA. wherein an increase in the level of breast cancer compared to a control indicates the presence of breast cancer in the subject.

[0102] Optionally, the method of the invention comprises determining the level of at least one small non-coding RNA in the sample. and providing a diagnosis of whether the subject has or does not have breast cancer based on the results. Additionally or alternatively, the methods of the present invention may include measuring at least one of the following: The differences in the levels of two small non-coding RNAs were associated with the diagnosis of breast cancer in subjects. In some embodiments, such a diagnosis is provided directly to the subject. The patient may be provided to another party involved in the care of the subject.

[0103] As shown herein, individual small non-coding RNA biomarkers are Although useful for cancer diagnostic applications, combinations of small non-coding RNA biomarkers are not sufficient for single Higher accuracy of breast cancer status than small non-coding RNA biomarkers when used alone Specifically, the detection of multiple small non-coding RNA biomarkers can provide a The accuracy, sensitivity, and / or specificity of diagnostic tests may be increased. Exemplary low RNA biomarkers and biomarker combinations are shown in Table 1. Molecular non-coding RNA biomarkers and biomarker combinations are shown in Table 2. Exemplary small non-coding RNA biomarkers and biomarker combinations are shown in Table 3. The present invention includes the individual biomarkers and biomarkers described in these tables. marker combinations and their use in the methods and kits described herein. Use is included.

[0104] Therefore, two or more small molecules in a sample containing circulating small non-coding RNAs from a subject Method for diagnosing breast cancer in a subject by determining the level of non-coding RNA - Patent Application 20070122999 The method further comprises measuring the difference in the level of small non-coding RNA relative to that of a normal subject (an appropriate control). (as determined by comparison with a) indicates the presence of breast cancer in a subject. In this embodiment, the small non-coding RNA is preferably one of the small non-coding RNAs shown in Table 1. In one embodiment, the small non-coding RNA preferably includes one or more of the following: In one embodiment, the small non-coding RNAs include one or more of the following: The small non-coding RNA preferably includes one or more of the small non-coding RNAs shown in Table 3. .

[0105] two or more small non-coding RNAs in a sample containing circulating small non-coding RNAs from a subject determining the level of NAs, and determining the levels of two or more small non-coding RNAs in a sample to determine normal The levels of the same small non-coding RNAs present in normal subjects and subjects with breast cancer were analyzed. and comparing the subject to a data set showing breast cancer or breast cancer based on the comparison. Also provided are methods for diagnosing breast cancer in a subject by diagnosing the absence of breast cancer. In this method, the dataset is used as an appropriate control or reference standard for comparison with subject-derived samples. It functions as such.

[0106] Comparison of a subject-derived sample to a dataset is performed by comparing two or more small non-coding RNAs in the sample. The overall levels of the same small molecule non-co- proteins present in normal subjects or subjects with breast cancer were compared. A classification algorithm that calculates whether there is a statistically significant difference between the levels of chromatin and DNA. can be assisted by

[0107] Generate a classification algorithm to assess cancer status In some embodiments, data generated using a sample, such as a "known sample," is The "known samples" can be pre-classified and used to "train" a classification model. samples classified as derived from normal subjects or subjects with breast cancer. The data derived from the spectra and used to form the classification model are called the "training data." Once trained, the classification model can be generated using unknown samples. The classification model can recognize patterns in the data derived from the spectra. It can then be used to classify unknown samples into classes. The body sample is associated with a certain biological state (e.g., diseased vs. non-disease). This can be useful in predicting whether a patient will develop a disease.

[0108] In some embodiments, the training data set used to form the classification model Data for this purpose are obtained using quantitative PCR (e.g., Ct values ​​obtained using the double delta Ct method). from, or high-throughput expression profiling such as microarray analysis (e.g. , total or normalized counts from small non-coding RNA expression assays ) can be obtained directly from

[0109] A classification model divides a collection of data into classes based on the objective parameters present in the data. formed using any suitable statistical classification (or "learning") method that attempts to separate Classification methods can be either supervised or unsupervised. An example of a classification process is given in Jain, "Statistical Pattern Recognition" ognition:A Review”, IEEE Transactions on Pattern Analysis and Machine Intelligenc e, Vol. 22, No. 1, January 2000, the teachings of which are Incorporated by reference.

[0110] In supervised classification, training data containing examples of known classes are used to define each of the known classes. The resulting set of relationships is then submitted to a learning mechanism that learns one or more sets of relationships that define the new The data can be applied to a learning mechanism, which then uses the learned relationships to learn new data. Examples of supervised classification processes include linear regression processes (e.g., multilinear regression). Multivariate regression (MLR), partial least squares (PLS) regression, and principal component regression (PCR), Decision trees (e.g., recursive partitioning processes such as CART - classification and regression trees), backpropagation nets artificial neural networks such as networks, discriminant analysis (e.g., Bayesian classifiers or filters), Scherr analysis), logistic classifier, and support vector classifier Examples include the Torumasin.

[0111] In other embodiments, the classification model that is created may be formed using unsupervised learning methods. Unsupervised classification is the process of performing a training dataset without prior classification of the spectra from which it was derived. They attempt to learn classification based on similarities in a training dataset. Unsupervised learning methods include Cluster analysis involves identifying clusters that are very similar to each other and are not related to other clusters. A "cluster" or It attempts to partition the data into groups. It then calculates some distances that measure the distance between the data items. A distance metric is used to measure similarity, which places data items closer to each other. Cluster them together. The clustering technique is McKean's K-means algorithm. and Kohonen's self-organizing map algorithm. The learning algorithms claimed for use in the present invention are described, for example, in International Patent Publication No. WO01 / 3 1580(Barnhill et al., “Methods and devices s for identifying patterns in biological systems and methods of use thereof), U.S. Patent Application No. 2002 0193950 A1 (Gavin et al., "Met hod or analyzing mass spectra), U.S. Patent Application No. No. 2003 0004402 A1 (Hitt et al., “Process f or discriminating between biological sta. tes based on hidden patterns from biolog ical data") and U.S. Patent Application No. 2003 0055615 A1 (Zhang and Zhang, “Systems and methods fo r processing biological expression data” ), the contents of which are incorporated herein by reference in their entirety. It can be enjoyed.

[0112] The classification model may be developed and used on any suitable digital computer. Examples of popular digital computers include Unix (registered trademark) and Windows (registered trademark). or any standard operating system, such as a Linux-based operating system. or micro, small, or large computers using special operating systems Examples include data.

[0113] The training data set(s) and the classification model are run or processed by a digital computer. The computer code may be expressed by a computer program that is used to program the optical disc. Any suitable computer-readable storage medium, including disks or magnetic disks, sticks, tapes, etc. It can be stored on a removable medium and can be written in any language, such as C, C++, visual basic, etc. It may be written in any suitable computer programming language.

[0114] The above learning algorithm was used to classify small non-coding RNA biomarkers for breast cancer. The classification algorithm can then be used alone or The diagnostic values ​​(e.g., cutoff points) for the biomarkers used in combination are By providing the antibody, it can be used in diagnostic tests.

[0115] Additional diagnostic tests The level of a small non-coding RNA biomarker indicative of the presence of breast cancer is determined by measuring the level of breast cancer in the subject. Optionally, the method of the present invention can be used as an independent diagnostic indicator of breast cancer. For example, the method may include performing at least one additional test that facilitates the diagnosis of breast cancer. determining the levels of one or more small non-coding RNA biomarkers to Other tests can be performed in addition to those used in clinical practice to facilitate the diagnosis of breast cancer. Any other test or combination of tests used may be used to identify small molecule non-coding RhoA as described herein. It may be used in conjunction with NA biomarkers.

[0116] Treatment method In some embodiments, where a subject is diagnosed with breast cancer by the methods described herein, the present invention The present invention further provides a method of treating such a subject confirmed to have breast cancer. In one embodiment, the present invention provides a method of treating breast cancer in a subject, comprising administering to the subject determining the level of at least one small non-coding RNA biomarker in the derived sample and determining whether at least one small non-coding molecule is present in the target gene, as determined by comparison with a suitable control. Differences in the levels of RNA biomarkers in breast cancer subjects relative to those in normal subjects and administering to the subject a therapeutically effective amount of a breast cancer therapeutic agent. In another embodiment, the present invention relates to a method of treating a subject with breast cancer. and at least one nucleotide sequence in a sample derived from the subject, as determined by comparison with a suitable control. The levels of small non-coding RNA biomarkers in and identifying subjects with progressive (e.g., increasing) breast cancer and providing the subjects with a therapeutically beneficial The method includes administering an effective amount of a breast cancer therapeutic agent.

[0117] The term "breast cancer therapeutic" includes, for example, US Food and Drug Administration (FDA)-approved anti-cancer drugs for the treatment of breast cancer. Contains substances approved by the Drug Administration to treat breast cancer. Approved drugs for this purpose include abemaciclib, avitrexate (methotrexate), Abraxane (paclitaxel-albumin-stabilized small particle formulation), Adotrastuz Mab emtansine, Afinitor (everolimus), anastrozole, Aredia ( Pamidronate disodium), Arimidex (anastrozole), Aromasin (extraneous Semestan), Capecitabine, Clafen (Cyclophosphamide), Cyclophosphamide , Cytoxan (cyclophosphamide), docetaxel, doxorubicin hydrochloride, Elence (epirubicin hydrochloride), epirubicin hydrochloride, eribulin mesylate, everolimus, Exemestane, 5-FU (fluorouracil injection), Fairston (toremifene) , Faslodex (fulvestrant), Femara (letrozole), Fluorourac Sil Injection, FOLEX (methotrexate), Folex PFS (methotrexate) ), fulvestrant, gemcitabine hydrochloride, Gemzar (gemcitabine hydrochloride), Gose Relin acetate, Halaven (eribulin mesylate), Herceptin (trastuzumab) , Ibrance (palbociclib), ixabepilone, Ixempra (ixabepilone), Kadcyla (ado-trastuzumab emtansine), Kisqali (ribociclib), and Lapatini ditosylate, letrozole, megestrol acetate, methotrexate, methotrex Methotrexate LPF (methotrexate), Mexate (methotrexate), Mexat e-AQ (methotrexate), Neosar (cyclophosphamide), neratinib maleate Neratinib maleate, Nerlynx (neratinib maleate), Nolvadex (tamoxifen Paclitaxel, Paclitaxel-albumin-stabilized small particle formulation, Bociclib, pamidronate disodium, Perjeta (pertuzumab), pertuzumab Ribociclib, Tamoxifen citrate, Taxol (paclitaxel), Taxon Telo (docetaxel), thiotepa, toremifene, trastuzumab, Tykerb (Rapamycin), tinib tosylate dihydrate), Velban (vinblastine sulfate), Velsar ( vinblastine sulfate), Verzenio (abemaciclib), vinblastine sulfate , Xeloda (capecitabine), and Zoladex (goserelin acetate), Not limited to:

[0118] The breast cancer therapeutic agent can be administered to a subject using a pharmaceutical composition. Suitable pharmaceutical compositions are available from Pharmacy a therapeutically effective amount of a breast cancer therapeutic agent (or a pharmaceutically acceptable salt or ester thereof) , optionally including a pharmaceutically acceptable carrier). In certain embodiments, these compositions optionally further comprising one or more additional therapeutic agents.

[0119] As used herein, the term "pharmaceutically acceptable salt" means a salt that is acceptable within the scope of sound medical judgment. in the tissues of humans and lower animals without excessive toxicity, irritation, or allergic response. refers to salts that are suitable for use in contact with and correspond to a reasonable benefit / risk ratio. Pharmaceutically acceptable salts of amines, carboxylic acids, and other types of compounds are well known in the art. For example, S. M. Berge et al., in reference to pharmaceutically acceptable salts, J. Pharmaceutical Sciences, incorporated herein by reference. , 66:1-19 (1977). Salts are the most preferred form of the compounds of the present invention. The free base or free acid functionality can be converted to a suitable amine, either in situ during subsequent isolation and purification or separately. For example, a free base function can be prepared by reacting with a suitable acid. Furthermore, when the compound of the present invention possesses an acidic moiety, its appropriate pharmaceutically acceptable salt may be used. The salts that can be used include alkali metal salts (e.g., sodium or potassium salts) and alkali metal salts. Metal salts such as earth metal salts (eg, calcium or magnesium salts) are included.

[0120] As used herein, the term "pharmaceutically acceptable ester" refers to a compound that is hydrolyzable in vivo. These esters are easily decomposed in the human body, leaving the parent compound or its salt. Suitable ester groups include, for example, esters derived from pharmaceutically acceptable aliphatic carboxylic acids. Derived ones, especially alkyl or alkenyl moieties, each advantageously have 6 or fewer carbon atoms. Alkanoic, alkenoic, cycloalkanoic, and alkanedioic acids (a Examples include methyl methyl ketone (methyl ketone) and methyl ketone (methyl ketone).

[0121] As mentioned above, the pharmaceutical composition may additionally contain a pharmaceutically acceptable carrier. The term "solvent" includes any solvent, diluent, or other suitable solvent to prepare the particular dosage form desired. liquid vehicle, dispersing or suspending aid, surfactant, isotonic agent, thickener or emulsifier, preservative These include additives, solid binders, and lubricants. Remington's Pharmace utical Sciences,Sixteenth Edition,EWMa rtin(Mack Publishing Co., Easton, Pa., 1980 ) is a list of various carriers used in formulating pharmaceutical compositions and known methods for their preparation. Some examples of materials that can function as pharmaceutically acceptable carriers include: sugars such as lactose, glucose, and sucrose; corn starch and Starches such as potato starch; sodium carboxymethylcellulose, ethylcellulose Cellulose and cellulose acetate and other cellulose derivatives; powdered tragacanth; wheat Buds; gelatin; talc; excipients such as cocoa butter and suppository wax; peanut oil, cottonseed Oils such as safflower oil, sesame oil, olive oil, corn oil and soybean oil, propylene glycol, etc.; ethyl oleate and ethyl laurate, etc. Esters; agar; buffers such as magnesium hydroxide and aluminum hydroxide; algin Acid; pyrogen-free water; isotonic saline; Ringer's solution; ethyl alcohol, and phosphorus Acid buffers include, but are not limited to, sodium lauryl sulfate and Other non-toxic compatible lubricants such as magnesium stearate, as well as coloring agents, Also contains additives, coating agents, sweeteners, flavorings and fragrances, preservatives and antioxidants. It may be present in the composition at the discretion of the person skilled in the art.

[0122] Compositions for use in the present invention may be formulated to have any desired concentration of a breast cancer therapeutic agent. In a preferred embodiment, the composition is formulated to contain a therapeutically effective amount of a breast cancer therapeutic agent. It is formulated.

[0123] The present disclosure generally relates to methods for diagnosing subjects with benign, pre-malignant, or malignant hyperproliferative cells. The method comprises detecting the presence of at least one non-coding RNA or a functional fragment thereof in a sample. In some embodiments, the method includes detecting the presence, absence, and / or amount of In the method, the detecting step comprises: subjecting a sample from a subject (e.g., a human subject) to one or more protease inhibitors; Each probe is exposed to one or more non-coding RNA molecules in the sample. In some embodiments, the probe comprises: A nucleic acid sequence of at least 70%, 80%, 85%, or 90% relative to any of the nucleic acid sequences of Tables 1, 2, and / or 3 %, 90%, 95%, 96%, 97%, 98%, 99% sequence homology or sequence identity In some embodiments, the nucleic acid molecule is a nucleic acid molecule (DNA, RNA, or a hybrid thereof) comprising the nucleic acid molecule. In this case, the probes are SEQ ID NO: 3, SEQ ID NO: 19, SEQ ID NO: 32, SEQ ID NO: 40, SEQ ID NO: No. 41, SEQ ID NO: 79, SEQ ID NO: 82, SEQ ID NO: 83, SEQ ID NO: 126, SEQ ID NO: 148 or at least 70%, 80%, 85%, 90%, 95% relative to SEQ ID NO: 191; Nucleic acid molecules (DNA) containing 96%, 97%, 98%, or 99% sequence homology or sequence identity , RNA, or a hybrid thereof). In some embodiments, the probes are Thymine is replaced by uracil, SEQ ID NO: 3, SEQ ID NO: 19, SEQ ID NO: 32, SEQ ID NO: No. 40, SEQ ID NO: 41, SEQ ID NO: 79, SEQ ID NO: 82, SEQ ID NO: 83, SEQ ID NO: 126, At least 70%, 80%, 85%, 90%, 100%, 110%, 120%, 130%, 140%, 150%, 160%, 170%, 180%, 190%, 200%, 210%, 220%, 230%, 240%, 250%, 260%, 270%, 280%, 290%, 300%, 310 R containing 0%, 95%, 96%, 97%, 98%, and 99% sequence homology or identity A nucleic acid molecule (DNA, RNA, or a hybrid of these) is a nucleic acid sequence. In an embodiment, the plurality of probes comprises SEQ ID NO:3, SEQ ID NO:19, SEQ ID NO:32, SEQ ID NO: No. 40, SEQ ID NO: 41, SEQ ID NO: 79, SEQ ID NO: 82, SEQ ID NO: 83, SEQ ID NO: 126 , SEQ ID NO: 148, or at least 70%, 80%, 85% of SEQ ID NO: 191; Contains 90%, 95%, 96%, 97%, 98%, and 99% sequence homology or identity It is one or a combination of nucleic acid sequences that are RNA complementary to the nucleic acid sequence. In this embodiment, the plurality of probes comprises one or a combination of nucleic acid sequences selected from: Combination of: SEQ ID NO: 3, SEQ ID NO: 19, SEQ ID NO: 32, SEQ ID NO: 40, SEQ ID NO: 4 1, SEQ ID NO: 79, SEQ ID NO: 82, SEQ ID NO: 83, SEQ ID NO: 126, SEQ ID NO: 148, or or SEQ ID NO: 191. In some embodiments, the plurality of probes comprises a nucleic acid selected from the following: The nucleic acid sequence may be one or a combination of the following: SEQ ID NO: 3, SEQ ID NO: 19, SEQ ID NO:32, SEQ ID NO:40, SEQ ID NO:41, SEQ ID NO:79, SEQ ID NO:82, SEQ ID NO: No. 83, SEQ ID NO: 126, SEQ ID NO: 148, or SEQ ID NO: 191.

[0124] In any of the embodiments of the disclosed methods, the subject is diagnosed with or has breast cancer. The detecting step may be performed after obtaining a sample from the subject. In any of the method embodiments of the present disclosure.

[0125] In some embodiments, the probe or probes include SEQ ID NO:3, SEQ ID NO:1 9, SEQ ID NO: 32, SEQ ID NO: 40, SEQ ID NO: 41, SEQ ID NO: 79, SEQ ID NO: 82, SEQ ID NO: SEQ ID NO: 83, SEQ ID NO: 126, SEQ ID NO: 148, or SEQ ID NO: 191 0%, 80%, 85%, 90%, 95%, 96%, 97%, 98%, 99%, or 10 Nucleic acid molecules (DNA, RNA, or any of these) that contain 0% sequence homology or sequence identity The antibody or antibody fragments are one or more antibodies or antibody fragments containing CDRs that bind to the antibody or antibody hybrid. In some embodiments, the probe or probes each have a sequence similar to SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5, SEQ ID NO: 6, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 9, SEQ ID NO: 10, SEQ ID NO: 11, SEQ ID NO: 12, SEQ ID NO: 13, SEQ ID NO: 14, SEQ ID NO: 15, SEQ Sequence number 19, sequence number 32, sequence number 40, sequence number 41, sequence number 79, sequence number 82 , SEQ ID NO: 83, SEQ ID NO: 126, SEQ ID NO: 148, or SEQ ID NO: 191 SEQ ID NO: 3, SEQ ID NO: 19, SEQ ID NO: 20, SEQ ID NO: 21, SEQ ID NO: 22, SEQ ID NO: 23, SEQ ID NO: 24, SEQ ID NO: 25, SEQ ID NO: 26, SEQ ID NO: 27, SEQ ID NO: 28, SEQ ID NO: 29, SEQ ID NO: 30, SEQ ID NO: 31, SEQ No. 32, SEQ ID NO: 40, SEQ ID NO: 41, SEQ ID NO: 79, SEQ ID NO: 82, SEQ ID NO: 83, At least 70%, 8% or more of SEQ ID NO: 126, SEQ ID NO: 148, or SEQ ID NO: 191 0%, 85%, 90%, 95%, 96%, 97%, 98%, 99%, or 100% distribution Nucleic acid molecules (DNA, RNA, or hybrids thereof) that contain sequence homology or sequence identity. In one embodiment, the antibody or antibody fragment comprises one or more CDRs that bind to the target polypeptide. In some of these, the methods of the present invention involve assaying the sample prior to exposing the sample to one or more probes. In some embodiments, the methods of the invention further comprise isolating RNA from the sample. by performing semi-quantitative or quantitative PCR or sequence analysis of non-coding RNAs in Detect or quantify the amount of non-coding RNA, such as small mRNA, in a sample The probe comprises a single-stranded nucleotide sequence comprising a non-coding RNA derived from the subject. ELISA plates, plastic, slides, and microphones to be exposed to the sample. The antibody may be immobilized on a solid support such as a microarray, a silica chip, or other surface. In embodiments, the probes may comprise a length of about 5 to about 100 nucleotides and are shown in Tables 1, 2, and any of the sequences in Tables 1, 2, and / or 3 or any of the sequences in Tables 1, 2, and / or 3 This includes any complementary sequence in RNA or DNA of the sequence. In either case, at least one non-coding RNA or one of the non-coding RNAs in the sample is detected. The presence, absence, and / or amount of a homologous sequence that is at least 70% homologous to one of the The detecting step may include using a chemiluminescent probe, a fluorescent probe, and / or fluorescence microscopy. by correlating the signal of the detectable probe with the presence of non-coding RNA using This includes calculating the presence or amount of

[0126] The present disclosure generally relates to detecting the presence of T3p in a sample and to detecting the presence of T3p in a sample. The present disclosure also relates to linking the presence of SEQ ID NO: 3, SEQ ID NO: 19, SEQ ID NO: 32, SEQ ID NO: 40, SEQ ID NO: 41, SEQ ID NO: 79, SEQ ID NO: 82, SEQ ID NO: 8 3, SEQ ID NO: 126, SEQ ID NO: 148, or SEQ ID NO: 191 or any of the sequence identifiers These RNA molecules have one or more thymines replaced by uracils. At least 70%, 80%, 85%, 90%, 95%, 96%, 97%, 98%, Comprising, consisting of, or essentially having 99% or 100% sequence homology or sequence identity The present invention is directed to detecting the presence of nucleic acid molecules (DNA, RNA, or hybrids thereof) consisting of In some embodiments, the probe or probes on the solid support are SEQ ID NO: 3, SEQ ID NO: 19, SEQ ID NO: 32, and the like, which are about 5 to about 1000 nucleotides in length. Sequence number 40, sequence number 41, sequence number 79, sequence number 82, sequence number 83, sequence number 12 6, comprising sequence complementarity to SEQ ID NO: 148 or SEQ ID NO: 191. In the present invention, the probe or probes on the solid support are from about 5 to about 500 nucleotides in length. SEQ ID NO: 3, SEQ ID NO: 19, SEQ ID NO: 32, SEQ ID NO: 40, SEQ ID NO: 41, No. 79, SEQ ID NO: 82, SEQ ID NO: 83, SEQ ID NO: 126, SEQ ID NO: 148 or SEQ ID NO: In some embodiments, the probe or The probes may be from about 5 to about 100 nucleotides in length, such as SEQ ID NO: 3, SEQ ID NO: 19, SEQ ID NO: 32, SEQ ID NO: 40, SEQ ID NO: 41, SEQ ID NO: 79, SEQ ID NO: 82, SEQ ID NO: 8 3, comprising sequence complementarity to SEQ ID NO:126, SEQ ID NO:148 or SEQ ID NO:191. In some embodiments, the probe or probes on the solid support are from about 5 to about 50 The nucleotide lengths of SEQ ID NO: 3, SEQ ID NO: 19, SEQ ID NO: 32, SEQ ID NO: 40, No. 41, SEQ ID NO: 79, SEQ ID NO: 82, SEQ ID NO: 83, SEQ ID NO: 126, SEQ ID NO: 148 or comprising the sequence complementarity to SEQ ID NO:191.

[0127] In some embodiments, any of the methods disclosed herein comprises the steps of: and / or 3, or any combination thereof. Correlating the presence or amount of the RNA to the likelihood that the subject has cancer, such as breast cancer. Further includes:

[0128] Kits for detecting small RNA biomarkers In another aspect, the present invention provides a kit for diagnosing breast cancer status in a subject, comprising: Table 1, Table 2, or Table 3, and combinations thereof (wherein the sequences are optionally containing uracil in place of one, more than one, or all of the thymines and kits that are useful for determining the level of one or more of the above-listed RNA biomarkers. In one embodiment, the one or more small non-coding RNAs are selected from the group consisting of those listed in Table 1. In one embodiment, the two or more small non-coding RNAs are selected from the group consisting of those listed in Table 2. In one embodiment, three or more small molecule non-covalent biomarkers are selected from the biomarkers listed in The RNA is selected from the biomarkers listed in Table 3. The kit includes a A small non-coding RNA or a group of small non-coding RNAs in a sample that is diagnostic for breast cancer The present invention may include materials and reagents suitable for selectively detecting the presence of A. For example, in one embodiment In one embodiment, the kit may include a reagent that specifically hybridizes to a small non-coding RNA. Such reagents may be nucleic acid molecules in a form suitable for detecting small non-coding RNAs, e.g., promoters. The kit may be a probe or primer. The kit may detect one or more small non-coding RNAs. Reagents useful in performing assays for the detection of one or more low-molecular-weight compounds, e.g., in a qPCR reaction The kit may also include reagents that can be used to detect non-coding RNAs. The present invention can include microarrays useful for detecting the above small non-coding RNAs.

[0129] In a further embodiment, the kit may include appropriate operating instructions in the form of a label or package insert. For example, the instructions may include instructions on how to collect the sample, how to prepare the sample, A method or test for determining the level of one or more small non-coding RNA biomarkers in a subject The levels of one or more small non-coding RNA biomarkers in the sample are associated with breast cancer status in the subject. It may also include information or instructions on how to link.

[0130] In another embodiment, the kit comprises an assay for detecting a biomarker in a test sample. Small molecule non-coding R-proteins used as reference standards, suitable controls, or for calibration It may contain one or more containers with samples of NA biomarkers.

[0131] Other embodiments are described in the following non-limiting examples: patents, published applications, Various publications, including technical and scholarly articles, are cited throughout this specification. Each of these cited publications is incorporated herein by reference in its entirety. [Example]

[0132] Example 1. Method Examples 2-6 were carried out by methods including, but not limited to, the following.

[0133] tissue culture MDA-MB-231 and MDA-LM2 cells were cultured in 10% fetal bovine serum, L-glutamine, and ethanol. amine, sodium pyruvate, penicillin-streptomycin, and amphotericin The cell lines were cultured in Dulbecco's medium supplemented with 100% ethanol. The cells were obtained from the American College of Cancer Culture Collection (ATCC) and transfected according to their protocol. and grew it.

[0134] All cells were cultured in a humidified incubator at 37°C and 5% CO2. B-231, MDA-LM2, CN34-par, CN34-Lm1a, MCF7, and and MDA-MB-453 cell lines were cultured in 4.5 g / L glucose, 10% FBS, 4 mM of L-glutamine, 1 mM sodium pyruvate, penicillin (100 units / mL), Supplemented with streptomycin (100 μg / mL) and amphotericin (1 μg / mL). HCC1395, ZR-75-1, and HCC1395 were grown in DMEM-based medium supplemented with HCl. CC38 cell line was cultured in 10% FBS, 2 mM L-glutamine, penicillin (100 units / mL), streptomycin (100 μg / mL), and amphotericin (1 μg / SK-BR-3 cell line was grown in RPMI 1640-based medium supplemented with 1000 mg of 10 ... 10% FBS, penicillin (100 units / mL), streptomycin (100 μL), in McCoy's 5a modified medium supplemented with 1 μg / mL), and amphotericin (1 μg / mL). HMECs were obtained from Thermo Fisher Scientific. and grown in pre-made HuMEC medium (Thermo Fisher Scientific). I bred them.

[0135] Small RNA and exosomal RNA extraction and sequencing of RNA from extracellular vesicles Preparation of conditioned medium and complete conditioned medium for isolation was performed using 7 x 10 5 Seeding cells with After 24 hours, the cells were washed twice with PBS and 10 mL of exosomes was added. After 48 hours, the medium was centrifuged at 200 × g for 15 minutes, and the supernatant was FBS was collected by removing the exosomes from the culture medium. Remove exosomes by substituting with HCl (Fisher Scientific) The exosome-depleted HMEC medium was incubated at 4°C for 100,000 cycles. The medium components of bovine pituitary extract were prepared by centrifugation at × g for 16 hours.

[0136] Extracellular vesicle RNA was collected using Cell Culture Media Exosome Pu rification and RNA Isolation kit(Norgen Using a PBS (BioTek), a single PBS was prepared from 5 mL of conditioned medium prepared as outlined above. RNA from the conditioned medium was purified using miRNeasy serum / plasma kit. The total intracellular ATP was isolated from 400 ul of complete conditioned medium using a Qiagen ELISA kit. RNA samples were purified using Norgen Biotek's small molecule RNAi kit according to the manufacturer's protocol. RNA samples were extracted using an RNA purification kit. The RNA samples were then purified according to the manufacturer's protocol ( Bio Scientific) to use NEXTflex Small RNA Prepared for high-throughput sequencing using Sequencing Kit v3 The resulting library was then sequenced and processed as recommended by the manufacturer. In summary, we used cutadapt(v1.4) to remove the adapter sequences and The first and last degenerate sequences of each read were trimmed. Using ie2 (v2.3.3), the obtained sequences were cloned into the human genome (build hg38 The resulting BAM files were then sorted and used for further analysis. Extracellular vesicle RNA was converted to BED for ELISA. a / serum Exosome Purification and RNA iso was isolated from serum samples using a lation kit (Norgen Biotek). .

[0137] Small RNA sequencing data from TCGA-BRCA and TCGA-BRCA projects The identification of oncRNA reads by the project was performed using the Genomic Data Common Download the sample in BAM format (hg38) from GDC A. Annotation was performed using PI. The Piranha package was used for BED format conversion. J 40 The loci of expressed small RNAs were identified using , merged across all samples using mergeBed to identify the genes occurring in breast tissue and breast cancer. We generated a comprehensive list of expressed small RNA loci.

[0138] By enumerating small RNA sequences obtained from breast cancer cell lines and HMECs, We generated a count table for each small RNA locus. They normalized the resulting table by library size and calculated the total number of replicates across all three HMEC replicates. Only loci for which no reads were observed in the whole genome were retained. Using robust statistical tests, we compared the data across all cancer cell lines or for each subtype individually (TNBC, HER2+, and luminal) were compared: (i) we used the DESeq R package (ii) we used Fisher's exact test to calculate adjusted p-values. The present inventors compared the presence and absence of each small RNA in the former test. had an adjusted P value <0.05 in the latter test or P across all comparisons in the latter test Loci with <0.1 were selected.

[0139] 437 loci (listed in Figure 1A) met these criteria. Next, we normalized each column to its maximum value and performed k-means clustering (k=3). For the TCGA-BRCA database, we have identified subtypes annotated Among all samples tested (based on PAM50 classification) and all small RNA loci Generate a similar count table and normalize the resulting table to counts per million reads. We generated a table of the number of small RNAs (cpm) in normal cells. To identify small RNAs that are rarely present in normal samples, we first Only loci with 90th percentile expression below 0.5 cpm in the sample were retained. Of the 437 loci listed above, 268 passed this step. We performed Fisher's exact test to confirm all the differences between tumor samples and normal biopsies. The present inventors compared the presence of small RNAs in normal samples and each of the breast cancer subtypes. We then performed a similar comparison between the two groups, with an adjusted p-value of <0.05. Loci that were significant in at least one of these tests were retained. Small RNAs pass through this final step and are therefore classified as orphan non-coding RNAs. The present inventors have not previously classified any of these small RNAs as miRNAs, s We confirmed that they were not annotated as noRNA or tRNA.

[0140] Small RNA sequencing of PDX models and normal epithelial samples All human samples used to generate PDX tumor and human non-tumor samples were previously It was stated 41 Small RNA profiling and data preprocessing were performed using Q 2 Sol The abundance of oncRNA in these samples was determined as described above. Comparison of oncRNA expression between low and high metastatic cells To identify oncRNAs that were significantly upregulated in highly metastatic cells, we performed , using the DESeq2 R package, the parent cell lines (MDA231 and CN3 4) and their in vivo selected highly metastatic derivatives (MDA-MB-231 background In this analysis, we compared the expression of T3p and oncRNA between the two groups. We also analyzed small RNA datasets previously generated in these cell lines. T3p was also confirmed in 7 In addition, the present inventors also performed quantitative RT-PCR assays. In this regard, the present inventors have investigated the relationship between the parental MDA-231 cells and their highly metastatic MDA-231 - Small RNA was extracted from LM2 (microRNA Purification Kit). it, Norgen), and stem-loop qPCR was performed using the following primers: R: 5'-CCAGTGCAGGGTCCGAGGTA and F: 5'-CCCAGGA CTCGGCTCACAC. Expression and clinical relevance of T3p in the TCGA-BRCA dataset We used the metadata associated with the TCGA-BRCA dataset to identify tumor samples. We performed a survival analysis based on the expression of T3p in the tissues. Stratify patients based on β and generate Kaplan-Meier curves using all tertiles. Log-rank (Mantel-Cox) tests were performed to calculate the associated P values. Clinical data were also used to compare T3p expression between early and late stage tumors (unilateral Mann-Whitney U test). T3p regulation and gene expression profiling We performed miR- CURY LNA inhibitor (Exiqon) was used: T3p:CAGGACTCGGC TCACACATGC;TERC:TTGTCTAACCCTAACTGAGAAGG; Scrambled sequence: AGACGACAGCTGGATCACACG. Similarly, the inventors used a T3p mimetic (IDT): rC*rArGrGrArCrUrCrG r GrCrUrCrArCrArCrArUrG*rC (T3p mimic) and rA*rG rA rCrGrA rCrArG rCrUrG rGrArU rCrArC rA rC*rG (control). We then administered LNA to highly metastatic MDA-LM2 cells. The mimics and mimetics were transfected into MDA-MB-231 parental cells and subjected to gene expression profiles as previously described. Profiling was performed 7 Differential gene expression analysis was also performed as previously described. 7 . Tough Decoy and in vivo lung colonization and tumor growth assays stomach MDA-LM2 cells were incubated with anti-T3p or scrambled LNA (same as above). After transfection, the cells were transfected into the tail vein of immunodeficient NOD SCIDγ (NSG) mice for 48 hours. The mice were injected into the vasculature via the endothelial cells (2.5 x 10 per mouse). 4 (n=5 per cohort) In vivo imaging and curve comparison were performed as previously described. 19 Next , Lungs were removed and fixed from at least three mice per cohort (middle signal). Sectioned, stained (H&E), and quantified as previously described 19 . To induce stable inhibition of T3p, we used a lentiviral backbone The T gene for this small RNA was expressed under the RNA Pol III promoter (pLKO.1). We then stably transduced MDA-LM2 cells and expressed pulmonary Colony formation assays were performed (as above; 5 × 10 per mouse). 4 cells) HCC1395 cells were similarly transduced, with 2 x 10 cells per mouse. 5 cells were injected Orthotopic tumor growth assays were performed in 50 ul of PBS mixed with 50 ul of Matrigel. Resuspended 2.5 x 10 5 The cells were cultured in 6- to 8-week-old female NOD / SCID γ-mammary oocytes. The injection was performed by using a 28-gauge needle into the mammary gland of a mouse. The tumor diameter (L) and width (W) are measured every 2 days and calculated using the formula πLW2 / 6. Once the tumor reached 800 mm, the tumor volume was determined. 3 When the volume reaches In vitro cell proliferation: Cancer cell proliferation assay was performed at 0 5 x 10 on the day 4 cells were seeded and then plated in triplicate on days 3 and 5. The logarithm of cell number versus days is estimated using a linear model. The slope of the best fit line between the number of cells and the growth rate (days) is recorded. -1 ) for cell cycle analysis. To achieve this, cells were grown to 80% confluency in 6 cm plates, harvested, and then cultured at 70% confluency. The cells were then pelleted and fixed with 50 μg / mL of propidium iodide. (Thermo Fisher Scientific) and 1 mg / mL of RNA Resuspended in digestion enzyme A (Thermo Fisher Scientific) and incubated for 37 min. The cells were then cultured at 4°C for 1 hour. Then, the cells were placed on a BD Aria2 flow cytometer for FACS analysis. Post-FACS analysis and cell cycle quantification were performed using the fcsparse This was done using the python package FCSparser:https: / / github.com / eyurtsev / fcsparser / tree / mas ter / fcsparser

[0141] Co-expression analysis to discover T3p biogenesis factors To identify regulators of T3p biogenesis In this study, we investigated the effect of nuclease activity (GO:0004540 and GO:000 4525) and furthermore, to list genes that interact with these nucleases. RNA-binding proteins with known binding sites were added. 42 Next, the present inventors investigated the TCGA- Co-expression between T3p levels in the BRCA dataset and levels of genes on this list The present inventors performed an analysis of the upregulated and regulated IL-111 in highly metastatic MDA-LM2 cells. and similarly in breast cancer samples compared to normal biopsies in the TCGA-BRCA dataset. Based on these criteria, genes with high and strong associations were overlaid. We identified seven candidates, two of which have known double-stranded binding activity. The CR7 domain of TERC is assembled (i.e., forms a double-stranded region), The inventors have demonstrated that these proteins (i.e., DROSHA and TARBP2) We concluded that DR1 is the best candidate for investigation. OSHA and TARBP2, and further interact with these proteins, respectively DGCR8 and DICER1, which are known to be involved in the development of gliomas, were knocked down (IDT). They used the following target sequences: TARBP2: 5'-ACCTGGGATTCTC TACGAAATTCAGT, DROSHA:5'-CCTTGATTGAGGTATA GTTCTTGTCT, DICER1:5'-TGGTGCTTAGTAAACTCTT GGTTCCA, and DGCR8: 5'-CTGCAGGAGTAAGGACAGGA After confirming siRNA gene transfer and knockdown, the present inventors Small RNA sequencing was performed as described.

[0142] Training and testing of oncRNA-based classifiers. Of the 201 oncRNAs, 100 were detected in at least one serum sample. For TCGA-BRCA samples annotated for subtypes using oncRNA We then trained the GBC (sklearn module). A compendium of serum samples from normal and 40 cancer patients was bootstrapped 100 times. Calculate the classifier's performance parameters, i.e., mean AUROC, precision, and accuracy scores We trained and tested on serum data in contrast to TCGA-BRCA. An independent evaluation of oncRNA was also performed by performing a 5-fold cross-validation. We performed a similar analysis as above using the following miRNAs: miR-1 0b-5p, miR-10b-3p, miR-148b-3p, miR-148b-5p , miR-155-3p, miR-155-5p, miR-34a-3p, miR-37 6a-3p, miR-652-3p, miR-133a-3p, miR-139-3p, miR-143-3p, miR-145-3p, miR-15a-3p, miR-18a -3p, miR-425-3p, miR-34a-5p, miR-376a-5p, mi R-652-5p, miR-133a-5p, miR-139-5p, miR-143- 5p, miR-145-5p, miR-15a-5p, miR-18a-5p, miR- 425-5p, miR-127-3p, miR-194-5p, miR-205-5p, miR-21-5p, miR-375, miR-376c-3p, miR-382-5p , miR-409-3p, and miR-411-5p. Animal studies All animal studies were performed in the U. university of California San Francisco IA Completed in accordance with CUC guidelines. Statistical methods used to assess data significance. The statistical tests used are described in the legend. In summary, unless otherwise stated, They performed pairwise comparisons using non-parametric tests. We used a two-way ANOVA with time as a covariate. For this study, we used a linear model. The analysis was performed using Python, R, and pri It was run in an sm environment.

[0143] Example 2. Systematic search for orphan small non-coding RNAs in breast cancer A novel class of proteins expressed in breast cancer cells but undetectable in normal breast tissue To search for cancer-specific small RNAs in multiple breast cancer subtypes and human breast epithelial cells, An unbiased approach based on small RNA sequencing of cells was used. Approximately 200 previously unknown differentially expressed small RNAs discovered To highlight their cancer-specific biogenesis, these RNAs were Borrowing a term from bacterial genetics, we have named these "orphan" non-coding RNAs (oncRNAs). It is attached.

[0144] First, we investigated the accessibility of potential regulators in cancer cells, which are present only in cancer cells. It was determined whether there existed a set of small RNAs that could provide a viable pool. OncRNA is detectable only in cancer cell lines, but not in normal cells. To test this hypothesis, small RNA sequencing was performed on nine species of breast cancer cell lines (all representing major breast cancer subtypes) and human mammary epithelial cells as a reference The results were performed on human mesenchymal stem cells (HMEC). The results were significant in all breast cancer lines, but not in HMEC samples. 437 unannotated small RNAs were identified that were not detected by the IL-1 gene (Figure 1A).

[0145] To further narrow the search and strengthen these findings, a similar analysis was performed on approximately 200 We provided small RNA expression profiles of normal tissue samples and all 1200 breast cancer biopsies. Small molecules obtained from The Cancer Genome Atlas (TCGA) This analysis was performed on RNA sequencing data. 268 cancer-specific low-molecular-weight genes were identified. Two RNA molecules were identified, 201 of which were also present in the breast cancer cell lines. The highly significant overlap between the independent analyses of 201 on with high confidence is shown in Table 1 below. A set of cRNAs was identified (Fig. 1B and Fig. 2A). [Table 1-1] [Table 1-2] [Table 1-3] [Table 1-4] [Table 1-5] [Table 1-6] [Table 1-7] [Table 1-8] [Table 1-9] [Table 1-10] [Table 1-11] [Table 1-12] [Table 1-13]

[0146] As a third line of evidence, 10 patient-derived xenograft (PDX) models and 4 normal epithelial models A dataset of small RNA profiles from unmatched samples was analyzed. As shown, these oncRNAs are almost absent in normal samples but are present in PDX models. By summing the expression of all 201 oncRNAs across all samples, A simple classification that perfectly separates normal and PDX profiles Taken together, these findings suggest that the expression of ribosomal proteins is essential for the development of breast cancer. We establish the existence of a large pool of oncRNAs that are strongly associated with cancer.

[0147] Example 3. Identification of T3p, an oncRNA associated with breast cancer progression In addition to the aforementioned cell lines, we selected for high metastatic potential in vivo in immunodeficient mice. Highly metastatic cell lines that have been identified have also been profiled (1, 15). When the expression of oncRNAs in highly metastatic cells was compared to their low metastatic parental lines, One oncRNA was observed whose levels were significantly increased in the 40-nucleotide The oncRNA of the otide is 3' to the TERC gene, which encodes the RNA component of telomerase. Therefore, this previously unknown small RNA A was named T3p because it is the 3' RNA of TERC. Analysis of a previously published dataset (7) demonstrated high expression of T3p in highly metastatic cells. This upregulation of T3p expression in metastatic cells was further confirmed by qPCR (Fig. 3C). This was confirmed by (Figure 3C).

[0148] Next, it was investigated whether increased T3p expression contributed to the pathogenesis of the underlying disease. Approximately 400 from BRCA (The Cancer Genome Atlas, breast cancer) Matched normal and breast cancer tumor tissue samples were analyzed, and T3p expression was found to be highly cancer-specific. It was found that there was a significant difference (Figure 3D). Next, TCG with approximately 1000 tumor samples was performed. The entire A-BRCA dataset was included. Consistent with its identity, T3p was not detected in the majority of normal samples, but It was detected at relatively high levels in tumor biopsies and, more importantly, in highly metastatic cell lines. Consistent with the high expression of T3p in rhesus monkeys, there was a highly significant association between patient survival and T3p expression. Furthermore, as shown in Figure 3G, T3p expression was significantly increased in TCGA-B cells. Normal samples, stage I, and stage II or III in the RCA dataset The detection of any level of T3p in tumor samples is indicative of breast cancer and The T-cell response in clinical breast cancer samples was strongly associated with both shorter and more severe overall survival (Figure 4A and Figure 4B). Higher expression of 3p also strongly correlated with advanced stage breast cancer (Figure 3E). Stratification of these cancer samples by HER2 and HER2 status was consistent with T3p levels. Strong association with strogen receptor, progesterone receptor, or HER2 receptor expression Consistent with this finding, PD in breast cancer compared with normal epithelial tissue was not observed (Figure 4C). Increased expression of T3p was also observed in the X model (Figure 4D). established oncRNA T3p as a cancer-specific biomarker with high prognostic value do.

[0149] Example 4. T3p acts as a broad regulator of gene expression in breast cancer cells The strong association between T3p expression and breast cancer progression from multiple independent data sets supports the conclusion that T3 This raises the possibility that p plays a direct and functional role in breast cancer progression. To elucidate the function of T3p, it was investigated whether modulation of T3p expression levels resulted in modulation of the outcome. To this end, highly metastatic MDA-LM2 cells were treated with antisense oligonucleotides targeting T3p. by transfection with LNA or scrambled LNA as a control. Gene expression profiling was then performed to determine whether T3p was silenced. We measured the genome-wide regulatory impact of T3p silencing. Surprisingly, thousands of T3p silencing significantly alters the cellular gene expression profile, affecting a wide range of genes. Significant changes were observed in many established transcription factors, including small non-coding RNAs. However, the effects of LNAs targeting T3p are comparable to those of post-regulatory factors (7, 16). also affect TERC function, which may account for the observed changes in gene expression. The full-length TERC transcript remains a potential confounding factor because it may be possible that Two independent methods were used to distinguish between the two. First, a scrambling LNA In addition, antisense LNAs against the 5' end of full-length TERC and T3p were also used. As shown in Figure 1, the gene expression changes caused by anti-T3p LNA were Whether a scrambled LNA or an anti-full-length TERC LNA is used as a reference This observation supports the conclusion that inhibition of full-length TERC is mediated by T3p inhibition. Furthermore, these findings suggest that ATP does not induce the same dramatic regulatory changes as ATP. To strengthen the relationship, gain-of-function experiments were also performed. MDA-MB-231 parental breast cancer cells were cultured using scrambled oligonucleotides as a control. Transfection with oligonucleotides and then gene expression profiling was performed. Similar to the LNA experiments, significant changes in the distribution of cellular gene expression were observed. Notably, these gene expression changes were similar to those observed in loss-of-function LNA experiments. This was generally anti-correlated with anti-T3p LNA and T3p mimics (Figure 6A). This is consistent with the expectation that α should induce opposing changes in gene expression. These observations establish T3p as a broad regulator of gene expression in breast cancer cells. do.

[0150] Example 5. T3p promotes breast cancer metastasis Broad regulatory effects of T3p on gene expression and its association with metastasis and breast cancer Given the association with poor survival in mice, we next investigated the role of this oncRNA in metastasis in vivo. To test this hypothesis, we investigated whether highly metastatic MDA-L M2 cells were transfected with anti-T3p LNA and these cells were transformed into immunodeficient mice. Metastatic lung colonization assays were performed by injecting the mice into the venous circulation. In vivo imaging was used to study the time course of metastatic lung colonization of these cells. The effect of T3p inhibition on T3p expression was measured. As shown in Figure 6B, anti-T3p LNA Cells transfected with α-glucan significantly attenuated their lung colonization ability. Macroscopic histological examination also revealed that the lungs of mice injected with T3p-LNA transfected cells As shown in Figure 6C, the results revealed significantly fewer visible metastatic nodules in the 100% PO4+ / 2 ... Visual metastatic nodules were counted in three mice from each cohort. Representative H&E-stained lung sections from the study are also shown, along with median counts. reveals the previously unknown functional role of T3p in driving breast cancer metastasis. Strongly support the role.

[0151] Example 6. Specific oncRNAs are sorted into the exosome compartment The exosome compartment contains small molecules such as small non-coding RNAs and tRNA fragments. It has previously been reported as a biologically relevant destination for dna RNA (28). Analysis of exosome small RNA-seq data from MDA-MB-231 cells (29 ) demonstrated that a large number of annotated oncRNAs in this study are exogenous to cancer cells. In comparison, these cytoplasmic vesicles were found to be highly resistant to ATP (Fig. 7A). Only a few of these oncRNAs were detected in exosome samples from HUVEC cells. For example, T3p was expressed in MDA-MB-231 cells but not in HUVEC cells. These observations support the idea that exosomes contain small molecules called R This prompted the next series of experiments aimed at profiling NA. In this study, small RNAs were isolated from exosomes secreted by eight breast cancer cell lines and HMECs. Small RNA sequencing of this material revealed 201 annotated oncRNAs. Of the A's, approximately two-thirds were found in exosomal RNA from one or more of these breast cancer lines. We found that IL-16 was detected in IL-16 cells but not in HMECs (Fig. 7B). Interestingly, T3p was detected in 5 of the 8 cell lines.

[0152] To assess whether oncRNAs are also present in the circulating RNA population, we analyzed breast cancer patient-derived We reanalyzed a collection of RNA-seq data generated from RNA isolated from serum of (31) The baseline included data collected from the serum of 11 healthy individuals. As shown in Figure 7C, the majority of oncRNAs were circulating RNAs derived from breast cancer patients. Although detectable in samples, it was generally absent in healthy individuals. This observation is consistent with the ncRNAs may be used for cancer fingerprinting using liquid biopsies To assess this possibility, a linear model was applied to the collected data from the cell line. We trained on the exosomal oncRNA dataset (Figure 7B) and used it to generate circulating The trained model predicted the classification of RNA profiles in 11 / 11 healthy individuals (Figure 7C). Normal samples and samples from 31 / 40 cancer patients were successfully assigned (AUC: 0.96 , AUPRC: 0.99, and ACC: 0.82). For example, T3p alone is associated with breast cancer The expression levels were significantly different between the control and healthy volunteers (Figure 7C and Figure 8B Given the success of this simple classifier, a more generalizable machine learning approach is being developed, known as TCGA- Train a gradient boosting classifier on 201 oncRNAs from the BRCA dataset This model, trained on the TCGA data, was then compared with the circulating hypothetical data in Figure 7C. The classifier was tested on 11 / 11 healthy samples and 37 / 4 0 patient samples were successfully classified (AUC: 0.976, AUPRC: 0.993, and Based on these results, we hypothesized that circulating oncRNA Detection should provide highly specific and robust information regarding the potential presence of cancer. The list of 67 identified circulating oncRNAs is shown in Table 2 below. vinegar. [Table 2-1] [Table 2-2] [Table 2-3] [Table 2-4] [Table 2-5]

[0153] Finally, from the 201 identified oncRNAs, the following oncRNAs shown in Table 3 were identified: Which has the strongest ability to predict the presence of breast cancer in subjects by analysis of serum samples? It was found that... [Table 3-1] [Table 3-2]

[0154] The current hypothesis of breast cancer development and progression is that abnormalities result in increased selection of oncogenic phenotypes. As a result, the development of cancer therapeutics and diagnostic agents is Targeting these pathways to reduce the ability of these cancer cells to survive, divide, or spread In an embodiment of the present invention, the cancer cells express cancer-specific regulatory pathways. It was proposed that the brain can evolve to create new cells. Systematic and unbiased discovery steps targeting cancer cell lines and HUMEC 201 expressed in breast cancer cells but nearly undetectable in normal tissues A group of RNA species, collectively termed orphan non-coding RNAs, was identified. These RNA molecules represent novel pathways that cancer cells can use to create novel regulatory circuits. This provides a diverse pool of potential regulatory factors. To answer this question, low- and high-metastatic cells were compared. One of these RNAs, tagged with α-glucan, was identified in both the cell line model and the clinical dataset. Finally, the present invention has been shown to be strongly associated with metastatic progression in the presence of IFN-γ. Examples include the fact that oncRNAs can be detected in the circulating and exosomal compartments. Indicates that.

[0155] These findings may contribute to understanding how cancer progression and tumors evolve and regulate their progression on the way to metastatic spread. It offers a new paradigm for how pathways can be rewired. The results also suggest a novel tool for breast cancer detection and monitoring that may complement current methods. Current screening methods for breast cancer, including mammography and ultrasound, are low-resolution Given that they provide limited detection signals due to Other strategies in development for early cancer detection involve extracting circulating tumors from patients' serum. Liquid biopsy, which attempts to detect biological markers of cancer, including tumor cells and DNA. We have focused on the high abundance of secreted exosomes in the serum of patients and on The cancer cell specificity of cRNA provides a more reliable method for early detection or screening. In other words, the research described herein may provide a significant enhancement to our repertoire for The study found that oncRNA acts as a digital fingerprint of potential tumors – i.e. , supporting the idea that each marker is either detected or not detected.

[0156] Although the examples described herein have mostly focused on the role of T3p in breast cancer metastasis, The techniques and concepts presented herein are generalizable and applicable to several cancers. Taken together, these findings support further investigation of cancer-specific RNA distribution. and oncRNA research will lead to alternative treatments and diagnostic methods for many cancer types. It opens up the possibilities that can be brought about. References 1.SFTavazoie et al., Endogenous human m icroRNAs that suppress breast cancer met astasis.Nature.451,147-U3(2008). 2. C.J. David, M. Chen, M. Assanah, P. Canoll, J. L.Manley,HnRNP proteins controlled by c- Myc deregulate pyruvate kinase mRNA spli cing in cancer.Nature.463,364-368(2010). 3. S. Vanharanta et al., Loss of the multif unctional RNA-binding protein RBM47 as a source of selectable metastatic traits in breast cancer.eLife.3(2014),doi:10.75 54 / eLife.02734. 4. L. 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Claims

1. A method for sequencing non-coding ribonucleic acid (RNA) molecules from a cell-free sample obtained from a human female subject, comprising: (a) providing said cell-free sample from said human female subject, said cell-free sample comprising a first set of non-coding RNA molecules; (b) subjecting the first set of non-coding RNA molecules to reverse transcription to generate one or more complementary deoxyribonucleic acid (cDNA) molecules; (c) sequencing the one or more cDNA molecules or derivatives thereof; and (d) determining, based on the sequencing of step (c), whether the first set of non-coding RNA molecules comprises one or more non-coding RNA molecules of a second set of non-coding RNA molecules, wherein the second set of non-coding RNA molecules is present in a breast tumor sample and the second set of non-coding RNA molecules has a 90th percentile expression of less than 0.5 cpm (counts per million) reads in a normal sample. A method comprising:

2. The method described in claim 1, wherein the non-coding RNA molecule has a length of less than 200 nucleotides.

3. The method described in claim 1, wherein the non-coding RNA molecule has a length of 50 to 100 nucleotides.

4. The method described in claim 1, further comprising, after step (b), a step of amplifying a cDNA molecule from the one or more cDNA molecules.

5. The method of claim 1, further comprising, after step (a), isolating the first set of non-coding RNA molecules from other components of the cell-free sample.

6. The method described in claim 5, wherein the isolation comprises filtration.

7. The method of claim 1, further comprising a step of using the results of the sequencing to determine the amount of non-coding sequences of the first set of non-coding RNA molecules in the cell-free sample.

8. The method of claim 1, wherein the acellular sample comprises serum.

9. The method of claim 1, wherein the acellular sample comprises plasma.

10. The method of claim 1, wherein the acellular sample comprises urine.

11. The method of claim 1, wherein the acellular sample comprises lymphatic fluid.

12. The method of claim 1, wherein the acellular sample comprises saliva.

13. The method described in claim 1, wherein the total volume of the acellular sample is between 20 microliters and 2 milliliters.

14. The method described in claim 1, wherein the total volume of the acellular sample is between 100 microliters and 500 microliters.

15. The method of claim 1, wherein the acellular sample comprises plasma and the total volume of the acellular sample is between 100 microliters and 1 milliliter.

16. The method described in claim 1, wherein the sequencing in step (c) generates sequencing reads, and the sequencing reads are processed to identify non-coding sequences of the non-coding RNA molecules of the first set of non-coding RNA molecules.

17. The method of claim 1, wherein the sequencing in step (c) includes sequencing-by-synthesis.

18. The method described in claim 1, wherein the normal sample is derived from a subject who does not have breast cancer.

19. The method of claim 4, wherein the amplifying step includes performing a polymerase chain reaction (PCR).

20. The method of claim 4, wherein the amplifying step comprises rolling circle amplification.

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