Small RNA-based prognostic signatures and therapeutic compositions for idiopathic pulmonary fibrosis

Abstract

The present disclosure provides methods, kits, and therapeutic molecules for assessing and treating patients with IPF and subtypes of IPF. Specifically, the present disclosure provides methods for diagnosing patients with IPF and subtypes of IPF based on the expression profile of small non-coding RNA biomarkers. The present disclosure also provides therapeutic molecules that target dysregulated sRNAs in the expression profile. In some aspects and embodiments, the present disclosure provides miR-92a-3p isoforms and compounds that mimic the action of miR-92a-3p or its isoforms for use in treatment, including but not limited to, the treatment of IPF.

Description

[Technical Field]

[0001] Priority This application claims the benefit of and priority to U.S. Provisional Application No. 63 / 539,640, filed September 21, 2023, and U.S. Provisional Application No. 63 / 416,662, filed October 17, 2022, the contents of which are incorporated herein by reference in their entireties.

[0002] Incorporation by reference of sequence listing This application is filed with an electronic Sequence Listing. The Sequence Listing is provided as file SRN-007PC_115987-5007_SequenceListing_ST26, created on October 16, 2023, and is 797,594 bytes in size. The information in the electronic format of the Sequence Listing is incorporated by reference in its entirety. [Background technology]

[0003] Idiopathic pulmonary fibrosis (IPF) is a heterogeneous interstitial lung disease (ILD) with variable etiologies and disease courses. Lack of effective treatments means IPF has a poor prognosis, with median survival after diagnosis ranging from 2 to 5 years based on several longitudinal studies. Some patients experience accelerated decline and death within months of diagnosis, while others experience slow, gradual progression over several years. The inherent uncertainty in the disease course hinders physicians from providing patients with timely care, including lifestyle planning, treatment, and referral to lung transplant centers. With the advent of antifibrotic agents such as nintedanib and pirfenidone, IPF disease progression can be slowed but not cured. This heterogeneous disease course presents significant challenges for both clinicians and drug developers.

[0004] There is a need for diagnostic tests and treatments, including therapies that utilize precision medicine-based approaches, for IPF and other fibrotic disorders. In various aspects and embodiments, the present disclosure fulfills these and other objectives. Summary of the Invention

[0005] The present disclosure provides methods and kits for assessing and risk stratifying subjects with idiopathic pulmonary fibrosis (IPF). Specifically, the present disclosure provides methods and kits for determining the expression profile of small non-coding RNA biomarkers that can predict the risk of death in subjects with IPF. In another aspect, the present disclosure provides therapeutic compositions for IPF and other conditions based on small non-coding RNAs, which have the potential to correct dysregulation of several messenger RNA targets, e.g., by sRNA mimics or antisense oligonucleotides targeting sRNAs. In various embodiments, the sRNA is an sRNA isoform (e.g., miR-92a-3p isoform) whose expression is dysregulated in disease states.

[0006] In one aspect, the present disclosure provides a method for risk stratification of a subject diagnosed with idiopathic pulmonary fibrosis (IPF), the method comprising providing a blood, serum, or plasma sample from the subject, generating an expression profile of at least five small RNAs listed in Table 2, and determining a risk of death as a function of the expression profile, thereby risk stratifying the subject. In embodiments, the method further comprises determining the subject's GAP stage and determining the risk of death based on the expression profile and the GAP stage. In embodiments, subjects with a high-risk stratification are selected or prioritized for surgical or pharmaceutical intervention.

[0007] In one aspect, the present disclosure provides a method for assessing idiopathic pulmonary fibrosis in a subject, the method comprising providing a blood, serum, or plasma sample from the subject, generating an expression profile of at least five small RNAs listed in Table 6, and identifying the subject as having a subtype of idiopathic pulmonary fibrosis that correlates with an overall risk of death based on the expression profile. In various embodiments, subjects with high-risk subtypes are selected or prioritized for surgical or pharmaceutical intervention.

[0008] In another aspect, the disclosure provides kits for evaluating samples for risk stratification of IPF, e.g., according to the methods described herein. In some embodiments, the kits include sRNA-specific probes and / or primers configured to detect multiple sRNAs listed in Table 2 (SEQ ID NOS: 1-44). In some embodiments, the kits include sRNA-specific stem-loop RT primers. Exemplary stem-loop primers are listed in Table 3. In various embodiments, the kits include forward and reverse primers for amplifying the reverse transcription product (i.e., resulting from reverse transcription using the stem-loop primer). In some embodiments, the reverse primer can be a universal primer. In some embodiments, the forward primer is listed in Table 3. Universal reverse primers are also listed in Table 3. In various embodiments, the kits include fluorescently labeled sRNA-specific probes for detecting amplicons in real time. In some embodiments, the probes further include a quencher moiety.

[0009] In another aspect, the disclosure provides kits for assessing a sample for high-risk subtypes of IPF, e.g., according to the methods described herein. In some embodiments, the kit includes sRNA-specific probes and / or primers configured to detect multiple sRNAs listed in Table 6 (SEQ ID NOS: 45-115). In some embodiments, the kit includes an sRNA-specific stem-loop RT primer. Exemplary stem-loop primers are listed in Table 7. In various embodiments, the kit includes a forward primer and a reverse primer for amplifying the reverse transcription product (i.e., resulting from reverse transcription using the stem-loop primer). In some embodiments, the reverse primer can be a universal primer. In some embodiments, the forward primer is listed in Table 7. Universal reverse primers are also listed in Table 7. In various embodiments, the kit includes a fluorescently labeled sRNA-specific probe for detecting amplicons in real time. In some embodiments, the probe further includes a quencher moiety.

[0010] In other aspects, the present disclosure provides therapeutic molecules based on the dysregulation of sRNAs in Table 2. Specifically, the present disclosure provides pharmaceutical compositions comprising molecules designed to mimic the action of sRNAs that are downregulated in subjects with IPF or IPF at high risk of death. In some embodiments, such molecules induce RNA interference of target RNAs (e.g., mRNAs targeted by specific sRNAs) in cells. In some embodiments, the present disclosure provides pharmaceutical compositions comprising antisense oligonucleotides designed to reduce the expression of sRNAs that are upregulated in subjects with IPF or IPF at high risk of death. Such antisense oligonucleotides can induce degradation of or prevent the action of the target sRNA.

[0011] In other aspects, the present disclosure provides therapeutic molecules based on the dysregulation of sRNAs in Table 6. Specifically, the present disclosure provides pharmaceutical compositions comprising molecules designed to mimic the action of sRNAs that are downregulated in subjects with IPF or IPF at high risk of death. In some embodiments, such molecules induce RNA interference of target RNAs (e.g., mRNAs targeted by specific sRNAs) in cells. In some embodiments, the present disclosure provides pharmaceutical compositions comprising antisense oligonucleotides designed to reduce the expression of sRNAs that are upregulated in subjects with IPF or IPF at high risk of death. Such antisense oligonucleotides can induce degradation of or prevent the action of target sRNAs.

[0012] In various embodiments, the siRNA is a mimic of miR-92a-3p or an isoform thereof (e.g., an isoform listed in Table 6). In various embodiments, the siRNA induces degradation of one or more mRNA targets of miR-92a-3p. In some embodiments, the siRNA induces degradation of one or more mRNA targets of an isoform of miR-92a-3p that is substantially under-abundant in high-risk IPF.

[0013] In some embodiments, the siRNA mimics the action of miR-92a-3p or an isoform thereof, such as the isoforms listed in Table 10 (SEQ ID NOS: 734-762). These siRNAs comprise an antisense sequence or strand having the nucleobase sequence of the sRNA isoform (optionally with a 3' overhang, such as dTdT), which can be chemically modified according to known techniques. Exemplary nucleobase sequences of the antisense strand are shown in Table 10 (SEQ ID NOS: 763-791). Exemplary sense or passenger strands are also shown (SEQ ID NOS: 792-820).

[0014] When introduced into a cell in vivo or ex vivo, the siRNA induces degradation of one or more target RNAs (e.g., target mRNAs) in the cell. In some embodiments, the siRNA induces degradation of multiple mRNAs in the target cell. In some embodiments, one or more mRNAs are decreased in expression in several pro-fibrotic pathways (WNT, TGF-beta, and focal adhesions). In some embodiments, one or more mRNAs are decreased in expression in pathways such as ECM, collagen, and interleukin-mediated inflammatory pathways. In some embodiments, the target cell is a lung epithelial cell. In various embodiments, the siRNA is formulated for systemic delivery or for local delivery to the lung. In various embodiments, the siRNA is encapsulated in lipid nanoparticles, polymer nanoparticles, or liposomes. In various embodiments, the siRNA is delivered by inhalation, optionally in aerosol (e.g., solution or powder aerosol) form.

[0015] In another aspect, the disclosure provides methods (or uses of compositions) for treating a subject with IPF, comprising administering an effective amount of the composition sufficient to reduce expression of a small RNA selected from Table 2 (SEQ ID NOS: 1-44). In various embodiments, the composition is effective to reduce expression of a small RNA in Table 2 that has been demonstrated herein to be elevated in abundance in IPF subjects at increased risk of mortality.

[0016] In another aspect, the disclosure provides methods (or uses of compositions) for treating a subject having a subtype of IPF, comprising administering an effective amount of the composition sufficient to reduce expression of a small RNA selected from Table 6 (SEQ ID NOS: 45-115). In various embodiments, the composition is effective to reduce expression of a small RNA in Table 6 that has been demonstrated herein to be elevated in abundance in IPF subjects at increased risk of mortality.

[0017] In another aspect, the disclosure provides methods (or use of compositions) for treating a subject with IPF, comprising administering an effective amount of the composition sufficient to mimic the effect of a small RNA selected from Table 2 (SEQ ID NOS: 1-44). In various embodiments, the composition is effective to mimic the effect of a small RNA in Table 2 demonstrated herein to be low in abundance in IPF subjects at high risk of mortality. In various embodiments, the composition comprises an siRNA or shRNA, or another suitable format for inducing RNAi as described above.

[0018] In another aspect, the disclosure provides methods (or use of compositions) for treating a subject with IPF, comprising administering an effective amount of the composition sufficient to mimic the effect of a small RNA selected from Table 6 (SEQ ID NOS: 45-115). In various embodiments, the composition is effective to mimic the effect of a small RNA in Table 6 demonstrated herein to be low in abundance in IPF subjects at high risk of mortality. In various embodiments, the composition comprises an siRNA or shRNA, or another suitable format for inducing RNAi as described above.

[0019] In some embodiments, the present disclosure provides methods for treating IPF, or IPF with a high risk of mortality, or a subtype of IPF (e.g., with a high risk of mortality) by administering a therapeutic agent that acts on or mimics miR-92a-3p or an isoform thereof (e.g., an isoform described herein). In some embodiments, the isoform is listed in Table 10. In various embodiments, the agent is an siRNA that induces degradation of one or more mRNA targets of miR-92a-3p. In some embodiments, the therapeutic agent is miR-92a-3p or an isoform thereof. In some embodiments, the therapeutic agent induces degradation of one or more mRNA targets of an isoform of miR-92a-3p that is substantially under-abundant in high-risk IPF.

[0020] In some embodiments, the subject has been documented to have IPF with an increased risk of mortality as described herein, or has otherwise been shown to have low or undetectable circulating levels of one or more miR-92a-3p isoforms that are low in abundance (or undetectable) in IPF with an increased risk of mortality.

[0021] In still other aspects and embodiments, the present disclosure provides methods (and uses of compositions) for treating inflammatory or fibrotic disorders. In various embodiments, the disorder is characterized by dysregulation of the WNT / TGF-b / ITGA / FAK regulatory axis. In various aspects and embodiments, the method or use comprises administering a composition comprising miR-92a-3p or an isoform thereof, or a mimic of miR-92a-3p or an isoform thereof. In some embodiments, the compound mimicking miR-92a-3p or an isoform thereof is an siRNA, and the antisense strand or sequence comprises a sequence of a microRNA or isoform (including those described herein). In various embodiments, the isoform is one that is downregulated in the disorder or disease of interest (e.g., downregulated in a tissue of interest).

[0022] Other aspects and embodiments of the present disclosure will become apparent from the following detailed description. [Brief explanation of the drawings]

[0023] [Figure 1] An outline of the study design is shown. [Figure 2] 10 is a chart showing regression coefficients (and 95% confidence intervals) of sRNA features in the Dataset 1 cohort model. [Figure 3] 10 is a chart showing regression coefficients (and 95% confidence intervals) of sRNA features in the Dataset 2 cohort model. [Figure 4] 1 shows graphs of comparative regression coefficients of statistically significant features in the Cox regression model for Dataset 1 and Dataset 2. [Figure 5] Decision curve analysis of the Dataset 1 cohort is shown applying the following models: Cox regression with sRNA features, Cox regression with GAP features, and Cox regression with GAP+sRNA features. [Figure 6] Decision curve analysis of the Dataset 2 cohort is shown applying the following models: Cox regression with sRNA features, Cox regression with GAP features, and Cox regression with GAP+sRNA features. [Figure 7A] Graph showing Kaplan-Meier curves for dataset 1, including HRs and log-rank test p-values ​​for Cox regression by sRNA feature. Risk thresholds for the sRNA and GAP+sRNA models are as follows: low: 0-25% probability of death within 3 years, moderate: 25-50% probability of death within 3 years, and high: >50% probability of death within 3 years. [Figure 7B] Graph showing Kaplan-Meier curves for dataset 1, including HRs and log-rank test p-values ​​for Cox regression by GAP stage. Risk thresholds for the sRNA and GAP+sRNA models are as follows: low: 0-25% probability of death within 3 years, moderate: 25-50% probability of death within 3 years, and high: >50% probability of death within 3 years. [Figure 7C] Graph showing Kaplan-Meier curves for dataset 1, including HRs and log-rank test p-values ​​for Cox regression by GAP+sRNA signature. Risk thresholds for the sRNA and GAP+sRNA models are as follows: low: 0-25% probability of dying within 3 years; moderate: 25-50% probability of dying within 3 years; high: >50% probability of dying within 3 years. [Figure 8] Graphs showing dataset 1 cumulative mortality curves for Cox regression by (A) sRNA signature, (B) GAP stage, and (C) GAP+sRNA signature. Risk thresholds for the sRNA and GAP+sRNA models are as follows: low: 0-25% probability of death within 3 years, moderate: 25-50% probability of death within 3 years, and high: >50% probability of death within 3 years. [Figure 9]Kaplan-Meier curves for dataset 1, including HRs and log-rank test p-values ​​for Cox regression by (A) sRNA signature, (B) GAP stage, and (C) GAP+sRNA signature. Risk thresholds are as follows: low: 0-40% probability of death within 3 years; high: >40% probability of death within 3 years. [Figure 10] Graphs showing dataset 1 cumulative mortality curves for Cox regression by (A) sRNA signature, (B) GAP stage, and (C) GAP+sRNA signature. Risk thresholds are as follows: low: 0-40% probability of dying within 3 years; high: >40% probability of dying within 3 years. [Figure 11] Graphs showing Kaplan-Meier curves for dataset 2 IPF, including HRs and log-rank test p-values ​​for Cox regression by (A) sRNA signature, (B) GAP stage, and (C) GAP+sRNA signature. Risk thresholds for the sRNA and GAP+sRNA models are as follows: low: 0-25% probability of death within 3 years, moderate: 25-50% probability of death within 3 years, and high: >50% probability of death within 3 years. [Figure 12] Figure 2 shows the dataset 2 IPF cumulative mortality curves for Cox regression by (A) sRNA signature, (B) GAP stage, and (C) GAP+sRNA signature. Risk thresholds for the sRNA and GAP+sRNA models are as follows: low: 0-25% probability of death within 3 years, moderate: 25-50% probability of death within 3 years, and high: >50% probability of death within 3 years. [Figure 13] Graphs showing Kaplan-Meier curves for dataset 2 IPF, including HRs and log-rank test p-values ​​for Cox regression by (A) sRNA signature, (B) GAP stage, and (C) GAP+sRNA signature. Risk thresholds are as follows: low: 0-35% probability of dying within 3 years; high: >35% probability of dying within 3 years. [Figure 14]Figure 2 shows the dataset 2 IPF cumulative mortality curves for Cox regression by (A) sRNA signature, (B) GAP stage, and (C) GAP+sRNA signature. Risk thresholds are as follows: low: 0-35% probability of dying within 3 years; high: >35% probability of dying within 3 years. [Figure 15] Graphs showing Kaplan-Meier curves for dataset 2 non-IPF, including HRs and log-rank test p-values ​​for Cox regression by (A) sRNA signature, (B) GAP stage, and (C) GAP+sRNA signature. Risk thresholds for the sRNA and GAP+sRNA models are as follows: low: 0-25% probability of death within 3 years, moderate: 25-50% probability of death within 3 years, and high: >50% probability of death within 3 years. [Figure 16] Figure 2 shows dataset 2 non-IPF cumulative mortality curves for Cox regression by (A) sRNA signature, (B) GAP stage, and (C) GAP+sRNA signature. Risk thresholds for the sRNA and GAP+sRNA models are as follows: low: 0-25% probability of death within 3 years, moderate: 25-50% probability of death within 3 years, and high: >50% probability of death within 3 years. [Figure 17] Graphs showing Kaplan-Meier curves for dataset 2 IPF, including HRs and log-rank test p-values ​​for Cox regression by (A) sRNA signature, (B) GAP stage, and (C) GAP+sRNA signature. Risk thresholds are as follows: low: 0-35% probability of dying within 3 years; high: >35% probability of dying within 3 years. [Figure 18] Figure 1 shows dataset 2 non-IPF cumulative mortality curves for Cox regression by (A) sRNA signature, (B) GAP stage, and (C) GAP+sRNA signature. Risk thresholds are as follows: low: 0-35% probability of dying within 3 years; high: >35% probability of dying within 3 years. [Figure 19] 1 shows a graph of principal component analysis stratification of the exploratory cohort. [Figure 20] Graphs of Kaplan-Meier curves for four patient subtypes correlated with overall survival are shown. [Figure 21]Characterization of the small RNA isoform landscape in IPF. (A) Schematic of sRNA biogenesis showing the mechanism of templated 5' and 3' isoform generation. (B) Distribution of sRNA reads by isoform type at each end, grouped by sample matrix and pre-sRNA arm of origin. [Figure 22] We show that miR-92a-3p isoform expression correlates with IPF and collagen expression. miR-92a-3p isoform expression was quantified in four independent datasets from seven different clinical centers: patient lung biopsies (A), whole blood samples (B), patient primary fibroblasts (C), and microarray data from mouse lung tissue (D). For mouse data, bleomycin-induced pulmonary fibrosis was defined as IPF, and the corresponding saline control was defined as "control." All comparisons are statistically significant (t-test, p<0.05). (E) The negative correlation between miR-92a-3p expression and COL1A1 expression in a primary fibroblast cell line indicates a regulatory influence of miR-92a-3p on collagen deposition. [Figure 23] We demonstrate that the miR-92a-3p isoform is a powerful predictor of 3-year survival in IPF patients. (A) Kaplan-Meier plots containing hazard ratios using sRNA sequencing data from IPF whole blood samples binned into GAP / GAPS+ stages I (low risk: 0-25%), II (intermediate risk: 25-50%), and III (high risk: >50%) according to the GAP Index scoring criteria and the presence or absence of blood-based sRNAs. The % risk represents the probability of death within 3 years. (B) Hazard ratios for each sRNA isoform and GAP Index component for the GAPS+ model indicate the miR-92a-3p isoform (highlighted) as a significant contributor to 3-year transplant-free survival. [Figure 24]Figure 1 shows that deficiency of the miR-92a-3p isoform enhances bleomycin-induced pulmonary fibrosis. (A) Percent weight loss from day 0. Percent weight loss data were analyzed by ANCOVA. Data are presented as mean ± SEM. *P<0.05, **P<0.01. The black dotted line indicates 5% (expected). The gray dotted line indicates 15%, the threshold for required euthanasia according to health guidelines. (B) Kaplan-Meier plot of overall survival. One wild-type animal was excluded due to a non-bleomycin-related mortality event. (C) Representative images of picrosirius red (PSR) staining in wild-type (top) and MIR92A-1+ / - (bottom) animals. (D) Quantification of PSR staining in wild-type (n=8) and MIR92A-1+ / - (n=9) animals. (E) Total miR-92-3p isoform expression (TRPM, mean ± SEM) in lung tissues collected on day 21. [Figure 25] Figure 1 shows that miR-92a-3p reversed bleomycin-induced pulmonary fibrosis in mice. (A) Schematic diagram showing the study design for in vivo efficacy. (B) Percentage change in body weight. (C) Plasma glucose levels of animals on day 21. (D) Lung (mg) to body weight (g) ratio. (E) Quantitative analysis of hydroxyproline in lung homogenates. (F) Representative images of picrosirius red (PSR) staining of lung sections showing the percentage of fibrotic lesions in mice treated with saline (n=8), bleomycin (n=10), and miR-92a mimic-treated bleomycin (n=8). Data are expressed as mean ± SEM. *P≦0.05, **P<0.01. [Figure 26]Activity screening of miR-92a-3p mimics in primary IPF fibroblasts from patients. (A) Heatmap showing the effect of cell proliferation on primary IPF fibroblasts treated with miR-92a-3p mimics (100 nM). (B) Heatmap showing the effect of collagen type 1 alpha 1 (COL1A1) expression in primary IPF fibroblasts treated with either scrambled control or miR-92a-3p mimics (100 nM). (C) Mean collagen inhibition by Oligo-006 is highlighted. Immunofluorescence images of representative IPF cells and treatment conditions stained for COL1A1, filamentous actin, and Hoechst staining. COL1A1 levels and cell proliferation data are normalized to the scrambled control. (D) Inhibition of cell proliferation using Oligo-006 is highlighted. Brightfield images of cells after 96 hours are shown. [Figure 27] Ex vivo efficacy of miR-92a-3p isoforms is shown using precision-cut lung slices. (A) Schematic of experimental design. PCLS were treated in duplicate. (B) Collagen expression was significantly reduced in PCLS treated with Oligo-006 (GHB1589) (p<0.05). Results are mean (±) standard deviation (n=3). (C) Inflammation scoring of interstitial tissue was completed on H&E-stained PCLS (n=2). (D) Fibrosis scoring of interstitial tissue was completed on H&E-stained PCLS (n=2). (E) Proteomic analysis of inflammatory and fibrotic biomarkers using Luminex. Results are shown as percent change relative to scrambled control (n=1). [Figure 28]Identification and mechanism of action of miR-92a-3p targets. (A) Volcano plot of differential expression analysis of IPF fibroblasts transfected with oligo-006 versus scrambled oligos (BH p-adjusted threshold = 0.05). (B) Pathway and transcription factor (TF) target enrichment analysis (*: p-adjust < 0.1, **: p-adjust < 0.01, ***: p-adjust < 0.001). (C) Binding site activity tested using a luciferase reporter after transfection with oligo-006. Key genes highlighted are profibrotic (*: p-adjust < 0.05, **: p-adjust < 0.01). [Figure 29] Figure 1 shows the confirmed mechanism of action of Oligo-006, illustrating the regulatory feedback loop involved in the propagation of fibrosis. Gene colors and values ​​indicate differential expression after transfection of Oligo-006 in fibroblasts. Underlined genes have miR-92a-3p binding sites, and highlighted genes were confirmed as physical targets of the mimetic by reporter assay. DETAILED DESCRIPTION OF THE INVENTION

[0024] The present disclosure provides methods and kits for assessing and risk stratifying subjects with idiopathic pulmonary fibrosis (IPF). Specifically, the present disclosure provides methods and kits for determining the expression profile of small non-coding RNA biomarkers that can predict the risk of death in subjects with IPF. In another aspect, the present disclosure provides therapeutic compositions for IPF and other conditions based on small non-coding RNAs, which have the potential to correct dysregulation of several messenger RNA targets, e.g., by sRNA mimics or antisense oligonucleotides targeting sRNAs. In various embodiments, the sRNA is an sRNA isoform (e.g., miR-92a-3p isoform) whose expression is dysregulated in disease states.

[0025] Idiopathic pulmonary fibrosis is a chronic, progressive lung disease. This condition causes the accumulation of scar tissue (fibrosis) in the lungs, preventing them from effectively transporting oxygen to the bloodstream. Idiopathic pulmonary fibrosis belongs to a group of conditions called interstitial lung diseases (ILDs), which are lung diseases involving inflammation or scarring of the lungs. Some patients with idiopathic pulmonary fibrosis develop other serious lung conditions, such as lung cancer, blood clots in the lungs (pulmonary embolism), pneumonia, or high blood pressure in the blood vessels supplying the lungs (pulmonary hypertension). Most patients survive 3 to 5 years after diagnosis. However, the course of the disease is highly variable; some patients become seriously ill within a few months, while others may survive for more than 10 years with the disease.

[0026] Traditionally, the GAP model has been used as a risk assessment system to determine the risk of death in patients with IPF. The baseline "GAP model" (named for the model variables: sex, age, and physiology) consists of two prognostic tools that provide physicians with a framework for discussing prognosis with patients and evaluating stage-specific management options. The first, the GAP index and staging system, provides a simple screening method for determining the average risk of death in IPF patients by GAP stage. The GAP calculator, an expanded version of the GAP index, provides more accurate estimates of mortality risk. The GAP index and GAP calculator estimate disease stage and / or mortality in IPF patients based on sex, age, forced vital capacity (%FVC), and diffusing capacity for carbon monoxide (%DLCO).

[0027] In aspects and embodiments, the present disclosure provides methods for assessing and risk stratifying patients diagnosed with IPF using a blood biomarker panel. The biomarker panel can be used independently or in conjunction with the GAP model to more accurately assess IPF mortality.

[0028] In one aspect, the present disclosure provides a method for risk stratification of a subject diagnosed with idiopathic pulmonary fibrosis (IPF), comprising providing a blood, serum, or plasma sample from the subject, generating an expression profile of at least five small RNAs listed in Table 2, and determining a risk of death as a function of the expression profile, thereby risk-stratifying the subject. In embodiments, the method further comprises determining the subject's GAP stage and determining the risk of death based on the expression profile and the GAP stage. In embodiments, the GAP stage comprises three thresholds based on the probability of death within three years. In some embodiments, the subjects are stratified into three groups based on risk of death. In some embodiments, the three groups are low risk, moderate risk, and high risk of death within three years. In some embodiments, the subjects are stratified into two groups based on risk of death. In some embodiments, the two groups are low risk and high risk of death within three years. For example, in some embodiments, expression profiles are generated for subjects at moderate and / or high risk of death by GAP Index, hi some embodiments, expression profiles are generated for subjects at low risk of death by GAP Index.

[0029] In various embodiments, subjects who are classified as high risk (according to the present disclosure) are selected or prioritized for surgical or pharmaceutical intervention. In various embodiments, subjects are selected or prioritized for lung transplantation. Thus, in some embodiments, subjects who are determined to be at high risk of death by the present disclosure receive lung transplantation (either single or double lung) within about 2 years, or within about 1 year, or within about 6 months (for example, determined from the time of blood sampling) of biomarker assessment.

[0030] In one aspect, the present disclosure provides a method for assessing idiopathic pulmonary fibrosis in a subject, the method comprising providing a blood, serum, or plasma sample from the subject, generating an expression profile of at least five small RNAs listed in Table 6, and identifying the subject as having a subtype of idiopathic pulmonary fibrosis that correlates with an overall risk of death based on the expression profile. In embodiments, subjects with a high-risk subtype are selected or prioritized for surgical or pharmaceutical intervention. In embodiments, subjects with a high-risk subtype are selected or prioritized for lung transplantation. Thus, in some embodiments, subjects determined to have a high-risk subtype by the present disclosure receive a lung transplant (either single or double) within about two years, or within about one year, or within about six months of biomarker assessment (e.g., as determined from the time of blood draw).

[0031] Thus, in various aspects and embodiments, the present disclosure provides a panel of small RNAs whose expression correlates with the risk of IPF or death in IPF patients. Small RNAs ("sRNAs") are non-coding RNAs less than 200 nucleotides in length, including microRNAs (miRNAs) (including iso-miRs), Piwi-interacting RNAs (piRNAs), small interfering RNAs (siRNAs), vault RNAs (vtRNAs), small nucleolar RNAs (snoRNAs), transfer RNA-derived small RNAs (tsRNAs), ribosomal RNA-derived small RNA fragments (rsRNAs), small rRNA-derived RNAs (srRNAs), and small nuclear RNAs (U-RNAs), as well as novel and uncharacterized RNA species. Generally, "isoforms" refer to sequences that have variations relative to a reference sequence (e.g., the Human Genome GRCh38 / hg38 build, miRBase, piRNAdb, etc.). In miRBase, each miRNA is associated with a miRNA precursor and one or two mature miRNAs (-5p and -3p). Deep sequencing has detected great variability in small RNA biogenesis, meaning that many different sequences can be generated from the same precursor RNA. Three main variations of isoforms exist: (1) template variants where the 5' and 3' ends are upstream or downstream of the reference, (2) non-template variants where nucleotides are added to the 5' and 3' ends that do not align with the reference, and (3) nucleotide substitutions where internal nucleotides do not align with the reference.

[0032] In various embodiments, the expression profile includes expression levels of a plurality of sRNAs in Table 2. Table 2 lists sRNA markers whose serum levels correlate (positively or negatively) with mortality in IPF. Table 2 provides 44 sRNA sequences whose expression levels correlate with risk of death in IPF patients and can be used to generate models for assessing and risk stratifying IPF subjects. As shown in Table 2, sRNAs include various types of RNA species, including miRNAs, tRNA-derived sRNAs, pre-microRNAs, and other species.

[0033] Table 2 shows the sRNA sequences in DNA format (e.g., sequences obtained after RT-PCR). Where the nucleotide sequences described herein are RNA or are intended to include RNA nucleotides, it is understood that thymine (T) is replaced with uracil (U) nucleobases.

[0034] In various embodiments, the expression profile comprises expression levels of at least 10 sRNAs from Table 2. In embodiments, the expression profile comprises expression levels of at least 20 sRNAs from Table 2. In various embodiments, the expression profile comprises expression levels of at least 30 sRNAs from Table 2. In various embodiments, the expression profile comprises expression levels of at least 40 sRNAs from Table 2. In various embodiments, the expression profile comprises, consists essentially of, or consists of expression levels of sRNAs from Table 2.

[0035] In various embodiments, the expression profile comprises expression levels of a plurality of sRNAs in Table 6. Table 6 provides 71 sRNA sequences whose expression levels identify different subtypes of IPF with different mortality risks. As shown in Table 6, the sRNAs include microRNA isoforms.

[0036] Table 6 shows the sRNA sequences in DNA format (e.g., sequences obtained after RT-PCR). Where the nucleotide sequences described herein are RNA or are intended to include RNA nucleotides, it is understood that thymine (T) is replaced with uracil (U) nucleobases.

[0037] In various embodiments, the expression profile comprises expression levels of at least 10 sRNAs from Table 6. In embodiments, the expression profile comprises expression levels of at least 20 sRNAs from Table 6. In embodiments, the expression profile comprises expression levels of at least 30 sRNAs from Table 6. In embodiments, the expression profile comprises expression levels of at least 40 sRNAs from Table 6. In embodiments, the expression profile comprises, consists essentially of, or consists of expression levels of sRNAs from Table 6.

[0038] In this context (with respect to sRNAs in Tables 2 and 6), the term "consisting essentially of" means that additional sRNAs may also be measured as part of the expression profile, and that such sRNAs do not significantly affect (i.e., reduce) the correlation between the expression profile and IPF mortality or are not included in the expression profile analysis. In some embodiments, the additional sRNAs may be used as a control for expression levels. Models may be developed using supervised regression modeling of expression profiles determined for IPF and control subjects randomized into training and test groups using a training cohort.

[0039] In some embodiments, a risk score is calculated for an expression profile (eg, based on RT-qPCR of markers in Table 2) according to the following formula (Equation 1):

number

[0040] Prior to sRNA detection and quantification, RNA can be extracted from the sample. RNA can be purified using a variety of standard procedures, such as those described in "RNA Methodologies, A Laboratory Guide for Isolation and Characterization, 2nd Edition, 1998, Robert E. Farrell, Jr., Ed., Academic Press." Additionally, there are various processes, as well as commercially available products, for isolating small RNAs, including the mirVANA™ Paris miRNA Isolation Kit (Ambion), the miRNeasy™ Kit (Qiagen), the MagMAX™ Kit (Life Technologies), and the Pure Link™ Kit (Life Technologies). For example, small RNAs can be isolated by organic extraction followed by purification on glass fiber filters. Alternative methods for isolating sRNA include hybridization to magnetic beads. Alternatively, sRNA processing for detection (e.g., cDNA synthesis) can be performed on the biological fluid sample, i.e., without an RNA extraction step.

[0041] In various embodiments, detection of sRNA in the expression profile involves one of a variety of detection platforms that can employ reverse transcription and amplification. In some embodiments, the detection platform involves probe hybridization. In some embodiments, the detection platform involves reverse transcription and quantitative PCR (e.g., RT-qPCR). In some embodiments, the sRNA is reverse transcribed using a stem-loop RT primer. Exemplary stem-loop primers are shown in Tables 3 and 7. In various embodiments, the reverse transcription product is amplified using a forward primer and a reverse primer. Exemplary forward and reverse primers are also shown in Tables 3 and 7. The reverse primer can be a universal primer based on the constant sequence of the stem-loop primer. In various embodiments, the quantitative PCR assay uses a fluorescent dye or a fluorescently labeled probe. In various embodiments, the quantitative PCR assay uses a fluorescently labeled probe (e.g., a TAQMAN probe) that further comprises a quencher moiety.

[0042] Generally, real-time PCR monitors the amplification of target DNA molecules during PCR, i.e., in real time. Real-time PCR can be used quantitatively and semi-quantitatively. Two common methods for detecting PCR products in real-time PCR are (1) non-specific fluorescent dyes (e.g., SYBR Green (I or II) or ethidium bromide) that intercalate with any double-stranded DNA, and (2) sequence-specific DNA probes consisting of oligonucleotides labeled with fluorescent reporters that can only be detected after hybridization with their complementary sequence (e.g., TAQMAN).

[0043] In some embodiments, the assay format is TAQMAN real-time PCR. TAQMAN probes are hydrolysis probes designed to increase the specificity of quantitative PCR. The TAQMAN probe principle relies on the 5' to 3' exonuclease activity of Taq polymerase to cleave a dual-labeled probe with fluorophore-based detection during hybridization to a complementary target sequence. TAQMAN probes are dual-labeled with a fluorophore and a quencher, and when the fluorophore is cleaved from the oligonucleotide probe by Taq exonuclease activity, the fluorophore signal is detected (e.g., the signal is no longer quenched by the proximity of the label). As in other quantitative PCR methods, the resulting fluorescent signal allows for quantitative measurement of product accumulation during the exponential stage of PCR. The TAQMAN probe format offers high sensitivity and specificity of detection.

[0044] Thus, in some embodiments, the sRNA of the expression profile is converted into cDNA using specific primers, such as stem-loop primers. The amplification of the cDNA can then be quantified in real time, for example, by detecting a signal from a fluorescent reporting molecule, and the signal intensity correlates with the level of DNA at each amplification cycle.

[0045] In various embodiments, the expression profile is determined using a hybridization assay. In some embodiments, the hybridization assay uses a hybridization array containing sRNA-specific probes. Exemplary platforms for detecting hybridization include surface plasmon resonance (SPR) and microarray technology. The detection platform can, in some embodiments, use microfluidics for convenient sample processing and sRNA detection.

[0046] In other embodiments, the expression profile is determined by nucleic acid sequencing, and sRNAs are identified in the sample by a process that includes trimming 5' and 3' sequencing adapters from the sRNA sequences. See U.S. Patent Nos. 10,889,862 and 11,028,440, the entire contents of which are incorporated herein by reference. These documents disclose a process that includes computationally trimming sequencing adapters from RNA sequencing data and sorting data according to unique sequence reads. In some embodiments, RNAs from multiple samples are pooled to determine the expression profile by sRNA sequencing, using sequences from different samples that contain distinguishing sample tag sequences (which can be added by RT-PCR or ligation). In various embodiments, the expression profile further includes the expression levels of one or more expression normalization controls.

[0047] Generally, any method for determining the presence or level of sRNA in a sample can be used. Such methods further include nucleic acid sequence-based amplification (NASBA), flap endonuclease-based assays, as well as direct RNA capture with branched DNA (QuantiGene™), Hybrid Capture™ (Digene), or nCounter™ miRNA detection (nanostring). In addition to determining sRNA abundance, the assay format can also provide, among other things, controls for inherent signal intensity variation. Such controls can include, for example, controls for background signal intensity and / or sample processing and / or hybridization efficiency, as well as other desirable controls for detecting sRNA in patient samples (e.g., collectively referred to as "normalization controls").

[0048] In some embodiments, the assay format is a flap endonuclease-based format, such as the Invader™ assay (Third Wave Technologies). When using the Invader method, an Invader probe containing a sequence specific to the 3' region of the target site and a primary probe containing a sequence specific to the 5' region of the target site of the template and an unrelated flap sequence are prepared. Cleavase can then act in the presence of these probes, the target molecule, and a FRET probe containing a sequence complementary to the flap sequence and a self-complementary sequence labeled with both a fluorescent dye and a quencher. When the primary probe hybridizes to the template, the 3' end of the Invader probe penetrates the target site, and this structure is cleaved by the cleavase, resulting in the release of the flap. The flap binds to the FRET probe, and the fluorescent dye moiety is cleaved by the cleavase, resulting in the emission of fluorescence.

[0049] In various embodiments, if the subject is determined to be at high risk of death from IPF, the subject is treated with a surgical or pharmaceutical intervention, optionally, the intervention is a pharmaceutical intervention described herein.

[0050] In some embodiments, the surgical intervention is lung transplantation. In some embodiments, the subject is selected or prioritized for lung transplantation. Thus, in some embodiments, the subject that is determined by the present disclosure to be at high risk of death will receive a lung transplant (either single or double lungs) within about 2 years, or within about 1 year, or within about 6 months (for example, can be calculated from the time of blood collection) of biomarker evaluation.

[0051] As used herein, the term "pharmaceutical intervention" means that, based on the results of sRNA expression profiling, a subject is prescribed (and administered) at least one additional medication (compared to any existing treatment prior to expression profiling), or the subject's medication regimen is altered in at least one medication (i.e., at least one active agent is substituted for one or more other medications in an ongoing regimen) or medication dose.

[0052] In embodiments where pharmaceutical intervention is desired, the pharmaceutical agent may be selected from, but is not limited to, nintedanib (Ofev®) and pirfenidone (Esbriet®). In some embodiments, the subject is administered a therapeutic agent described herein for targeting or mimicking the action of an sRNA based on the results of the sRNA biomarker expression profile. In some embodiments, the pharmaceutical intervention is an siRNA that mimics the miR-92a-3p isoform, optionally administered locally to the lung by inhalation. An exemplary isoform is provided herein as SEQ ID NO: 739 and can be mimicked with an siRNA comprising, for example, an antisense sequence or strand having the nucleobase sequence of SEQ ID NO: 768 (or a derivative thereof as described herein). Other miR-92a-3p isoforms and siRNAs for use in the present disclosure are set forth in Table 10 (which can be modified according to the present disclosure).

[0053] In various embodiments, the method is repeated at least annually, or at least once every six months, or at least once every two months to monitor the progression of the subject's disease.

[0054] In another aspect, the present disclosure provides kits for evaluating samples for risk stratification of IPF, e.g., according to the methods described herein. In some embodiments, the kits include sRNA-specific probes and / or primers configured to detect multiple sRNAs listed in Table 2 (SEQ ID NOS: 1-44). In various embodiments, the kits include sRNA-specific probes and / or primers configured to detect at least 10 sRNAs listed in Table 2 (SEQ ID NOS: 1-44). In various embodiments, the kits include sRNA-specific probes and / or primers configured to detect at least 20 sRNAs listed in Table 2 (SEQ ID NOS: 1-44). In various embodiments, the kits include sRNA-specific probes and / or primers configured to detect at least 30 sRNAs listed in Table 2 (SEQ ID NOS: 1-44). In various embodiments, the kits include sRNA-specific probes and / or primers configured to detect at least 40 sRNAs listed in Table 2 (SEQ ID NOS: 1-44). In various embodiments, the kits include sRNA-specific probes and / or primers configured to detect the sRNAs listed in Table 2 (SEQ ID NOs: 1-44).

[0055] In some embodiments, the kit includes an sRNA-specific stem-loop RT primer. Exemplary stem-loop primers are listed in Table 3. The stem-loop primer includes a constant region that forms a stem loop and a variable nucleotide extension (e.g., about 5-8 nucleotides, e.g., 6 nucleotides). The constant region serves as a priming region for the reverse primer during amplification. The variable region of the stem-loop RT primer is configured to specifically reverse transcribe an sRNA in Table 2. In various embodiments, the kit includes a forward primer and a reverse primer for amplifying the reverse transcription product (i.e., resulting from reverse transcription with the stem-loop primer). In some embodiments, the reverse primer can be a universal primer. In some embodiments, the forward primer is listed in Table 3. The universal reverse primer is also listed in Table 3. In various embodiments, the kit includes a fluorescently labeled sRNA-specific probe for detecting amplicons in real time. In some embodiments, the probe further includes a quencher moiety. The probe can be a TAQMAN probe.

[0056] In various embodiments, the kit comprises an array of sRNA-specific hybridization probes configured to detect at least 20, at least 30, at least 40, at least 50, or all of the sRNAs in Table 2.

[0057] In another aspect, the disclosure provides kits for assessing a sample for high-risk subtypes of IPF, e.g., according to the methods described herein. In some embodiments, the kit includes sRNA-specific probes and / or primers configured to detect multiple sRNAs listed in Table 6 (SEQ ID NOs: 45-115). In various embodiments, the kit includes sRNA-specific probes and / or primers configured to detect at least 10 sRNAs listed in Table 6 (SEQ ID NOs: 45-115). In various embodiments, the kit includes sRNA-specific probes and / or primers configured to detect at least 20 sRNAs listed in Table 6 (SEQ ID NOs: 45-115). In various embodiments, the kit includes sRNA-specific probes and / or primers configured to detect at least 30 sRNAs listed in Table 6 (SEQ ID NOs: 45-115). In various embodiments, the kit includes sRNA-specific probes and / or primers configured to detect at least 40 sRNAs listed in Table 6 (SEQ ID NOs: 45-115). In various embodiments, the kit comprises sRNA-specific probes and / or primers configured to detect at least 50, at least 60, or all of the sRNAs listed in Table 6 (SEQ ID NOs: 45-115).

[0058] In some embodiments, the kit includes an sRNA-specific stem-loop RT primer. Exemplary stem-loop primers are listed in Table 7. The stem-loop primer includes a constant region that forms a stem loop and a variable nucleotide extension (e.g., of about 5-8 nucleotides, e.g., 6 nucleotides). The constant region serves as a priming region for the reverse primer during amplification. The variable region of the stem-loop RT primer is configured to specifically reverse transcribe the sRNA in Table 6. In various embodiments, the kit includes a forward primer and a reverse primer for amplifying the reverse transcription product (i.e., resulting from reverse transcription with the stem-loop primer). In some embodiments, the reverse primer can be a universal primer. In some embodiments, the forward primer is listed in Table 7. Universal reverse primers are also listed in Table 7. In various embodiments, the kit includes a fluorescently labeled sRNA-specific probe for detecting amplicons in real time. In some embodiments, the probe further includes a quencher moiety. The probe can be a TAQMAN probe.

[0059] In various embodiments, the kit comprises an array of sRNA-specific hybridization probes configured to detect at least 20, at least 30, at least 40, at least 50, or all of the sRNAs in Table 6.

[0060] In other aspects, the present disclosure provides therapeutic molecules based on the dysregulation of sRNAs in Table 2. Specifically, the present disclosure provides pharmaceutical compositions comprising molecules designed to mimic the action of sRNAs that are downregulated in subjects with IPF or IPF at high risk of death. In some embodiments, such molecules induce RNA interference of target RNAs (e.g., mRNAs targeted by specific sRNAs) in cells. In some embodiments, the present disclosure provides pharmaceutical compositions comprising antisense oligonucleotides designed to reduce the expression of sRNAs that are upregulated in subjects with IPF or IPF at high risk of death. Such antisense oligonucleotides can induce degradation of or prevent the action of the target sRNA.

[0061] In other aspects, the present disclosure provides therapeutic molecules based on the dysregulation of sRNAs in Table 6. Specifically, the present disclosure provides pharmaceutical compositions comprising molecules designed to mimic the action of sRNAs that are downregulated in subjects with IPF or IPF at high risk of death. In some embodiments, such molecules induce RNA interference of target RNAs (e.g., mRNAs targeted by specific sRNAs) in cells. In some embodiments, the present disclosure provides pharmaceutical compositions comprising antisense oligonucleotides designed to reduce the expression of sRNAs that are upregulated in subjects with IPF or IPF at high risk of death. Such antisense oligonucleotides can induce degradation of or prevent the action of target sRNAs.

[0062] RNA interference (RNAi) is a sequence-specific RNA degradation process that theoretically knocks down or silences any gene containing homologous sequences. In naturally occurring RNAi, double-stranded RNA (dsRNA) is cleaved by the RNase III / helicase protein (Dicer) into small interfering RNA (siRNA) molecules, which are 19–27 nucleotide (nt) dsRNAs with 2-nt overhangs at the 3' end. The siRNAs are then incorporated into a multicomponent ribonuclease called the RNA-induced silencing complex (RISC). One strand of the siRNA remains associated with the RISC and guides the complex toward a cognate RNA with a sequence complementary to the guide ss-siRNA in the RISC. This siRNA-directed endonuclease digests the RNA, resulting in truncation and inactivation of the targeted RNA.

[0063] In various embodiments, the present disclosure provides compositions comprising a small interfering RNA (siRNA) comprising an antisense strand and a sense strand, wherein the antisense strand comprises a nucleotide sequence selected from Table 2 (or at least 12, 14, 16, 18, 20, 21, or 22 contiguous nucleotides of a sequence selected from Table 2).

[0064] In various embodiments, the present disclosure provides a composition comprising a small interfering RNA (siRNA) comprising an antisense strand and a sense strand, wherein the antisense strand comprises a nucleotide sequence selected from Table 6 (or at least 12, 14, 16, 18, 20, 21, or 22 contiguous nucleotides of a sequence selected from Table 6). In various embodiments, the siRNA is a mimic of miR-92a-3p or an isoform thereof (e.g., an isoform listed in Table 6). In various embodiments, the siRNA induces degradation of one or more mRNA targets of miR-92a-3p. In some embodiments, the siRNA induces degradation of one or more mRNA targets of an isoform of miR-92a-3p that is substantially under-abundant in high-risk IPF. In various embodiments, the siRNA comprises the antisense sequence of SEQ ID NO: 732 (or at least 20, 21, or 22 contiguous nucleotides of SEQ ID NO: 732). The sense strand (i.e., passenger strand) for inducing RNAi can be designed as known in the art or as described below.Exemplary sense strands include SEQ ID NO: 733, or at least 16, 17, 18, 19, 20, or 21 consecutive nucleotides of SEQ ID NO: 733 (together with the antisense strand of SEQ ID NO: 732).In these embodiments, dTdT overhangs are optional.

[0065] In some embodiments, the siRNA mimics the action of miR-92a-3p or an isoform thereof, such as the isoforms listed in Table 10 (SEQ ID NOS: 734-762). These siRNAs comprise an antisense sequence or strand that has the nucleobase sequence of the sRNA isoform (optionally with a 3' overhang, such as dTdT), and can be chemically modified according to known techniques, including those described herein. Exemplary nucleobase sequences of antisense strands are shown in Table 10 (SEQ ID NOS: 763-791). Exemplary sense or passenger strands are also shown (SEQ ID NOS: 792-820).

[0066] When introduced into a cell in vivo or ex vivo, the siRNA induces degradation of one or more target RNAs (e.g., target mRNAs) in the cell. In some embodiments, the siRNA induces degradation of multiple mRNAs (e.g., at least two, three, four, five, or more) in the target cell. In some embodiments, one or more mRNAs are decreased in expression in several pro-fibrotic pathways (WNT, TGF-beta, and focal adhesions). In some embodiments, one or more mRNAs are decreased in expression in pathways such as ECM, collagen, and interleukin-mediated inflammatory pathways. In some embodiments, the target cell is a lung epithelial cell. In various embodiments, the siRNA is formulated for systemic delivery (e.g., parenteral delivery) or for local delivery to the lung, such as, but not limited to, by inhalation. In various embodiments, the siRNA is encapsulated in lipid nanoparticles, polymer nanoparticles, or liposomes. In various embodiments, the siRNA is delivered by inhalation, optionally in aerosol form (e.g., solution or powder aerosol). These delivery forms are well known in the art.

[0067] In various embodiments, the siRNA comprises a chemical modification, including any of the known chemical modifications for siRNA. In various embodiments, the chemical modification increases stability, reduces endonuclease degradation, reduces immunogenicity, and / or reduces Toll-like receptor recognition. In various embodiments, the chemical modification is a nucleobase modification, a backbone modification, and / or a sugar modification.

[0068] In embodiments, the nucleobase modification inhibits RNA recognition by Toll-like receptors (TLRs). In embodiments, the nucleobase modification is selected from pseudouridine (ψ), N1-methyl-pseudouridine (N1mΨ), 5-methylcytidine (m5C), 2'-thiouridine (s2U), N6'-methyladenosine (m6A), and 5'-fluorouridine.

[0069] In various embodiments, siRNA can have one or more backbone modifications selected from phosphorothioate, phosphorodithioate, methylphosphonate, and methoxypropylphosphonate.For example, such modifications can be located at and / or near the 3'-end of antisense strand and / or sense strand.Other modified linkages are described elsewhere herein.

[0070] In various embodiments, the siRNA comprises one or more sugar modifications, such as those selected from 2'-methoxy (2'-Ome), 2'-O-methoxyethyl (2'-O-MOE), 2'-fluoro (2'-F), 2'-arabino-fluoro (2'-Ara-F), constrained ethyl (cEt), bridged nucleic acid (BNA), and locked nucleic acid (LNA). BNA and LNA nucleotides are described elsewhere herein. In various embodiments, the antisense strand comprises a 5' phosphate. Other suitable modifications for the 5' end are known in the art.

[0071] In various embodiments, the siRNA comprises a sense and an antisense strand, each having a length of about 12 to about 40 nucleotides. In various embodiments, the siRNA comprises two substantially complementary RNA strands having a duplex length of about 12 to about 40 base pairs (e.g., 16 to 24 base pairs). In various embodiments, the siRNA comprises a sense strand overhang and an antisense strand overhang at the 3' end. The overhang may be an RNA overhang or a deoxythymidine (dT-dT) overhang. In various embodiments, the siRNA is an asymmetric siRNA (asiRNA) having a blunt end corresponding to the 5' end of the antisense strand. In various embodiments, the antisense strand or sequence corresponds to the sequence of an sRNA or isoform whose action is to be mimicked.

[0072] Other siRNA formats that can be used, including but not limited to, short hairpin RNAs (shRNAs) (e.g., containing the sequence of a desired isoform), are described in US2008 / 0188430, which is incorporated herein by reference.

[0073] In various aspects and embodiments, the present disclosure provides compositions comprising antisense oligonucleotides targeting sRNA isoforms upregulated in IPF or another fibrotic disease. For example, the antisense oligonucleotides are at least 10 linked nucleotides in length and have a sequence complementary to a nucleotide sequence selected from Table 2 (SEQ ID NOS: 1-44). In various embodiments, the oligonucleotides are at least 10, at least 12, at least 15, or at least 20 nucleotides in length. In various embodiments, the oligonucleotides are about 12 to about 40 nucleotides in length, or about 12 to about 25 nucleotides in length. In various embodiments, the oligonucleotides are 12, 13, 14, 15, 16, 17, 18, 19, 20, or 21 nucleotides in length. In various embodiments, the antisense oligonucleotides can reduce the expression level of a target sRNA in cells (e.g., lung epithelial cells) ex vivo or in vivo. In various embodiments, the oligonucleotides consist of a nucleotide sequence complementary to a sequence selected from SEQ ID NOS: 1-44.

[0074] In various aspects and embodiments, the present disclosure provides compositions comprising antisense oligonucleotides that are at least 10 linked nucleotides in length and have a sequence complementary to a nucleotide sequence selected from Table 6 (SEQ ID NOS: 45-115). In various embodiments, the oligonucleotides are at least 10, at least 12, at least 15, or at least 20 nucleotides in length. In various embodiments, the oligonucleotides are about 12 to about 40 nucleotides in length, or about 12 to about 25 nucleotides in length. In various embodiments, the oligonucleotides are 12, 13, 14, 15, 16, 17, 18, 19, 20, or 21 nucleotides in length. In various embodiments, the antisense oligonucleotides are capable of reducing the expression level of a target sRNA in cells (e.g., lung epithelial cells) ex vivo or in vivo. In various embodiments, the oligonucleotides consist of a nucleotide sequence complementary to a sequence selected from SEQ ID NOS: 45-115.

[0075] In some embodiments, the oligonucleotide has a contiguous sequence of at least 6, or at least 8, or at least 10 DNA nucleotides sufficient to recruit RNase H. RNase H is a non-sequence-specific endonuclease enzyme that catalyzes RNA cleavage in hybridized RNA / DNA substrates. In some embodiments, the oligonucleotides of the present disclosure are "gapmers," i.e., the oligonucleotides contain a central block of deoxynucleotides (also referred to herein as "DNA nucleotides"). In various embodiments, the term "DNA nucleotide" refers to a nucleotide that is not an RNA nucleotide. DNA nucleotides typically have a 2'H, but may alternatively have a variety of 2' chemical modifications, including 2'-halo and 2'-lower alkyl (e.g., C1-4). In some embodiments, the 2' chemical modifications of the DNA nucleotides are independently selected from 2'-fluoro, 2'-methyl, and 2'-ethyl. Gapmers typically further comprise a 5' segment and a 3' segment, each of which is 2-6 nucleotides or 2-4 nucleotides, and the 5' segment and the 3' segment do not contain any DNA nucleotides. In embodiments, one or more nucleotides of the 5' segment and the 3' segment comprise a 2'-O substituent, and optionally all of the nucleotides of the 5' segment and the 3' segment comprise a 2'-O substituent. In embodiments, the 2'-O substituent is selected from 2'-O alkyl (e.g., 2'-O methyl, 2'-O ethyl), 2'-O methoxyethyl (MOE), and bridged nucleotides having a 2' to 4' bridge. In embodiments, the bridged nucleotide has a methylene bridge (LNA) or a constrained ethyl bridge (cEt).

[0076] In some embodiments, the oligonucleotide comprises one or more locked nucleotides or bicyclic nucleotides, e.g., a bridge between the 2' and 4' positions ("bridged nucleotides"). Locked nucleic acids (LNAs) or "locked nucleotides" are described, for example, in U.S. Patent Nos. 6,268,490, 6,316,198, 6,403,566, 6,770,748, 6,998,484, 6,670,461, and 7,034,133, all of which are incorporated herein by reference in their entireties. LNAs are modified nucleotides containing a bridge between the 2' and 4' carbons of the sugar moiety, resulting in a "locked" conformation and / or bicyclic structure. Other suitable locked nucleotides that can be incorporated into the oligonucleotides of the present disclosure are described in U.S. Patent Nos. 6,403,566 and 6,833,361, both of which are incorporated herein by reference in their entireties. In exemplary embodiments, the locked nucleotides are independently selected from a 2' to 4' methylene bridge and a constrained ethyl (cEt) bridge (see U.S. Pat. Nos. 7,399,845 and 7,569,686, which are incorporated by reference in their entireties).

[0077] In various embodiments, the oligonucleotide has a modified polynucleotide backbone or modified internucleotide linkage. The term "internucleotide linkage" refers to the linkage between two adjacent nucleosides in a polynucleotide molecule. Naturally, the internucleotide linkage is a phosphodiester linkage formed between two oxygen atoms of the phosphate group and the oxygen atom of the sugar (either the 3' or 5' position), forming two ester bonds bridging two adjacent nucleosides. Modification of the internucleotide linkage can provide different properties, including, but not limited to, enhanced stability. For example, phosphorothioate or phosphorodithioate linkages increase the resistance of the internucleotide linkage to nucleases. Another example is a phosphoacetate linkage (PACE), which improves transfection properties and enhances nuclease resistance. Internucleotide linkage and oligonucleotide backbone modifications that can be used in the oligonucleotides herein include, but are not limited to, phosphodiester, phosphorothioate, phosphorodithioate, methyl phosphonate, alkyl phosphonate, alkyl phosphonothioate, phosphotriester, phosphoramidate, phosphoramidite, phosphorodiamidate, siloxane, carbonate, carboalkoxy, acetamidate, carbamate, morpholino, peptide nucleic acid, borano, thioether, bridged phosphoramidate, bridged methylene phosphonate, bridged phosphorothioate, and sulfone internucleoside linkages.

[0078] In some embodiments, an oligonucleotide contains one or more phosphorothioate or phosphorodithioate internucleotide linkages. These linkages replace sulfur atoms with non-bridging oxygens in the phosphate backbone of the oligonucleotide and can be effective in reducing nuclease digestion. In some embodiments, phosphorothioate or phosphorodithioate linkages can be introduced between the last three to five nucleotides at the 5' and / or 3' ends of an oligonucleotide to inhibit exonucleolytic degradation. In some embodiments, an oligonucleotide contains a combination of phosphodiester and phosphorothioate / phosphorodithioate linkages. In some embodiments, an oligonucleotide contains at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, or at least ten phosphorothioate or phosphorodithioate internucleotide linkages. In some embodiments, an oligonucleotide contains substantially alternating phosphodiester and phosphorothioate internucleotide linkages. In some embodiments, the oligonucleotide is fully phosphorothioate / phosphorodithioate linked (ie, all linkages are either phosphorothioate or phosphorodithioate).

[0079] In some embodiments, oligonucleotides have morpholino backbones, especially when the recruitment of RNase H is not desired.Morpholino oligonucleotides do not induce the degradation of their target RNA molecules and can be effective in sterically blocking target RNA sequences.Morpholino oligonucleotides and their synthesis are generally disclosed in U.S. Patent No. 11,028,386, U.S. Patent No. 10,947,533, and U.S. Patent No. 10,927,378, each of which is incorporated herein by reference in its entirety.Other backbones that can be used include thiomorpholino and peptide nucleic acid (PNA).

[0080] In various embodiments, the melting temperature of an oligonucleotide hybridized to its target sequence is at least about 35°C. The Tm of an oligonucleotide is the temperature at which 50% of the oligonucleotide is duplexed with its perfect complement and 50% is free in solution. The Tm can be determined experimentally by measuring the change in absorbance of the oligonucleotide and its complement as a function of temperature. The Tm can also be estimated using known publicly available Tm calculators. In some embodiments, the Tm of an oligonucleotide hybridized to its target sequence is at least about 40°C, or at least about 45°C, or at least about 50°C. In some embodiments, the Tm of an oligonucleotide hybridized to its target sequence is between about 35°C and about 60°C. In some embodiments, the Tm of an oligonucleotide hybridized to its target sequence is between about 40°C and about 60°C, or between about 50°C and about 60°C.

[0081] In various embodiments, the antisense oligonucleotide is formulated for systemic delivery (e.g., parenteral delivery) or for local delivery to the lung, such as, but not limited to, by inhalation. In various embodiments, the antisense oligonucleotide is encapsulated in a lipid nanoparticle, a polymer nanoparticle, or a liposome. In various embodiments, the antisense oligonucleotide is delivered by inhalation, and optionally in the form of an aerosol (e.g., a solution or a powder aerosol).

[0082] In some embodiments, the siRNA or oligonucleotide further comprises a targeting moiety or cell-penetrating moiety that increases the distribution or accumulation of the drug in certain cells or tissues (e.g., lung epithelium). For example, such a targeting moiety or cell-penetrating moiety can be directly or indirectly conjugated to the 3' end of the oligonucleotide, optionally via a biologically cleavable linker. In some embodiments, the conjugate comprises a sterol conjugate (e.g., a cholesterol conjugate) or a fatty acid conjugate, such as a palmitoyl or stearyl lipid conjugate. Other conjugates are known.

[0083] In various embodiments, the targeting moiety or cell-penetrating moiety comprises an antibody or antigen-binding fragment thereof, an aptamer, a peptide, a biological ligand (including, for example, glycoconjugates), a lipid, a sterol, cholesterol or a derivative thereof, an integrin, an RGD peptide, or a cell-penetrating peptide (CPP). More specifically, the targeting moiety may be a single domain antibody, a single chain antibody, a bispecific antibody, a recombinant heavy chain only antibody (VHH), a single chain antibody (scFv), a shark heavy chain only antibody (VNAR), a microprotein (cysteine ​​knot protein, knottin), a DARPin, a tetranectin, an affibody, a transbody, an anticalin, an adnectin, an affilin ( The antibody may be selected from Affilin, Microbody, phylomer, stradobody, maxibody, ebibody, finomer, armadillo repeat protein, Kunitz domain, avimer, atrimer, probody, immunobody, triomab, troibody, pepbody, baxibody, unibody, duobody, Fv, Fab, Fab', F(ab')2 and peptidomimetic molecules. Various ligand binding platforms are disclosed in U.S. Patents or Patent Publication Nos. US 7,417,130, US 2004 / 132094, US 5,831,012, US 2004 / 023334, US 7,250,297, US 6,818,418, US 2004 / 209243, US 7,838,629, US 7,186,524, US 6,004,746, Nos. US 5,475,096, US 2004 / 146938, US 2004 / 157209, US 6,994,982, US 6,794,144, US 2010 / 239633, US 7,803,907, US 2010 / 119446, and / or US 7,166,697, the contents of which are incorporated herein by reference in their entireties.

[0084] In still other embodiments, the siRNA or oligonucleotide is encapsulated in a liposome, polymer nanoparticle, or lipid nanoparticle, as known in the art. In various embodiments, the LNP comprises a cationic or ionizable lipid, a neutral lipid, cholesterol or a cholesterol moiety, and a PEGylated lipid. Lipid particle formulations used in embodiments of the present disclosure include those described in US9,738,593, US10,221,127, and US10,166,298, the entire contents of which are incorporated herein by reference. In some embodiments, the LNP, liposome, or nanoparticle further comprises a targeting moiety as described. Thus, in some aspects, the present disclosure provides pharmaceutical compositions comprising an effective amount of the compositions described herein, including LNP, liposome, and polymer particle compositions, and one or more pharmaceutically acceptable excipients or carriers.

[0085] In another aspect, the disclosure provides methods (or uses of compositions) for treating a subject with IPF, comprising administering an effective amount of the composition sufficient to reduce expression of a small RNA selected from Table 2 (SEQ ID NOS: 1-44). In various embodiments, the composition is effective to reduce expression of a small RNA in Table 2 that has been demonstrated herein to be elevated in abundance in IPF subjects at high risk of mortality. In various embodiments, the composition comprises an oligonucleotide or composition described herein. Exemplary oligonucleotide sequences are set forth in Table 4. These nucleotides may include chemical modification patterns described herein.

[0086] In another aspect, the disclosure provides methods (or use of compositions) for treating a subject having a subtype of IPF, comprising administering an effective amount of the composition sufficient to reduce expression of a small RNA selected from Table 6 (SEQ ID NOS: 45-115). In various embodiments, the composition is effective to reduce expression of a small RNA in Table 6 that has been demonstrated herein to be elevated in abundance in IPF subjects at high risk of mortality. In various embodiments, the composition comprises an oligonucleotide or composition described herein. Exemplary oligonucleotide sequences are set forth in Table 8. These nucleotides may include chemical modification patterns described herein.

[0087] In another aspect, the present disclosure provides methods (or use of compositions) for treating a subject with IPF, comprising administering an effective amount of the composition sufficient to mimic the effect of a small RNA selected from Table 2 (SEQ ID NOS: 1-44). In various embodiments, the composition is effective to mimic the effect of a small RNA in Table 2 demonstrated herein to be low in abundance in IPF subjects at high risk of mortality. In various embodiments, the composition comprises an siRNA or shRNA, or another suitable format for inducing RNAi as described above. In some embodiments, the pharmaceutical composition comprising the siRNA or shRNA is as described herein. Exemplary siRNAs are listed in Table 5. These nucleotides may include chemical modification patterns as described herein.

[0088] In another aspect, the present disclosure provides methods (or use of compositions) for treating a subject with IPF, comprising administering an effective amount of the composition sufficient to mimic the effect of a small RNA selected from Table 6 (SEQ ID NOS: 45-115). In various embodiments, the composition is effective to mimic the effect of a small RNA in Table 6, which has been demonstrated herein to be low in abundance in IPF subjects at high risk of mortality. In various embodiments, the composition comprises an siRNA or shRNA, or another suitable format for inducing RNAi as described above. In some embodiments, pharmaceutical compositions comprising the siRNA or shRNA are as described herein. Exemplary siRNAs are listed in Table 9. These nucleotides may include chemical modification patterns as described herein.

[0089] In some embodiments, the subject is identified as having IPF, IPF at high risk of mortality, or a subtype of IPF according to the methods described herein (e.g., sRNA expression profiling). Dosage and administration schedules can vary depending on the patient's condition and the chemical nature of the composition. In various embodiments, the composition is administered more than once a week, about once a week, about every two months (i.e., about every other week), about once a month, or about four times a year. Dosage and administration schedules can include various doses and administration frequencies based on the route or delivery (e.g., parenteral, or direct administration to the target tissue) and patient response.

[0090] In some embodiments, the present disclosure provides methods for treating IPF, or IPF with a high risk of mortality, or a subtype of IPF (e.g., with a high risk of mortality) by administering a therapeutic agent that acts on or mimics miR-92a-3p or an isoform thereof (e.g., an isoform described herein). In some embodiments, the isoform is listed in Table 10. In various embodiments, the agent is an siRNA that induces degradation of one or more mRNA targets of miR-92a-3p. In some embodiments, the therapeutic agent is miR-92a-3p or an isoform thereof. In some embodiments, the therapeutic agent induces degradation of one or more mRNA targets of an isoform of miR-92a-3p that is substantially under-abundant in high-risk IPF. In various embodiments, the siRNA comprises an antisense sequence of SEQ ID NO: 732, or at least 19, 20, or 21 contiguous nucleotides of SEQ ID NO: 732. The nucleobase sequence of the sense strand (i.e., passenger strand) for inducing RNAi can be designed as known in the art or as described below. Exemplary passenger strands include SEQ ID NO: 733, or at least 16, 17, 18, 19, or 21 contiguous nucleotides of SEQ ID NO: 733. In some embodiments, the composition has an antisense sequence or strand comprising the nucleobase sequence of SEQ ID NO: 739 (optionally with a 3' overhang, such as dTdT, as set forth in SEQ ID NO: 768). An exemplary passenger strand is provided herein as SEQ ID NO: 797. Known chemical modifications, such as 5' phosphates, 2' modifications, and backbone modifications, can be used as described herein and as known in the art. Exemplary siRNAs are represented by SEQ ID NO: 768 and SEQ ID NO: 797.

[0091] In some embodiments, the subject has documented IPF with an increased risk of mortality, as described herein, or otherwise has been shown to have low or undetectable circulating levels of one or more miR-92a-3p isoforms that are low in abundance (or undetectable) in IPF with an increased risk of mortality (as described herein). In some embodiments, the therapeutic agent is administered systemically (e.g., parenterally), or in other embodiments, directly to the lung, e.g., by inhalation. The therapeutic agent can optionally be encapsulated in particles, such as LNPs, liposomes, or polymeric nanoparticles, as previously described. The composition can be administered periodically, such as once daily to about once monthly, including about once weekly to about once monthly.

[0092] In still other aspects and embodiments, the present disclosure provides methods (and uses of compositions) for treating inflammatory or fibrotic disorders. In various embodiments, the disorder is characterized by dysregulation of the WNT / TGF-b / ITGA / FAK regulatory axis. In various embodiments, the disorder is selected from IPF, nonalcoholic steatohepatitis (NASH), heart failure, cardiomyopathy, Crohn's disease, ulcerative colitis, Alzheimer's disease, Parkinson's disease, Huntington's disease, amyotrophic lateral sclerosis (ALS), preeclampsia, psoriasis, Pompe disease, sCID, breast cancer, and other cancers. In various aspects and embodiments, the method or use comprises administering a composition comprising miR-92a-3p or an isoform thereof, or a mimic of miR-92a-3p or an isoform thereof. In some embodiments, the compound mimicking miR-92a-3p or an isoform thereof is an siRNA, and the antisense strand or sequence comprises a sequence of a microRNA or isoform (including those described herein). In various embodiments, the isoform is an isoform that is downregulated in a disorder or disease of interest (e.g., downregulated in a tissue of interest). In some embodiments, the isoform is set forth in Table 10. In some embodiments, the isoform is SEQ ID NO: 739.

[0093] In various embodiments, the compositions are administered locally to the affected tissue or systemically, hi some embodiments, the compounds are encapsulated in particles, including but not limited to lipid nanoparticles (as previously described).

[0094] Other aspects and embodiments of the present disclosure will become apparent from the following examples and claims.

[0095] As used herein, the term "about" means ±10% of the associated value, unless the context requires otherwise.

[0096] References (1)Wilson MS, Wynn TA.Pulmonary fibrosis: pathogenesis, etiology and regulation.Mucosal Immunol 2009;2:103-21. (2)Ley B,Collard HR,King TE.Clinical Course and Prediction of Survival in Idiopathic Pulmonary Fibrosis.Am J Respir Crit Care Med 2011;183:431-40. (3)Nagai S, Kitaichi M, Hamada K, et al.Hospital-based historical cohort study of 234 histologically proven Japanese patients with IPF.Sarcoidosis Vasc Diffuse Lung Dis Off J WASOG 1999;16:209-14. (4)Kaunisto J, Salomaa ER, Hodgson U, et al.Demographics and survival of patients with idiopathic pulmonary fibrosis in the FinnishIPF registry.ERJ Open Res 2019;5:00170-2018. (5)Quinn C,Wisse A,Manns ST.Clinical course and management of idiopathic pulmonary fibrosis.Multidiscip Respir Med 2019;14:35. (6)Fraser E,Hoyles RK.Therapeutic advances in idiopathic pulmonary fibrosis.Clin Med Lond Engl 2016;16:42-51. (7)Ley B,Ryerson CJ,Vittinghoff E,et al.A Multidimensional Index and Staging System for Idiopathic Pulmonary Fibrosis.Ann Intern Med 2012;156:684. (8)Herazo-Maya JD,Sun J,Molyneaux PL,et al.Validation of a 52-gene risk profile for outcome prediction in patients with idiopathic pulmonary fibrosis:an international,multicentre,cohort study.Lancet Respir Med 2017;5:857-68. (9)Zhang N,Guo Y,Wu C,Jiang B,Wang Y.Identification of the Molecular Subgroups in Idiopathic Pulmonary Fibrosis by Gene Expression profiles.Comput Math Methods Med 2021;2021:7922594. (10)He Y,Shang Y,Li Y,et al.An 8-ferroptosis-related genes signature from Bronchoalveolar Lavage Fluid for prognosis in patients with idiopathic pulmonary fibrosis.BMC Pulm Med 2022;22:15. (11)Huang T,He W-Y.Construction and Validation of a Novel Prognostic Signature of Idiopathic Pulmonary Fibrosis by Identifying Subtypes Based on Genes Related to 7-Methylguanosine Modification.Front Genet 2022;13:890530. (12)Zhang C.Novel functions for small RNA molecules.Curr Opin Mol Ther 2009;11:641-51. (13)Zelli V,Compagnoni C,Capelli R,et al.Circulating MicroRNAs as Prognostic and Therapeutic Biomarkers in Breast Cancer Molecular Subtypes.J Pers Med 2020;10:98. (14)Israeli D,Poupiot J,Amor F,et al.Circulating miRNAs are generic and versatile therapeutic monitoring biomarkers in muscular dystrophies.Sci Rep 2016;6:28097. (15)Gupta SK,Bang C,Thum T.Circulating MicroRNAs as Biomarkers and Potential Paracrine Mediators of Cardiovascular Disease.Circ Cardiovasc Genet 2010;3:484-8. (16)Herrera-Rivero M,Zhang R,Heilmann-Heimbach S,et al.Circulating microRNAs are associated with Pulmonary Hypertension and Development of Chronic Lung Disease in Congenital Diaphragmatic Hernia.Sci Rep 2018;8:10735. (17)Komatsu M,Yamamoto H,Kitaguchi Y,et al.Clinical characteristics of non-idiopathic pulmonary fibrosis,progressive fibrosing interstitial lung diseases:A single-center retrospective study.Medicine(Baltimore)2021;100:e25322. (18)Maher TM,Oballa E,Simpson JK,et al.An epithelial biomarker signature for idiopathic pulmonary fibrosis:an analysis from the multicentre PROFILE cohort study.Lancet Respir Med 2017;5:946-55. (19)Bommert A,Welchowski T,Schmid M,Rahnenfuhrer J.Benchmark of filter methods for feature selection in high-dimensional gene expression survival data.Brief Bioinform 2022;23:bbab354. (20)Longato E,Vettoretti M,Di Camillo B.A practical perspective on the concordance index for the evaluation and selection of prognostic time-to-event models.J Biomed Inform 2020;108:103496. (21)Harrell FE.Regression modeling strategies:with applications to linear models,logistic and ordinal regression,and survival analysis,2.ed.Cham:Springer,2015. (22)Vickers AJ,Elkin EB.Decision Curve Analysis:A Novel Method for Evaluating Prediction Models.Med Decis Making 2006;26:565-74. (23)Clark TG,Bradburn MJ,Love SB,Altman DG.Survival Analysis Part I:Basic concepts and first analyses.Br J Cancer 2003;89:232-8. (24)Blondal T, Brunetto MR, Cavallone D, et al.Genome-Wide Comparison of Next-Generation Sequencing and qPCR Platforms for microRNA Profiling in Serum.In:Dalmay T,ed.MicroRNA Detection and Target Identification.New York,NY:Springer New York,2017:21-44. (25) Glass DS, Grossfeld D, Renna HA, et al. Idiopathic pulmonary fibrosis: Current and future treatment. Clin Respir J 2022;16:84-96. (26) Amor MS, Rosengarten D, Shitenberg D, Pertzov B, Shostak Y, Kramer MR. Lung Transplantation in Idiopathic Pulmonary Fibrosis: Risk Factors and Outcome. Isr Med Assoc J IMAJ 2020;22:741-6. (27)Cottin V, Hirani NA, Hotchkin DL, et al.Presentation, diagnosis and clinical course of the spectrum of progressive-fibrosing interstitial lung diseases.Eur Respir Rev 2018;27:180076. [Example]

[0097] Example 1: Small RNA biomarkers predict 3-year transplant-free survival in idiopathic pulmonary fibrosis participants The study design is summarized in Figure 1. PAXgene blood RNA tubes were collected from patients enrolled in the Prospective Study of Fibrosis In The Lung Endpoints (Dataset 1) (n=540) and from patients participating in a longitudinal cohort study related to Dataset 2 (n=153 patients with IPF and n=189 patients with fibrotic ILD).

[0098] Demographic information and spirometry results, including forced vital capacity (FVC) and diffusing capacity of the lung for carbon monoxide (DLCO), were collected at the time of blood draw for Dataset 1 cohort and within 6 months of blood draw for Dataset 2 cohort. Transplant-free survival, as a decimal number from blood draw, was censored at 3 years for both datasets.

[0099] Data generation and NGS sequencing Total RNA was extracted in 24 batches using the PAXgene Blood RNA Extraction Kit (Qiagen). RNA quality was assessed using the RNA Pico Sensitivity Kit (Perkin Elmer) on a LabChip GX Touch (Perkin Elmer). The average RIN score for samples was 8.6 (±1.1). Small RNA libraries were prepared in 96 batches from 250 ng of input RNA using the NextFlex Small RNA-Seq Kit v3 (Perkin Elmer) with 20 PCR cycles. The resulting libraries were pooled and sequenced on a NovaSeq 6000 (Illumina) using a flow cell with S4,300 cycles at a target depth of 20 million reads per sample.

[0100] Adapter trimming and short read alignment Sequencing reads were processed by trimming the adapter sequence using a Regex-based search and trimming algorithm. 5'TGGAATTCCTCGGGTGCCAAGG3' (SEQ ID NO: 342) (including a 3' truncation of up to 15 nucleotides) was input to identify the 3' adapter, with a Levenshtein distance of 2 or a Hamming distance of 5. The parameters for the Regex search required that the first nucleotide of the 3' adapter be unchanged with respect to nucleotide insertion, deletion, and / or swap. The 5' adapter 5'TCTTTCCCTACACGACGCTCTTCCGATCT3' (SEQ ID NO: 343) (including a 5' truncation of up to 15 nucleotides) was input to identify the 5' cloning adapter sequence, with a Levenshtein distance of 2 or a Hamming distance of 5. The parameters for the Regex search required that the 29th nucleotide of the user-specified search term be unchanged with respect to nucleotide insertion, deletion, and / or swap. Paired-end reads were removed if they were not an exact match. Unique small RNA reads were quantified using the 4-nucleotide NNNN prefix and NNNN postfix as unique molecular indices (UMIs). The UMIs were removed after quantification. Reads were aligned to a 17-95 nucleotide tile array of the human genome (hG38) at a Levenshtein distance of 2. The number of trimmed reads per million was calculated for each cloned unique small RNA in the dataset.

[0101] Feature Selection Feature expression of sRNAs was calculated using trimmed reads per million (TRPM). A feature selection pipeline using 10-fold cross-validation on the Dataset 1 cohort incorporated filtering methods and Cox proportional hazards regression with elastic net penalty (GLMNET) filtered to a candidate pool of features most likely to predict survival. Two filtering methods for sRNA feature selection were chosen from recommendations by Bommert et al. for high-dimensional gene expression survival data: (1) correlation with martingale residuals and (2) variance selection. Martingale residuals were calculated by fitting a Cox proportional hazards regression model without covariates to predict 3-year transplant-free survival. Variance selection refers to filtering features with the highest variance, based on the assumption that features with high variance are more likely to exhibit a signal.

[0102] For each fold split, miRNA, pre-miRNA, and tRNA features present in at least 40% of the training set were included for panel consideration if the absolute value of Spearman's rho between TRPM feature expression and martingale residuals was ≥ 0.01 and p-value < 0.05. The feature pool was filtered to the top 300 small RNAs with the highest variance. Finally, Cox proportional hazards regression with elastic net penalty (GLMNET) was fitted to the 300 sRNA features using the training set with a lambda cutoff of 0.01. The resulting candidate feature set included 504 unique small RNAs from the Cox proportional hazards model described above for each fold split.

[0103] The Wasserstein and Cramer-von Mises distances for the 504 feature candidate set were calculated and compared for tests in Dataset 1 and Dataset 2. Features were restricted to those with Cramer-von Mises and Wasserstein distances below the median across the 504 features. The final 44sRNA panel was selected by fitting a Cox proportional hazards regression with elastic net penalty (GLMNET) to the complete Dataset 1 dataset for the remaining 235 features, with a cutoff of lambda = 0.04.

[0104] Survival time analysis To determine whether the 44 sRNA panel has utility compared with or in combination with the GAP index, three Cox proportional hazards regression models were fitted using the following features: (1) sRNA data alone, (2) numerical features based on age, sex, FVC, and DLCO, which were combined to create the GAP index, and (3) sRNA data and the aforementioned GAP features. All models including sRNA features utilize log10-transformed TRPM expression for the 44 features in the final panel. Cox regression models were fitted separately to dataset 1 and dataset 2 (both IPF and non-IPF). The performance of the three models was compared using the concordance index, or C-index, which summarizes how well the predictive risk score described the survival data. C-indexes were compared using 50 bootstraps, both retrospectively and with confidence intervals (using the rms package in R).

[0105] Decision curve analysis was used to compare stratification performance across threshold ranges. Thresholds were selected using the 3-year probability of death extracted from the fitted survival model. Kaplan-Meier curves and cumulative incidence plots were used to assess differences in transplant-free survival and mortality across risk strata and compared with GAP stage. Hazard ratios were used to compare risk strata for each model.

[0106] Dataset comparison and model coefficients The regression coefficients of the Cox regression model for sRNA alone in each dataset (dataset 1 IPF and dataset 2 pan-ILD) can be found in Figures 2 and 3, respectively. miR-92a-3p (3' extended isoform), tRNA-Gly-GCC-2-6 (multiple swap isoform), miR-10401-3p (complete mapping), let-7a-5p (complete mapping), mir-629-5p (complete mapping), mir-1307-3p (3' extended isoform), let-7d-3p (3' extended isoform), tRNA-Pro-TGG-3-4 (complete mapping), miR-4433b-5p (complete mapping), miR-4433c-5p (complete mapping), miR-4433d-5p (complete mapping), miR-4433e-5p (complete mapping), miR-4433f ... Of the 13 sRNAs with statistically significant coefficients in either model, including miR-423-5p (fully mapped), miR-423-5p (3' extended isoform), tRNA-Gly-GCC-1-5 (fully mapped), miR-595-3p (fully mapped), and tRNA-Gly-GCC-2-8 (5' extended isoform), 10 of the 13 had consistent directionality across the two models, indicating an overall similarity across models (Figure 4).

[0107] Comparative Concordance Index In the Dataset 1 cohort, the sRNA-only Cox regression model achieved a retrospective C-index of 0.746, a bootstrap training C-index of 0.772 (95% CI, 0.769-0.777), and a bootstrap test C-index of 0.714 (95% CI, 0.713-0.716).The GAP component-only Cox regression model achieved a retrospective C-index of 0.725, a bootstrap training C-index of 0.728 (95% CI, 0.723-0.732), and a bootstrap test C-index of 0.722 (95% CI, 0.720-0.723). The sRNA+GAP Cox regression model achieved a retrospective C-index of 0.792, a bootstrap training C-index of 0.815 (95% CI, 0.810–0.818), and a bootstrap test C-index of 0.767 (95% CI, 0.764–0.769).

[0108] In the Dataset 2 pan-ILD cohort, the sRNA-only Cox regression model achieved a retrospective C-index of 0.757, a bootstrap training C-index of 0.818 (95% CI, 0.810-0.825), and a bootstrap test C-index of 0.705 (95% CI, 0.700-0.711). The GAP component-only Cox regression model achieved a retrospective C-index of 0.729, a bootstrap training C-index of 0.731 (95% CI, 0.718-0.722), and a bootstrap test C-index of 0.720 (95% CI, 0.718-0.722). The sRNA+GAP Cox regression model achieved a retrospective C-index of 0.801, a bootstrap-trained C-index of 0.854 (95% CI, 0.850-0.861), and a bootstrap overfitting-corrected C-index of 0.744 (95% CI, 0.738-0.751).

[0109] Decision curve analysis The 3-year probability of death was extracted from the Cox regression model fitted to each model. The net effect of stratification at various probability thresholds was calculated using the method described by Vickers et al. (2008). Figure 5 presents the results of a decision curve analysis plotting the net effect versus treatment threshold for the Dataset 1 cohort, comparing the net effects of the three Cox regression models in addition to the all-treated and all-untreated cases. The effect of the sRNA signature-only model is greater than that of the GAP model at all thresholds above approximately 0.25, while the sRNA + GAP signature model has the largest net effect at nearly all thresholds.

[0110] For the Dataset 2 pan-ILD cohort, the results of a decision curve analysis plotting net effect versus treatment threshold are presented in Figure 6, comparing the net effect of the three Cox regression models in addition to the all-treated and all-untreated cases. The effects of both the sRNA model alone and the sRNA + GAP model were greater than the GAP model at almost all thresholds, with the sRNA alone and sRNA + GAP models alternately having the highest effect at different thresholds.

[0111] Survival time analysis Two stratification methods were considered to identify high-risk individuals requiring treatment or transplantation: three-tiered binning and two-tiered binning. For both datasets (Dataset 1 IPF and Dataset 2 pan-ILD), the three-tiered thresholds were as follows: a 0-25% probability of death within 3 years (low risk), a 25-50% probability of death within 3 years (moderate risk), and a >50% probability of death within 3 years (high risk). These stratifications were applied to the sRNA and sRNA + GAP models, while the GAP-only equivalent was represented by stratification using GAP stage. The two-tiered thresholds were as follows for the sRNA, GAP, and sRNA + GAP models: a 40% probability of death within 3 years for Dataset 1 and a 35% probability of death within 3 years for Dataset 2.

[0112] Clinical metadata for risk stratification of the three-class model was evaluated using the sRNA model, GAP stage, and sRNA+GAP model for the Dataset 1 cohort. While the sRNA model stratification did not differ significantly by gender (p = 0.401) or age (p = 0.063), both the GAP stage and sRNA+GAP stratifications differed significantly by gender and age. Furthermore, the high-risk group in the sRNA model stratification had a higher proportion of members who died within 3 years and had a similar overall survival rate to the GAP stage III group, although the population was more than twice as large (163 vs. 74). Kaplan-Meier curves for the three-class model of Dataset 1, along with hazard ratios, are shown in Figure 7, and cumulative mortality curves are shown in Figure 8. In both the sRNA and sRNA+GAP models, the resulting three classes differed significantly with respect to transplant-free survival (log-rank p < 0.001), as did the three GAP stages. The hazard ratio for the sRNA model alone was significantly greater than for GAP stage, especially for high / low risk (8.82 vs. 5.58), and the sRNA+GAP model outperformed both the sRNA and GAP stage models (13.23 HR for high / low).

[0113] Clinical metadata for risk stratification of the two-class model was evaluated using the sRNA, GAP, and sRNA+GAP models for the Dataset 1 cohort. Although differences existed between the GAP stage distributions for the sRNA and GAP+sRNA models, members of all three GAP stages appeared in all strata. The stratification of the sRNA and sRNA+GAP models was not significantly different by gender (p = 0.59 and p = 0.078, respectively), but GAP stratification differed significantly by gender. All two-class stratification models were partially differentiated by age. Furthermore, the high-risk group in the sRNA model stratification had a higher proportion of members who died within 3 years and had a similar overall survival rate to the high-risk GAP group. Kaplan-Meier curves for the two-class model of Dataset 1, along with hazard ratios, are shown in Figure 9, and cumulative mortality curves are shown in Figure 10. The two classes obtained by both the sRNA and sRNA+GAP models were significantly different in terms of transplant-free survival (log-rank p-value < 0.001), as were the three GAP stages. The hazard ratio for the sRNA model alone was significantly greater than for the GAP stage (4.46 vs. 3.44), and the sRNA+GAP model outperformed both the sRNA and GAP stage models (HR = 6.04).

[0114] Clinical metadata for risk stratification of the three-tier model was evaluated using the sRNA model, GAP stage, and sRNA+GAP model for the Dataset 2 IPF cohort. Differences existed between the GAP stage distributions for the sRNA and GAP+sRNA model strata, but members of all three GAP stages appeared in all strata. For the sRNA model stratification, there were no significant differences by gender (p=0.32) or age (p=0.754). For the GAP stage stratification, there were differences by gender (p=0.002), but not by age (p=0.118). For the sRNA+GAP stratification, there were no significant differences by gender (p=0.29) or age (p=0.823). Kaplan-Meier curves for the Dataset 2 IPF three-class model, along with hazard ratios, are shown in Figure 11, and cumulative mortality curves are shown in Figure 12. The three classes obtained by both the sRNA and sRNA+GAP models were significantly different in terms of transplant-free survival (log-rank p-value < 0.001), as were the three GAP stages. The hazard ratio for the sRNA model alone was moderately larger than for the GAP stages, especially those at high / low risk (6.57 vs. 6.11), and the sRNA+GAP model outperformed both the sRNA and GAP stage models (8.66 HR for high / low).

[0115] Clinical metadata for risk stratification of the two-class model was evaluated using the sRNA, GAP, and sRNA+GAP models for the Dataset 2 IPF cohort. In this case, no models were differentiated by gender or age, likely due to the small sample size. Furthermore, the high-risk and low-risk groups had similar proportions of members who died within 3 years across models, with slightly more high-risk members in the sRNA and sRNA+GAP models. Kaplan-Meier curves for the two-class model of Dataset 2 IPF, along with hazard ratios, are shown in Figure 13, and cumulative mortality curves are shown in Figure 14. The two classes obtained in all models were significantly different in terms of transplant-free survival, with log-rank p values ​​<0.001. The hazard ratio for the sRNA model alone (4.37) was higher than the GAP model (HR = 3.81) and the sRNA+GAP model (HR = 4.29).

[0116] Clinical metadata for risk stratification of the three-tier model was evaluated using the sRNA model, GAP stage, and sRNA+GAP model for the Dataset 2 non-IPF cohort. Differences existed between the GAP stage distributions for the sRNA and GAP+sRNA model strata, but members of all three GAP stages appeared in all strata. The sRNA model stratification did not differ significantly by gender (p=0.76) or age (p=0.57). The GAP stage stratification differed by gender (p=0.003) and age (p=0.004). The sRNA+GAP stratification did not differ significantly by gender (p=0.237) or age (p=0.313). None of the strata appeared to have any differences in diagnosis. Furthermore, the high-risk group in the sRNA model stratification had a higher proportion of members who died within 3 years and had a similar overall survival rate to the GAP stage III group, albeit nearly twice as large (42 vs. 22).

[0117] Kaplan-Meier curves for the three-class model of dataset 2 non-IPF are shown in Figure 15 along with hazard ratios, and cumulative mortality curves are shown in Figure 16. The three classes obtained by both the sRNA and sRNA+GAP models were significantly different in terms of transplant-free survival (log-rank p-value < 0.001), as were the three GAP stages. The hazard ratio for the sRNA model alone was moderately larger than for GAP stages, especially those at high / low risk (10.62 vs. 6.90), and the sRNA+GAP model outperformed both the sRNA and GAP stage models (18.78 HR for high / low).

[0118] Clinical metadata for risk stratification of the two-class model was evaluated using the sRNA, GAP, and sRNA+GAP models for the Dataset 2 non-IPF cohort. In this case, no models were differentiated by gender or age, likely due to the small sample size. Furthermore, the high-risk group in the sRNA+GAP model had a slightly higher proportion of members who died within 3 years compared with the other two models, and slightly more high-risk members than the GAP model. Kaplan-Meier curves for the Dataset 2 IPF two-class model, along with hazard ratios, are shown in Figure 17, and cumulative mortality curves are shown in Figure 18. The two classes obtained in all models were significantly different in terms of transplant-free survival, with log-rank p values ​​<0.001. The hazard ratio for the sRNA model alone (5.37) was greater than that of the GAP model (HR = 3.87), and the sRNA+GAP model outperformed both the sRNA and GAP models (HR = 9.49).

[0119] A signature of 44 small RNAs was identified in the exploratory cohort (Dataset 1) as a predictor of 3-year transplant-free survival. Filtering criteria identified features statistically significantly associated with transplant-free survival using correlation and variance selection methods. Martingale residuals were used as the uncorrected continuous survival outcome variable, allowing for correlation-based filtering. Cox regression with elastic net penalty using cross-validation produced a more robust predictive model. These 44 features were used to fit a separate Cox regression model to the validation cohort (Dataset 2). Decision curve analysis showed that the model including sRNA features performed better than the GAP index, and the model including both GAP and sRNA features performed best. Both two- and three-tiered risk classifications were created for each dataset, with Dataset 2 separating IPF from non-IPF. The rationale for each was as follows: the three-tiered model allowed for direct comparison with the GAP staging model, while the two-tiered model allowed for efficient decision-making among physicians, with high-risk patients receiving treatment or transplant and low-risk patients not. The combination of sRNA and clinical prediction models including TRPM features in addition to age, sex, FVC% and DLCO% performed better than GAP features alone.

[0120] Example 2: Idiopathic pulmonary fibrosis subtyping sRNA panel Forty-nine IPF PAXgene Blood RNA samples served as the exploratory cohort. RNA was extracted in 24 batches using the PAXgene Blood RNA Extraction Kit (Qiagen). The extracted RNA was (1) quantified in triplicate using the quant-IT RNA Assay Kit (ThermoScientific) on a Fluoroskan fluorometer (ThermoScientific) to calculate concentration, and (2) RNA quality was assessed using the RNA Pico Sensitivity Kit (PerkinElmer) on a LabChip GX Touch (PerkinElmer). Small RNA sequencing was performed on the purified RNA samples in 96 batches using the NextFlex Small RNA-Seq Kit v3 for Sciclone Automation on a Sciclone iQ NGS workstation (PerkinElmer) using next-generation sequencing (NGS) libraries prepared from 250 ng of input RNA.

[0121] To facilitate sample pooling, i7 / i5 indexing was incorporated using the NextFlex Small RNA-Seq Kit v3 for Sciclone Automation (BI001). Libraries were quantified in triplicate using the quant-IT dsDNA HS Assay Kit (Thermo) on a Fluoroskan fluorometer (Thermo). Library quality analysis was assessed using the LabChip DNA 3K NGS Assay Kit (PerkinElmer) to verify the generation of appropriate library sizes.

[0122] Libraries were pooled, requantified using the KAPA NGS Library Quantification Kit (Kapa Biosciences), and diluted to a final concentration of 1.6 nM, using a factor of 200 bp as the average calculated insert size. Libraries were individually prepared using the XP 4-Lane Kit (Illumina) to target 20 million reads per sample. Libraries were sequenced on a NovaSeq 6000 Sequencing System (Illumina) using the S4,300-cycle Flow Cell Kit (Illumina).

[0123] Sequencing reads were processed by trimming the adapter sequence using a Regex-based search and trimming algorithm. 5'TGGAATTCCTCGGGTGCCAAGG3' (SEQ ID NO: 342) (including a 3' truncation of up to 15 nucleotides) was input to identify the 3' adapter, with a Levenshtein distance of 2 or a Hamming distance of 5. The parameters for the Regex search required that the first nucleotide of the 3' adapter be unchanged with respect to nucleotide insertion, deletion, and / or swap. The 5' adapter 5'TCTTTCCCTACACGACGCTCTTCCGATCT3' (SEQ ID NO: 342) (including a 5' truncation of up to 15 nucleotides) was input to identify the 5' cloning adapter sequence, with a Levenshtein distance of 2 or a Hamming distance of 5. The parameters for the Regex search required that the 29th nucleotide of the user-specified search term be unchanged with respect to nucleotide insertion, deletion, and / or swap. Paired-end reads were removed if they were not an exact match. Unique small RNA reads were quantified using the 4-nucleotide NNNN prefix and NNNN postfix as unique molecular indices (UMIs). The UMIs were removed after quantification. Reads were aligned to a 17-95 nucleotide tile array of the human genome (hG38) at a Levenshtein distance of 2. The number of trimmed reads per million was calculated for each cloned unique small RNA in the dataset.

[0124] Corresponding control PAXgene blood RNA sRNA NGS data were obtained from GSE100467 and GSE46579 and downloaded from the GEO database. Additional control samples were obtained from healthy volunteers. The total control cohort consisted of 170 samples that were either healthy or diagnosed with a neurodevelopmental disorder, 57% of which were male, with a mean age of 69.31 (±7.85). The 49 PAXgene IPF samples were 87.8% male, with a mean age of 64.67 (±8.71). An initial sRNA signature of 86 sRNA features that distinguished IPF from non-IPF controls was identified. Features were selected based on filtering criteria that maximized inter-class separation, and then filtered for features with high classification importance based on coefficients from a GLMnet ridge classification model. Finally, a support vector machine (SVM) was fitted using a linear kernel. SVM model testing resulted in an AUC of 0.999 (p<0.001) and an accuracy of 99.6%. This sRNA signature was used to identify four putative subtypes within the discovery cohort. These subtypes were identified using principal component analysis (PCA) and hierarchical clustering on principal components, which combines two clustering algorithms: hierarchical clustering and k-means clustering. PCA reduces the dimensionality of high-dimensional datasets by geometrically projecting a set of features onto low-dimensional summaries known as principal components. Principal components are uncorrelated and minimize the distance between the data and their projections. Input variables for PCA included log10-transformed sRNA expression data measured in trimmed reads per million (TRPM) and scaled using unit variance scaling. Goodness of fit (R 2 ) and predictability (Q 2 Using the metric of variability (i.e., the first five principal components calculated using singular value decomposition) were selected as the optimal number to capture the variation in the data. A scree plot confirmed the selection of five principal components to explain most of the variation in the data.

[0125] Hierarchical clustering using Ward's linkage and k-means clustering merged the partitions using a predetermined number of clusters of four. A projection of the data onto the first two principal components is shown in the score plot in Figure 19. Principal component 1 (PC1) and principal component 2 (PC2) accounted for 59% and 18% of the variability in the data, respectively.

[0126] After two rounds of 10-fold cross-validation, an sRNA signature of 719 sRNA features was identified that classified the four subtypes in the discovery cohort. The SVM model yielded an area under the curve (AUC) of 0.917 (p<0.001) with a minimum per-class accuracy of 88%.

[0127] After the initial search for putative subtypes, an additional 546 samples were obtained from the Dataset 1 study as a validation cohort. Wasserstein and Cramer-von Mises distances were calculated for each sRNA in the 719 sRNA feature set for three comparison pairs: the two experimental batches of the discovery cohort versus the validation cohort, and the two validation batches. sRNA expression was measured by log10-transformed trimmed reads per million and scaled to the mean and standard deviation for each marker. For each pair of cohorts filtering for miRNAs only, a subset of 71 sRNA features was identified using filtering criteria of both Cramer-von Mises and Wasserstein distances below the median. Applying this SVM model to the validation cohort yielded stratified cohorts across the Dataset 1 study, revealing four distinct subtypes that correlated with overall survival (Figure 20).

[0128] Example 3: Therapeutic potential of mir92a small RNA isoforms for treating idiopathic pulmonary fibrosis sRNAs play a key role in controlling regulatory pathways associated with IPF progression. This example evaluates IPF sRNA expression in lung tissue, whole blood, and primary lung fibroblast samples collected from IPF patients and mice with bleomycin-induced pulmonary fibrosis (PF). These results identify genomic hotspots for sRNA isoforms with significant gain or loss of expression in IPF subjects. Loss of sRNA isoforms mapping to the miR92A locus was observed in IPF subjects across all datasets and was a significant predictor of 3-year survival. miR92-1+ / - mice exhibited an accelerated and more severe disease course after bleomycin induction compared with wild-type mice, recapitulating findings from human populations and confirming the protective role of the miR-92a-3p isoform in IPF. Furthermore, inhaled miR-92a-3p mimics reversed bleomycin-induced PF in mice. Twenty-two sRNA mimics were synthesized, representing the most significantly downregulated miR-92a-3p isoforms identified by computational modeling. One lead (oligo-006, Table 10) was most effective in reducing collagen deposition and IPF fibroblast growth. Furthermore, oligo-006 reduced collagen, fibrotic, and inflammatory biomarkers in precision-cut lung slices (hPCLS) from IPF patients. These results illustrate the important role of mapping sRNA isoforms to the MIR92A locus in disease and demonstrate the novel therapeutic potential of miR-92a-3p and its isoforms in IPF.

[0129] Introduction Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive, and fatal disorder. Patients with IPF have different outcomes depending on a combination of environmental and genetic factors that influence the severity and clinical course of the disease. Lung transplantation is the only treatment option for IPF, but the number of healthy lung donors is a limiting factor, and pharmaceutical intervention is essential for most patients. 1Two FDA-approved antifibrotic treatments (pirfenidone and nintedanib) are available, but they do not significantly improve outcomes. Furthermore, severe adverse side effects from these medications often lead to poor adherence in IPF patients. Therefore, new treatment options are needed to improve patient outcomes and quality of life. 2-3 .

[0130] IPF is characterized by progressive decline in lung function, decreased blood oxygen levels, and exercise-induced exertion. Pathologically, IPF is defined by the transdifferentiation of type 2 pneumocytes into (myofibroblasts) and the presence of fibrotic lesions with leukocyte infiltration and structural abnormalities. Multiple signaling pathways are involved in IPF, including transforming growth factor beta (TGFβ), α and β integrins (ITGA / ITGB), Wingless-related integrin pathway (WNT), extracellular matrix (ECM), and cytokine signaling. 4-6 .

[0131] Novel therapeutics targeting these proteins and signaling pathways are currently in various stages of clinical development. However, current investigational drugs face two major challenges. First, they rely on a single therapeutic mechanism of action, suggesting a single disease-driving factor. However, given the complexity of the regulatory network in IPF, successful therapeutics will need to target multiple pathways. 7 Second, their oral administration poses the risk of drug-induced side effects, especially in the gastrointestinal tract, where these same regulatory networks are disproportionately activated. 8 This creates an opportunity to develop multi-drug inhaled therapies that address current challenges.

[0132] Recent evidence shows safe and effective direct pulmonary delivery of small interfering RNA (siRNA) with a persistence of >50 days 9,10. siRNA is a powerful modality for selectively targeting and inhibiting messenger RNA (mRNA). The siRNA backbone can also be used to deliver mimics that restore the activity of endogenous sRNA genes. sRNAs are master regulators of gene expression that play important roles in controlling stress responses, proliferation, and differentiation pathways. 11 sRNAs are 18-26 nucleotide RNAs that are bound by Argonaute proteins to create effector RNA-induced silencing complexes (i.e., RISCs). 12、13 .

[0133] RISC is guided to mRNAs that have target sites complementary to the loaded sRNA. Three major functional motifs within the sRNA sequence have been characterized: the 5'-terminal nucleotide is required for RISC loading, nucleotides 2-8 are required for mRNA targeting, and nucleotides 9-12 determine the mechanism of gene silencing. Complementarity at the 3'-end is also important but less limiting. Because the functional motif is very short, a single sRNA can target many mRNAs, making them pleiotropic (or multipharmacological) effectors. 14 Previous studies have implicated the role of sRNAs in IPF and IPF-related regulatory pathways. 15 However, increasing evidence suggests that sRNAs are expressed as an array of sequences called isoforms, which has implications for analysis and biological modeling. 16、17 Isoforms may have higher expression levels and greater differential gene expression changes when compared to annotated sRNAs, indicating biological significance. 18 Isoforms can have additions and removals of nucleotides at the 5' and 3' ends, as well as internal swaps that affect their function. 19 .

[0134] Thus, according to aspects of the present disclosure, sRNA isoforms may provide novel biomarkers for stratifying IPF patients and may provide a reservoir of novel multipharmacological therapeutic targets that can be delivered directly to the lung for the treatment of IPF. To this end, the inventors analyzed sRNA sequencing data generated from samples ranging from tissue and blood, human and animal, and in vivo and in vitro sources. This dataset enabled the identification of novel, translatable sRNA drug targets.

[0135] The expression of unique sRNA isoforms was characterized across genomic loci. Loci with extreme numbers of unique sRNAs are called "isoform hotspots." Scrutiny revealed uniformly downregulated isoforms from a hotspot on chromosome 13, coinciding with the miR92A1 locus, which strengthened the prediction of 3-year transplant-free mortality. MIR92-1+ / - mice exhibited rapidly progressive and severe bleomycin-induced pulmonary fibrosis compared with wild-type animals, indicating a protective role for this locus in disease. Replacing the miR-92a-3p isoform with a therapeutic mimic inhibited collagen deposition and cell proliferation in primary IPF fibroblasts and precision-cut lung slices. Inhaled delivery of the miR-92a-3p mimic reversed bleomycin-induced PF in mice and improved overall health. Furthermore, we identified a large set of miR-92a-3p mRNA targets that were successfully downregulated in primary IPF fibroblasts after treatment with miR-92a-3p mimics. Many of these genes are involved in ECM production and regulation (including COL5A1, ITGAV, ITGA5, and FBN1). 20、21 Demonstrating the pleiotropic effects of these isoforms, these results provide for the identification and validation of oligonucleotide therapeutics that could be used to treat IPF patients with reduced expression of the miR-92a-3p isoform, thereby opening the door to precision medicine in patients with the most severe outcomes.

[0136] Discovery of sRNA isoform drug targets in human and mouse IPF datasets Therapeutic programs that incorporate biomarkers into early-stage R&D are five times more likely to achieve FDA approval due to the ability to select patients during clinical trial enrollment 22、23 sRNAs offer a unique opportunity for early biomarker incorporation because up- or down-regulation can be quantified in samples and dysregulated sRNAs can be directly targeted by oligonucleotide therapeutics. 24 For a biomarker to be useful in early-stage R&D, it needs to correlate with clinically relevant endpoints and translate across tissues and blood, humans and animals, and in vivo and in vitro systems.

[0137] To enable the discovery of translatable small RNA drug targets, samples were aggregated from humans and animals, tissues and blood, and in vitro and in vivo systems (Table 1). sRNA sequencing data were generated from PAXgene Blood RNA samples collected at three independent laboratories. Matched mRNA sequencing data were generated from 176 samples. Matched sRNA and mRNA sequencing data were generated from primary IPF patient fibroblast cell lines (BioIVT and Lonza). Matched sRNA and mRNA sequencing data were generated from mouse lung tissue collected at days 3, 5, 7, 14, and 21 after treatment from a longitudinal study of saline- or bleomycin-induced C57Bl / 6 animals. Saline-treated mice were considered controls, and bleomycin-treated mice were considered IPF. Additionally, matched sRNA and mRNA microarray data from human lung biopsies were incorporated from GSE3253925. TIFF2025534768000003.tif94170

[0138] The sRNAs are derived from either the 3 prime (3p) arm or the 5 p (5p) arm of the pre-miRNA and are cleaved by two RNase III enzymes, Drosha and Dicer. The 5' end of the 3p arm and the 3' end of the 5p arm are cleaved by Drosha, and the 3' end of the 3p arm and the 5' end of the 5p arm are cleaved by Dicer. 26、27 Thus, isoforms can be characterized by additions or deletions at the 3' or 5' end and can be divided by those with mapped sRNAs derived from the 3p or 5p arms (Figure 21A). Isoforms were considered valid if they had a prevalence of at least 5% and a minimum representation of 1 trimmed read per million (TRPM). Using these filters, 5,687 unique isoforms were identified for 404 annotated sRNAs in PAXgene blood RNA samples, 11,805 unique isoforms for 605 annotated sRNAs in primary fibroblasts, and 4,867 unique isoforms for 234 annotated sRNAs in lung tissue from bleomycin-induced mice. The percentage of reads attributable to annotated sRNAs was compared across sample types, origin arms, and ends (3' or 5') using a two-proportion test, and all comparisons were statistically significant (p<0.05) (Figure 21B). 1,798 isoforms mapping to 225 annotated sRNAs were conserved across all three cohorts, representing a pool of novel translatable and druggable sRNA targets.

[0139] Searching for the miR-92a-3p hotspot: a regulator of progressive IPF biology Previous studies have shown that genetic mutations and RNA editing hotspots create sRNA isoforms that can potentially drive disease biology. 28、29Therefore, we identified sRNA hotspots, where an excessive number of isoforms were expressed. Hotspots were defined as genomic loci with at least 100 unique isoforms within each dataset, with a TRPM of ≥ 1 and a frequency of ≥ 5%. These parameters corresponded to a 0.1% FDR threshold for the negative binomial distribution of valid isoforms per genomic locus.

[0140] Analysis of sRNA hotspots in human PAXgene blood RNA and primary fibroblast cell lines revealed miR-92a-3p as a hotspot with 108 isoforms shared between the two datasets. Isoforms from this hotspot mapped ambiguously to the MIR92A-1 (chromosome 13) and MIR92A-2 (X chromosome) loci due to sequence identity. The miR-92a-3p hotspot was not observed in bleomycin-induced mice, which may be due to the homogeneity of the mice. Nevertheless, 25 miR-92a-3p isoforms were conserved between humans and mice.

[0141] The total expression level of miR-92a-3p isoforms was calculated using trimmed reads per million (TRPM). A T-test comparing the total number of miR-92a-3p isoforms in IPF samples with controls showed that miR-92a-3p was significantly downregulated in PAXgene blood RNA, IPF fibroblasts, and lung tissue from bleomycin-induced mice (Figures 22B, 22C, and 22D). These findings were independently validated using sRNA microarray data from GSE32539, which showed significant downregulation of miR-92a-3p in lung tissue collected from IPF patients compared with controls (Figure 22A). These results indicate that IPF is associated with a loss of miR-92a-3p isoform expression.

[0142] Increased collagen deposition is a characteristic feature of IPF30. Therefore, we characterized collagen expression in primary fibroblast cell lines. Results showed that collagen levels were significantly elevated in fibroblasts from IPF patients compared with fibroblasts from healthy donors (Figure 22E). IPF fibroblasts exhibited a wide range of collagen expression, with a five-fold difference between the highest and lowest expressing cell lines (Figure 22E). sRNA sequencing data also suggested a wide range of miR-92a-3p isoform expression in IPF fibroblasts, with a four-fold difference between the highest and lowest expressing cell lines (Figure 22E). miR-92a-3p has previously been implicated in the regulation of collagen expression. 31 Therefore, the expression of the miR-92a-3p isoform was correlated with collagen. The results showed that the miR-92a-3p isoform was negatively correlated with collagen (Spearman's rho: -0.5710, p<0.001) (Figure 22E). These results suggest that the miR-92a-3p isoform may play a conserved role in regulating pathways controlling collagen deposition, closely linking the expression of the miR-92a-3p isoform to the biological phenomena of IPF.

[0143] miR-92a-3p isoform is a predictor of 3-year transplant-free survival in IPF To assess the importance of the miR-92a-3p isoform, a Cox proportional hazards regression model was compared with stratification based on the IPF Clinical GAP Index. 32 A Cox model was fitted to IPF blood samples (n = 697) containing 44 small RNA signatures and the four clinical components of the IPF GAP Index (sex, age, DLCO, and FVC). Risk stratification criteria were based on the probability of death within 3 years extracted from fitting the Cox regression model and were as follows: 0-25% (I), 25-50% (II), and >50% (III) (Figure 23A).

[0144] These three risk strata were compared with the clinical GAP index, expressed using GAP stage (I, II, or III). Both models yielded three classes with significant differences in 3-year transplant-free survival (log-rank p<0.001). Blood-based sRNA uptake identified more than twice as many high-risk patients compared with the GAP index alone (two-pronged ratio test, p<0.05). Furthermore, the hazard ratios between stage II / I and stage III / I increased from 2.65 to 4.19, 5.43, and 11.74, respectively, with blood-based sRNA uptake (Figure 23A). One miR-92a-3p isoform was the second most important feature for predicting survival, with a significant hazard ratio of 0.17 (p<0.001, log-rank test) (Figure 23B). Additionally, 41% of patients from IPF blood samples in the bottom quartile of miR-92a-3p hotspot expression died within 3 years compared with 31.7% of patients in the top 3 quartiles of miR-92a-3p hotspot expression (two proportions test, p<0.05).

[0145] The miR-92a-3p isoform protects against bleomycin-induced pulmonary fibrosis in mice Given the mounting evidence suggesting loss of miR-92a-3p in IPF across multiple exploratory cohorts, we hypothesized that the miR-92a-3p isoform plays a protective role in IPF. To test this, we induced pulmonary fibrosis in miR92-1 heterozygous knockout mice using 1.45 mg / kg bleomycin via oropharyngeal (OP) aspiration. Weight loss and survival were tracked from day 0 through the survival period of the observational study. Bleomycin-induced pulmonary fibrosis and miR-92a-3p isoform expression were assessed on day 21.

[0146] Weight loss from day 0 to day 21 is a key feature of the bleomycin-induced mouse model. 33Wild-type mice exhibit a maximum 8–12% weight loss on days 8–9 after bleomycin challenge compared to saline-treated animals. After bleomycin challenge, wild-type animals recover to day 0 weight on days 14–16 and stabilize until the end of the study on day 21. This is accompanied by increased respiratory rate, decreased activity, and histologically increased interstitial collagen deposition, inflammation, and fibrosis.

[0147] Our results demonstrated that MIR92-1 + / - animals exhibited a more rapid progression of bleomycin-induced pulmonary fibrosis compared with wild-type controls. While wild-type animals lost 8–12% of their body weight by day 8 of the study (p<0.001), MIR92-1 + / - animals lost 15–20% of their body weight at the same time point, indicating a greater severity of bleomycin-induced fibrosis compared with wild-type controls (Figure 24A). Furthermore, three of nine MIR92-1 + / - animals (30%) lost more than 20% of their body weight from day 0. This exceeded the study center's wellness protocol and led to the early euthanasia of these animals. Although the difference in overall survival was not significant (log-rank test, p>0.05), these results model our observations in human populations (Figure 24B).

[0148] On study day 21, animals were euthanized and the lungs perfused. The left lung was inflated and fixed for histological analysis, and the right lung was snap-frozen for molecular analysis. Left lungs were sectioned (three per lung) and stained for collagen using picrosirius red (PSR). Blinded scoring by a board-certified pathologist showed that MIR92-1 + / - animals had significantly more bleomycin-induced collagen deposition compared to wild-type mice (p = 0.033) (Figures 24C and 24D).

[0149] In mice, miR-92a-3p is expressed at two independent loci on chromosome 14 (mIR92-1) and chromosome X (mIR92-2). The knockout mice used in this study contained a heterozygous knockout of the chromosome 14 allele, demonstrating that haploinsufficiency of the miR-92a-3p isoform is sufficient to increase the severity of bleomycin-induced IPF. Results from human PAXgene blood RNA samples suggested that IPF patients had a 40% reduction in miR-92a-3p isoform compared to healthy donors. Experiments were performed to understand the extent to which the heterozygous knockout contributed to haploinsufficiency and the resulting phenotype. sRNA sequencing data generated from the right lung showed a significant reduction in miR-92a-3p isoform compared to wild-type (C57BL / 6) mice (t-test, p = 0.02) (Figure 24E). These results establish an association between translated miR-92a-3p haploinsufficiency and IPF severity between human and mouse subjects.

[0150] miR-92a-3p mimic reversed bleomycin-induced pulmonary fibrosis in mice A miR-92a-3p mimic (Oligo-019, Table 10) was synthesized to determine whether overexpression of miR-92-3p was sufficient to reverse bleomycin-induced pulmonary fibrosis. The mimic was formulated in LNPs to facilitate delivery to the lung. Formulated compound (1 μg / mouse) or saline control was delivered directly to the lungs of bleomycin-challenged animals via oropharyngeal (OP) inhalation on days 5, 10, 13, and 17 after bleomycin challenge. Body weights were measured daily from day 1. Animals were sacrificed on day 21, at which time blood and lung tissue were collected (Figure 25A).

[0151] Bleomycin-treated mice (n = 10) showed a significant decrease in body weight starting on day 5 compared with saline controls (n = 8). Body weight was restored by miR-92a-3p (Oligo-019) in bleomycin-treated animals (n = 8, Figure 25B). In miR-92a-3p-treated animals, weight restoration was accompanied by an increase in blood glucose levels (Figure 25C). Furthermore, pulmonary inhalation of bleomycin significantly increased lung weight (p < 0.01), which was restored by miR-92a-3p (p < 0.05, Figure 25D).

[0152] Consistent with these results, mice treated with miR-92a-3p (Oligo-019) showed protection against bleomycin-induced pulmonary fibrosis, as indicated by a significant reduction in collagen content (p<0.01) in bleomycin-induced animals, as measured by hydroxyproline (Figure 25E). This result was reinforced by histopathological evaluation of PSR staining in lung tissue (Figure 25F). Histological evaluation of H&E staining suggested that pulmonary inhalation of bleomycin induced inflammatory infiltrates in lung tissue (inflammatory scores: Sal / Sal: 0.0±0.0, Bleo / Sal: 3.19±0.284, and Bleo / Oligo-019: 2.5±0.236). This was ameliorated by delivery of miR-92a-3p in bleomycin-treated mice (Figure 25F).

[0153] In vitro screening of miR-92 isoform mimics Nine primary fibroblast cell lines were selected to screen miR-92a-3p isoforms and obtain broad-spectrum results that best model the human population. The use of primary IPF fibroblasts from patients allowed for the screening of miR-92a-3p isoforms in a "native" (uninduced) background. Cell proliferation was measured continuously every 4 hours for 96 hours. Collagen expression was measured at 48 hours.

[0154] IPF cells proliferate faster and produce more collagen than NHLF cells. To assess the effect of miR-92a-3p isoforms on the ability to slow proliferation and / or reduce COL1A1 production, an in vitro screen was performed in IPF human lung fibroblasts derived from nine IPF patients. The effect of 22 different mimetics on proliferation at 10 nM and 100 nM concentrations over 96 hours was measured, and the effect on COL1A1 in the 100 nM mimetics after 48 hours of exposure was measured.

[0155] Results showed that at 10 nM and 100 nM of the compounds, 18 of the 22 mimetics attenuated proliferation in all nine fibroblast cell lines by up to 60% of the scrambled control (Figure 26A). These differences were statistically significant (p<0.001) using an unpaired two-tailed t-test with Welch's correction for unequal standard deviations for all tested mimetics except Oligo-013, 014, 015, 017, and 019. Visual analysis of the cells after 96 hours of exposure showed no cell death or morphological changes after treatment. This indicated that the miR-92-3p mimetics indeed inhibit cell proliferation and do not cause cell death or rounding, which could be confused with inhibiting cell proliferation.

[0156] Collagen was significantly reduced in all nine fibroblast cell lines by 14 of the 22 mimetics, to varying degrees, up to 50% of the control (Figure 26B). Initial screening revealed that the level of collagen inhibition varied considerably among fibroblast cell lines and isoform mimetics. All mimetics except Oligo-009 and 010 were able to significantly alter collagen levels (p<0.001 using an unpaired two-tailed t-test with Welch's correction for unequal standard deviations). These results were independently confirmed by immunostaining, which showed reduced collagen expression in mimetic-treated fibroblast cell lines. Based on the initial screening, six mimetics with the highest average activity for collagen and fibroblast growth inhibition were selected (Oligo-006, 008, 013, 016, 018, and 019).

[0157] The mimetics were further evaluated using dose-response curves to assess the EC50 for fibroblast proliferation and collagen inhibition in the most sensitive cell line of the nine, IPF005. They were evaluated against the current standard of care (pirfenidone and nintedanib) and a competing product, saracatinib (AstraZeneca), which is currently undergoing Phase 1 clinical trials and has received orphan drug designation. The mimetics are 6-1000 times more effective than the small molecule drug.

[0158] Ex vivo efficacy of miR-92a-3p isoforms using precision-cut lung slices Next, we tested the efficacy of miR-92a-3p in pulmonary fibrosis using precision-cut lung slices (hPCLS) collected from pulmonary fibrosis donors. To do this, PCLS were transfected in duplicate with the most active miR-92a-3p mimic (10 μM). The mimic was chemically modified at the 2'-hydroxyl, phosphodiester backbone, 3' end, and 5' end to increase stability. PCLS were subjected to molecular pathology and histopathological analysis after acute (48 h) or chronic (96 h) exposure. Collagen expression was measured after acute exposure. Inflammatory and fibrotic markers were measured after chronic exposure using Luminex and histopathology. A scrambled mimic was used as a negative control.

[0159] After two rounds of screening, Oligo-006 (also known as GHB1589) was determined to be the most effective mimetic for reducing collagen, inflammation, and fibrotic markers. Oligo-006 reduced collagen by more than 50% after 48 hours of acute exposure (Figure 27B). H&E staining for interstitial inflammatory cell infiltration and fibrosis was performed on PCLS after chronic (96 hours) exposure. Results showed that Oligo-006 reduced the number of inflammatory cells and foci throughout the section (Figure 27C). Furthermore, Oligo-006 reduced alveolar septal fibrosis by more than 40% and reduced alveolar septal thickness by threefold (Figure 27D). Scoring was performed on two independent PCLS, and results represent the mean (±) standard deviation. Although the small sample size precluded statistical analysis, pathology results showed a trend in the correct direction, covering two independent sections per treated PCLS.

[0160] Molecular analysis showed a significant decrease in IL-6, IL-8, MCP-1, ProColA1, FN1, and TIMP-1 in the medium and lysates collected at 96 hours compared to the scrambled control. Reduced levels of MMP-3 and MMP-7 were observed in the medium collected at 96 hours compared to the scrambled control. These analytes were not detected in the lysates (Figure 27E). Collectively, these results indicate that Oligo-006 (miR-92a-3p isoform) was sufficient to reverse pulmonary fibrosis in human-derived PCLS.

[0161] Pleiotropic repression of profibrotic genes by miR-92a-3p isoform To identify the mechanism of action by which miR-92a-3p isoforms suppress fibrosis development, we performed mRNA sequencing (NGS) on four replicates of one primary human lung fibroblast cell line (IPF005) 48 hours after transfection with a miR-92a-3p mimic (oligo-006) or scrambled siRNA (control). Differential gene expression revealed over 8,000 differentially expressed genes in treated cells with respect to the scrambled siRNA, indicating that transfection of the mimic significantly impacted the mRNA landscape (Figure 28A). Using our in-house sRNA target site identification method conceived by TargetScan, we identified sRNA target sites. 35 , we identified potential targets of miR-92a-3p. These targets were significantly enriched among down-regulated genes in treated cells (1,565 down-regulated genes out of 4,249 genes with binding sites, chi-squared p-value <10). -16 ).

[0162] Significant enrichment of downregulated genes was also found in the following pathways associated with fibrosis: focal adhesions, TGF-beta pathway, WNT pathway, ECM, and mucin production. Target-target enrichment analysis of transcription factors (TFs) provided evidence that oligo-006 suppressed the expression of genes downstream of profibrotic pathways: SMAD4 and TCF7L2, as well as the pro-inflammatory regulator STAT3.36 Furthermore, oligo-006 appeared to repress genes involved in cell cycle promotion (KEGG pathway hsa04110, adjusted p = <0.05), consistent with our investigation of the isoform's effects on cell proliferation and potentially linked to repression of the E2F4 TF (Figure 28B). COL1A1 and other collagen genes lacking the miR-92a-3p binding site were not downregulated by oligo-006, contradicting the ELISA results. These results suggest that downregulation of COL1A1 protein by miR-92a-3p isoforms is indirect, either translationally or post-translationally.

[0163] More than 200 genes harboring miR-92a-3p binding sites are involved in three major profibrotic pathways: WNT (FZD4, FZD6, WNT5A, CCN4), TGF-beta (TGFBR2, SMAD2, SMAD4, BMPR2), and focal adhesions (ITGA5, ITGAV, SRC). Some genes harboring miR-92a-3p binding sites are also involved in the ECM and collagen pathway (COL5A1, COL1A2, FBN1, FBN2) or interleukin-mediated inflammation (IL1R1, STAT3). 31、37 Many of these genes are down-regulated after transfection with oligo-006 (Fig. 28B).

[0164] To confirm the direct interaction of miR-92a-3p isoforms with the mRNAs of these genes, we used a dual-luciferase reporter assay to test miR-92a-3p activity at their binding sites. A total of 88 binding sites from 70 genes were introduced into the 3'UTR of a luciferase reporter plasmid, and A549 cells carrying the plasmid were transfected with oligo-006. Significant downregulation was observed for 34 binding sites (p-value < 0.05), confirming the activity of miR-92a-3p isoforms at the corresponding genes (Figure 28C).

[0165] Among the most significantly downregulated genes with active binding sites are COL5A1, ITGAV, ITGA5, FZD4, and FBN1 (Figures 28C and 29). Notably, these genes are involved in ECM sensing and induce profibrotic pathways. 38 ITGAV is particularly important because it is involved in the release of TGF-beta from latency-associated peptide (LAP) and acts on both focal adhesion and TGF-beta signaling. 39、40 These five genes highlight the pleiotropic effects of miR-92a-3p isoforms, but many other genes are also involved in the anti-fibrotic effects of miR-92a-3p, either through active binding sites (SRC, BMPR2, CCN4, SMAD4) or downregulation in our NGS data. These results suggest a mechanism of action for Oligo-006 drug. After external stress, collagen and other ECM and integrin compounds are produced, triggering a cycle of focal adhesions, TGF-beta, cell proliferation, and fibrosis regulation. 38 Our findings suggest that the miR-92a-3p isoform suppresses this cycle at multiple nodes, consistent with the worsened outcomes of patients with low levels of these miRNA isoforms. Reintroducing a mimic of this miR-92a-3p isoform as a multidrug therapy should modify IPF progression through its effects on the integrin alpha, collagen, WNT, and TGF-beta pathways.

[0166] Consideration In this study, a disease-independent approach was used to identify the miR-92a-3p locus as a miRNA isoform hotspot using lung tissue samples, blood samples, and fibroblast cell lines from IPF patients. Using multiple methods, including NGS sequencing, ELISA, and hydroxyproline assays, we provide evidence that miR92A is a key driver of IPF progression. Furthermore, we present evidence of the therapeutic efficacy of miR-92a-3p mimetic oligonucleotide therapeutics for IPF. These data provide strong evidence that miR-92a-3p isoform mimics are equivalent to or superior to two FDA-approved drugs, nintedanib and pirfenidone, in suppressing pulmonary fibrosis in both in vitro and ex vivo models derived from IPF donors.

[0167] IPF is a heterogeneous disease with variable rates of clinical progression, decline in lung function, and response to treatment. 41 Identifying novel, effective, and long-term antifibrotic agents that target the underlying mechanisms of IPF is an unmet clinical need. Individual sRNAs can regulate the expression of multiple mRNA targets and have broad effects on multiple cellular pathways. Therefore, therapies targeting individual sRNAs may have broader impacts than traditional monotherapy approaches.

[0168] At the start of the study, small RNA sequencing was performed on human PAXGene blood samples and primary human lung fibroblasts. sRNA hotspots (i.e., specific genomic loci with at least 100 isoform variants) were identified with a trimmed reads per million (TRPM) of at least 1 and a prevalence of at least 5% per study. Among these hotspots, the miR-92a-3p hotspot, which ambiguously mapped to chromosomes 13 and X, was consistently downregulated in all IPF cohorts compared with their respective controls. Furthermore, the miR-92a-3p isoform was the second-highest weighted contributor to a Cox proportional hazards model predicting 3-year transplant-free survival in IPF.

[0169] These findings were confirmed in an open-source microarray dataset of lung biopsy samples obtained from patients with IPF. 25 Analysis of RNA sequencing data from human IPF cell lines also confirmed downregulation of the miR-92a hotspot compared with normal human lung fibroblast (NHLF) cell lines. Expression of miR-92a-3p also correlated with upregulation of collagen expression (p<0.05). sRNA NGS studies in a mouse model of bleomycin-induced pulmonary fibrosis confirmed consistent downregulation of the miR-92a-3p hotspot, suggesting that miR-92a-3p is a key driver of IPF in mouse models. Collectively, data from IPF patients and mouse models indicate that miR-92a-3p isoforms may be potential therapeutic targets for the control of pulmonary fibrosis.

[0170] MicroRNA biogenesis begins with pri-miRNA transcription by RNA polymerase II, which is processed in the nucleus by Drosha and assisted by DGCR. 8 Although Drosha cleavage is consistent, changes in pri-miRNA structure, such as stem length or loop size, can affect the efficiency and accuracy of cleavage and therefore the biological properties of the sRNA. 42Compared to the canonical sequence, sRNA isoforms can be classified according to variations in length, sequence, or both. 17 To date, although sRNA isoforms have been recognized, their biological functions have been overlooked, thus leading to many conflicting conclusions in the sRNA field. 19 .

[0171] miR-92a-3p, located in the miR-17 / 92 cluster, has been characterized in various diseases, including cancer, coronary artery disease, and pulmonary fibrosis, as an established profibrotic factor. 43 However, due to the diversity of sRNA isoforms, the mechanism of action remains elusive. Therefore, we hypothesized that different miR-92a-3p isoforms exert differential functions, potentially affecting IPF disease progression. To test our hypothesis, we ranked and selected 22 human miR-92a-3p isoforms and tested their antifibrotic potential using in vitro and ex vivo systems. Given the heterogeneity of IPF, we measured the function of miR-92a-3p isoforms in IPF fibroblasts collected from different donors. Consistent with our hypothesis, we observed that different isoforms from the same miR-92-3p family possess varying degrees of antifibrotic activity. The mimetics identified in the in vitro screen were further tested in fibrotic human precision-cut lung slices (hPCLS), an established ex vivo model system. 44 A key advantage of the hPCLS model is that the structural and functional heterogeneity of the organ is preserved, in part due to the presence of cell-matrix and cell-cell interactions. 45 .

[0172] Our results show that the miR-92a-3p isoform mimics (Oligo-006, GLB1589), which showed the strongest inhibition of proliferation and collagen accumulation, also target multiple genes involved in the regulation of WNT / TGF-β / FAK cycling. Importantly, the ITGAV ITGA5, COL5A1, FBN1, and FDZ4 genes in these pathways have been demonstrated to be physically targeted by the isoforms, four of which are upregulated in IPF (FBN1, COL5A1, ITGAV, FZD4). This demonstrates the antifibrotic efficacy of the mimics through multiple pharmacological mechanisms of action.

[0173] Although sRNAs are conserved across mice and humans, individual isoforms may not be conserved, and inherent genetic differences between humans and mice may limit the targeting efficacy of human miRNA sequences in preclinical studies. 46 Therefore, mouse surrogate siRNA sequences are commonly used in siRNA preclinical drug discovery. 47 sRNA sequencing was performed in a bleomycin-induced pulmonary fibrosis mouse model at 3, 5, 7, 14, and 21 days after bleomycin administration. 48 Consistent with the human dataset, the miR-92a-3p isoform, which maps to chromosome 13, was downregulated in a bleomycin-induced mouse model of pulmonary fibrosis. Six miR-92a-3p isoforms with TRPM >100 and decreased expression after bleomycin treatment on day 7 (the onset of fibrosis) were identified for in vivo testing. Most importantly, delivery of mouse miR-92a-3p mimics encapsulated in LNPs via the oropharyngeal (OP) route to the lung rescued disease-related phenotypes in a bleomycin-induced IPF mouse model, demonstrating the pivotal role of miR-92a-3p in IPF treatment.

[0174] In conclusion, our study provides evidence for the discovery of disease-induced biomarkers and therapeutic agents using patient biofluids. Using in vitro, ex vivo, and in vivo models, we confirmed the role of the miR-92a-3p isoform in the prognosis and treatment of IPF. Furthermore, computational analysis of 24 different small RNA sequencing datasets also identified distinct miR-92a-3p isoform hotspots in 14 other disease states (NASH, heart failure, cardiomyopathy, Huntington's disease, Parkinson's disease, sCID, ALS, Alzheimer's disease, Crohn's disease, ulcerative colitis, psoriasis, Pompe disease, breast cancer, and preeclampsia). While previous studies have demonstrated individual pathways involved in MOA, the role of the miR-92a-3p isoform in regulating the WNT / TGFβ / ITGA / FAK regulatory axis is novel and surprising.

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Claims

1. 1. A method for risk stratification of a subject diagnosed with idiopathic pulmonary fibrosis (IPF), comprising: providing a blood, serum, or plasma sample from said subject; generating an expression profile of at least five small RNAs listed in Table 2; and determining a risk of death as a function of said expression profile, thereby risk stratifying said subject.

2. 10. The method of claim 1, further comprising determining the subject's GAP stage and determining a risk of death based on the expression profile and the GAP stage.

3. 3. The method of claim 2, wherein the GAP stage comprises three thresholds based on the probability of death within three years.

4. The method of claims 1 to 3, wherein the subjects are stratified into three groups based on risk of death.

5. The method of claims 1 to 4, wherein said subjects with high-risk stratification are selected for surgical or pharmaceutical intervention.

6. 6. The method of claim 5, wherein the surgical intervention is a lung transplant.

7. The method of any one of claims 1 to 6, wherein the expression profile comprises the expression levels of at least 10 sRNAs from Table 2.

8. 8. The method of claim 7, wherein the expression profile comprises expression levels of at least 20 sRNAs from Table 2.

9. 8. The method of claim 7, wherein the expression profile comprises expression levels of at least 30 sRNAs from Table 2.

10. 8. The method of claim 7, wherein the expression profile comprises expression levels of at least 40 sRNAs from Table 2.

11. 8. The method of claim 7, wherein the expression profile comprises, consists essentially of, or consists of expression levels of sRNAs from Table 2.

12. The method of any one of claims 1 to 11, wherein the expression profile is determined by a quantitative PCR assay.

13. 13. The method of claim 12, wherein the sRNA is reverse transcribed using a stem-loop RT primer.

14. 14. The method of claim 13, wherein the reverse transcription product is amplified using a forward primer and a reverse primer.

15. The method of any one of claims 12 to 14, wherein the quantitative PCR assay uses a fluorescent dye or a fluorescently labeled probe.

16. 16. The method of claim 15, wherein the quantitative PCR assay uses a fluorescently labeled probe, the probe further comprising a quencher moiety.

17. The method of any one of claims 1 to 11, wherein the expression profile is determined using a hybridization assay.

18. 18. The method of claim 17, wherein the hybridization assay uses a hybridization array comprising sRNA-specific probes.

19. 12. The method of any one of claims 1 to 11, wherein the expression profile is determined by nucleic acid sequencing and the sRNA is identified in the sample by a process comprising trimming of 5' and 3' sequencing adaptors from the sRNA sequence.

20. 20. The method of claim 19, wherein RNA from multiple samples is pooled to determine the expression profile, and sequences from different samples contain distinguishing sample tag sequences.

21. The method of any one of claims 1 to 20, wherein the expression profile further comprises the expression levels of one or more expression normalization controls.

22. 22. The method of any one of claims 1 to 21, wherein the subject is risk stratified using a risk score calculated from Equation 1.

23. 23. The method of any one of claims 1 to 22, wherein the method is repeated at least once a year, or at least once every six months, or at least once every two months.

24. 1. A kit for assessing a sample for idiopathic pulmonary fibrosis (IPF), comprising: The kit comprises sRNA-specific probes and / or primers configured to detect multiple sRNAs listed in Table 2 (SEQ ID NOs: 1-44).

25. 25. The kit of claim 24, comprising sRNA-specific probes and / or primers configured to detect at least 10 sRNAs listed in Table 2 (SEQ ID NOs: 1-44), wherein the probes and / or primers are listed in Table 3.

26. 25. The kit of claim 24, comprising sRNA-specific probes and / or primers configured to detect at least 20 sRNAs listed in Table 2 (SEQ ID NOs: 1-44), wherein the probes and / or primers are listed in Table 3.

27. 25. The kit of claim 24, comprising sRNA-specific probes and / or primers configured to detect at least 30 sRNAs listed in Table 2 (SEQ ID NOs: 1-44), wherein the probes and / or primers are listed in Table 3.

28. 25. The kit of claim 24, comprising sRNA-specific probes and / or primers configured to detect at least 40 sRNAs listed in Table 2 (SEQ ID NOs: 1-44), wherein the probes and / or primers are listed in Table 3.

29. 25. The kit of claim 24, comprising sRNA-specific probes and / or primers configured to detect at least 50 sRNAs listed in Table 2 (SEQ ID NOs: 1-44), wherein the probes and / or primers are listed in Table 3.

30. 30. The kit of any one of claims 24 to 29, comprising an sRNA-specific stem-loop RT primer, optionally from Table 3.

31. 31. The kit of any one of claims 24 to 30, comprising a forward primer pair and a reverse primer pair for amplifying sRNA reverse transcription products, optionally as shown in Table 3.

32. 32. The kit of any one of claims 24 to 31, comprising an sRNA-specific probe for detecting the amplicon, optionally one of those listed in Table 3.

33. 33. The kit of claim 32, wherein the sRNA-specific probe is a fluorescently labeled probe.

34. 34. The kit of claim 33, wherein the probe further comprises a quencher moiety.

35. The kit of any one of claims 24 to 34, comprising an array of sRNA-specific hybridization probes.

36. A small interfering RNA (siRNA) comprising an antisense strand and a sense strand, wherein the antisense strand comprises at least 12 consecutive nucleotides of a sequence in Table 2.

37. 37. The siRNA of claim 36, wherein the siRNA comprises a chemical modification.

38. 38. The siRNA of claim 37, wherein the chemical modification increases stability, reduces endonuclease degradation, reduces immunogenicity, and / or reduces Toll-like receptor recognition.

39. The siRNA of claim 37 or 38, wherein the chemical modification is a nucleobase modification, a backbone modification, and / or a sugar modification.

40. 40. The siRNA of claim 39, wherein the nucleobase modification inhibits RNA recognition by a Toll-like receptor (TLR).

41. 41. The siRNA of claim 39 or 40, wherein the backbone modification is selected from phosphorothioate, phosphorodithioate, methylphosphonate, and methoxypropylphosphonate.

42. 42. The siRNA of any one of claims 39 to 41, wherein the sugar modification is selected from 2'-methoxy (2'-OMe), 2'-O-methoxyethyl (2'-O-MOE), 2'-fluoro (2'-F), constrained ethyl (cEt), bridged nucleic acid (BNA), and locked nucleic acid (LNA).

43. 43. The siRNA of any one of claims 36 to 42, wherein the sense and antisense strands each have a length of about 12 to about 40 nucleotides.

44. The siRNA of any one of claims 36 to 43, wherein the siRNA comprises two substantially complementary RNA strands having a duplex length of about 12 to about 40 base pairs.

45. The siRNA of any one of claims 36 to 44, wherein the siRNA comprises one or two 3'-end overhangs.

46. 46. ​​The siRNA of claim 45, wherein the siRNA comprises a sense strand overhang and an antisense strand overhang.

47. 47. The siRNA of claim 45 or 46, wherein the overhang is a deoxythymidine (dT-dT) overhang.

48. The siRNA of claim 47, wherein the siRNA is in a 19+2 format.

49. The siRNA of claim 44 or 45, wherein the siRNA is an asymmetric siRNA (asiRNA) having a blunt end corresponding to the 5' end of the antisense strand.

50. 50. The siRNA of claim 49, wherein the asiRNA comprises an antisense strand of 19 to 24 nucleotides and a sense strand of 15 to 21 nucleotides.

51. The siRNA of any one of claims 36 to 50, wherein the asiRNA has an antisense strand having a nucleotide at the 5' end that is not base-paired with the sense strand.

52. The siRNA of any one of claims 36 to 51, wherein the composition is formulated for parenteral delivery or for local delivery to the lung.

53. 53. The siRNA of claim 52, wherein the siRNA is encapsulated in a lipid nanoparticle, a polymer nanoparticle, or a liposome.

54. 54. The siRNA of claim 52 or 53, wherein the siRNA is formulated to be delivered by inhalation, optionally in aerosol form.

55. An antisense oligonucleotide that is at least 10 linked nucleotides in length and has a sequence complementary to a nucleotide sequence selected from Table 2 (SEQ ID NOS: 1-44).

56. 56. The antisense oligonucleotide of claim 55, which is completely complementary to a nucleotide sequence selected from Table 2 (SEQ ID NOs: 1-44).

57. 57. The antisense oligonucleotide of any one of claims 55 or 56, which is from about 12 to about 40 nucleotides in length.

58. 58. The antisense oligonucleotide of claim 57, which is 12, 13, 14, 15, 16, 17, 18, 19, or 20 nucleotides in length.

59. The antisense oligonucleotide according to any one of claims 55 to 58, consisting of a nucleotide sequence complementary to a sequence selected from SEQ ID NOs: 1 to 44.

60. 60. The antisense oligonucleotide of any one of claims 55 to 59, having a contiguous sequence of at least 10 DNA nucleotides sufficient to recruit RNase H.

61. 61. The antisense oligonucleotide of claim 60, wherein the oligonucleotide is a gapmer having a 5' segment, a 3' segment, and an intermediate segment that recruits RNase H, wherein each of the 5' and 3' segments is 2 to 6 nucleotides in length or 2 to 4 nucleotides in length, and wherein the 5' and 3' segments do not contain any DNA nucleotides.

62. 62. The antisense oligonucleotide of claim 61, wherein one or more nucleotides of the 5' segment and the 3' segment comprise a 2'-O substituent, and optionally, all of the nucleotides of the 5' segment and the 3' segment comprise a 2'-O substituent.

63. 63. The antisense oligonucleotide of any one of claims 55 to 62, comprising one or more 2' chemical modifications independently selected from 2'-fluoro, 2'-methyl, and 2'-ethyl.

64. 64. The antisense oligonucleotide of any one of claims 55 to 63, comprising one or more 2'-O substituents selected from 2'-O methyl, 2'-O ethyl, 2'-O methoxyethyl (MOE), and bridged nucleotides having a 2' to 4' bridge.

65. 65. The antisense oligonucleotide of claim 64, wherein the bridged nucleotide comprises a methylene bridge (LNA) or a constrained ethyl bridge (cEt).

66. 66. The antisense oligonucleotide of any one of claims 55 to 65, having a modified backbone.

67. 67. The antisense oligonucleotide of claim 66, comprising one or more phosphorothioate or phosphorodithioate nucleotides.

68. 68. The antisense oligonucleotide of claim 67, which is fully phosphorothioate or phosphorodithioate linked.

69. The antisense oligonucleotide of any one of claims 55 to 68, wherein the cytidine nucleobase is 5-methylcytidine.

70. 60. The antisense oligonucleotide of any one of claims 55 to 59, having a morpholino or thiomorpholino backbone.

71. The antisense oligonucleotide of any one of claims 55 to 59, which has a PNA backbone.

72. 72. The antisense oligonucleotide of any one of claims 55 to 71, wherein the Tm of the oligonucleotide hybridized to a target sequence is at least about 35°C.

73. 73. The antisense oligonucleotide of claim 72, wherein the Tm of the oligonucleotide hybridized to the target sequence is at least about 40°C, or at least about 45°C, or at least about 50°C.

74. 74. The antisense oligonucleotide of claim 72 or 73, wherein the Tm of the oligonucleotide hybridized to the target sequence is from about 35°C to about 60°C, or from about 40°C to about 60°C, or from about 50°C to about 60°C.

75. The antisense oligonucleotide of any one of claims 55 to 74, wherein the composition further comprises a targeting moiety or a cell-penetrating moiety.

76. 76. The antisense oligonucleotide of any one of claims 55 to 75, formulated for parenteral delivery or for local delivery to the lung.

77. 77. The antisense oligonucleotide of claim 76, which is encapsulated in a lipid nanoparticle, a polymer nanoparticle, or a liposome.

78. 78. The antisense oligonucleotide of claim 76 or 77, formulated for delivery by inhalation, optionally in aerosol form.

79. A pharmaceutical composition comprising an effective amount of the siRNA or antisense oligonucleotide of any one of claims 36 to 78, and one or more pharmaceutically acceptable excipients or carriers.

80. 80. The pharmaceutical composition of claim 79, wherein the siRNA or the antisense oligonucleotide is encapsulated in a liposome, polymeric nanoparticle, or lipid nanoparticle.

81. 81. A method for treating a subject with idiopathic pulmonary fibrosis, comprising administering an effective amount of the pharmaceutical composition of claim 79 or 80.

82. 1. A method for assessing idiopathic pulmonary fibrosis in a subject, comprising: providing a blood, serum, or plasma sample from said subject; The method comprises generating an expression profile of at least five small RNAs listed in Table 6, and identifying whether the subject has an elevated risk of death based on the expression profile.

83. 83. The method of claim 82, wherein the subject is identified as having a subtype of IPF that correlates with a high risk of mortality.

84. 84. The method of claim 83, wherein the subject is selected for surgical or pharmaceutical intervention.

85. 85. The method of claim 84, wherein the surgical intervention is a lung transplant.

86. 86. The method of any one of claims 82 to 85, wherein the expression profile comprises the expression levels of at least 10 sRNAs from Table 6.

87. 87. The method of claim 86, wherein the expression profile comprises expression levels of at least 20 sRNAs from Table 6.

88. 87. The method of claim 86, wherein the expression profile comprises expression levels of at least 30 sRNAs from Table 6.

89. 87. The method of claim 86, wherein the expression profile comprises expression levels of at least 40 sRNAs from Table 6.

90. 87. The method of claim 86, wherein said expression profile comprises, consists essentially of, or consists of expression levels of sRNAs from Table 6.

91. 91. The method of any one of claims 82 to 90, wherein the expression profile is determined by a quantitative PCR assay.

92. 92. The method of claim 91, wherein the sRNA is reverse transcribed using a stem-loop RT primer.

93. 93. The method of claim 92, wherein the reverse transcription product is amplified using a forward primer and a reverse primer.

94. 94. The method of any one of claims 91 to 93, wherein the quantitative PCR assay uses a fluorescent dye or a fluorescently labeled probe.

95. 95. The method of claim 94, wherein the quantitative PCR assay uses a fluorescently labeled probe, the probe further comprising a quencher moiety.

96. 91. The method of any one of claims 82 to 90, wherein the expression profile is determined using a hybridization assay.

97. 97. The method of claim 96, wherein the hybridization assay uses a hybridization array comprising sRNA-specific probes.

98. 91. The method of any one of claims 82 to 90, wherein the expression profile is determined by nucleic acid sequencing and the sRNA is identified in the sample by a process comprising trimming of 5' and 3' sequencing adaptors from the sRNA sequence.

99. 99. The method of claim 98, wherein RNA from multiple samples is pooled to determine the expression profile, and sequences from different samples contain distinguishing sample tag sequences.

100. 100. The method of any one of claims 82 to 99, wherein said expression profile further comprises said expression levels of one or more expression normalization controls.

101. 1. A kit for assessing a sample for a subtype of idiopathic pulmonary fibrosis (IPF), comprising: The kit comprises sRNA-specific probes and / or primers configured to detect multiple sRNAs listed in Table 6 (SEQ ID NOs: 45-115).

102. 102. The kit of claim 101, comprising sRNA-specific probes and / or primers configured to detect at least 10 sRNAs listed in Table 6 (SEQ ID NOS: 45-115), wherein the probes and / or primers are listed in Table 7.

103. 102. The kit of claim 101, comprising sRNA-specific probes and / or primers configured to detect at least 20 sRNAs listed in Table 6 (SEQ ID NOS: 45-115), wherein the probes and / or primers are listed in Table 7.

104. 102. The kit of claim 101, comprising sRNA-specific probes and / or primers configured to detect at least 30 sRNAs listed in Table 6 (SEQ ID NOS: 45-115), wherein the probes and / or primers are listed in Table 7.

105. 102. The kit of claim 101, comprising sRNA-specific probes and / or primers configured to detect at least 40 sRNAs listed in Table 6 (SEQ ID NOS: 45-115), wherein the probes and / or primers are listed in Table 7.

106. 102. The kit of claim 101, comprising sRNA-specific probes and / or primers configured to detect at least 50 sRNAs listed in Table 6 (SEQ ID NOS: 45-115), wherein the probes and / or primers are listed in Table 7.

107. 107. The kit of any one of claims 101 to 106, comprising an sRNA-specific stem-loop RT primer, optionally from Table 7.

108. 108. The kit of any one of claims 101 to 107, comprising a forward primer pair and a reverse primer pair for amplifying sRNA reverse transcription products, optionally as shown in Table 7.

109. 109. The kit of any one of claims 101 to 108, comprising an sRNA-specific probe for detecting the amplicon, optionally one of those listed in Table 7.

110. 110. The kit of claim 109, wherein the sRNA-specific probe is a fluorescently labeled probe.

111. 111. The kit of claim 110, wherein the probe further comprises a quencher moiety.

112. 107. The kit of any one of claims 101 to 106, comprising an array of sRNA-specific hybridization probes.

113. A small interfering RNA (siRNA) comprising an antisense strand and a sense strand, wherein the antisense strand comprises at least 12 contiguous nucleotides of a sequence in Table 6.

114. The siRNA of claim 113, wherein the siRNA is a mimic of miR-92a or an isoform thereof.

115. The siRNA of claim 113, wherein the antisense strand comprises the nucleotide sequence of SEQ ID NO: 732, and the sense strand is optionally SEQ ID NO:

733.

116. The siRNA of any one of claims 113 to 115, wherein the siRNA comprises a chemical modification.

117. 117. The siRNA of any of claims 116, wherein the chemical modification increases stability, reduces endonuclease degradation, reduces immunogenicity, and / or reduces Toll-like receptor recognition.

118. The siRNA of claim 117, wherein the chemical modification is a nucleobase modification, a backbone modification, and / or a sugar modification.

119. The siRNA of claim 118, wherein the nucleobase modification inhibits RNA recognition by a Toll-like receptor (TLR).

120. 120. The siRNA of any one of claims 118 or 119, wherein the backbone modification is selected from phosphorothioate, phosphorodithioate, methylphosphonate, and methoxypropylphosphonate.

121. 121. The siRNA of any one of claims 118 to 120, wherein the sugar modification is selected from 2'-methoxy (2'-OMe), 2'-O-methoxyethyl (2'-O-MOE), 2'-fluoro (2'-F), constrained ethyl (cEt), bridged nucleic acid (BNA), and locked nucleic acid (LNA).

122. The siRNA of any one of claims 113 to 121, wherein the siRNA comprises a sense and an antisense strand, each having a length of about 12 to about 40 nucleotides.

123. The siRNA of any one of claims 113 to 122, wherein the siRNA comprises two substantially complementary RNA strands having a duplex length of about 12 to about 40 base pairs.

124. The siRNA of any one of claims 113 to 123, wherein the siRNA comprises one or two 3'-end overhangs.

125. The siRNA of claim 124, wherein the siRNA comprises a sense strand overhang and an antisense strand overhang.

126. 126. The siRNA of claim 124 or 125, wherein the overhang is a deoxythymidine (dT-dT) overhang.

127. The siRNA of any one of claims 113 to 126, wherein the siRNA is in a 19+2 format.

128. The siRNA of any one of claims 113 to 124, wherein the siRNA is an asymmetric siRNA (asiRNA) having a blunt end corresponding to the 5' end of the antisense strand.

129. The siRNA of claim 128, wherein the asiRNA comprises an antisense strand of 19 to 24 nucleotides and a sense strand of 15 to 21 nucleotides.

130. The siRNA of any one of claims 113 to 129, wherein the asiRNA has an antisense strand having a nucleotide at the 5' end that is not base-paired with the sense strand.

131. The siRNA of any one of claims 113 to 130, wherein the siRNA is formulated for parenteral delivery or localized delivery to the lung.

132. 132. The siRNA of claim 131, wherein the siRNA is encapsulated in a lipid nanoparticle, a polymer nanoparticle, or a liposome.

133. 133. The siRNA of claim 131 or 132, wherein the siRNA is delivered by inhalation, optionally in aerosol form.

134. An antisense oligonucleotide that is at least 10 linked nucleotides in length and has a sequence complementary to a nucleotide sequence selected from Table 6 (SEQ ID NOS: 45-115).

135. 135. The antisense oligonucleotide of claim 134, which is perfectly complementary to a nucleotide sequence selected from Table 6 (SEQ ID NOs: 45-115).

136. 136. The antisense oligonucleotide of any one of claims 134 or 135, which is from about 12 to about 40 nucleotides in length.

137. 137. The antisense oligonucleotide of claim 136, which is 12, 13, 14, 15, 16, 17, 18, 19, or 20 nucleotides in length.

138. The antisense oligonucleotide according to any one of claims 134 to 137, consisting of a nucleotide sequence complementary to a sequence selected from SEQ ID NOs: 45 to 115.

139. The antisense oligonucleotide of any one of claims 134 to 138, having a contiguous sequence of at least 10 DNA nucleotides sufficient to recruit RNase H.

140. 140. The antisense oligonucleotide of claim 139, wherein the oligonucleotide is a gapmer having a 5' segment, a 3' segment, and an intermediate segment that recruits RNase H, wherein each of the 5' and 3' segments is 2 to 6 nucleotides in length or 2 to 4 nucleotides in length, and wherein the 5' and 3' segments do not contain any DNA nucleotides.

141. 141. The antisense oligonucleotide of claim 140, wherein one or more nucleotides of the 5' segment and the 3' segment comprise a 2'-O substituent, and optionally, all of the nucleotides of the 5' segment and the 3' segment comprise a 2'-O substituent.

142. 142. The antisense oligonucleotide of any one of claims 134 to 141, comprising one or more 2' chemical modifications independently selected from 2'-fluoro, 2'-methyl, and 2'-ethyl.

143. 143. The antisense oligonucleotide of any one of claims 134 to 142, comprising one or more 2'-O substituents selected from 2'-O methyl, 2'-O ethyl, 2'-O methoxyethyl (MOE), and bridged nucleotides having a 2' to 4' bridge.

144. 144. The antisense oligonucleotide of claim 143, wherein the bridged nucleotide has a methylene bridge (LNA) or a constrained ethyl bridge (cEt).

145. 145. The antisense oligonucleotide of any one of claims 134 to 144, having a modified backbone.

146. 146. The antisense oligonucleotide of claim 145, comprising one or more phosphorothioate or phosphorodithioate nucleotides.

147. 147. The antisense oligonucleotide of claim 146, which is fully phosphorothioate or phosphorodithioate linked.

148. The antisense oligonucleotide of any one of claims 134 to 147, wherein the cytidine nucleobase is 5-methylcytidine.

149. The antisense oligonucleotide of any one of claims 134 to 138, having a morpholino or thiomorpholino backbone.

150. The antisense oligonucleotide of any one of claims 134 to 138, having a PNA backbone.

151. The antisense oligonucleotide of any one of claims 134 to 150, wherein the Tm of the oligonucleotide hybridized to a target sequence is at least about 35°C.

152. The antisense oligonucleotide of claim 151, wherein the Tm of the oligonucleotide hybridized to the target sequence is at least about 40°C, or at least about 45°C, or at least about 50°C.

153. The antisense oligonucleotide of claim 151, wherein the Tm of the oligonucleotide hybridized to a target sequence is from about 35°C to about 60°C, or from about 40°C to about 60°C, or from about 50°C to about 60°C.

154. The antisense oligonucleotide of any one of claims 134 to 153, wherein the composition further comprises a targeting moiety or a cell-penetrating moiety.

155. The antisense oligonucleotide of any one of claims 134 to 154, wherein the composition is formulated for parenteral delivery or for local delivery to the lung.

156. 156. The antisense oligonucleotide of claim 155, which is encapsulated in a lipid nanoparticle, a polymer nanoparticle, or a liposome.

157. The antisense oligonucleotide of claim 155 or 156, wherein the siRNA is formulated for delivery by inhalation, optionally in aerosol form.

158. A pharmaceutical composition comprising an effective amount of the siRNA or antisense oligonucleotide of any one of claims 113 to 157, and one or more pharmaceutically acceptable excipients or carriers.

159. The pharmaceutical composition of claim 158, wherein the siRNA or the antisense oligonucleotide is encapsulated in a liposome, a polymeric nanoparticle, or a lipid nanoparticle.

160. 160. A method for treating a subject with idiopathic pulmonary fibrosis, comprising administering an effective amount of the pharmaceutical composition of claim 158 or 159.

161. 161. The method of claim 160, wherein the siRNA is a mimic of miR-92a or an isoform thereof.

162. 161. The method of claim 160, wherein the mimic is an siRNA, and the siRNA optionally comprises an antisense sequence of SEQ ID NO: 732, and optionally a sense strand of SEQ ID NO:

733.

163. siRNA comprising an antisense sequence or strand corresponding to an isoform of miR-92a-3p.

164. The siRNA of claim 163, wherein the isoform is listed in Table 10.

165. The siRNA of claim 164, wherein the isoform is SEQ ID NO:

739.

166. The siRNA of any one of claims 163 to 165, comprising an antisense strand and a sense strand.

167. The siRNA of claim 166, wherein the antisense strand and / or the sense strand has a 3' overhang, which is optionally dTdT.

168. 168. The siRNA of claim 167, wherein the antisense strand is selected from Table 10.

169. 169. The siRNA of claim 168, wherein the sense strand is selected from Table 10.

170. The siRNA of any one of claims 163 to 169, wherein the siRNA is encapsulated in a lipid nanoparticle or a polymer nanoparticle.

171. A method for treating an inflammatory or fibrotic disorder comprising administering a compound that mimics miR-92a-3p or an isoform thereof.

172. 172. The method of claim 171, wherein the compound is an siRNA.

173. The method of claim 172, wherein the compound is an siRNA according to any one of claims 163 to 170.

174. 174. The method of any one of claims 171 to 173, wherein the disorder is characterized by dysregulation of the WNT / TGF-b / ITGA / FAK regulatory axis.

175. 175. The method of any one of claims 171 to 174, wherein the disorder is IPF.

176. 175. The method of any one of claims 171 to 174, wherein the disorder is selected from non-alcoholic steatohepatitis (NASH), heart failure, cardiomyopathy, Crohn's disease, ulcerative colitis, Alzheimer's disease, Parkinson's disease, Huntington's disease, amyotrophic lateral sclerosis (ALS), preeclampsia, psoriasis, Pompe's disease, sCID, breast cancer, and other cancers.

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