Compositions and methods for targeting FXR1 for the treatment of diseases and disorders associated with FXR1 expression

Abstract

Disclosed are compositions for RNAi of fragile X-related protein 1 (FXR1), nanoparticles comprising the same, pharmaceutical compositions comprising the same and method of treating diseases and disorders associated with FXR1 expression in a subject in need thereof. The methods may comprise modified nucleotides, e.g., locked nucleic acids (LNAs). The methods may comprise administering a therapeutically effective amount of the disclosed compositions to a subject in need thereof, e.g., a subject suffering from a disease or disorder associated with FXR1 expression.

Description

Atty. Dkt. No. 650053.01226COMPOSITIONS TARGETING FXR1 AND METHODS OF USING THE SAME FOR THE TREATMENT OF DISEASES AND DISORDERS ASSOCIATED WITHFXR1 EXPRESSIONCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] The present application claims priority to U.S. Provisional Patent Application No. 63 / 683,329 that was filed August 15, 2024. the entire contents of which is hereby incorporated by reference.STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

[0002] Not applicable.SEQUENCE LISTING

[0003] A Sequence Listing accompanies this application and is submitted as an xml file of the sequence listing named “650053_01226.xmf?which is 39.962 bytes in size and was created on July 23, 2025. The sequence listing is electronically submitted via Patent Center and is incorporated by reference herein in its entirety7.BACKGROUND

[0004] Ovarian cancer is the second most common gynecological cancer in the United States and causes more deaths than any other cancer of the female reproductive system. Accordingly, novel therapies to treat ovarian cancer, and other cancers are required.SUMMARY OF THE INVENTION

[0005] In an aspect of the current disclosure, dsRNAs are provided. In some embodiments, the dsRNAs comprise: a polynucleotide selected from one of SEQ ID NOs: 1-10, or a sequence with at least 95% identity to one of SEQ ID NOs: 1-10. and wherein the dsRNA comprises one or more modified nucleic acids. In some embodiments, the polynucleotide is one of SEQ ID NOs: 3-6, or a sequence with at least 95% identity to one of SEQ ID NOs: 3-6. In some embodiments, the polynucleotide is SEQ ID NO: 3 or 4, or a sequence with at least 95% identity to SEQ ID NO: 3 or 4. In some embodiments, the polynucleotide is SEQ ID NO: 5 or 6, or a sequence with at least 95% identity to SEQ ID NO: 5 or 6. In some embodiments, the polynucleotide is SEQ ID NO: 3 or 4. In some embodiments, the polynucleotide is SEQ ID NO: 5 or 6. In some embodiments, the one or more modified nucleic acids are one or more 2’-O-methyl nucleotides, one or more 2’- fluoro nucleotides, one or more 2-methoxyethyl nucleotides. In some embodiments, the one orAtty. Dkt. No. 650053.01226 more modified nucleic acids comprise a phosphorothioate modification. In some embodiments, the one or more modified nucleotides comprise a locked nucleic acid (LNA). In some embodiments, the polynucleotide is selected from SEQ ID NOs: 21 -24, or a sequence with at least 95% identity to SEQ ID NOs: 21-24. In some embodiments, the polynucleotide is SEQ ID NO: 23 or 24. In some embodiments, the dsRNA comprises at least one nucleotide overhang, optionally, wherein the nucleotide overhang is a deoxynucleotide overhang.

[0006] In another aspect of the current disclosure, pharmaceutical compositions are provided. In some embodiments, the pharmaceutical compositions comprise: a polynucleotide selected from one of SEQ ID NOs: 1-10, or a sequence with at least 95% identity to one of SEQ ID NOs: 1-10, and wherein the dsRNA comprises one or more modified nucleic acids. In some embodiments, the polynucleotide is one of SEQ ID NOs: 3-6, or a sequence with at least 95% identity to one of SEQ ID NOs: 3-6. In some embodiments, the polynucleotide is SEQ ID NO: 3 or 4, or a sequence with at least 95% identity to SEQ ID NO: 3 or 4. In some embodiments, the polynucleotide is SEQ ID NO: 5 or 6, or a sequence with at least 95% identity to SEQ ID NO: 5 or 6. In some embodiments, the polynucleotide is SEQ ID NO: 3 or 4. In some embodiments, the polynucleotide is SEQ ID NO: 5 or 6. In some embodiments, the one or more modified nucleic acids are one or more 2’-O- methyl nucleotides, one or more 2’-fluoro nucleotides, one or more 2-methoxyethyl nucleotides. In some embodiments, the one or more modified nucleic acids comprise a phosphorothioate modification. In some embodiments, the one or more modified nucleotides comprise a locked nucleic acid (LNA). In some embodiments, the polynucleotide is selected from SEQ ID NOs: 21- 24, or a sequence with at least 95% identity to SEQ ID NOs: 21-24. In some embodiments, the polynucleotide is SEQ ID NO: 23 or 24. In some embodiments, the dsRNA comprises at least one nucleotide overhang, optionally, wherein the nucleotide overhang is a deoxynucleotide overhang.

[0007] In another aspect of the current disclosure, nanoparticles are provided. In some embodiments, the nanoparticles comprise a dsRNA comprising: a polynucleotide selected from one of SEQ ID NOs: 1-10, or a sequence with at least 95% identity to one of SEQ ID NOs: 1-10, and wherein the dsRNA comprises one or more modified nucleic acids. In some embodiments, the polynucleotide is one of SEQ ID NOs: 3-6, or a sequence with at least 95% identity to one of SEQ ID NOs: 3-6. In some embodiments, the polynucleotide is SEQ ID NO: 3 or 4, or a sequence with at least 95% identity to SEQ ID NO: 3 or 4. In some embodiments, the polynucleotide is SEQ ID NO: 5 or 6, or a sequence with at least 95% identity7to SEQ ID NO: 5 or 6. In some embodiments, the polynucleotide is SEQ ID NO: 3 or 4. In some embodiments, the polynucleotide is SEQ ID NO: 5 or 6. In some embodiments, the one or more modified nucleic acids are one or more 2’-O-Atty. Dkt. No. 650053.01226 methyl nucleotides, one or more 2’-fluoro nucleotides, one or more 2-methoxyethyl nucleotides. In some embodiments, the one or more modified nucleic acids comprise a phosphorothioate modification. In some embodiments, the one or more modified nucleotides comprise a locked nucleic acid (LNA). In some embodiments, the polynucleotide is selected from SEQ ID NOs: 21- 24, or a sequence with at least 95% identity to SEQ ID NOs: 21-24. In some embodiments, the polynucleotide is SEQ ID NO: 23 or 24. In some embodiments, the dsRNA comprises at least one nucleotide overhang, optionally, wherein the nucleotide overhang is a deoxynucleotide overhang. In some embodiments, the nanoparticle comprises a liposome, polyethylenimine (PEI). In some embodiments, the nanoparticle comprises l,2-di-(9Z-octadecenoyl)-sn-glycero-3-phosphocholine (DOPC).

[0008] In another aspect of the current disclosure, further pharmaceutical compositions are provided. In some embodiments the pharmaceutical compositions comprise a nanoparticle comprising: a polynucleotide selected from one of SEQ ID NOs: 1-10, or a sequence with at least 95% identity to one of SEQ ID NOs: 1-10. and wherein the dsRNA comprises one or more modified nucleic acids. In some embodiments, the polynucleotide is one of SEQ ID NOs: 3-6, or a sequence with at least 95% identity to one of SEQ ID NOs: 3-6. In some embodiments, the polynucleotide is SEQ ID NO: 3 or 4, or a sequence with at least 95% identity to SEQ ID NO: 3 or 4. In some embodiments, the polynucleotide is SEQ ID NO: 5 or 6, or a sequence with at least 95% identity to SEQ ID NO: 5 or 6. In some embodiments, the polynucleotide is SEQ ID NO: 3 or 4. In some embodiments, the polynucleotide is SEQ ID NO: 5 or 6. In some embodiments, the one or more modified nucleic acids are one or more 2’-O-methyl nucleotides, one or more 2’- fluoro nucleotides, one or more 2-methoxyethyl nucleotides. In some embodiments, the one or more modified nucleic acids comprise a phosphorothioate modification. In some embodiments, the one or more modified nucleotides comprise a locked nucleic acid (LNA). In some embodiments, the polynucleotide is selected from SEQ ID NOs: 21-24, or a sequence with at least 95% identity to SEQ ID NOs: 21-24. In some embodiments, the polynucleotide is SEQ ID NO: 23 or 24. In some embodiments, the dsRNA comprises at least one nucleotide overhang, optionally, wherein the nucleotide overhang is a deoxynucleotide overhang. In some embodiments, the nanoparticle comprises a liposome. In some embodiments, the nanoparticle comprises l,2-di-(9Z- octadecenoyl)-sn-glycero-3-phosphocholine (DOPC).

[0009] In another aspect of the current disclosure, methods of treating a disease or disorder associated with FXR1 expression in a subject in need thereof are provided. In some embodiments, the methods comprise: administering a pharmaceutical composition comprising a polynucleotideAtty. Dkt. No. 650053.01226 selected from one of SEQ ID NOs: 1-10, or a sequence with at least 95% identity to one of SEQ ID NOs: 1-10. and wherein the dsRNA comprises one or more modified nucleic acids to the subj ect to treat the disease or disorder associated with FXR1 expression in the subject. In some embodiments, the polynucleotide is one of SEQ ID NOs: 3-6, or a sequence with at least 95% identity to one of SEQ ID NOs: 3-6. In some embodiments, the polynucleotide is SEQ ID NO: 3 or 4, or a sequence with at least 95% identity to SEQ ID NO: 3 or 4. In some embodiments, the polynucleotide is SEQ ID NO: 5 or 6, or a sequence with at least 95% identity to SEQ ID NO: 5 or 6. In some embodiments, the polynucleotide is SEQ ID NO: 3 or 4. In some embodiments, the polynucleotide is SEQ ID NO: 5 or 6. In some embodiments, the one or more modified nucleic acids are one or more 2'-O-methyl nucleotides, one or more 2’-fluoro nucleotides, one or more 2- methoxy ethyl nucleotides. In some embodiments, the one or more modified nucleic acids comprise a phosphorothioate modification. In some embodiments, the one or more modified nucleotides comprise a locked nucleic acid (LNA). In some embodiments, the polynucleotide is selected from SEQ ID NOs: 21-24, or a sequence with at least 95% identity to SEQ ID NOs: 21-24. In some embodiments, the polynucleotide is SEQ ID NO: 23 or 24. In some embodiments, the dsRNA comprises at least one nucleotide overhang, optionally, wherein the nucleotide overhang is a deoxynucleotide overhang. In some embodiments, the disease or disorder associated FXR1 expression is associated with an increase in the copy number of FXR1. In some embodiments, the disease or disorder is a cell proliferative disease or disorder. In some embodiments, the cell proliferative disease or disorder is a cancer. In some embodiments, the cancer is selected from lung cancer, ovarian cancer, cervical cancer, esophageal cancer, or breast cancer. In some embodiments, the cancer is ovarian cancer.

[0010] In some embodiments, the methods comprise administering a pharmaceutical composition comprising a nanoparticle comprising: a polynucleotide selected from one of SEQ ID NOs: 1-10, or a sequence with at least 95% identity to one of SEQ ID NOs: 1-10, and wherein the dsRNA comprises one or more modified nucleic acids to the subject to treat the disease or disorder associated with FXR1 expression in the subject. In some embodiments, the polynucleotide is one of SEQ ID NOs: 3-6, or a sequence with at least 95% identity to one of SEQ ID NOs: 3-6. In some embodiments, the polynucleotide is SEQ ID NO: 3 or 4, or a sequence with at least 95% identity to SEQ ID NO: 3 or 4. In some embodiments, the polynucleotide is SEQ ID NO: 5 or 6, or a sequence with at least 95% identity to SEQ ID NO: 5 or 6. In some embodiments, the polynucleotide is SEQ ID NO: 3 or 4. In some embodiments, the polynucleotide is SEQ ID NO: 5 or 6. In some embodiments, the one or more modified nucleic acids are one or more 2’-O-methylAtty. Dkt. No. 650053.01226 nucleotides, one or more 2’-fluoro nucleotides, one or more 2-methoxy ethyl nucleotides. In some embodiments, the one or more modified nucleic acids comprise a phosphorothioate modification. In some embodiments, the one or more modified nucleotides comprise a locked nucleic acid (LNA). In some embodiments, the polynucleotide is selected from SEQ ID NOs: 21-24, or a sequence with at least 95% identity to SEQ ID NOs: 21-24. In some embodiments, the polynucleotide is SEQ ID NO: 23 or 24. In some embodiments, the dsRNA comprises at least one nucleotide overhang, optionally, wherein the nucleotide overhang is a deoxynucleotide overhang. In some embodiments, the disease or disorder associated FXR1 expression is associated with an increase in the copy number of FXR1. In some embodiments, the disease or disorder is a cell proliferative disease or disorder. In some embodiments, the cell proliferative disease or disorder is a cancer. In some embodiments, the cancer is selected from lung cancer, ovarian cancer, cervical cancer, esophageal cancer, or breast cancer. In some embodiments, the cancer is ovarian cancer.

[0011] In another aspect of the current disclosure, methods of treating ovarian cancer in a subject in need thereof are provided. In some embodiments, the methods comprise: administering a pharmaceutical composition comprising: a polynucleotide selected from one of SEQ ID NOs: 1- 10, or a sequence with at least 95% identity to one of SEQ ID NOs: 1-10, and wherein the dsRNA comprises one or more modified nucleic acids to a subject to treat ovarian cancer in the subject. In some embodiments, the polynucleotide is one of SEQ ID NOs: 3-6, or a sequence with at least 95% identity to one of SEQ ID NOs: 3-6. In some embodiments, the polynucleotide is SEQ ID NO: 3 or 4, or a sequence with at least 95% identity to SEQ ID NO: 3 or 4. In some embodiments, the polynucleotide is SEQ ID NO: 5 or 6, or a sequence with at least 95% identity to SEQ ID NO: 5 or 6. In some embodiments, the polynucleotide is SEQ ID NO: 3 or 4. In some embodiments, the polynucleotide is SEQ ID NO: 5 or 6. In some embodiments, the one or more modified nucleic acids are one or more 2’-O-methyl nucleotides, one or more 2?-fluoro nucleotides, one or more 2- methoxy ethyl nucleotides. In some embodiments, the one or more modified nucleic acids comprise a phosphorothioate modification. In some embodiments, the one or more modified nucleotides comprise a locked nucleic acid (LNA). In some embodiments, the polynucleotide is selected from SEQ ID NOs: 21-24, or a sequence with at least 95% identity to SEQ ID NOs: 21-24. In some embodiments, the polynucleotide is SEQ ID NO: 23 or 24. In some embodiments, the dsRNA comprises at least one nucleotide overhang, optionally, wherein the nucleotide overhang is a deoxynucleotide overhang. In some embodiments, the subject has been diagnosed with an ovarian tumor, and wherein the ovarian tumor expresses FXR1. In some embodiments, the ovarian tumor comprises at least one tumor cells comprising additional genetic copies of FXR1. The method ofAtty. Dkt. No. 650053.01226 claims 20-26. wherein the method causes apoptosis in transformed or cancerous cells of the subject.

[0012] Tn some embodiments, the methods comprise: administering a pharmaceutical composition comprising: a nanoparticle comprising a polynucleotide selected from one of SEQ ID NOs: 1-10, or a sequence with at least 95% identity to one of SEQ ID NOs: 1-10, and wherein the dsRNA comprises one or more modified nucleic acids to a subject to treat ovarian cancer in the subject. In some embodiments, the polynucleotide is one of SEQ ID NOs: 3-6, or a sequence with at least 95% identity to one of SEQ ID NOs: 3-6. In some embodiments, the polynucleotide is SEQ ID NO: 3 or 4, or a sequence with at least 95% identity7to SEQ ID NO: 3 or 4. In some embodiments, the polynucleotide is SEQ ID NO: 5 or 6, or a sequence with at least 95% identity to SEQ ID NO: 5 or 6. In some embodiments, the polynucleotide is SEQ ID NO: 3 or 4. In some embodiments, the polynucleotide is SEQ ID NO: 5 or 6. In some embodiments, the one or more modified nucleic acids are one or more 2’-O-methyl nucleotides, one or more 2’-fluoro nucleotides, one or more 2-methoxy ethyl nucleotides. In some embodiments, the one or more modified nucleic acids comprise a phosphorothioate modification. In some embodiments, the one or more modified nucleotides comprise a locked nucleic acid (LNA). In some embodiments, the polynucleotide is selected from SEQ ID NOs: 21-24, or a sequence with at least 95% identity to SEQ ID NOs: 21-24. In some embodiments, the polynucleotide is SEQ ID NO: 23 or 24. In some embodiments, the dsRNA comprises at least one nucleotide overhang, optionally, wherein the nucleotide overhang is a deoxynucleotide overhang. In some embodiments, the subject has been diagnosed with an ovarian tumor, and wherein the ovarian tumor expresses FXR1. In some embodiments, the ovarian tumor comprises at least one tumor cells comprising additional genetic copies of FXR1. The method of claims 20-26, wherein the method causes apoptosis in transformed or cancerous cells of the subject.BRIEF DESCRIPTION OF THE FIGURES

[0013] FIGs. 1A, IB, 1C, ID, IE, and IF show sequence-specific siRNAs targeting FXR1 suppress ovarian cancer growth. LNA modification enhances knockdown efficiency, tumor penetration, and antitumor activity, a, Ovarian cancer cells were transfected with 5nM siCont and 2.5nM or 5nM siRNAs (seql to 5) for FXR1 for 48h, then cell lysates were prepared, and Western blot was performed to determine the level of FXR1. -actin, loading control, b, Representative images depicting GFP+ OVCAR8 cells co-cultured with NucLight Red-labeled OSE cells for 24h, followed by treatment with siFXRl (seq3) or siCont at 2.5nM, were captured every 6h over 3 days using the IncuCyte live-cell analysis system (left). The graph displays time-Atty. Dkt. No. 650053.01226 dependent cell count curves for GFP+ 0VCAR8 cells andNucLight Red-labeled OSE cells treated with FXR1 siRNAs (right) (n=9). Scale bars, 100pm. c, Chemical structures of locked nucleic acid (LNA) modification. The ribose ring is connected by a methylene bridge between the 2’-0 and 4’- C atoms, "locking" the ribose ring, d, Oligonucleotide sequences of siCont-LNA and siFXRl - LNAs (seq2 and seq3) target FXR1, where red color letters indicates LNA modifications incorporated sites at the 3 ’end of sense and antisense strands of RNAs. Sequences, from top to bottom, are SEQ ID NOs: 36, 37, and 21-24. e, Western blots show the effects of transfection of siFXRl-2, siFXRl-2-LNA, siFXRl-3 or siFXRl-3-LNA on FXR1 levels after 48h transfection in ovarian cancer cells. [Lactin, loading control, f, Kuramochi and OVCAR8 cells were transfected with siCont-LNA, siFXRl-3 or siFXRl-3-LNA. DNA damages were detected by COMET assay, 48hr after transfection of siRNAs. Representative images of comet structures were photographed (left) and quantitative analysis for % of Comet-like structures are presented (right) (n=3). e, Error bars indicate mean ± SEM. Significance was determined by comparing with siCont, Student’s t- test. where *p < 0.05, **p<0.01. ***p<0.001, ****p<0.0001. ns, non-significant

[0014] FIGs. 2A, 2B, 2C, 2D, 2E, 2F, 2G, and 2G show LNA-modified FXRl-siRNA exhibited better cellular uptake and improved stability at intracellular level, a, Representative images of spheroids of OVCAR8 cells, were transfected with siCont-LNA, siFXRl or siFXRl- LNA. Scale bars, 300 pm. b, Representative images of 3D spheroid of GFP-labelled OVCAR8 cells exhibit uptake of Texas red labelled-siFXRl or siFXRl-LNA. Scale bars, 50 pm. c, Ovarian cancer cells were transfected with Texas red labelled native siFXRl or siFXRl-LNA, then images for cellular uptake and intracellular distribution were captured at the indicated time points using confocal microscopy. The nucleus was stained with Hoechst, the lysosome vesicles were labeled by Lysotracker Red, and the siRNA were labeled with Texas red. Scale bar represents 50pm in unzoomed images and 20pm in zoomed images, d, TUNEL staining was performed to determine the apoptotic effect of siFXRl-3-LNA on ovarian cancer cells, 48h after transfection. Apoptotic cells were marked as green fluorescence after TUNEL staining observed under a fluorescent microscope (arrow indicates TUNEL-positive cells) (top). Scale bar represents 50pm. Bar graph shows number of apoptotic cells as determined by TUNEL assay (bottom) (n=3 images) e, Stability of native siFXRL siFXRl -LNA and their JetPEI® nanocomplex was determined by treating with or without RNase I for 30min by agarose gel electrophoresis. siRNA band intensify was quantified to calculate the percentage of siFXRl -LNA remaining compared with native siRNA (n=2). f, Native siFXRl and FXR1-LNA nanocomplex were incubated in 10% human serum (HS) and mouse serum (MS) at 37°C for the time points indicated. Samples were then separated by PAGEAtty. Dkt. No. 650053.01226 and visualized after ethidium bromide staining, g, Representative IVIS image of tumor-bearing mouse shows Texas Red biodistribution after Ihr of Texas Red labelled siFXRl-3 or siFXRl-3- LNA injection. Mouse was then sacrificed and then tumor tissues from the peritoneal cavity (marked by dashed rectangle) and other major organs with tumor metastasis such as liver, kidneys, spleen, and ovaries were isolated and imaged for Texas Red-labelled siFXRl-3 and siFXRl-3- LNA biodistribution. Organs such as heart and lungs, where no metastasis was detected were used as a negative control (right panel), h, Representative confocal microscopy images (top) of tumor tissues were collected from mouse was treated with native siFXRl-3 or siFXRl-3-LNA. Cell nuclei were stained with DAPI (blue), and siRNA was labeled with Texas Red (red). Scale bar represents 100 pm. Bar graph showing the average Texas red intensity in tumor tissues sections (bottom) (n=3). Error bars indicate mean ± SEM. Significance was determined by Student's t-test. where ***p<0.001, ****p<0.0001.

[0015] FIGs. 3A, 3B, 3C, 3D, 3E, 3F, and 3G show in vivo delivery of LNA-modified FXR1 siRNAs exhibited superior level of inhibition of the growth and metastasis of ovarian and breast cancer cells, a, Schema shows the schedule of injections of PEI-incorporated siCont-LNA, native siRNA or siFXRl-LNA injected (twice / week) intraperitoneally (IP) in OVCAR8 tumorbearing female athymic nude mice. Each group contains seven mice (n = 7). On day 42, all mice were euthanized, and tumors w ere collected for further analysis, b, Mice from a were imaged using an IVIS imager and representative images of two mice per group were presented at the indicated time point, c, Bioluminescent signals were from b and quantitated at the indicated time points and presented, d, Representative image (left) of the anatomy of peritoneal canty of mice from each group. Areas circled in blue indicate tumor nodule formed in each peritoneal organ. Primary7and disseminated tumors were collected from b and total tumor w eight was recorded (right), e, Western blot analysis of indicated proteins in the lysates from representative tumor tissues collected from each treatment group (n=3) from b. 0-actin, loading control, f, H&E, immunohistochemical examination of Ki67 and cleaved Caspase3 (Cl. Casp3) expression g, Schema shows the schedule of injections of PEI-incorporated siCont-LNA, native siRNA or siFXRl-LNA injection (10 pg / dose; twice / week) intraperitoneally for six weeks in MDA-MB-231 tumor-bearing female athymic nude mice. On week 8, all mice were euthanized, and tumors were collected and photographed, h, Tumors from each group were isolated and photographed at the end point; (n = 5 mice per group), i, Bar graph represents tumor mass in grams quantitated at the end point, and j, tumor volume in mm3, was measured at the indicated time point for six weeks after tumor cells inoculation. Asterisk indicates p-value determined on the last time point k, Representative H&EAtty. Dkt. No. 650053.01226 staining images of lymph node of different groups. Metastatic regions are marked with arrow. Scale bar represents 500pm and 50pm. Significance was determined by Student’s t-test, where *p < 0.05, **p<0.01, ***p<0.001 , ****p<0.0001.

[0016] FIGs. 4A, 4B, 4C, 4D, 4E, 4F, 4G, and 4H show scRNA-seq analysis demonstrated that FXR1 RNAi treatment enhances the anti-cancer immune response and reduces the tumor cell population within epithelial cell clusters in vivo, a, Schema shows the overall study design of sample collection adapted for lOx Genomics scRNA-seq analysis using ascites samples collected from PEI encapsulated siCont-LNA or siFXRl-LNA treated mice. Ascites from 3 mice were pooled in each group, b, UMAP plot shows 11 clusters of siCont-LNA or siFXRl-LNA treated groups were identified by integrated analysis. Each dot corresponds to a single cell, colored by major cell types in clusters. NK, natural killer, c, A comparative quantitative bar graph indicates the frequency of each cell type in the siCont-LNA group versus the siFXRl-LNA group, p-values were determined using Wilcoxon Rank Sum test between respective groups. Exact p values are included in source data, d, Dot plot showing signature genes among the 11 clusters. The size of the dots indicates percent cells expressing the gene, while the color of the dots indicates average gene expression level, e, Circle plot shows the number of interaction and strength network generated by CellChat in siCont-LNA or siFXRl-LNA treated sample groups. Circle size represents the number of cells within each cluster, the larger size and brighter color correspond to more frequent interactions for different cell types. Edge color represents signaling direction, and edge thickness indicates communication strength (left). Bar graph shows the comparison of the number and strength of interaction in the cell populations from the group were treated with siCont- LNA or siFXRl-LNA as in a (right), f, UMAP plot and proportion bar plot shows the chromosomal copy number variation (CNV) status in epithelial cells from the siCont-LNA or siFXRl-LNA groups, p-values were determined using Wilcoxon Rank Sum test between respective groups. Exact p values are included in source data, g, UMAP plot and proportion bar plot shows the distribution of cell cycle phases in epithelial cells from the siCont-LNA and siFXRl-LNA groups (p values are provided in source data file), h, Violin plot represents the expression for indicated genes in siCont-LNA and siFXRl-LNA, and p-values are calculated by Wilcoxon Rank Sum test. Exact p-values are included in source data file.

[0017] FIGs. 5A, 5B, 5C, 5D, 5E, 5F, 5G, 5H, 51, and 5J show FXR1 RNAi improved macrophage and dendritic cells (DCs) population with anti-tumor characteristics in vivo, a, UMAP plot shows subclusters of macrophages in cell populations were collected from siCont- LN A or siFXRl -LN A treated groups, b, Dot plot shows macrophage subtypes marker genes acrossAtty. Dkt. No. 650053.01226 three subclusters. The dot size denotes the percentage of cells expressing the marker gene in the respective cell population, and the color scale denotes the level of normalized RNA expression, c, Bar graph illustrates the proportion of distribution for macrophage subtypes across three subclusters in siCont-LNA or siFXRl-LNA treated groups (p-values are provided in source data file), d, Violin plot shows Ml like macrophage signature score and M2 like macrophage signature score in macrophage populations in siCont-LNA or siFXRl-LNA treated groups, p-values are calculated by Wilcoxon rank sum test, e, Stacked bar plot (Upper panel) of inferred cell proportions of TAM subpopulations in siCont-LNA and siFXRl-LNA groups. Representative mean fluorescence intensity (MFI) histograms (Lower panel) of flow cytometry analysis of indicated markers such as Pdll, Cdl63 and Mrcl in siCont-LNA or siFXRl-LNA treated groups were quantitated, f, Violin plot shows expression for indicated genes in siCont and siFXRl -LN A treated groups, p-values are calculated by Wilcoxon rank sum test, g, UMAP plot shows subclusters of DCs in siCont-LNA or siFXRl -LNA treated groups, h, Bar graph illustrates the proportion of DC subtypes across three subclusters in siCont-LNA or siFXRl -LNA treated groups (p-values are included in source data file), i Dot plot shows proportions of each DC subtype across three subclusters, j, Violin plot shows expression for indicated genes in siCont-LNA or siFXRl -LNA treated groups, p-values are calculated by Wilcoxon Rank Sum test. Error bars indicate mean ± SEM. Significance was determined by Student’s t-test, where **p<0.01, ****p<0.0001.

[0018] FIGs. 6A, 6B, 6C, 6D, 6E, 6F, 6G, 6H, 61, 6J, and 6K show FXR1 RNAi improved helper and cytotoxic T cells and cytotoxic NK cells within TME. a, UMAP plot shows subclusters of T cells in siCont-LNA or siFXRl-LNA treated groups, b, Dot plots show the signature gene expressions across the T cell subty pes. The dot size denotes the percentage of cells expressing the marker gene in the respective cell population, and the color scale denotes the level of normalized RNA expression, c, Bar graph illustrates the proportion of T cell subtypes across six subclusters in siCont-LNA or siFXRl -LNA treated groups (p values are provided in source data file), d, Violin plot shows average expression of cytotoxic markers in Cd8+and Cd4+T cells from siCont-LNA and siFXRl -LNA groups, p-values are calculated by Wilcoxon rank sum test, e, Representative images of H&E, immunohistochemical examination of Cd4+and Cd8+T cell infiltration in siCont-LNA or siFXRl-LNA treated tumor tissue sections. Scale bar represents 50pm f, Quantitative bar graph of Cd4+and Cd8+T cell infiltration in flow cytometry analysis in the tumor ascites collected from siCont-LNA or siFXRl -LNA treated group, g, UMAP plot shows abundance of NK cells in the TME of siCont-LNA or siFXRl -LNA treated groups, h, Violin plot shows the expression of indicated genes in siCont-LNA or siFXRl -LNA treated groups, p-valuesAtty. Dkt. No. 650053.01226 are calculated by Wilcoxon rank sum test, i, UMAP plot shows NK cells three subclusters, j, Bar graph illustrates the proportion of NK cells subtypes across three subclusters in siCont-LNA or siFXRl -LNA treated groups (p values are provided in source data file), k, Dot plots showing the signature gene expressions across the NK cell subty pes. Error bars indicate mean ± SEM. Significance was determined by Student’s t-test, where *p<0.05.

[0019] FIG. 7 shows a model figure depicting how in vivo FXR1 knockdown via siRNA-LNA nanocomplexes suppresses tumor growth, reprograms immune cell microenvironment and contributes to immune cell activation.

[0020] FIGs. 8A, 8B, 8C, 8D, and 8E show FXR1 knockdown using target specific FXR1 siRNAs promotes cell death of ovarian cancer cells, a, Schematic map shows the target sequences of each FXRl-siRNAs (seql to 5) on the CDS and the UTR of human FXR1 mRNA variant 1. b, Representative histograms of flow cytometry based cell cycle analysis was performed for ovarian cancer cells were transfected with 2.5nM siCont or FXR1 siRNAs (seql-5) for 48h (left). Graphs represent the percentages of cell populations in Gl, S, and G2 / M phases of the cells (right) (n = 3). c, Western blots to check levels of proteins using indicated antibodies after 48h of transfection. 0-actin, loading control. Fold change in protein levels were quantitated with respect to the control and presented below each blot, d, Representative dot plots of flow cytometry analysis were performed using annexin V-FITC and Pl-stained cells were transfected with 2.5nM siCont or FXR1 siRNAs (seql-5) after 48h of transfection. Q2 and Q3 represents late and early apoptotic cells respectively and Q4 represents live cells (left). Quantitative graph to show %apoptosis in ovarian cancer cells (right) (n = 3). e, Ovarian cancer cells w ere transfected with 2.5nM siCont or FXR1 siRNAs (seql-5) for 48h and subjected to colony formation assay. Error bars indicate mean ± SEM. Significance was determined by Student’s t-test, where asterisks denotes as *p < 0.05, **p<0.01, ***p<0.001, and ****p<0.0001. ns, non-significant.

[0021] FIGs. 9A, 9B, 9C, and 9D FXR1 siRNAs are not cytotoxic to normal cells, a, Quantitative bar graph for FXR1 mRNA expression in normal human OSE, ovarian surface epithelial cells, FTE, fallopian tube epithelial cells, fibroblast, PBMC T-cells and human ovarian cancer cell lines, fi-actin; loading control, b, OSE, FTE, Kuramochi, OVCAR8 and OVCAR3 cells were transfected with two individual FXR1 siRNAs (seq2 or seq3), at 2.5 nM concentration up to 72hrs. The number of viable cells were quantitated after transfection using CCK8 assay (n=4-5). Bars represent mean normalized absorbance at 450 nm. c, Representative images depicting GFP+ OVCAR8 cells co-cultured with NucLight Red-labeled FTE cells for 24 hours, followed by treatment with siFXRl (seq3) or siCont at 2.5nM. Cells were captured every 6 hours over 3 daysAtty. Dkt. No. 650053.01226 using the IncuCyte live-cell analysis system (left). The graph displays time-dependent cell count curves for GFP+ 0VCAR8 cells and NucLight Red-labeled FTE cells were treated with siCont or FXR1 siRNAs (right) (n=3). d, Fluorescence images were captured for GFP+ 0VCAR8 cells cocultured with OSE and FTE cells for 24 hrs, followed by transfection with 2.5nM of FXR1 siRNAs (seq3) or siCont (left), respectively. Cell numbers were quantified at different timepoints using live cell imaging with GFP and Eloechst stain. A graph illustrates the proportion of 0VCAR8 cells were generated by dividing the number of GFP+ cells by the total number of Hoechst+ nuclei (n=3) (right). Scale bars, 100 pm. Error bars indicate mean ± SEM. Significance was determined by Student’s t-test, where asterisks denote as *p < 0.05, **p<0.01, ***p<0.001, and ****pO .0001. ns, non-significant.

[0022] FIGs. 10A, 10B, 10C, 10D, and 10E show LNA modified FXR1 siRNAs exerts antitumor effects in ovarian cancer cells, a, Representative histograms shows flow cytometry analysis of cell cycle, performed for ovarian cancer cells were transfected with 0.5nM siCont- LNA, native siFXRl-2, siFXRl-2-LNA, native siFXRl-3 or siFXRl-3-LNA (right). Graphs represent the percentages of cell populations in Gl, S. and G2 / M phases of the cells (right) (n=3). b, Western blots to check levels of proteins using indicated antibodies after 48h of transfection. |3- actin, loading control. Fold change in protein levels were quantitated with respect to the control and presented below each blot, c, Representative dot plots show flow cytometry7analysis were performed using annexin V-FITC and Pl-stained cells for ovarian cancer cells transfected with 0.5nM siCont-LNA, native siFXRl-2, siFXRl-2-LNA, native siFXRl-3 or siFXRl-3-LNA for 48h. d, Quantitative graph to show %apoptosis in ovarian cancer cells (n=3). e, Quantitative bar graph for caspase 3 / 7 activity7recorded after 0.5nM siCont-LNA, native siFXRl-2, siFXRl -2- LNA, native siFXRl-3 or siFXRl-3-LNA treatment in ovarian cancer cells (n=3). Error bars indicate mean ± SEM. Significance was determined by Student's t-test. where *p < 0.05, **p<0.01. ***p<0.001, and ****p<0.0001. ns, non-significant.

[0023] FIGs. HA, 11B, 11C, 11D, HE, and HF show LNA modified FXR1 siRNA demonstrates improved cellular uptake in ovarian cancer cells and mouse model, a, Ovarian cancer cells were transfected with native siFXRl or siFXRl-LNA, then cellular uptake and intracellular distribution were determined by immunoflourescence. The nucleus were stained with Hoechst, the lysosome vesicles were labeled with Lysotracker Red, and the siRNA were labeled with Texas red. Scale bar represents 50pm in unzoomed images and 20pm in zoomed images, b, TUNEL staining was performed to determine the apoptotic effect of siFXRl -LNA in ovarian cancer cells, 48hr after transfection. Green fluorescence indicates TUNEL staining (arrowAtty. Dkt. No. 650053.01226 indicates TUNEL-positive cells) as a marker of apoptotic cells (left). Scale bar represents 50pm. Bar graph showing number of apoptotic cells were determined by TUNEL assay (right) (n=3) c, TUNEL staining (green fluorescence, left) of the tumor sections were performed from Fig. 3a. Scale bar represents 100 pm. Bar graph showing number of apoptotic cells in tumor tissues as determined by TUNEL assay (right). A total of 3 fields from each treatment group were counted, d. Western blot analysis of FXR1 levels in human normal breast cells and cancer cells, [3-actin, loading control, e, Western blot analysis of FXR1 levels after native siFXRl (seq2 or seq3) or siFXRl-LNA (seq2 or seq3) were transfected in MDA-MB-231 cells. P-actin, loading control. Fold change in protein levels were quantitated with respect to the control and presented below each blot, f, H&E analysis of main organs from toxicity study of the mice were treated with siCont- LNA. siFXRl or siFXRl -LN A; no obvious pathological changes were observed. Scale bar represents 50 pm. Error bars indicate mean ± SEM. Significance was determined by Student’s t- test, where **p<0.01, ***p<0.001,****p<0.0001.

[0024] FIGs. 12A, 12B, 12C, 12D, 12E, 12F, 12G, 12H, 121, 12J, and 12K show Single-cell RNA sequencing (scRNA-seq) identified immune cell modulation supports anti-cancer mechanisms upon FXR1 RNAi in immunocompetent mice bearing mouse ovarian cancer, a, Sequence complementarity between siRNA sequences and mouse FXR1 mRNA. Sequences, from top to bottom, are SEQ ID NOs: 38-41. b, Immunoblots shows FXR1 levels after native siFXRl (seq2 or seq3) or siFXRl -LNA (seq2 or seq3) were transfected in mouse ovarian cancer cell lines. P-actin, loading control. Fold change in protein levels were quantitated with respect to the control and presented below each blot, c, Schema shows the overall study design of scRNA-seq analysis using ascites samples collected from PEI encapsulated siCont-LNA or siFXRl -LNA treated FVB / N mice. On day 30. all mice were euthanized, ascites fluid and tumors were collected for further analysis, d, Representative image of the mouse with ascites fluid formation. Primary and disseminated tumors were collected from c, then e, total tumor weight and f, ascitic fluid volume were recorded, g, Kaplan-Meier survival plot of immunocompetent FVB / N mice injected with Br- Luc mouse ovarian cancer cells and treated with JetPEFD-carried siCont-LNA (n=10) or siFXRl- LNA (n=10). h, UMAP for the integrated data of duplicate samples at a resolution of 0.1 of scRNA-seq analysis of tumor ascites samples isolated from siCont-LNA or siFXRl -LNA treated mice. The combination of two biological replicates for each population were presented for each group. i,UMAP plot shows abundance of different cell types in the TME of siCont-LNA vs. siFXRl -LNA ascitic samples, j, Bar graph illustrates the cell count in each cluster. k,HeatmapsAtty. Dkt. No. 650053.01226 shows the interaction quantity and interaction strength between each cell population in siCont- LNA or siFXRl-LNA treated group.

[0025] FIGs. 13A, 13B, 13C, and 13D show CellChat analysis based on scRNA-seq analysis identified ECM-receptor signaling was down-regulated, whereas secreted signaling and cellcell contact signaling were up-regulated upon FXR1 RNAi. a, Bar graph shows change in percentage of genes involved in the indicated pathways identified among cell populations isolated from siCont-LNA or siFXRl-LNA treated groups, b, c, and d, Dot plot shows the top ligandreceptor pairs contributing to the ECM-receptor signaling, cell-cell contact and secreted signaling probability between cells of interest, including epithelial cells, macrophages, T cells, B cells, NK cells and DCs in siCont-LNA or siFXRl-LNA treated groups. The color represents the groups and the dot size represents scores of communication probability.

[0026] FIGs. 14A, 14B, 14C, and 14D show delivery of siFXRl-LNA reduced the levels of FXR1 in tumor cells in vivo. A. Violin plot shows the level of distribution of Fxrl mRNA in epithelial cells subclusters including tumor cells based on CNVs in siCont-LNA or siFXRl-LNA treated groups, b, c, Violin plot shows the expression of genes indicated in epithelial cells subclusters isolated from siCont-LNA or siFXRl-LNA treated groups, p-values are calculated by Wilcoxon Rank Sum test, d, Bar graph shows enrichment of canonical pathways of DEGs in epithelial cells. Pathway activity scores were calculated by IPA software.

[0027] FIGs. 15A, 15B, 15C, 15D, 15E, 15F, and 15G show FXR1 RNAi resulted into the enrichment of macrophages with anti-tumor characteristics and CellChat analysis identified possible interactions and mechanisms between DCs, T cells and NK cells, a, UMAP plot shows the abundance of macrophage subclusters in siCont-LNA and siFXRl-LNA treated groups, b, Violin plot shows the distribution of indicated chemokines and their receptors in macrophages subclusters, p-values are calculated by Wilcoxon rank sum test, c, Dot plot shows macrophage subtypes marker genes in siCont-LNA or siFXRl-LNA treated groups, d, Flow cytometry gating strategy used for analyzing Pdll, Mrcl, and Cdl63 expression in tumor-associated macrophages (TAMs) in mouse ascites samples, e, Immunofluorescence (IF) analysis for F4 / 80, Argl and Mrcl in siCont-LNA and siFXRl-LNA treated tumor tissue sections were performed. Scale bar represents 50pm and 20pm. f, UMAP plot shows abundance of DCs in siCont-LNA or siFXRl- LNA treated groups, g, Dot plot shows the probabilities of cell-cell communication from pDC to NK cells, Cd8+and Cd4+cytotoxic T cell populations.

[0028] FIGs. 16A, 16B, 16C, 16D, and 16E show FXR1 RNAi improved the enrichment of T cells with cytotoxic functions and promoted interactions between macrophages, tumorAtty. Dkt. No. 650053.01226 cells and T cells favors anti-tumor mechanisms, a, UMAP plot showing abundance of T cells in siCont-LNA and siFXRl-LNA groups, b, Dot plot shows proportions of each T cell subtype in the siCont-LNA and siFXRl-LNA groups, c, Flow cytometry gating strategy for analyzing Cd4+and Cd8+T cells in mouse ascites samples, d, Dot plot denotes the probabilities of cell-cell communication from Cd8+and Cd4+cytotoxic T cell subtypes to macrophages subtypes, as well as from Cd8+and Cd4+cytotoxic T cells to epithelial cells, respectively in siFXRl-LNA treated group, e. Dot plot illustrates the probabilities of cell-cell communication from macrophages subtypes to Cd8+and Cd4+cytotoxic T cell subtypes in siFXRl-LNA treated group.

[0029] FIGs. 17A, 17B, 17C, 17D, 17E, and 17F a, Oligonucleotide sequences are shown for control siRNA (siCont). two mutated siRNAs (seq2 and seq3) with mutations indicated in red both sense and antisense strands, and siRNAs targeting FXR1. Sequences, from top to bottom, are SEQ ID NOs: 3, 4, 30, 31, 5, 6, 34, and 35. b, Western blots to show knockdown efficiency of indicated siRNAs after 48h transfection against FXR1 in OVCAR8 ovarian cancer cells, c, Schematic representation of the injection schedule for PEI-formulated siCont-LNA, mutated siFXRl (mutsiFXRl). native siRNA, or siFXRl-LNA. Treatments were administered intraperitoneally (IP) once per week at a dose of 10 pg per mouse, starting on day 7 and continuing for six weeks in OVCAR8 tumor-bearing female athymic nude mice, d, Mice from a were imaged using an IVIS imager and representative images of tw o mice per group were presented at the indicated time point. e, Bioluminescent signals were from d and quantitated at the indicated time points and presented. f, Representative image (top) of the anatomy of peritoneal cavity of mice from each group. Areas circled in blue indicate tumor nodule formed in each peritoneal organ. Primary and disseminated tumors were collected from d and total tumor weight was recorded (bottom). Significance was determined by Student’s t-test, where **p<0.01, ***p<0.001, ****p<0.0001, ns, non-significant.

[0030] FIGs. 18A, 18B, 18C, 18D, 18E, and 18F a, Schema shows the schedule of injections of PEI -incorporated siCont-LNA, native siRNA and siFXRl-LNA injection (10 pg / dose; twice / week) intraperitoneally for six w eeks in MDA-MB-231 tumor-bearing female athymic nude mice. On week 8, all mice were euthanized, and tumors were collected and photographed, b, Western blot analysis of FXR1 levels after native siFXRl (seq2 or seq3) and siFXRl-LNA (seq2 or seq3) were transfected in MDA-MB-231 cells. (3-actin, loading control. Fold change in protein levels were quantitated with respect to the control and presented below each blot, c, Tumors from each group were isolated and photographed; (n = 5 mice per group) at the end point, d, Bar graph represents tumor mass in grams at the end point, and e, tumor volume in mm3, was measured at the indicated time point for six weeks after tumor cells inoculation. Asterisk indicates p-valueAtty. Dkt. No. 650053.01226 determined on the last time point f, Representative H&E staining images of lymph node of different groups. Metastatic regions are marked with arrow. Scale bar represents 500pm and 50pm. Significance was determined by Student’s t-test, where *p < 0.05, **p<0.01, ***p<0.001, ****p<0.0001.DETAILED DESCRIPTION

[0031] FXR1 (Fragile X-related protein 1) gene encodes an RNA binding protein, which is highly elevated or copy -gained in ovarian cancer. Amplification and copy -gain of FXR1 increased the expression of FXR1 mRNA and FXR1 protein in ovarian cancer patients. FXR1 is also amplified and expressed in lung, cervical, and esophageal cancers. Based on data collected by the inventors, FXR1 may be a master regulator of oncogenesis and metastasis in ovarian and other cancers including lung, cervix, head and neck, esophagus and breast cancers.

[0032] The inventors further hypothesize that FXR1 stabilizes the expression of several oncogenic transcripts and promotes the translation of several oncogenic proteins.

[0033] Accordingly, the inventors have developed dsRNAs, e g., locked-nucleic acid incorporated duplex strand of nucleic acids (LNA-FXR1 -siRNA) to treat cancer, e.g., ovarian cancer.

[0034] The disclosed dsRNAs, nanoparticles, pharmaceutical compositions, and methods have several novel attributes and potential therapeutic applications: Currently, there are no therapeutic approaches to target and inhibit expression of FXR1. Furthermore, RNA interference (RNAi) is a powerful technology for treating diseases that functions by disrupting messenger RNA encoding proteins related disease-causing proteins. However, the delivery of RNAi technology is not well developed.

[0035] The inventors have designed anti-FXRl dsRNA comprising modified nucleotides and discovered that the anti-FXRl dsRNAs, disclosed herein, inhibit the growth and function of cancer cells, e.g., ovarian cancer cells. Notably, LNA-FXR1 -siRNA was able to inhibit FXR1 more efficiently at nanomolar concentrations as compared to siRNAs not comprising modified nucleotides. In addition, nucleic acid stability assays demonstrated that LNA-FXR1 -siRNA forms are highly stable when incubated with human and mouse serum supporting the hypothesis that the disclosed siRNAs have robust therapeutic efficacy (FIG. 3C). The inventors also observed that the disclosed siRNAs, e.g., LN A-FXR1 -siRNA, were able to inhibit the growth of cancer cells more effectively than the conventional dsRNAs.CompositionsAtty. Dkt. No. 650053.01226

[0036] The inventors disclose herein novel compositions targeting fragile X-related protein 1 (FXR1). In an aspect of the cunent disclosure, dsRNAs are disclosed. In some embodiments, the dsRNAs comprise: a polynucleotide selected from one of SEQ ID NOs: 1-10, or a sequence with at least 95% identity to one of SEQ ID NOs: 1-10, and wherein the dsRNA comprises one or more modified nucleic acids. The inventors developed siRNA sequences targeting FXR1, e g., which may comprise, e.g., SEQ ID NOs: 1-10. SEQ ID NOs: 2. 4, 6, 8, and 10 correspond to the antisense strand which is designed to target and hybridize with the FXR1 mRNA transcript. Furthermore, the disclosed dsRNAs may comprise one or more modified nucleotides.

[0037] Exemplary dsRNAs may comprise a polynucleotide selected from SEQ ID NOs: 1-37, or a sequence with at least about 80%, at least about 81%, at least about 82%, at least about 83%, at least about 84%, at least about 85%, at least about 86%. at least about 87%. at least about 88%. at least about 89%, at least about 90%, at least about 91%, at least about 92%, at least about 93%, at least about 94%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, at least about 99%, or about 100% identity to one of SEQ ID NOs: 1-37. Further, SEQ ID NOs: 1- 10 correspond to duplex pairs, i.e., SEQ ID NO: 1 corresponds to the sense strand of FXR1, and SEQ ID NO: 2 corresponds to the antisense strand that is designed to target FXR1 mRNA. Thus, SEQ ID NOs: 1 and 2 form a dsRNA duplex, when hybridized, and so on for the pairs: SEQ ID NOs: 3 and 4, 5 and 6, 7 and 8, and 9 and 10.

[0038] The phrases “% sequence identity;’ “percent identity,” or “% identity” refer to the percentage of amino acid residue matches between at least two amino acid sequences aligned using a standardized algorithm. Methods of amino acid sequence alignment are well-known. Some alignment methods take into account conservative amino acid substitutions. Such conservative substitutions, explained in more detail below, generally preserve the charge and hydrophobicity at the site of substitution, thus preserving the structure (and therefore function) of the polypeptide. Percent identity for amino acid sequences may be determined as understood in the art. (See, e g., U.S. Patent No. 7,396,664, which is incorporated herein by reference in its entirety). A suite of commonly used and freely available sequence comparison algorithms is provided by the National Center for Biotechnology Information (NCBI) Basic Local Alignment Search Tool (BLAST), which is available from several sources, including the NCBI, Bethesda, Md., at its website. The BLAST software suite includes various sequence analysis programs including “blastp,” that is used to align a known amino acid sequence with other amino acids sequences from a variety of databases.Atty. Dkt. No. 650053.01226

[0039] As used herein, “modified nucleotides'’ refer to nucleotide bases which are not found in nature. Exemplars’ modified nucleotides may include, but are not limited to. modified nucleotides such as 2'-O-methyl (2'0Me) nucleotides, 2'-deoxy-2'-fluoro (2'F) nucleotides, 2'-deoxy nucleotides, 2'-O-(2-methoxyethyl) (MOE) nucleotides, and the like. The preparation of modified siRNA is known by one skilled in the art. In some embodiments, the disclosed dsRNA molecules include one or more modified nucleotides at the 5'-terminus of the passenger strand of the dsRNA that prevent incorporation of the passenger strand into RISC. (See, e.g., Walton et al., Minireview: “Designing highly active siRNAs for therapeutic applications,” the FEBS Journal, 277 (2010) 4806-4813). Further, the disclosed compositions may comprise nucleotides w ith phosphorothioate modifications to the ribose sugar moiety on a nucleotide or “locked nucleic acids”, a type of modified nucleotide, which, as used herein, refers to nucleotides comprising a 2 -0. 4 -C methylene bridge. An advantage of LNA incorporation into dsRNAs comprises increased stability, as demonstrated by FIG. 3E, which shows that LNA incorporation into the disclosed dsRNA compositions increases the dsRNA compositions' stability- in mouse serum.

[0040] The disclosed compositions (double-stranded RNAs (dsRNAs), small interfering RNAs (siRNAs)) function through a process known as RNA interference (RNAi). The mechanism of action of siRNA is understood by the skilled person. After processing in a cell, an siRNA is capable of targeting specific messenger RNA (mRNA) and silencing (i.e., inhibiting) the expression of a target gene. During this process, dsRNA (which may include shRNA) is enzymatically processed into short-interfering RNA (siRNA) duplexes of ~21 -23 nucleotides in length. The anti-sense strand of the siRNA duplex is then incorporated into a cytoplasmic complex of proteins (RNA- induced silencing complex or RISC). The RISC complex containing the anti-sense siRNA strand also binds mRNA which has a sequence complementary to the anti-sense strand-allowing complementary base-pairing between the anti-sense siRNA strand and the sense mRNA molecule. The mRNA molecule is then specifically cleaved by an enzyme (RNase) associated with RISC resulting in specific gene silencing. For gene silencing or knock down (i.e., mRNA cleavage) to occur, anti-sense RNA (i.e., siRNA) has to become incorporated into the RISC. This represents an efficient process that occurs in nucleated cells during regulation of gene expression.

[0041] As such, siRNA-mediated RNA interference may be considered to involve two-steps: (i) an initiation step, and (ii) an effector step. In the first step, input siRNA is processed into small fragments, such as ~21 -23-nucl cotide “guide sequences.” The guide sequences can be incorporated into the protein-RNA RISC complex which is capable of degrading mRNA. The RISC complex acts in the second effector step to destroy rnRNAs that are recognized by the guide RNAs throughAtty. Dkt. No. 650053.01226 base-pairing interactions. RNA interference via use of siRNA may be considered to involve the introduction by any means of double stranded RNA into a cell which triggers events that cause the degradation of a target RNA, and as such siRNA may be considered to be a form of post- transcriptional gene silencing. The skilled person understands how to prepare and utilize siRNA molecules. (See, e.g., Hammond et al., Nature Rev Gen 2: 110-119 (2001); and Sharp, Genes Dev 15: 485-490 (2001). the contents of which are incorporated herein by reference in their entireties).

[0042] The disclosed compositions, e.g., dsRNAs, siRNAs, may be discussed herein in terms of “dsRNAs comprising a polynucleotide." However, it is to be understood that siRNAs comprising the same polynucleotides or polynucleotide sequences are contemplated in this disclosure.

[0043] The disclosed dsRNAs may further comprise an “overhang" on one or both ends of the dsRNA. As used herein, “overhang7’ or “nucleotide overhang” refers to one or more nucleotides that extend beyond the dsRNA duplex on either the 5’ or 3’ end of one or both strands of the duplex. Exemplary dsRNAs may comprise a polynucleotide selected from SEQ ID NOs: 11-20, which correspond to SEQ ID NOs: 1-10, with the addition of nucleotide overhangs. Further, SEQ ID NOs: 11-20 correspond to duplex pairs, i.e., SEQ ID NO: 11 corresponds to the sense strand of FXR1, and SEQ ID NO: 12 corresponds to the antisense strand that is designed to target FXR1 mRNA. Thus, SEQ ID NOs: 11 and 12 form a duplex with overhangs, when hybridized, and so on for the pairs: SEQ ID NOs: 13 and 14, 15 and 16, 17 and 18, and 19 and 20. dsRNAs comprising additional or alternative overhangs are disclosed herein and may be determined by a skilled artisan according to standard procedures. The overhangs may comprise ribonucleic acid overhangs or deoxyribonucleic acid overhangs.Nanoparticles

[0044] The inventors contemplate that the deliver}' of the disclosed compositions, e.g., dsRNAs, siRNAs, may be accomplished in vivo or in vitro through administration of nanoparticles. Accordingly, in another aspect of the current disclosure, nanoparticles are provided.

[0045] The nanoparticles of the instant disclosure may comprise the disclosed dsRNAs. Further, the nanoparticles may comprise one or more lipid, e.g., l,2-di-(9Z-octadecenoyl)-sn-glycero-3- phosphocholine (DOPC) or polyethyleneimine (PEI), which may suitably be formed into a liposome.

[0046] Additional or alternative exemplary’ lipids for incorporation into nanoparticles are known in the art and include, but are not limited to, polyethyleneimine (PEI), 1,2-dipalmitoyl-sn-glycero- 3-phosphoethanolamine-N-[3-(2-pyridyldithio) propionate] (PDP-PE), 3060iio, tetrakis(8-Atty. Dkt. No. 650053.01226 methylnonyl) 3,3',3",3"'-(((methylazanediyl) bis(propane-3.1 diyl))bis(azanetriyl))tetrapropionate; 9A1P9. decyl (2-(dioctylammonio)ethyl) phosphate; A2-Iso5- 2DC18, ethyl 5,5-di((Z)-heptadec-8-en-l-yl)-l-(3-(pyrrolidin-l-yl)propyl)-2,5-dihydro-l / 7- imidazole-2-carboxylate; ALC-0315, ((4-hydroxybutyl)azanediyl)bis(hexane-6,l-diyl)bis(2- hexyldecanoate); ALC-0159, 2- [(polyethylene glycol)-2()()()|-A.A'-ditetradecylacetamide; 0- sitosterol, (35,85,95,107?, 137?.145, 177?)- 17-((27?,57?)-5-ethyl-6-methylheptan-2-yl)- 10,13- dimethyl-2,3,4,7,8,9,10,l l,12,13,14,15,16,17-tetradecahydro-177-cyclopenta[a]phenanthren-3-ol; B AME-016B, bis(2-(dodecy 1 disulfanyl)ethyl) 3 ,3 '-((3 -methy 1-9-oxo- 10-oxa- 13,14-dithi a-3 ,6- diazahexacosyl)azanediyl)dipropionate; BHEM-Chol esterol, 2-(((((35,85,95, 107?, 137?, 145,177?)- 10, 13-dimethyl- 17-((7?)-6-methylheptan-2-yl)-2,3,4,7,8,9, 10,11.12,13,14,15,16,17- tetradecahydro-17 / -cyclopenta[a]phenanthren-3-yl)oxy)carbonyl)amino)-AJV-bis(2- hydroxyethyl)-A-methylethan-l-aminium bromide; Cl 2-200, l,l'-((2-(4-(2-((2-(bis(2- hydroxydodecyl)amino)ethyl) (2-hydroxydodecyl)amino)ethyl) piperazin- l-yl)ethyl)azanediyl) bis(dodecan-2-ol); cKK-E12, 3,6-bis(4-(bis(2-hydroxydodecyl)amino)butyl)piperazine-2,5- dione; DC-Cholesterol. 30-[A-(A'A^-dimethylaminoethane)-carbamoyl] cholesterol; DLin-MC3- DMA, (6Z,9Z,28Z,31Z)-heptatriaconta-6,9,28,31-tetraen-19-yl 4-(dimethylamino) butanoate; DOPE, 1 .2-dioleoyl-s77-glycero-3-phosphoethanolamine: DOSPA, 2.3-dioleyloxy-A-|2- (sperminecarboxamido)ethyl]-AA^-dimethyl-l-propanaminium trifluoroacetate; DOTAP, 1,2- dioleoyl-3-trimethylammonium-propane; DOTMA, 1 ,2-di-(9-octadecenyl-3- trimethylammonium-propane; DSPC, l .2-distearoyl-s77-glycero-3-phosphocholine; ePC, ethylphosphatidylcholine; FTT5, hexa(octan-3-yl) 9,9',9",9"',9''",9'""- ((((benzene- 1,3,5- tricarbonyl)yris(azanediyl)) tris (propane-3,1 -diyl)) tris(azanetriyl))hexanonanoate; Lipid H (SM- 102), heptadecan-9-yl 8-((2-hydroxyethyl)(6-oxo-6- (undecyl oxy )hexyl)amino) octanoate; OF- Deg-Lin, (((3.6-dioxopiperazine-2,5-diyl)bis(butane-4, 1 -diyl))bis(azanetriyl))tetrakis(ethane-2, 1 - diyl) (9Z,9'Z,9"Z,9"'Z,12Z,12'Z,12''Z,12"'Z)-tetrakis (octadeca-9,12-dienoate); PEG2000-DMG, l,2-dimyristoyl-rac-glycero-3-methoxypolyethylene gly col-2000; TT3, A1,A3A^5-tris(3-(didodecylamino)propyl)benzene-1.3,5-tricarboxamide.

[0047] The PEI may comprise a linear polyethylenimine derivative, free of components of animal origin, including, but not limited to, JetPEI®.

[0048] An advantage of using nanoparticle formulations of the disclosed dsRNAs, is the potential for increased stability, e.g., in the bloodstream.

[0049] Further, disclosed herein are methods of making the novel nanoparticles comprising dsRNAs which target FXR1 by RNAi.Atty. Dkt. No. 650053.01226

[0050] Methods of generating / making nanoparticles are know n in the art. Exemplary methods of generating / making nanoparticles are provided in Example 1.Pharmaceutical compositions

[0051] The inventors envision that the disclosed dsRNAs and nanoparticles are used to target and downregulate the expression of FXR1 in cancer, which may lead to cell death, e g., due to apoptosis, in cancer cells, see, for example, FIGs. IF and 2D.

[0052] Accordingly, in another aspect of the current disclosure, pharmaceutical compositions are provided. The pharmaceutical compositions may comprise the disclosed dsRNAs, siRNAs, or nanoparticles comprising the disclosed dsRNAs or siRNAs. The pharmaceutical compositions may further comprise a pharmaceutically acceptable carrier or excipient. Formulation of such pharmaceutical compositions comprising the novel nanoparticles and pharmaceutical carriers or excipients may be performed by one of ordinary skill in the art by known methods.

[0053] The pharmaceutical compositions may comprise a therapeutically effective amount of the dsRNAs or nanoparticles.

[0054] As used herein, “a therapeutically effective amount ’ refers to an amount of a composition that achieves a particular treatment response, e.g., a reduction in tumor volume, a reduction in tumor number, a reduction in tumor burden, an improved prognosis, an increased lifespan of the subject, etc. Methods of assessing the forgoing treatment response metrics are known in the art.Methods

[0055] As discussed above, the inventors have demonstrated that the disclosed dsRNAs and nanoparticles effectively kill cancer cells, e.g., ovarian cancer cells. Accordingly, in another aspect of the current disclosure, methods, e.g., methods of treatment are provided.

[0056] In some embodiments, the methods are methods of treating a disease or disorder associated with FXR1 expression, e.g., aberrant FXR1 expression, in a subject in need thereof and comprise: administering a pharmaceutical composition comprising the disclosed dsRNAs, siRNAs, or nanoparticles to the subject to treat the disease or disorder associated with FXR1 expression in the subject.

[0057] As used herein, "disease or disorder associated with FXR1 expression” refers to any disease or disorder wherein FXR1 expression is elevated, e.g., protein expression, and / or RNA expression is elevated as compared to a healthy control, in cells, or is elevated and detectable in, e.g., blood, serum, urine, etc. RNA or protein expression may be elevated, for example, due to aAtty. Dkt. No. 650053.01226 copy number gain of FXR1, which, as described above, has been detected in human cancers. An exemplary class of diseases or disorders associated with FXR1 expression comprises: cancer, e.g.. lung cancer, ovarian cancer, cervical cancer, esophageal cancer, and breast cancer.

[0058] The disclosed methods may cause apoptosis in target cells, e.g., cancer cells, see, for example, FIGs. IE and 2D. Apoptosis may be measured in any one of several standard methods known in the art, e.g., by flow cytometry using the markers annexin V and a dye that indicates permeable cell membranes, e.g., propidium iodide, see, e.g., FIG. 10D, or by measuring cleavage of poly (ADP -ribose) polymerase (PARP1), compare Full length PARP (Fl. PARP) with cleaved PARP (Cl. PARP) in FIG. 10C. Apoptosis may be measured by detecting caspase 3 / 7 activity', see, e.g., FIG 10E.

[0059] In some embodiments, administration of the disclosed compositions results in a decrease in tumor size and / or tumor growth rate. Methods of analysis of tumor status, such as size and / or grow th rate, are well-known to the skilled artisan, and may include, by way of example only and not by way of limitation, palpitation, imaging, and biopsy.

[0060] The compositions of the present disclosure may be administered to the subject by any appropriate mode known to the skilled artisan, including, but not limited to direct injection into a tumor, intravenous administration, inhalation, intrathecal administration, and intraperitoneal administration.

[0061] It is anticipated that a subject in need thereof treated with the disclosed composition will exhibit a reduction in tumor size and / or a reduction in tumor growth as compared to a subject in need thereof who did not receive a cancer therapeutic, or who did not receive the claimed therapeutic composition.

[0062] In some embodiments, the composition of the present disclosure is administered to a subject in need thereof (e.g., a subject diagnosed with an FXRl-related cancer such as ovarian, cervical, or lung cancer), once as a single administration, or multiple times over the course of a day, a week, a month, several months or one or more years. By way of example, the subject may be treated once per week for 1, 2, 3. or 4 yveeks or more, or once a month for 2, 3, 4, 5, 6. 7, 8, 9, 10, 11, or 12, months, or any combination thereof.

[0063] As used herein, “a subject’ ' may refer to a mammal, e.g., a human, a dog, a cat, a horse, etc.

[0064] In some embodiments, the therapy is administered in combination (e.g., during the course of treatment) yvith one or more additional cancer therapies, including but not limited to chemotherapy, radiation therapy, and surgery.Atty. Dkt. No. 650053.01226

[0065] As used herein, “increasing immune infiltration” refers to increasing the number or frequency of an immune cell in a particular area, e.g., in a tumor. Immune cells may be, e.g., T cells, B cells, Natural killer (NK) cells, dendritic cells (DCs), monocytes, neutrophils, or other immune cells.

[0066] The present invention is described further herein using several definitions, as set forth below and throughout the application.Definitions

[0067] The disclosed subject matter may be further described using definitions and terminology as follows.

[0068] As used in this specification and the claims, the singular forms “a,” “an,” and “the” include plural forms unless the context clearly dictates otherw ise. For example, the term “a substituent” should be interpreted to mean “one or more substituents,” unless the context clearly dictates otherwise.

[0069] As used herein, “about”, “approximately,” “substantially,” and “significantly” will be understood by persons of ordinary skill in the art and will vary' to some extent on the context in which they are used. If there are uses of the term which are not clear to persons of ordinary' skill in the art given the context in which it is used, “about” and “approximately” will mean up to plus or minus 10% of the particular term and “substantially” and “significantly” will mean more than plus or minus 10% of the particular term.

[0070] As used herein, the terms “include” and “including” have the same meaning as the terms “comprise” and “comprising.” The terms “comprise” and “comprising” should be interpreted as being “open” transitional terms that permit the inclusion of additional components further to those components recited in the claims. The terms “consist” and “consisting of’ should be interpreted as being “closed” transitional terms that do not permit the inclusion of additional components other than the components recited in the claims. The term “consisting essentially of should be interpreted to be partially closed and allowing the inclusion only of additional components that do not fundamentally alter the nature of the claimed subject matter.

[0071] The phrase “such as” should be interpreted as “for example, including.” Moreover, the use of any and all exemplary language, including but not limited to “such as”, is intended merely to better illuminate the invention and does not pose a limitation on the scope of the invention unless otherwise claimed.Atty. Dkt. No. 650053.01226

[0072] Furthermore, in those instances where a convention analogous to "at least one of A, B and C, etc.” is used, in general such a construction is intended in the sense of one having ordinary skill in the art would understand the convention (e g., “a system having at least one of A, B and C” would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and / or A, B, and C together.). It will be further understood by those within the art that virtually any disjunctive word and / or phrase presenting two or more alternative terms, whether in the description or figures, should be understood to contemplate the possibilities of including one of the terms, either of the terms, or both terms. For example, the phrase "A or B” w ill be understood to include the possibilities of “A” or ‘B or “A and B.”

[0073] All language such as “up to,” “at least,” “greater than,” “less than,” and the like, include the number recited and refer to ranges which can subsequently be broken down into ranges and subranges. A range includes each individual member. Thus, for example, a group having 1-3 members refers to groups having 1, 2, or 3 members. Similarly, a group having 6 members refers to groups having 1, 2, 3, 4, or 6 members, and so forth.

[0074] The modal verb “may” refers to the preferred use or selection of one or more options or choices among the several described embodiments or features contained within the same. Where no options or choices are disclosed regarding a particular embodiment or feature contained in the same, the modal verb “may” refers to an affirmative act regarding how to make or use and aspect of a described embodiment or feature contained in the same, or a definitive decision to use a specific skill regarding a described embodiment or feature contained in the same. In this latter context, the modal verb “may” has the same meaning and connotation as the auxiliary verb “can.”EXAMPLES

[0075] The following Examples are illustrative and should not be interpreted to limit the scope of the claimed subject matter.Example 1 - Single-Cell Transcriptomics Reveals FXR1 as an Actionable Target for siRNA Therapy in Ovarian Cancer

[0076] Ovarian cancer is one of the leading causes of cancer-related mortality among women and remains exceptionally difficult to manage and treat effectively in the clinic. Fragile X-related protein 1 (FXR1) is highly amplified and overexpressed in ovarian and several other cancers. FXR1 is a key regulator of translation of multiple oncogenes. Therefore, FXR1 could serve as a vulnerable target for cancer therapy. RNA interference (RNAi) of FXR1 using locked nucleic acid (LNA) form of siRNA (siFXRl -LNA) inhibited tumor growth, ascites formation and metastasis of ovarian cancerAtty. Dkt. No. 650053.01226 efficiently than the native form of FXR1 siRNA in vivo. LNA modification of siRNA improved resistance to RNase mediated degradation and tumor tissue uptake with robust inhibition of its target mRNA in tumor tissues. Single-cell RNA sequencing (scRNA-seq) of ascites composed of tumor, stromal and immune cells analysis revealed that FXR1 silencing inhibited tumor cell proliferation, and reduced tumor-promoting M2-like macrophages. FXR1 silencing also increased cytotoxic T and NK cells, and dendritic cells with anti-tumor characteristics in vivo. Altogether, our data demonstrates that FXR1 is an important regulator of oncogenic process in cancer tissues and serve as a therapeutic liability. Therefore, FXR1 silencing in tumor tissues provides a novel opportunity to treat tumors expressing high levels of FXR1.

[0077] Introduction

[0078] Ovarian cancer, a leading cause of cancer deaths among women w ith a 1 in 87 lifetime risk, often goes undetected until its aggressive later stages, leading to low survival rates and frequent recurrences despite early treatment success. Studies from The Cancer Genome Atlas1, us2, and others3have reported that ovarian cancer is driven by copy number variations (CNVs), such as copy number gain, amplification, or deletion of genome. Many genes, such as PI3KCA4, EVI1 5, and TERC6were reported as amplified within the 3q26 locus amplification for their role in ovarian cancer progression. We have reported that non-coding microRNAs, such as the miR569 and miR551b, that are amplified as part of the 3q26.2 locus, contribute to the oncogenesis and progression of the breast and ovarian cancers2’7‘8. Although many genes were reported for ovarian cancer progression as driver genes or passenger genes, targeted therapy is not w ell developed for ovarian cancer.

[0079] Our recent work identified that fragile X-related protein 1 (FXR1), is a master regulator of stability and translation of several oncogenic mRNAs9. FXR1 is copy -gained or overexpressed in many cancers such as those of lung, ovary, esophagus, head and neck, cervical and uterine9Therefore, silencing FXR1 in tumor tissues could offer therapeutic benefits for ovarian and multiple other cancers that exhibit FXR1 amplification and / or overexpression. However, there is no inhibitor readily available that targets and inhibits FXR1 for therapy. Hence, the aim of this study is to develop RNA interference (RNAi) techniques, employing both in vitro and in vivo models, to target and suppress FXR1 for cancer therapy.

[0080] RNAi was a Noble Prize-winning discovery made by Dr. Craig Mello and Andrew Fire in 199810-n. RNAi based therapeutic approaches haven’t received any significant attention for clinical care until 2018 when FDA approved the first RNAi drug Patisiran to treat hereditaryAtty. Dkt. No. 650053.01226 transthyretin amyloidosis, and subsequently RNAi drugs Givosiran and Lumasiran got approved for treating hepatic porphyria and hyperoxaluria in 2019 and 2020. respectively12, 13, 14. Since then. RNA-based therapy has become an important area of research for silencing many genes which were considered undruggable previously. However, the therapeutic potential of RNAi has not met the goal of treating diseases like cancers as expected, potentially due to lack of cancer cell specific RNAi targets and / or effective delivery mechanisms. Additionally, the impact of RNAi on normal cells and immune cell toxicity has not thoroughly addressed for cancer therapy. Given this background, our research aims to explore the potential of using FXR1 siRNA not only for its ability to inhibit cancer cell growth and induce the death of cancer cells, but also for its immune-supporting effects, which could enhance anti-cancer responses.

[0081] Several challenges currently limit the clinical use of siRNA-based therapies, including difficulties in delivering siRNA specifically to target cells, low uptake levels within these cells, and rapid degradation of siRNA by exonucleases and RNases. Another major concern is the off-target effects of siRNA, which silence unintended RNA targets, potentially leading to adverse outcomes15. Introducing chemical modifications in siRNAs evolved as a strategy to improve the stability of small RNAs by reducing the impact of nuclease induced degradation16, 17. The chemical modifications can be introduced to the 5'- or 3'- terminus, backbone, sugar, or in the nucleotide bases of siRNAs17, 18. Among the chemical modifications, phosphorothioates (PS), 2'-(9-methylation (2'-0-Me), 2'- O-allyl, 2'-deoxy -fluorouridine and locked nucleic acid (LNA) forms were known for improving the stability of siRNA for therapy. LNA modification is a bicyclic nucleic acid where a ribonucleoside monomers is linked between the 2’-oxygen and the 4’-carbon atoms with a methylene unit19In contrast to other modifications, the LNA modifications have been reported to substantially increased the potency and activity of siRNAs in both in vitro and in vivo studies with minimal toxicity20, 21, 22,23. Another challenge in the RNAi research is the development of efficient and safe delivery systems. Recent advances, such as GalNAc conjugates and lipid nanoparticles (LNPs), have emerged as effective strategies for encapsulating siRNAs in ionizable lipids for delivering them intracellularly for target gene knockdown24, 25.

[0082] Although many RNAi studies were reported anti-tumor effects of siRNAs in vitro and in vivo, not many of them were advanced through clinical trials for cancer. This drawback was mainly due to the non-specific targeting of siRNAs on other RNAs and their effects in non-tumor cells. Therefore, it is required to validate the effects of siRNAs in whole tumor tissues comprehensively using advanced technologies like scRNA-seq. However, scRNA-seq has not yet been fully utilizedAtty. Dkt. No. 650053.01226 in the current drug discovery approaches including siRNA therapy to evaluate the effects of drugs broadly in all cell populations in the tumor tissues.

[0083] Ovarian cancer is a peritoneally progressing cancer where the tumor cells shed into the peritoneal cavity, then circulates through ascites fluid and undergo transcoelomic metastasis a.k.a. peritoneal seeding26-27. Consequently, tumor cell clusters and spheroids isolated from ascites are considered as a representative model of studying transcriptomic signatures of advanced-stage ovarian cancer28. Given to the nature of ovarian cancer, high throughput studies have utilized these ascites-derived clusters and spheroids to perform transcriptomic analyses at the single-cell level, providing insights into tumor heterogeneity and microenvironmental interactions29 ?0-31. In line w ith those strategies, the objective of this study is to develop siRNAs incorporating LNA modifications to enhance their stability and target knockdown efficiency along with approaches to evaluate the therapeutic impact of FXR1 -targeting siRNAs using scRNA-seq.

[0084] Results

[0085] Sequence specific screening identified siRNAs with enhanced FXR1 silencing and subsequent cell growth and apoptotic effects

[0086] siRNAs bind to complementary mRNA sequences to inhibit gene expression. Thus, each target sequence is expected to exhibit varying levels of gene silencing. Therefore, we designed five siRNAs numbered as seql to seq5 (Table 1), which specifically target coding sequences (CDS) or the sequences in untranslated region (UTR) of FXR1 gene as marked in FIG. 8a. First, we used siRNAs (siFXRl) at two different concentrations 2.5nM and 5nM and the respective control (scrambled) siRNA (siCont) at 5nM and found that the transfection of seq2 and seq3 siRNAs, targeting the CDS exhibited -70% to -85% inhibition of FXR1 protein in ovarian cancer cell lines (FIG. la). While we observed -80% inhibition of FXR1 protein by seq5 in HeyA8 and OVCAR8 cells, the level of inhibition was only -50% in the Kuramochi cell line. In contrast, the seql and seq4 sequences exhibited low level inhibition of FXR1 compared to other sequences (FIG. la). In brief, we observed CDS-targeting siRNAs demonstrated superior level of inhibition of FXR1 compared to the sequences targeting non-CDS region (FIG. 8a and FIG. la).

[0087] Next, we determined the knockdown effects of all the five siRNAs at its lowest effective concentration 2.5nM on cell cycle phases using flow cytometry. Similar to the sequence specific effects of siRNAs on FXR1 inhibition (FIG. la), seq2 and seq3 exhibited most profound effect on G1 phase arrest and a reduction in S phase (FIG. 8b). Similarly, those sequences inhibited G1 -phase proteins CDK2. CDK4. CDK6. Cyclin DI and Cyclin El levels, most effectively compared to the other sequences (FIG. 8c). In conjunction, seq2 and seq3 FXR1 siRNAs induced cellular apoptosisAtty. Dkt. No. 650053.01226-70% with reduced BCL2 and an increase in PARP cleavage compared to control siRNA (siCont) (FIG. 8c, d). In agreement with the level of FXR1 knockdown, a modest level in the increase in apoptosis was only observed with seql, seq4 and seq5 (FIG. 8d). We and others have reported that cMYC is a key target of FXR19, 32Supporting this notion, cMYC protein level was also inhibited mostly by seq2 and seq3 siRNAs (FIG. 8c). Similarly, seq2 and seq3 siRNAs also inhibited colony forming ability of ovarian cancer cells (FIG. 8e).

[0088] FXR1 siRNA preferentially inhibits the growth of FXRl-high expressing cancer cells compared to normal cells

[0089] One of the key challenges of siRNA therapy for cancer is due to its uptake by normal cells, that leading to both targeted and non-specific effects. Therefore, it is crucial to assess the growth-inhibitory effects of FXR1 siRNA specifically in cancer cells, ensuring minimal harm to non-tumor cells along with immune cell activation. Therefore, we used the most potent siRNAs (seq2 and seq3) to validate their effects on tumor grow th inhibition and apoptosis by transfecting in both normal and cancer cells independently or in co-culture. In conjunction with FXR1 mRNA expression data (FIG. 9a), the transfection of FXR1 siRNA effectively inhibited the growth of tumor cells, which express high levels of FXR1. In contrast, the normal cells that express low' levels of FXR1 expression were unaffected by FXR1 siRNA. This data suggests that the growth-inhibitory effects caused by seq2 and seq3 siRNAs are primarily driven through target-specific inhibition of FXR1 (FIG. 9b). Next, we employed a co-culture model where GFP-labelled OVCAR8 cells expressing high levels of FXR1 co-cultured with RFP-labeled normal ovarian surface epithelial cells (OSE) or fallopian tube epithelial cells (FTE) expressing very low levels of FXR1 in a single well. As expected, treatment with FXR1 siRNAs reduced the overall GFP signal, indicating inhibition of tumor cell growth, while the unchanged RFP signal reflected that non-tumor cells express low levels of FXR1 were not affected by FXR1 siRNA treatment. (FIG. lb, and FIG. 9a, c).

[0090] We also conducted a second co-culture assay, where GFP-labelled OVCAR8 cells incubated with normal OSE or FTE cells. Upon reaching 80% confluence, w'e transfected the cocultures of OVCAR8-GFP / OSE and OVCAR8-GFP / FTE either with siFXRl (seq3) or respective control siRNAs, then GFP signal was quantitated for tumor growth in two days interval up to 6 days. This assay also demonstrated a decrease in the overall percentage of GFP signal from OVCAR8 cells without affecting the viability of non-FXRl overexpressing OSE when comparing siFXRl - transfected cells to the control siRNA group (FIG. 9d).

[0091] LNA form of siRNA improved the level of FXR1 silencing and augmented cancer cell death compared to native siRNAAtty. Dkt. No. 650053.01226

[0092] Based on the reports that LNA modifications can improve gene silencing potency with minimal toxicity20’21, 22, 23, we introduced LNA modification at the 3 ’site as described (FIG. 1c, d) as shown in both seq2 and seq3 (hereafter referred to as siFXRl -2-LNA and siFXRl -3-LNA respectively). We then evaluated whether this modification enhanced their growth inhibitory effect in cancer cells. Remarkably, the LNA-modified version of seq3 (siFXRl-3-LNA) achieved over 90% FXR1 knockdown at just 0.5 nM; whereas such effect was obtained only with 2 nM of the unmodified siRNA (FIG. le). Compared to siFXRl-3-LNA, LNA modified version of siFXRl-2 (siFXRl-2-LNA) was not able to exert such superior activity in knocking down FXR1 in its low concentrations.

[0093] In conjunction, siFXRl-3-LNA was again able to cause G1 arrest more prominently and reduced G2 / M phase than native form of siFXRl-3 in both Kuramochi and OVCAR8 cells (FIG. 10a) Proteins associated with cell cycle regulators such as Cyclin DI, Cyclin El, CDK2, CDK4, CDK6, cMYC and BC12 were also inhibited predominantly by siFXRl-3-LNA than its native form. In contrast, the inhibition induced by siFXRl-2-LNA was less effective in comparison with siFXRl- 3-LNA on inhibiting above cell cycle regulators (FIG. 10b). Similarly, a subsequent increase was observed in the levels of cleaved PARP, caspase 3 / 7 activity, and cellular apoptosis when OVCAR8 and Kuramochi cancer cells were transfected with LNA-modified siFXRl-3 compared to its native form (FIG. lOb-e) Our comet assay33, 34also demonstrated a markable increase in DNA damage potentially due to cellular apoptosis in ovarian cancer cells, particularly when the cells were transfected with siFXRl-3-LNA compared to the unmodified form (FIG. If)

[0094] LNA form of FXR1 siRNA demonstrated superior cellular and tissue uptake with improved stability over nucleases

[0095] The primary object of this study is to assess the therapeutic effects of LNA-modified FXR1 siRNA on tumor growth inhibition via FXR1 silencing in preclinical models. Therefore, we sought to use an intermediary approach of 3D culture model that connects traditional 2D cultures and in vivo systems. Ovarian cancer cells were cultured on an extracellular matrix to form tumor spheroids, allowing us to simulate in vivo tumor growth and assess the growth-inhibitory effects of FXR1 siRNA more accurately. Similar to its effect in 2D culture (FIG. 1), siFXRl-LNA was able to inhibit the growth of ovarian cancer spheroids more efficiently than native siRNAs (FIG. 2a). Furthermore, high level uptake of siFXRl-LNA was also observed by tumor spheroids compared to native siRNA (FIG. 2b).

[0096] Once internalized, siRNA is often trapped in the endosome and transported to the lysosome, where it gets degraded by lysosomal enzymes quickly, significantly reducing itsAtty. Dkt. No. 650053.01226 effectiveness35-36. Therefore, we decided to determine whether LNA modification can rescue siRNA from lysosomal degradation. Herein, we used Texas red labeled siRNAs of both native and LNA forms and transfected into cancer cells and the cellular uptake levels were determined by imaging (FIG. 2c). Strikingly, we observed high level of siFXRl-LNAs uptake within Ihr after transfection in two different cancer cell lines Kuramochi and 0VCAR8, whereas only modest level of siRNA uptake was observed when cells were transfected with native siRNA (FIG. 2c and FIG. Ila). Consistently, siFXRl-LNAs showed minimum localization within lysosomes, suggesting reduced lysosomal degradation. In contrast, native siRNAs displayed a strong lysosomal accumulation compared to LNA form (FIG. 2c and FIG. Ila). This data suggests that LNA modified siRNA exhibits greater stability and can evade lysosome mediated degradation. Our Terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assay also showed an increase in the level of cellular apoptosis when siFXRl-LNA transfected cells compared to those transfected with native siRNA (FIG. 2d and FIG. 11b). These findings led us to investigate whether LNA modification protects siRNA from RNase activity and if encapsulating LNA form siRNA in nanoparticle further enhance its stability. Here, we used polyethylenimine (PEI) nanoparticle for encapsulation of siRNA and found that unmodified siRNA either in free or in encapsulated form were degraded rapidly compared to LNA-modified siRNA (FIG. 2e). Notably, PEI encapsulation of siFXRl-LNA enhanced its stability, and demonstrated least degradation in the presence of RNase (FIG. 2e)

[0097] We also used serum as a physiologically relevant source of exonucleases and RNases (ribonucleases) to assess w ether LNA modification and PEI encapsulation protects siRNA from RNases mediated degradation. Consistent with the earlier results, LNA modifications in siRNAs improved the stability over native siRNAs, and this stability was further enhanced upon encapsulation in PEI nanoparticles (FIG. 21). Next, we examined whether siFXRl-LNA exhibits improved uptake in tumor tissues compared to normal organs when injected into tumor- bearing mice. As anticipated, siFXRl-LNA showed enhanced tissue uptake in peritoneal tumors and tumors at organ sites, with minimal uptake in tissues devoid of tumor growth (FIG. 2g). Specifically, high level of siRNA uptake was observed in tumor tissues and ovaries with tumor presence, whereas no uptake was detected in lungs, and heart, which were free of tumor grow th. Uptake was also very minimal in the liver, kidneys, and spleen, where minimal tumor presence was observed (FIG. 2g). Similarly, immunofluorescence of tumor tissue also confirmed higher level of siFXRl-LNA in tumor tissues compared to native siFXRl (FIG. 2h). Collectively, our findings demonstrate that LNA modification of FXR1 siRNA not only protects FXR1 -siRNAs from RNAse and nucleases.Atty. Dkt. No. 650053.01226 but also enhances its tumor-specific uptake, suggesting improved therapeutic potential for treating cancer in preclinical models.

[0098] The in vivo administration of LNA-modified FXR1 siRNAs demonstrated a superior level of inhibition in the growth and metastasis of ovarian cancer cells

[0099] In this aim. we delivered LNA-modified siFXRl or its native form complexed with PEI intraperitoneally (IP) to mice bearing ovarian cancer cells. Briefly, OVCAR8 cells were injected IP in female athymic nude mice and siRNA encapsulated in PEI were delivered into the mice twice a week for five weeks after one week of tumor inoculation as depicted in the schema (FIG. 3a). Control group of mice were treated wi th LNA modified scrambled siRNA encapsulated in PEI as above. Bioluminescence imaging was performed once a week to monitor tumor growth. Notably, mice were treated with native siFXRl showed a markable reduction in the overall tumor growth, whereas LNA modified siFXRl displayed greater level of reduction in the overall tumor growth compared to the native form of siRNAs (FIG. 3b-d).

[0100] To evaluate the silencing effect of the siRNA complex in vivo, we isolated proteins from the tumor specimen and evaluated the protein expression of FXR1 and its target MYC oncogene by Western blot. As shown in FIG. 3e, all the tumors treated with the siFXRl -LNA exhibited high level inhibition of FXR1 and MYC protein compared to the PEI encapsulated siCont-LNA treated group. Next, we validated the target specific effect of FXR1 siRNA on the downstream effectors of apoptosis in tumor tissues isolated from each group of mice were treated with control, native or LNA-modified siRNAs by immunohistochemistry (IHC) analysis. Our IHC of tumor tissues demonstrated that LNA-modified FXR1 siRNA exhibited a robust effect on inhibiting Ki67 proliferation marker levels and a subsequent upregulation in the levels of apoptosis marker cleaved- caspase 3 (FIG. 31). TUNEL assay was also demonstrated an extensive TUNEL staining as an indication of cell death in the tumors isolated from mice treated with siFXRl-LNA compared to native siFXRl and siControl (FIG. 11c).

[0101] Next, we validated the tumor inhibitory effects of siFXRl -LNA in a subcutaneous xenograft model using a highly aggressive triple-negative breast cancer cell line MDA-MB-231 which express high levels of FXR1 (FIG. 3g, FIG. lid). Consistently. siFXRl-3-LNA demonstrated more effective knockdown of FXR1 and its downstream target MYC in MDA-MB- 231 cells compared to siFXRl -2-LNA (FIG. lie). We selected a TNBC model due to its genomic similarities with High-Grade Serous Ovarian Carcinoma (HGSOC) including frequent TP53 and BRCA mutations, high genomic instability and the prolific growth and metastatic behavior of MDA- MB-231 cell line.Atty. Dkt. No. 650053.01226

[0102] Consistent with the response observed in 0VCAR8 tumors, systemic retro-orbital injections of siFXRl-LNA also significantly inhibited tumor growth of MDA-MB-231 tumors compared to the unmodified siFXRl treatment (FIG. 3h-3j). Furthermore, histological analysis of lymph nodes used as indicators of early metastasis also revealed no signs of metastasis in the mice were treated with siFXRl -LNA unlike those were treated with control siRNA-treated mice (FIG. 3k). We further examined whether the delivery of native or LNA modified FXR1 siRNA causes any tissue damage or associated toxicity by performing H&E-staining of sections of liver, lung, heart, and kidney. Notably, neither form FXR1 siRNA induced any observable changes in tissue histology compared to the respective control, indicating no detectable tissue damage associated with cellular toxicity (FIG. 111). We also assessed key enzymatic and protein for liver and kidney functions including aspartate Aminotransferase (AST); Alanine Aminotransferase (ALT); Alkaline Phosphatase (ALP); Total Bilirubin (TBIL); Total Protein (TP) and found that delivery of both native and LNA modified FXR1 siRNA caused no significant changes in the levels of these markers (Table 2).

[0103] Taken together, results from our in vitro and in vivo models, along with toxicity assessments, demonstrate that LNA-modified FXR1 siRNA effectively inhibits tumor growth and metastasis by silencing its target FXR1 with minimal or no adverse effects on tissue integrity or organ functions.

[0104] Single-cell transcriptome profiling demonstrated an anti-tumor immune response upon LNA-modified FXR1 siRNA delivery

[0105] One of the major challenges of translating RNAi-based therapies in clinical practice is the risk of immune cell toxicities and unintended effects on stromal components within the tumor microenvironment (TME). Therefore, we performed scRNA-seq method to assess whether any adverse effects on transcriptomic changes induced by RNAi treatment in both tumor cells and the cells in TME comprehensively. For this goal, we used both native and LNA-modified forms of FXR1 -targeting siRNAs (seq2 or seq3) to knockdown FXR1 in mouse ovarian cancer cell lines, where seq2 showed 92% sequence complementarity and seq3 showed 100% complementarity' with mouse FXR1 mRNA (FIG. 12a). Consistent with the target knockdown effects in human cell lines and high level sequence complementarity, seq3 siRNA showed superior level of FXR1 inhibition in two mouse ovarian cancer cell lines Br-Luc (genotype: p53- / -; brcal- / -; myc; Akt-myr) and Cl l (genotype: p53- / -; myc; KrasG12D)37. Markedly, the LNA-modified versions exhibited more robust inhibition of FXR1 levels compared to unmodified versions (FIG. 12b).

[0106] Atty. Dkt. No. 650053.01226

[0107] Br-Luc cells were then selected because of its mutational similarity with human HGSOC for establishing an immunocompetent syngeneic model of ovarian cancer by IP injection of Br-Luc cells in immunocompetent FVB mice38Mice were then treated with siCont-LNA or siFXRl -LNA encapsulated in PEI nanoparticles (10 pg / mouse) twice a week for five weeks (FIG. 12c). In conjunction with our human xenograft model, we observed a significant reduction in both tumor weight and ascites formation when the mice were treated with PEI encapsulated siFXRl-LNA (FIG. 12d-f). We also observed siFXRl-LNA treatment improved the survival of Br-Luc ovarian cancer bearing mice compared to the control siRNA-LNA treated group (FIG. 12g).

[0108] Ascites samples from tumor-bearing mice treated with the siCont-LNA and siFXRl -LNA were used for scRNA-seq, followed by clustering and CellChat analysis to delineate the role of various cell populations within the TME on tumor progression (FIG. 4a). It has been reported by other scRNA-seq experts that ascites represents a clinically valuable source of transcriptional information of both tumor cells and tumor-associated immune and stromal cells29, 30. These cells can be isolated through minimal invasive procedures, and cell clusters within ascites can be more readily and easily dissociate into single cells compared to solid tumors. Moreover, ascites often reflects advanced metastatic disease and immunosuppressive signaling, providing critical insights into mechanisms of how tumors escape from immune surveillance or therapies39. In brief, 16851 high- quality cells (-11621 cells from siCont-LNA and -5230 cells from siFXRl-LNA group) were selected for generating single-cell transcriptomic profiles (FIG. 12h).

[0109] The cell clusters were then visualized using Uniform Manifold Approximation and Projection (UMAP) for the integrated duplicates performed at a resolution of 0.1 annotation level according to sample type with differentially expressed genes (DEGs) (FIG. 12i). Integrative analysis identified 11 clusters of cells in the murine TME components in the ascites (FIG. 4b and FIG. 12j). Among the cell types, macrophages (cluster 0), epithelial cells (clusters 1, 4), T cells (cluster 3), NK cells (cluster 7), and DCs (cluster 8) showed high level differences between clusters among siCont- LNA and siFXRl -LNA groups (FIG. 4b and FIG. 12j). Overall, the composition of cell clusters was variably influenced by siFXRl -LNA treatment compared to the siCont-LNA group (FIG. 4c).

[0110] Interestingly, we observed a notable reduction in epithelial cells and a substantial increase in DCs, NK, and T cells in the siFXRl -LNA treated group (FIG. 4c), indicating enhanced immune cell infiltration and a decrease in overall tumor growth potentially due to the direct inhibition of FXR1 in tumor cells as well as the effect through improved immune cell infiltration. While we identified distinct markers among the cells belong to main clusters in FIG. 4b-d, further analysis identified considerable heterogeneity among the cells present in each cluster. For example, cluster 0Atty. Dkt. No. 650053.01226 represents macrophage populations since many of the cells in this cluster express genes like, Cd68, Argl. Adgrel, Apoe and Lyz2 (FIG. 4c, d and FIG. 12j) but considerable level of heterogeneity was observed in this population. Likewise, clusters 1 and 4 were annotated as epithelial cells (tumor cells) based on high level of expression of Krtl 9, Krtl 8, Krt8, Epcam and Mucl 6 in those population (FIG. 4c, d and FIG. 12j) Cells in cluster 3 were identified as T cell based on Left, Cd3e, Cd3g, Cd3d. Cd4 and Cd8a and cluster 5 was determined as B cell based on Cdl9, Bankl, Ebfl, Igkc and Ighm expression (FIG. 4c, d and FIG. 12j). Cluster 7 showed expression of canonical markers of NK cells expressing Gzma, Ccl5, Nkg7, Ncrl and Ilr2b while cluster 8 was classified as DCs due to the presence of Siglech, Cd74, Grm8, Bell la, Itgae, and Clec9a (FIG. 4c, d and FIG. 12j). Clusters 9 and 10 were relatively small population and marked as mast cells and fibroblast respectively (FIG. 4c, d and FIG. 12j)

[0111] Because we identified a considerable decrease in the numbers of epithelial tumor cells and an increase in immune cells (clusters 0, 1, 3, 4, 7 and 8, FIG. 4b-d), we performed CellChat analysis to determine the potential ligand-receptor interactions among cell types40. Notably, the interactions between tumor cells to macrophages and other immune cells were very high in the control group, which significantly reduced upon siFXRl-LNA treatment (FIG. 4e and FIG. 12k). Furthermore, communications of T and NK cells with tumor cells were greatly enhanced upon siFXRl-LNA treatment compared to the control suggesting an anti -tumor response mechanism. In addition to T and NK cells, an increase in the interaction between DCs, B cells and tumor cells was observed in the siFXRl-LNA group (FIG. 4e and FIG. 12k). This data prompted us to determine the level of cellular interaction by quantitating the magnitude of interaction between ligands and receptors expressed by each cell population using CellChat analysis.

[0112] In the CellChat all the ligand-receptor interactions were grouped into ECM-receptor interaction, secreted signaling, and cell-cell contact. We found that ECM-receptor signaling is downregulated and secreted signaling and cell-cell contact signaling are up-regulated in the siFXRl- LNA treated group compared to the siCont-LNA group (FIG. 13a). Mostly the ECM signaling regulated through collagen, laminins, and fibronectin were predominant in the control group, where they potentially act as an immunosuppressive signaling through paracrine mechanism or as an oncogenic signaling in tumor cells through autocrine mechanism. In contrast, such signaling was not present in the siFXRl-LNA treated group. Specifically, collagens (encoded by7Col4al, Col4a2, Col4a5, and Col4a6), laminins (Lama3 and Lamcl), and fibronectin (Fnl) were expressed by epithelial cells and the receptor partner such as various integrins, Cd44, and Sdc4 were observed in tumor cells, and immune cells in the control group (FIG. 13b). Other ECM-related outgoingAtty. Dkt. No. 650053.01226 signaling from macrophages, involving Fnl and its interactions with integrins, Cd44, and Sdc4 receptors, were observed in both siFXRl-LNA and siCont-LNA treated groups (FIG. 13b).

[0113] We also observed a gain in cell-to-cell contact signaling through MHC-I / IT signaling components such as H2-t23, H2-aa, H2-abl, H2-dma, H2-ebl, H2-oa and H2-ob among immune cells with notable magnitude from macrophages, DCs, B cells in partnership with T and NK cells mainly in the siFXRl-LNA treated group. In contrast we did not observe such interactions in the siCont-LNA group (FIG. 13c). In sum, this data suggests that macrophages, DCs, and B cells primarily functioned as antigen-presenting cells (APCs) and deliver MHC-II molecules to T and NK cells for anti-tumor responses (FIG. 13c). Similarly, the control group showed low expression of ligands like Cd401g, Cd80, and Cd86 with their respective receptors Cd40 and Cd28, which are important for activating T and NK cells (FIG. 13c). In contrast, APCs like macrophages, B cells, and DCs in the siFXRl-LNA group exhibited robust Cd80-Cd28 and Cd86-Cd28 interaction, suggesting that T cells and NK cells are the primary recipients of signals from APCs, which again confirmed the existence of strong anti -tumor effects upon siFXRl-LNA treatment (FIG. 13c). Likewise. Cd40-Cd401g interaction was also observed in high level in the siFXRl-LNA group (FIG. 13c), which is known for T cell proliferation, survival, and differentiation, as well as for enhancing the antibody production capabilities of B cells as reported before41.

[0114] 11-18 interactions with Il-18rl and 11-8 receptor accessory protein (Il-18rap) through macrophages to NK and T cells act as the recipients were also observed high in the siFXRl-LNA group suggest 11-18 mediated activation of NK and T cells (FIG. 13d). Tgf-(3-associated cellular interact ons, such as Tgfbl signaling through the Tgfbrl and Tgfbr2 receptors, as well as Tgfbl signaling through the Acvrl and Tgfbr2 receptors as immune cell activation, were also observed high in the siFXRl-LNA treated group (FIG. 13d).

[0115] In vivo silencing of FXR1 inhibited oncogenic mechanisms and tumor growth subsequently

[0116] scRNA-seq analysis identified that the control siRNA treated group had a large number of epithelial cells that includes tumor cells, whereas siFXRl-LNA treatment reduced the numbers of epithelial cells (FIG. 4c). Considering that the epithelial cells could consist of both tumor cells and nonmalignant epithelial cells, we used the CopyKAT algorithm42to identify tumor cells based on aneuploid status, determined by copy number variation (CNV). As expected, the proportion of tumor cells (aneuploid) were very high over normal epithelial cells (diploid) in the control group, whereas the aneuploid cell numbers were markedly diminished without affecting diploid cells when treated with siFXRl-LNA (FIG. 4f).Atty. Dkt. No. 650053.01226

[0117] Further analysis of Fxrl in the aneuploid cells showed a notable reduction in Fxrl expression upon siFXRl-LNA treatment (FIG. 14a). which again confirmed that our siRNAs are specifically silencing FXR1 in tumor cells. Additionally, transcriptome profile of cell cycle phase also showed a decrease in S phase cells and an increase in G1 phase genes in siFXRl-LNA treated group compared to those treated with control siRNA (FIG. 4g). We also observed down-regulation of tumor cell markers, including Epcam, Mucl6, Krtl9, Krtl8, and Krt8, following siFXRl-LNA treatment (FIG. 4h). Furthermore, a significant downregulation of genes associated with G1 -phase such as Ccndl and Cdk4, along with a notably upregulation of the cell cycle arrest gene Cdknlb (p27Kipl) were observed in the cells belongs to the siFXRl-LNA treated group (FIG. 4h). We also observed a significant decrease in the expression of the apoptosis-related gene Parpl, along with an increase in the expression of Casp3 and Casp8 upon FXR1 silencing (FIG. 4h). A reduction in the expression of the proliferation gene MKi67 (FIG. 4h) and genes associated with DNA replication such as Top2a and Mcm6 were also observ ed upon siFXRl-LNA treatment (FIG. 14b). Eukary otic translation-related genes Eif4gl and Eif4e, which are the direct targets of FXR1 were also markedly reduced after siFXRl-LNA treatment (FIG. 4h). Most importantly, Fxrl expression was significantly downregulated in siFXRl-LNA treated epithelial cells compared to those treated with control siRNA (FIG. 14c), again confirmed the specificity of siFXRl-LNA on silencing FXRlin tumor cells.

[0118] Ingenuity pathway analysis (IP A) of epithelial cluster genes further revealed enrichment of gap junction signaling, cell cycle control of chromosomal replication, cell cycle regulation etc., in the siFXRl-LNA group compared to control (FIG. 14d). Consistent with our previous work reported the role of FXR1 in oncogenic translation mechanism9, we observed FXR1 silencing significantly suppressed the expression of genes involved in translation initiation, elongation and termination in the tumor cells compared to the controls (FIG. 14d). Pathways related to mTOR. Keap-Nfe212, and PPAR family signaling pathways, which are crucial for oncogenic metabolism43,44, 45were also dow nregulated upon treatment with si-FXRl-LNA (FIG. 14d).

[0119] In vivo silencing of FXR1 resulted into the polarization of macrophages and increased infiltration of DCs exhibiting anti-tumor characteristics

[0120] Tumor associated macrophages (TAMs) are known for their effects in cancer progression and metastasis46, 47, 48, 49, 5°. TAMs are also known for inducing immune suppressive effects on T cells and NK cells by modulating their functions either by secreting anti-inflammatory cytokines, chemokines or by modulating the functions of immune checkpoint proteins51, 52, 53, 54Notably, our primary analysis identified macrophages as the dominant cell population in cluster 0 comprisingAtty. Dkt. No. 650053.01226-35% of the total cell population (FIG. 4b, c). UMAP clustering of this population at 0.1 resolution generated about 3 distinct clusters as M l -like. M2-like, and Ml / M2 / monocyte mixed lineage population in the siCont-LNA and siFXRl-LNA groups (FIG. 15a, FIG. 5a, b). In brief, cluster 0 were designated as M2-like TAMs with high expression of Argl, Cdl63, Mrcl, and Adgrel and cluster 1 was identified as Ml -like macrophages expressing anti -tumor factors including Ccl2, Ccl3, Ccl7, Cxcl9, CxcllO, and Cxcll6 (FIG. 5a, b). The remaining cells in cluster 3 was identified as mixed lineage of Ml / M2 / monocyte with the presence of monocyte markers LyzL Ly6c2, and Cdl4 along with Ml and M2 markers (FIG. 5a, b).

[0121] Next, we examined the expression of Ccl2 and its receptor Ccr2, as well as Ccl7, CxcllO, Ccl5, and its receptor Ccr5 in each macrophage subtype. Ml -like macrophages (cluster 1) exhibited significantly higher expression of these genes compared to M2-like macrophages (cluster 0), which facilitates the recruitment and activation of T cells (FIG. 15b) While tumor promoting M2-like macrophage populations were enriched over Ml -like macrophages in the control group, siFXRl- LNA treatment resulted an enrichment of Ml -like macrophages with less abundance of M2-like macrophages (FIG. 5c and FIG. 15c). To further characterize the macrophage population in detail, we computed Ml -like and M2-like signatures score using gene signature scores based on gene sets derived from CIBERSORT55. These scores w ere then integrated to generate module scores using the AddModuleScore function. As anticipated, the Ml -like macrophage signature was significantly higher and the tumor promoting M2 macrophage signature scores were very low in the siFXRl-LNA treated group compared to the controls (FIG. 5d). To further validate the transcnptomic data identified by scRNA-seq, we assessed the protein levels of M2 macrophage markers using flow cytometry' and immunofluorescence. Consistent with the scRNA-seq data, flow cytometry' revealed enrichment of macrophages with M2-like markers Mrcl, Cd 163 and Pdll in the control group, while siFXRl-LNA treatment significantly reduced the expression of these markers significantly (FIG. 5e, and FIG. 15d) We also observed a significant decrease in Pdll+TAMs in the siFXRl -LNA treated group, which again confirms the anti -tumor effects of siFXRl-LNA (FIG. 5e, and FIG. 15d) Immunofluorescence of tumor tissues further confirmed a decrease in the infiltration of M2 macrophages as evidenced by low expression of Argl and Mrcl in the tumor samples isolated from mice were treated with siFXRl-LNA compared to the controls (FIG. 15e).

[0122] Next, we analyzed the dendritic cells (DCs), which are known as the sentinels of the immune system and could be modulated for immunotherapeutic treatment strategies56. Thus, we analyzed the population of DCs for their antigen-presenting capabilities such as recognizing, processing, and presenting "threat signals" obtained upon siFXRl-LNA treatment. Our analysisAtty. Dkt. No. 650053.01226 identified distinct expression profiles of DCs isolated from mice treated with control siRNA and siFXRl LNA (FIG. 151). Notably, DCs expressing high levels of genes associated with DC maturation and migration namely Cd74, Cd80, Ccr7, Cd83, Cd86 were observed in the group treated with siFXRl-LNA (FIG. 51). Because these cells express a specific gene signature for DC activation and maturation, we performed a more detailed subcluster analysis and found three distinct subclusters of DCs in the tumor (FIG. 5g). Cluster 0 was identified as the monocyte derived DCs (MoDCs) expressing Cst3, Mrcl and Argl genes, cluster 1 as plasmacytoid DCs (pDC) expressing Bell la, Siglech, Bst2 and Ly6d and cluster 2 as type I conventional DCs (cDCl) expressing Btla and Clec9a (FIG. 5g-j). We also observed that the ratio of MoDCs, a subset of DCs that differentiate in response to inflammatory stimuli and are recruited to inflammatory sites such as the TME, was significantly reduced in siFXRl -LNA treated sample groups (FIG. 5h). Importantly, the proportion of pDCs, which promote anti-tumor immunity via type I interferons (IFN-I)57, 58, and facilitates cDCl maturation to enhance Cd8+T cell and NK cell cytotoxicity59, was significantly increased in the tumor samples from mice treated with siFXRl -LNA (FIG. 5h). However, no significant changes were observed in the cDCl population (FIG. 5h).

[0123] Next, we performed CellChat analysis to investigate the interactions between pDC and NK cells as well as Cd8+and Cd4+cytotoxic T cells, to assess their impact within TME. In the siFXRl-LNA group, pDC ligands (Klrbla, Klrblb, Klrblc, Klrblf) were found to interact with with Clec family receptors on NK cells (FIG. 15g). These interactions are expected to enhance NK cell activation and functionality, promoting the recognition and destruction of tumor cells60. Additionally, pDCs which known as for APCs, providing signals to Cd8+and Cd4+cytotoxic T cells through interactions with MHC class I and II receptors were also predominant in the siFXRl -LNA group (FIG. 15g). Overall, our analysis demonstrates that these pDCs-mediated interactions, which are important for bridging innate and adaptive immunity, facilitating T cell priming and activation in the presence of tumor antigens were enhanced upon siFXRl -LNA treatment.

[0124] siFXRl-LNA treatment improved infiltration of cytotoxic T and NK cells in vivo

[0125] Our primary analysis showed an increase in T and NK cell populations in samples treated with siFXRl -LNA compared to those treated with control siRNA (FIG. 4c). Unsupervised clustering based on expression of Cd3d, Cd3e, and Cd3g for tumor-infiltrating lymphocytes (TILs) and Nkg7 for NK cells identified six distinct T cell clusters and three NK cell clusters in our sample sets (FIG. 6a, FIG. 16a). Specifically, our T-cell subtyping identified subclusters 0 and 1 as naive Cd4+and Cd8+T cells (Lefl+, Tcf . Sell4, Ccr7+), while subclusters 2 and 3 were characterized as cytotoxic Cd4+and Cd8+T cells (Nkg7+and Gzmb+). Subcluster 4 included a small fraction of Cd4+Atty. Dkt. No. 650053.01226 exhausted T cells / Tregs (Tigit / Foxp3+), and subcluster 5 was identified as effector memory Cd47Cd81T cells (Isg 151) (FIG. 6b). Quantification of all cell populations in both groups detected abundance of Cd4+T cells over C'd8 T and other T cell population following FXR1 siRNA treatment (FIG. 6c). Most strikingly, we observed a shift in the overall population of naive Cd4+T cells and Cd8+T cells along with cytotoxic form of Cd4 T cells and Cd8+T cells. In brief, we found a decrease in naive Cd4+T cells and Cd8+T cells. In contrast, we found an increase in the enrichment of Cd8+T cells and Cd4+T cells with cytotoxic function indicated by the marker genes Nkg7, Prfl, and Gzmb upon FXR1 siRNA treatment (FIG. 6d and FIG. 16b).

[0126] We also identified a small cluster of Cd4+T cells that express markers associated with exhausted T cells and Tregs in our T cell clustering (cluster 4; FIG. 6a, b). However, we did not observe any significant differences in the proportions of Cd4+Treg cells between the siFXRl-LNA and control groups (data not shown). In complement to scRNA-seq analysis, our IHC analysis of tumor tissue samples were also demonstrated high levels of T cell infiltration in the tumor tissues upon FXR1 silencing compared to controls (FIG. 6e). Additionally, flow cytometry analysis of the ascites samples collected from the mice treated with control or FXR1 siRNA also exhibited an increase in Cd4+and Cd8+T cells upon siFXRl -LNA treatment compared to the siCont-LNA group (FIG. 6f, and FIG. 16c). Overall, our findings demonstrate a substantial increase in total T cells, particularly an increase in the cytotoxic forms of Cd4+, Cd8+T cells in the tumor bearing mice treated with siFXRl -LNA.

[0127] Next, we performed Cell Chat analysis40to determine cell-cell communication analysis between cytotoxic Cd8+and Cd4+T cells populations with macrophages and with tumor cells (epithelial cells), which identified numerous interactions between macrophages and tumor cells with T cells (FIG. 16d). Among them, the interaction of Ccl5 ligand with its receptor Ccrl and Ccr5 between Cd8 cytotoxic and Cd4 cytotoxic T cell subtypes. Ml- and M2-like macrophages and tumor cells were observ ed high as a mechanism of T cell mediated cell death in the siFXRl -LNA treated group compared to the control (FIG. 16d). We also found that the interaction of adhesion molecules such as Icaml with Itgal, Itgab2, and Itgam, along with Thyl's interaction with Adgre5, Itgam, and Itgb2 between macrophages and tumor cells with T cells were observed only in the siFXRl -LNA group as a potential mechanism of T cell activation and recruitment of macrophages into tumor sites for the elimination of tumor cells (FIG. 16d) We also observed prominent interactions between Cd401g with Itga5, Itgam, Itgb2 and Cd40, which are critical for T cell activation, and T cell mediated anti-tumor immune response in siFXRl-LNA group (FIG. 16d).Atty. Dkt. No. 650053.01226

[0128] Cell Chat analysis also identified other ligands and receptor interactions within M1 / M2 macrophages and CdS cytotoxic and Cd4 cytotoxic T cell subtypes majorly through interaction with MHC-I / II signaling genes (such as H2-dl, H2-aa, H2-kl, H2-dma, H2-m3 and H2-t23) in siFXRl-LNA treated group (FIG. 16e and FIG. 13c), as part of immune response mechanisms in siFXRl-LNA group. The cytokines and chemokines from cytotoxic Cd4+and Cd8+cytotoxic cells interact with their receptors (Ccll2-Ccr2, Ccl2-Ccr2, Ccl7-Ccr2, Ill 8-1118rl / Il 18rap) in Ml-like macrophage were also identified interact on in siFXRl-LNA group (FIG. 16e), potentially for enhancing the immune response. Furthermore, interactions between Cd80, Cd86 from macrophages to Cd28 receptor present on cytotoxic T cells again indicating a trigger for anti-tumor response by cytotoxic T cells in siFXRl-LNA treated group (FIG. 16e and FIG. 13c).

[0129] Natural Killer (NK) cells possess a unique capacity to directly engage and eliminate tumor cells, seting them apart from other immune cell types. Studies using both in experimental mouse tumor models and in cancer patients have demonstrated crucial roles of NK cells in controlling tumor progression and inhibiting metastasis in patients61>62’63-64Supporting to this notion, the treatment of siFXRl-LNA group resulted into anotable increase in NK cells expressing Ifhg, Gzmb, Cd244a, Itga2, 112rb, and Nkg7 — markers indicative of their cytotoxic and activated states against tumor cells (FIG. 6h, i). Our analysis of NK cells identified three distinct sub-clusters (FIG. 6j), characterized using known markers for cytotoxic and activated NK cells were enriched upon siFXRl-LNA treatment. Among the three subclusters, cluster 0 displayed predominantly as a phenotype of a cytotoxic and activated state, with almost 2-fold increase upon siFXRl-LNA treatment (FIG. 6k). We also identified cluster 2 as a partially cytotoxic and activated phenotype, while cluster 1 showed no clear phenotype distinction (FIG. 6k). Taken together, our data highlight that siFXRl-LNA treatment improved anti-tumor mechanism by promoting the enrichment of cytotoxic and activated NK cells.

[0130] Our results established that the delivery of siFXRl-LNA encapsulated PEI circumvents lysosomal degradation and silenced FXR1 very efficiently within tumor cells. Consequently, administration of the siFXRl-LNA complex instigated several adaptations in TME that helps antitumor mechanisms. Primarily, siFXRl-LNA treatment effectively reduce the amelioration of tumor epithelial cells, bolstered the enrichment of Cd4+and Cd8+T cells, activated and cytotoxic subsets of NK cells and activated DCs with anti-tumor properties. Furthermore, macrophages predominantly exhibit immunosuppressive characteristics were shifted into macrophages with anti-tumor characteristics when the tumors were treated with siFXRl-LNA (FIG.7).

[0131] DiscussionAtty. Dkt. No. 650053.01226

[0132] Studies have demonstrated that FXR1 is important gene for tumor formation, progression, and tumor relapse across various cancer types9’65. Our research has shown that FXR1 is an important oncogenic driver in ovarian cancer9Precisely, FXR1 stabilizes MYC mRNA by binding to its AU- rich elements, then inducing mRNA circularization and recruiting translation initiation factors to the translation initiation site for facilitating MYC translation9. Previous research has demonstrated that down-regulation of another FXR1 family protein, FMRP, limits tumor growth in a mouse model of pancreatic ductal adenocarcinoma (PDAC) by influencing T cell inflammation and immunosuppression66.

[0133] Therefore, our data suggest that FXR1 is a potential target for treatment for ovarian and other cancers exhibits FXR1 amplification. However, its therapeutic potential has not been fully explored in translational research, primarily due to the lack of drugs that inhibits the actions of FXR1. Considering that there are no small molecule inhibitors or any other FDA approved agents readily available for FXR1 therapy, here we have developed LNA modified FXR1 siRNA as an RNAi therapy approaches for in vivo delivery to treat ovarian cancer as a model system.

[0134] Among the five different siRNA sequences targeting FXR1, the two most effective siRNAs with robust silencing of FXR1 expression, accompanied by notable suppression of tumor proliferation, colony formation, and cell cycle progression were selected for LNA structure modification. Importantly, our co-culture experiments revealed that siFXRl selectively inhibited tumor cell growth without impacting normal epithelial cells. This selective action mitigates concerns about off-target effects and toxicity to normal cells, a common challenge in cancer therapeutics. The ability of siFXRl to discriminate between tumor and non-tumor cells suggests a favorable therapeutic index, making it an attractive candidate for further development. Importantly, the incorporation of LNA modifications into the most effective siFXRl -3 significantly enhanced its efficacy, achieving over 90% inhibition of FXR1 expression at a concentration as low as 0.5nM. compared to the 2nM required by its native counterpart. This enhanced silencing translated into a more pronounced G1 phase arrest superior inhibition of key cell cycle regulators, compared to the native siFXRl-3 along with similar level of induction in cellular apoptosis. These findings underscore the critical role of LNA modifications in enhancing siRNA potency and highlight siFXRl -3-LNA as a promising candidate for further therapeutic development. Mechanistic validation further revealed that tumors treated with LNA-modified siFXRl showed a pronounced reduction in the proliferation marker Ki67 and an increase in apoptotic markers such as cleaved- caspase 3. These findings also highlight the potential of using LNA-modified siFXRl as a targeted therapeutic approach for treating ovarian cancer and other cancers amplified FXR1.Atty. Dkt. No. 650053.01226

[0135] In the past, we have used native form of siRNAs and anti-miRs incorporated nanoparticles for treating the tumors2’7’8’9However, we observed that the native form of small RNAs are unstable and exhibited low level presence in the recipient cells, which also warrants the use of LNA modifications in siRNA for in vivo delivery. As expected, siFXRl-LNA exhibited improved uptake in ovarian cancer cells, with reduced localization in lysosome that causes siRNA degradation, and improved stability from RNase and serum nucleases. Consequently, our siFXRl-LNA exhibited better tumor tissue uptake along with a correlative and improved tumor growth inhibition in both immunocompromised and immunocompetent mice models in vivo. To therapeutically silence FXR1 in ovarian tumors in vivo, we used PEI nanoparticles incorporating the selected FXR1 siRNA. Pharmacodynamics of siRNA delivery’ systems are primarily influenced by the siRNA composition, where the choice of nanoparticle used for encapsulation can also affect these dynamics. Importantly, our choice of PEI nanoparticle used for the delivery of siFXRl-LNA did not exert any noticeable tissue damage due to organ toxicities, as evidenced by immunohistochemistry and biochemical assays of enzymes associated with liver and kidney functions.

[0136] Several RNAi-based approaches are currently undergoing assessment in phase I and II clinical trials67. However, the impact of siRNA sequences and the nanoparticles used for their delivery7on immune cell modulation, immune cell suppression, or immune cell toxicity are not fully understood yet. The scRNA-seq technique has greatly advanced our understanding of tumor cells, tumor-associated stromal cells, and immune cells, particularly in terms of the genetic and molecular adaptations within tumor cells, thus providing deeper insights into the heterogeneity of tumor tissues. However, the impact of small molecule inhibitors, monoclonal antibodies and RNAi agents on tumor progression using scRNA-seq technology' were not well exploited in the drug discovery' research. Therefore, we employed scRNA-seq to characterize the impact of siFXRl-LNA in tumor cells, stromal cells, and immune cells in the TME with a goal of transitioning our preclinical testing to phase I and II clinical trials. Previous studies have utilized ascites samples as a clinically valuable source of transcriptional information, capturing tumor cells alongside tumor-associated immune and stromal populations. Ascites is particularly relevant in the context of advanced metastatic disease, where an immunosuppressive microenvironment predominates, enabling tumor cells to evade immune surveillance and contributing to therapeutic resistance.

[0137] Molecular phenotyping of epithelial cell cluster further revealed that siFXRl-LNA treatment markedly down-regulated the expression of cancer-associated epithelial cell markers, and genes associated with cell cycle, proliferation, and translation. CellChat analysis40of cellular communication revealed that the control group express high levels of FXR1 group displayedAtty. Dkt. No. 650053.01226 signaling tied to extracellular matrix components of collagens, laminins and fibronectin that augment oncogenic signaling in tumor cells through autocrine mechanisms, as well as causing immunosuppressive pathways by abrogating immune cell activation.

[0138] Actively growing tumors create an immunosuppressive TME, which is mainly manifested by the presence of TAMs, exhaustion of cytotoxic and helper T cells, lack of NK cell activity, presence of Tregs and dysfunctional DCs responses. These factors are major obstacles to effective therapeutic interventions and contribute to the tumor's ability to evade the immune system. Macrophages in TME are classified into two polarized categories: Ml-like and M2-like. Ml-like macrophages, or classically activated macrophages, are know n for their protective functions against cancer cell growth, whereas M2-like macrophages, are considered key players in promoting cancer progression. Additionally, macrophages can impair T-cell functions and suppress their anti-tumor activity. Therefore, reducing the recruitment of TAMs, particularly M2-like macrophages, within the TME could help inhibit tumor growth. This mechanism was observed following our siFXRl-LNA treatment. Our flow cytometry' analysis based on high levels of Pdll protein in M2-like macrophages in control group demonstrates the mechanism of how ovarian cancer associated macrophages inhibits T cell function68. Conversely, Ml-like macrophages characterized by upregulation of genes associated with anti-tumor responses and immune activation (e.g., Ccl2, Ccl7, CxcllO, Tgfbl) were markedly enriched in the tumor site upon siFXRl-LNA treatment, suggesting a potential protective role of Ml-like macrophages against tumor growth. Moreover, such enrichment in macrophages in FXR1 silenced group was associated with enhanced T cell activation within the TME.

[0139] The role of T cell populations within TME is a critical mechanism which directly influence tumor growth. Research has shown that a low density of Cd8+cytotoxic T cells and Cd4+helper T cells, coupled with a higher prevalence of Tregs, is often associated with worsened prognosis in ovarian cancer69Using a combination of scRNA-seq. immunohistochemistry’ of tumors and flow cytometry analysis, we observ ed an increase in both Cd4+and Cd8+T cells with cytotoxic characteristics as evidenced with high levels ofNkg7, Prfl, and Gzmb expression. In brief, the treatment with siFXRl-LNA led to a reduction in immunosuppressive T cell populations while enriching T cells characterized by anti-tumor properties, such as Cd4+and Cd8+T cells. This was further corroborated by an increase in NK cells expressing key activation and cytotoxicity markers, including Ifng, Gzmb, Cd244a, Itga2, I12rb, and Nkg7, which again underscore their heightened functionality’ in combating tumor cells in vivo. By enhancing the cytotoxicity’ of both Cd4+and Cd8+T cells and promoting the activation of NK cells, FXR1 silencing demonstrates a capability to shift the immune microenvironment favorable for anti-tumor actions.Atty. Dkt. No. 650053.01226

[0140] It is expected that in a typical immune cell activated settings upon siFXRl-LNA treatment, mature DCs initiate and sustain T cell-mediated anti-tumor immunity. The primary role of DCs is to prime naive T cells for proliferation (i.e., in antigen presentation), for which they are well equipped when mature70. In this study, we observed high expression of genes associated w ith DC maturation and migration such as Cd80 and Cd86 when treated with siFXRl-LNA. We observed that FXR1 knockdown modulates the DC landscape in the TME, shifting it from a pro-inflammatory to an anti-tumorigenic state, potentially enhancing anti-tumor immune responses. Specifically, the significant reduction in the ratio of MoDCs, which are associated with inflammatory responses and express markers such as Cst3, Mrcl, and Argl, suggests a diminished recruitment of these pro- inflammatory cells to the TME. Conversely, we observed a notable increase in pDCs, characterized by the expression of Bel 11 a, Siglech, Bst2. and Ly6d, which play a pivotal role in anti-tumor immunity. These cells not only promote the production of type I interferons (IFN-I) but also enhance the maturati on of eDC 1 expressing Btla and Clec9a, thereby boosting the cytotoxic functions of Cd8+T cells and NK cells. Overall, our single-cell profiling of ascites revealed that siFXRl-LNA therapy effectively suppressed tumor cell survival, proliferation, and immunosuppressive pathways, while simultaneously enhancing anti-tumor immune responses. However, ascitic samples alone may not fully capture the spatial complexity of immune cell interactions and cellular behavior as same as in solid tumor tissues. To address this limitation, complementary approaches such as spatial transcriptomics using ovarian cancer solid tumor samples are essential for mapping cell-cell communication within the native tissue architecture. Notably, ongoing studies in our laboratory are actively employing spatial transcriptomics and spatial proteomics to further elucidate these interactions.

[0141] In conclusion, data presented in this study have provided us with a comprehensive understanding of the mechanism of our RNAi mediated anti-tumor therapeutic strategy by the delivery of siFXRl-LNA incorporated PEI in vivo. This highly efficient tumor-targeted siRNA incorporated PEI nanoparticle simultaneously inhibited tumor growth reduced the infiltration of tumor promoting TAM (M2-like macrophages), whereas enriched the amount of tumor inhibitory TAMs (Ml -like macrophages), and improved the enrichment of immunostimulant T cell, NK cell and DCs. We envision that the siFXRl-LNA developed in this study can serve as a therapeutic agent against multiple cancers that express high level of FXR1 and their delivery through nanoparticles tike PEI provide unprecedented opportunities to treat cancer patients.

[0142] Materials and Methods

[0143] Cell cultureAtty. Dkt. No. 650053.01226

[0144] HeyA8 cells were received from the Characterized Cell Line core at MD Anderson Cancer Center, Houston, TX, USA. Kuramochi cells were received from Taru Muranen at Beth Israel Deaconess Medical Center, Boston, MA, USA. OVCAR8 cells were purchased from the National Cancer Institute (NCI) cell line repository. NIH-OVCAR3 and MDA-MB-231 cells were purchased from ATCC / PBCF repository. BR-Luc and C-l I murine cell lines were received as a kind gift from Dr. Sandra Orsulic. University of California. Los Angeles, CA. Ovarian surface epithelial (OSE) cells were isolated as described earlier71. FTE187 was received from Dr. Jinsong Liu at MD Anderson Cancer Center, Houston, Texas, USA. All cancer cell lines were cultured in RPMI-1640 medium (ATCC, Manasassas, VA, USA)) supplemented with 10% fetal bovine serum (FBS, Omega Scientific), 1% Antibiotics (Anti-Anti 100X, Thermo Scientific). OSE and FTE187 were maintained in cell culture medium consisting of 1 : 1 Medium 199 and MCDB105 medium (Sigma- Aldrich) with 10% FBS, 10 ug / rnL Insulin Solution (Sigma- Aldrich), and 10 ng / rnL hEGF (Peperotech). Cells were routinely tested and deemed free of PlasmotestTM Mycoplasma Detection Kit (InvivoGen, San Diego, CA). Authenticity of the cell lines used were confirmed by STR characterization at IDEXX Bioanalytics Services (Columbia, MO).

[0145] Isolation of CD8+T cells from the PBMCs

[0146] T cells were isolated using the EasySep™ Human CD8+T Cell Isolation Kit (STEMCELL Technologies, Cambridge, MA, USA). Briefly, the frozen peripheral blood mononuclear cells (PBMCs) isolated from the whole blood were resuspended in the RPMI medium and centrifuged at 1500g for 5 min. The resulting pellet was resuspended in RoboSep™ Buffer to which the Isolation Cocktail containing the antibody complexes was added in the concentration of 50ul / ml of sample. This mixture w as further subjected to negative selection by the addition of EasySep™ Dextran RapidSpheres. This resulted in the labelling of unwanted cells with the antibodies and magnetic particles and the subsequent separation of the CD81T cells which were poured off into another tube and was used for further analysis.

[0147] Western blotting

[0148] For preparing cell lysates, the cells were washed twice with lx ice-cold PBS and lysed on ice in lx RIPA lysis buffer containing freshly added lx protease inhibitor cocktails (Sigma- Aldrich). For preparing the tissue lysates, the tumor tissues were homogenized in lx RIPA lysis buffer over ice. After 30 min of incubation, the lysates were collected by centrifugation at 4°C for 10 min at 10,000 rpm. The amount of total protein w as determined using a BCA protein assay kit (Pierce, Rockford. IL, USA). An equal amount of total protein (30pg) was resolved on precast 4-12% SDS- PAGE gels (Biorad, Hercules, CA. USA), transferred onto PVDF membranes, and incubated withAtty. Dkt. No. 650053.01226 desired primary antibodies, followed washing and incubation with HRP conjugated secondary antibodies (Cell Signaling Technology') and detecting of protein bands using chemiluminescence kit (Pierce, Rockford, IL, USA).

[0149] siRNA transfection

[0150] All siRNA duplexes for human FXR1 and negative control were purchased from Integrated DNA Technologies, Inc. (IDT, Inc. Coralville, IW). siRNA sequences are listed in Table SI. Reverse transfections were performed using the Lipofectamine RNAiMAX transfection reagent (Thermo Fisher Scientific Inc., Waltham, MA). At 48 hrs post-transfection, cells were harvested for further analysis. Unlabeled and Texas red labeled LNA modified siRNAs were synthesized by Eurogentec (Liege, Belgium) and purified by high performance liquid chromatography (HPLC).

[0151] In vitro activity assays

[0152] Cell proliferation, colony formation, cell cycle and annexin V / PI staining assays were performed as described earlier9

[0153] Cellular uptake and lysosomal escape of siRNA

[0154] To examine the uptake and escape of the siRNAs from lysosomes, native siFXRl and siFXRl-LNA labelled with Texas-red, kuramochi and OVCAR8 cells were seeded in the 35 mm glass bottom tissue culture plates (Cellvis LLC) and allow to attach overnight. On the second day, cells were transfected with respective siRNAs using Lipofectamine RNAiMAX transfection reagent (Thermo Fisher Scientific Inc). Cells were washed twice with lx PBS and stained with Hoechst 33342 and LYSO-ID® Green detection kit (Enzo Life Sciences, New York, USA) before imaging. Images of the live cells were captured at 1 hr, 3 hr, 6 hr and 24 hr post siRNAs treatment with a 40X objective using a confocal laser scanning microscope (LSM 510; Zeiss, Oberkochen, Germany).

[0155] At 48 hrs of siRNAs treatment, a TUNEL assay was conducted using an In Situ Cell Death Detection Kit (Roche Applied Science. IN) according to the instructions to detect apoptotic cells. Images from each treatment group were evaluated using a confocal laser scanning microscope (LSM 510; Zeiss, Oberkochen, Germany) and TUNEL-positive cells were quantified using Aim 4.2 software LSM 510.

[0156] Serum and enzymatic stability assays

[0157] To study the resistance to RNase I, native siFXRl and LNA modified siFXRl complexed with JetPEI® containing a total amount of 1 pM siRNA were incubated with 1 units of RNase I at 37 °C for 30 min, follow ed by incubation at 90 °C for 30 min to inactivate the enzyme. Heparin (200 pg mL ') was added to the samples and the mixture was incubated for additional 30 min at roomAtty. Dkt. No. 650053.01226 temperature to release the siRNA from the lipid complex. 1% TAE- Agarose gel electrophoresis was used to determine siRNA integrity- and siRNA band intensity was quantified using ImageJ software.

[0158] Serum stability' study was performed with human and mouse sera as previously reported9The native siFXRl and LNA modified siFXRl complexed with JetPEI® incubated with 10% human or mouse serum for different time intervals at 37°C. siRNAs were then released from the complex by incubation with heparin (200 pg mL ’) for 30 min and then analyzed by electrophoresis in a 20% TBE-polyacrylamide gel electrophoresis.

[0159] Live cell incucyte assay

[0160] OSE and FTE cells were nuclear-labeled red with the Incucyte® Nuclight Rapid Red Dye for Live-Cell Nuclear Labeling (Sartorius, USA) according to the manufacturer’s protocol. GFP labelled OVCAR8 were individually co-cultured with OSE and FTE NucLight Red cells in 1 : 1 ratio and allowed to attach overnight The media were removed, and cells were transfected with siCont- LNA and siFXRl-3-LNA using Lipofectamine RNAiMAX transfection reagent. After 24 hrs, cocultured cells were trypsinized and 5xl03cells were reseeded in quadruplicates in a 96-well plate containing complete medium. Live images were taken every per well every 6 hrs for a period of 72 hrs using The IncuCyte® Live Cell imaging system (Sartorius, USA). Green cell counts based on number of live cells w ere performed using IncuCyte® S3 Software (Sartorius, USA).

[0161] Co-culture assay

[0162] 24 hrs prior to transfection with siCont-LNA or siFXRl -3-LNA, OSE and FTE cells and GFP expressing OV CAR8 cells were seeded together into a 6 well, glass bottom slides (Cellvis LLC) plate at 1 : 1 ratio, respectively. Prior to imaging, cells were stained with Hoechst (Life Technologies; 5 ng / mL). Plates w ere then imaged at day 0 (day of transfection), 2 d, 4 d, and 6 d after transfection using a with a 40X objective using a confocal laser scanning microscope (LSM 510; Zeiss, Oberkochen, Germany). Counting on the GFP channel was done using the Aim 4.2 software LSM 510 and used to quantify the number of OV C AR8 cells in the culture. T otal cell populations per well were quantified by counting Hoechst+ nuclei using the Aim 4.2 software LSM 510. Proportion of OVCAR8 cells to total cells in each well was quantified by dividing the number of GFP+ cells by total Hoechst+ cells.

[0163] Comet assay

[0164] To evaluate DNA damage in a cell, we performed an alkaline comet assay using Comet SCGE assay kit according to the manufacturer’s instructions (Enzo Life Sciences, New- York, USA). Briefly, Kuramochi and OV CAR8 cells were transfected with siCont, siFXRl -3 and siFXRl -3-LNA using Lipofectamine RNAiMAX transfection reagent. After 48 hrs, cells were gently scraped andAtty. Dkt. No. 650053.01226 suspended at 1 x io5cells / mL in ice cold PBS. 50 pL of cells combined with molten LM Agarose at a ratio of 1: 10 (v / v) were dropped and spread onto Comet Slide. After gelling LM Agarose, slides were treated with lysis solution for 1 hr at 4° C and alkaline unwinding solution for 20 min at room temperature. The slides were placed in electrophoresis tray containing TBE electrophoresis solution and subjected to electrophoresis at 21 volts for 15 min. After staining cells with CYGREEN green Nucleic acid dye. cell images were obtained at 20X magnification using EVOS M5000 imaging system (Thermo Fisher Scientific). Percent DNA in the tail and tail moment or comet-like structures from at least 50 randomly selected cells per sample were analyzed using OpenComet vl .3.1 software 72

[0165] In vivo study

[0166] We performed sequence alignment analysis for both siFXRl sequences (seq2 and seq3) using CLUSTALW before using them for in vivo study. This analysis revealed that seq3 has 100% sequence homology7between human (NCBI Reference Sequence: NM_001013439.3) and mouse (NCBI Reference Sequence: NM_008053.4) FXR1, supporting its use in the murine model.

[0167] Athymic nude mice (J:NU. Strain #:007850), and FVB / NJ mice (Strain #001800) approximately 4 to 6 weeks old female were purchased from Jackson Laboratories and housed under specific pathogen-free conditions in accordance with guidelines and therapeutic interventions approved by the Institutional Animal Care and Use Committee (IACUC) at the Medical College of Wisconsin. For tumorgenicity study we performed experiment with OVCAR8 ovarian cancer cell lines. A total of 0.5 / 106OVCAR8 cells expressing luciferase were intraperitoneally (IP) injected into mice (n=7 / group) to generate a human ovarian xenograft mouse model. After 7 days, tumor cells inoculated mice were randomized into three groups and w ere IP injected with lOpg / mouse siCont- LNA, siFXRl and siFXRl-LNA complexed with 16 pL of in vivo-jetPEI® transfection reagent (PolyPlus Transfection. Illkirch, France) in 200 pL of 5% glucose twice / week over a period of 28 days73. For bioluminescence imaging, mice were IP injected with 150 mg / kg of D-luciferin in 200 pL PBS and bioluminescence signal was captured using a IVIS Lumina II in vivo imaging System (Caliper Life Sciences).

[0168] To assess the toxicity of siRNAs, athymic nude mice were randomly assigned to three groups (n = 5 / group). They were IP injected twice weekly for 4 weeks with 10 pg / mouse of siCont- LNA, native siFXRl, or siFXRl -LNA, each combined with PEI nanoparticle. After the final IP injection, the major organs (kidney, lungs, liver and brain) of the mice were excised, fixed, sectioned, and stained with H&E for histological analysis. Serum from blood samples was also collected andAtty. Dkt. No. 650053.01226 shipped to IDEXX Bioanalytics (Columbia, MO) for hematological analysis. The blood biochemical analysis includes evaluation of ALT, AST, bilirubin, albumin, and creatinine levels.

[0169] For breast tumorigenicity study, MDA-MB-231 cells (5xl06cells / mouse) mixed in Matrigel (Coming) (1: 1) were injected subcutaneously (s.c) in female athymic nude mice. When the tumor volumes reached 70-100mm?, mice were randomly divided into three groups (n=5 / group) and were retro-orbitally injected with lOpg / mouse siCont-LNA, siFXRl and siFXRl-LNA complexed with 16 pL of in vivo-jetPEI® transfection reagent (PolyPlus Transfection, Illkirch, France) in 100 pL of 5% glucose twice / eek over a period of 7 weeks. The tumors were measured by vernier caliper every week and tumor volumes were calculated using the following: tumor volume (mm3) = length x (width2) / 2. The mice were sacrificed at 7thweek. For scRNA-seq, FVB / Nj mice were IP injected with 0.5 x lO6Br-Luc cells and 7 days after tumor cells inoculation, mice were IP injected with siCont-LNA (n=10), and siFXRl -LNA (n=10), with the latter designed to complement the mouse FXR1 sequence (NCBI Reference Sequence: NM_008053.4), combined with jetPEI® respectively as mentioned above. For the survival study, FVB mice were IP injected with 0.5xl06Br-Luc cells and treated with siCont-LNA (n=10), and siFXRl -LNA (n=10), moribund mice showing ascites formation were considered as the 'endpoint’ and sacrificed.

[0170] Bioluminescence imaging

[0171] The IVIS Lumina II Bioluminescence and Fluorescence Imaging System (Caliper Life Sciences) was used for in vivo bioluminescent imaging. Mice were injected (IP) with 150 mg / kg body weight D-luciferin substrate (Gold Biotechnology, St. Louis, MO) and imaging was performed 10 min later (the peak time point). Images of the tumor were taken under the following settings: exposure time = 0.5 seconds, f / stop = 16, medium binning, field of view = 12.5 x 12.5 cm2. Living Image software was used to quantify the bioluminescent signals, reported as units of tissue radiance (photons / s / cm2 / sr).

[0172] For in vivo uptake and biodistribution study, tumor-bearing mice were imaged using IVIS Spectrum system (Perkin Elmer, Shelton) at 24 hrs post IP injection of Texas-red labelled siFXRl- LNA at a single dose. After imaging, mice were sacrificed, and tumors and major organs were excised and imaged.

[0173] Immunohistochemistry (IHC) and TUNEL assay

[0174] For this purpose, the slides were dewaxed in xylene and rehydrated through graded ethanol to distilled water. Antigen retrieval for the slide specimens were performed using IHC-Tek epitope retrieval solution and steamer set (IHC World, LLC.). The slides were then immersed in 3% H2O2 for 10 mm to quench endogenous peroxidase followed by blocking with 10% goat serum forAtty. Dkt. No. 650053.012261 hr. Tissue sections were then stained overnight at 4°C with the indicated primary antibodies. The slides were counterstained with Harris modified hematoxylin (Thermo Fisher Scientific Inc.. Rockford, IL), dehydrated with graded ethanol and xylene, and finally mounted with paramount. IHC slides was digitally scanned using Pannoramic 250 FLASH III scanner (3D HISTECH ltd. Version 2.0) and, using the Case View er softw are (3D HISTECH ltd. Version 2.0) w as used to view the images.

[0175] A TUNEL assay kit (Roche, Basel, Switzerland) was used to determine apoptotic cells in tumor specimen according to manufacturer’s instructions. Images from each treatment group were evaluated using a confocal laser scanning microscope (LSM 510; Zeiss, Oberkochen, Germany) and TUNEL-positive cells were quantified using Aim 4.2 software LSM 510.

[0176] 3D tumor spheroid invasion and penetration study

[0177] 3D tumor spheroids were prepared with growth factor reduced matrigel (GFR Matrigel, Coming Life Sciences, NY, USA) as previously reported. Thousand OVACR8 cells were suspended in 100 pL of spheroid formation ECM and added into a Coming 96-well ultralow attachment microplate, followed by centrifugation at 200 g for 3 min at 4°C. The plate was incubated at 37°C for 24 hrs to induce the formation of spheroids. The tumor spheroids were incubated with siFXRl- LNA labelled with Texas-red to evaluate the tumor penetration capability of siRNA.

[0178] For spheroid invasion assay, the spheroids were embedded in matrix from the Cultrex Spheroid Cell Invasion Assay kit (Trivigen. Gaithersburg, MD) at 37°C for 60 min and transfected with the siCont-LNA and siFXRl-LNA using Lipofectamine RNAiMAX transfection reagent for 24 hours. The medium was then replaced by DMEM containing 10% FBS with 5ng / mL hEGF, and the spheroids were incubated at 37°C for up to 4 days. Invasion of the spheroids in the matrix was photographed every 24 hrs using an inverted microscope (Nikon Ti2E).

[0179] scRNA-seq sample preparation, data acquisition and pre-processing

[0180] Ascites collected from three biological replicates were pooled together as one sample and a set of two samples per treatment group (siCont-LNA or siFXRl-LNA) were used for scRNA sequencing. Samples were then processed for single cell using tissue dissociation enzymes. scRNA- seq was performed using the Chromium Next GEM Single Cell 3' Reagent Kits v3.1 (Dual Index). Briefly, cells were loaded into the 10x Chromium Controller (I0x Genomics) for barcoding. scRNA- seq libraries were then generated according to the manufacturer’s protocol. After the scRNA-seq library' construction, Agilent 4200 Tape Station system and High Sensitivity7D5000 and D1000 Screen Tapes were used to assess the size profiles of the amplified cDNA. A NextSeq 500 / 550 High Output Kit v2.5 (150 cycles; 20024907: Illumina) with 28 cycles for read 1, 10 cycles for i7 index.Atty. Dkt. No. 650053.0122610 cycles for i5 index and 90 cycles for read 2 and was used to sequence the samples. Raw sequencing data were downloaded from Illumina BaseSpace, then demultiplexed and converted to gene-barcode matrices using the “mkfastq” and “count” functions in Cell Ranger v8.0 (10x Genomics). To reduce potential batch effects among samples, all cDNA libraries were constructed using the same reagent kit and protocol.

[0181] scRNA-seq data analysis for cell type clustering and annotation

[0182] After aligning raw sequencing reads to mouse mmlO reference genome, cell barcode and unique molecular index (UMI) count matrices were generated. Pre-processing of the data and downstream analyses were performed in R (v.4.3.3) using Seurat package (v.5.1.0). Cells expressing less than 100 or higher than 4800 genes or expressing higher than 15% of UMI counts from mitochondrial genes were removed due to poor quality or potential doubles. After quality control, a total of 16851 cells remained for downstream analysis. We used log2 transformation with 10,000 as scaling factor for normalization, and then selected top 2000 most variable genes, followed by performing principal components analysis (PCA) for denoising the data into 50 PCs.

[0183] During our analysis we found that one of the replicates among the siFXRl-LNA group exhibited fewer sequencing reads which resulted into identifying less cell numbers presumably due to the therapeutic effects of siFXRl LNA and associated decrease in overall tumor burden and ascites (FIG. 12d and e) This sample was excluded for further analysis. In brief, we identified 16851 high- quality cells (~11621 cells from siCont-LNA and -5230 cells from siFXRl-LNA group) for further subtyping (FIG. 12g).

[0184] Shared nearest neighbor (SNN) of each cell was constructed for each cell and then clustered using the Louvain-Jaccard graph-based algorithm, implemented by functions FindNeighbours and FindClusters with the resolution parameter set to 0.1. We used Uniform Manifold Approximation and Projection (UMAP) as dimensional reduction algorithm to visualize the data in two-dimension along with cluster results from the clustering algorithm. Cluster marker genes were identified by using Wilcoxon rank sum tests with adjusted p-value less than 0.05 (with Bonferroni correction for multiple testing). The main cell types were defined using cluster marker genes along with canonical markers.

[0185] Dimension reduction plots, heatmaps, violin plots, and dot plots were generated using functions DimPlot, DoHeatmap, VlnPlot, and DotPlot provided in Seurat, respectively. Bar plots were made by using the R package ggplot2 (version 3.5.1).

[0186] The scoring of cell function based on a specific gene set was performed through the built- in “AddModuleScore” function of the Seurat package.Atty. Dkt. No. 650053.01226

[0187] Subset analysis for epithelial, macrophage, T, NK, and Dendritic cells

[0188] Specific subgroup of cells was extracted from original dataset and re-ran the whole analysis pipeline as aforementioned, including normalization, select highly variable genes, denoising procedure by PCA, clustering analysis and dimension reduction by UMAP.

[0189] We performed pathway enrichment analysis with the differentially expressed gene list (Table S3) from each epithelial cell cluster using the IP A software.

[0190] CNV estimation and cell cycle analysis

[0191] To identify malignant cells from epithelial cells, we used the R package CopyKAT (version 1.1.0)42to estimate the copy number variations (CNVs) for each cell and predict if it is aneuploid or diploid. We assessed the cell cycle phase of the cells using the CellCycleScoring function74provided by the Seurat package.

[0192] Cell-cell communication analysis

[0193] The R package CellChat (v2.1.2)40was used to analyze cell-to-cell communication between tumor cells and other cell types. First, a CellChat object was created by grouping defined clusters. The ligand-receptor interaction database we used for analysis was "CellChalDB. mouse", without additional supplementation. Preprocessing steps were all conducted with default parameters. The functions computeCommunProb and computeCommunProbPathway were applied to infer the network of each ligand-receptor pair and each signaling pathway separately. A circle plot w as used as different visualization forms. Number of interaction and strength plot were made by using netVisual difflnteraction function.

[0194] Flow cytometry of TAM and T cells

[0195] After blocking with Fc Receptor Blocking Solution (Biolegend), cell surface staining was performed in FACS buffer containing antibody cocktails (Cd45, Pdll, Mrcl (Cd206), Cdl63, Cd4, Cd8) on ice for 1 hr. After washing twice with FACS buffer, the cells were fixed using BD Cytofix / cy toperm solution (BD Bioscience) 20 min on ice. Cells were washed with BD permAvash buffer (BD Bioscience), intracellular blocking with mouse IgG and Miltenyi FcR blocking, then intracellular staining was performed using PE-anti-LAMP3 (BD Biosciences), or PE-isotype control (BD Biosciences) for 1 hr on ice. Cells were washed twice with perm / wash buffer and then analyzed on the BD Fortessa.

[0196] Tissue IF staining

[0197] FVB mouse tumor tissue slices from siCont and siFXRl-LNA groups were dewaxed in xylene and rehydrated through graded ethanol to distilled water. Antigen retrieval for the slide specimens were performed using IHC-Tek epitope retrieval solution and steamer set (1HC World.Atty. Dkt. No. 650053.01226LLC.). The slides were then immersed in 3% H2O2 for 10 min to quench endogenous peroxidase followed by blocking with 10% BSA for 1 hr. Tissue sections were then stained overnight at 4°C with the indicated primary antibodies. After washing with PBS, tissue sections were incubated with secondary' antibodies, Alexa Fluor goat ant -mouse 488 (Cat#38731, Life Technologies, Carlsbad, CA) and Alexa Fluor 568 goat anti-rabbit (Cat#35646, Life Technologies. Carlsbad, CA) for 1 hr at room temperature. Glass slides were mounted using ProLong Gold Antfade Reagent (Life Technologies, Carlsbad, CA) containing DAPI. Images were acquired with a 40X objective using a confocal laser scanning microscope (LSM 510; Zeiss, Oberkochen, Germany) and analyzed using the Aim 4.2 software LSM510.

[0198] Statistical analysis

[0199] In most cases, data obtained from three or four biological replicates were analyzed, unless indicated otherwise in the Fig. legends. Statistical significance defined as a P value < 0.05 or < 0.01 was determined by unpaired Student’s t-test. Data are presented as the mean ± standard error (SEM) as indicated in the Fig. legends. Graphpad Prism 7 (GraphPad, San Diego, CA) was used to perform statistical analysis and p-value determinations. Overall survival was assessed with the Kaplan-Meier method and compared with the log-rank test.

[0200] Acknowledgements

[0201] This work was supported in part to P.C.-R. by DoD W81XWH-21-1-0365, HT9425-23- 1-0311 NCI R01CA229907, and Linda G. and Herbert J. Buchsbaum Endowment, Women's Health Research Program (WHRP) and the Sharon L. La Macchia Innovation Fund at MCW. S.P. was supported by, the, the Department of Defense (DoD W81XWH-21-1-0361 and W81XWH-21-1- 0138), and NCI R01CA258433. J.G was partially supported by MCW Cancer Center postdoctoral award. P.C.-R was also supported by seed funds from MCW Cancer Center and Advancing a Healthier Wisconsin Endowment funds. We also thank the animal core facility, and biomedical imaging shared resource core of Medical College of Wisconsin, and the Children’s Research Institute’s histology' core. All contributing authors reviewed and provided consent for publication.Table 1: List of siRNA sequences used in this exampleAtty. Dkt. No. 650053.01226Table 2: Acute toxicity (athymic nude mice) clinical biochemistryAspartate Aminotransferase (AST); Alanine Aminotransferase (ALT); Alkaline Phosphatase (ALP); Total Bilirubin (TBIL); Total Protein (TP)Atty. Dkt. No. 650053.01226Table 3 - Source data for FIG. 4CTable 4 - source data for FIG. 4FTable 5 - Source data for FIG. 4GTable 6 - source data for FIG. 4HAtty. Dkt. No. 650053.01226Table 7 - Source data for FIG. 5CTable 8 - Source data for FIG. 5HTable 9 - Source data for FIG. 6CAtty. Dkt. No. 650053.01226Table 10 - Source data for FIG. 6 J

[0202] Example 2 - Changes in the siRNA sequences abrogate siFXRl ’s effect on FXR1 levels

[0203] The inventors tested the effects of mutated sequence of FXR1 siRNAs (mutsiFXRl) to confirm if changes in the siRNA sequences abrogate siFXRl’s effect on FXR1 levels. Herein, we mutated eight nucleotides as highlighted in red letters in FIG. 17a in siFXRl-2 and siFXRl-3 sequences. As expected, the transfection of mutated siRNAs (seq2 or seq3) did not exhibit any silencing of FXR1 in OVCAR8 cells compared (FIG. 17b).

[0204] We further tested the effects of FXR1 siRNA, its mutated variants, and corresponding controls after encapsulation in PEI nanoparticles in OVCAR8 tumor-bearing nude mice. Briefly, mice were injected once weekly w ith FXR1 siRNA, mutated variants, or control siRNA at a dose of 10 pg per mouse for six weeks. Weekly administration of siFXRl effectively inhibited tumor growth, with siFXRl -LNA show ing a more pronounced reduction in tumor growth compared to the native form (FIG. 17c-17h).

[0205] We also validated the tumor inhibitory effects of siFXRl -LNA in a subcutaneous xenograft model using a highly aggressive triple-negative breast cancer cell line MDA-MB-231 which express high levels of FXR1 (FIG. 18a). Consistently, siFXRl -3-LNA demonstrated more effective knockdown of FXR1 and its downstream target MYC in MDA-MB-231 cells compared to siFXRl -2-LNA (FIG. 18b). We selected a TNBC model due to its genomic similarities with High- Grade Serous Ovarian Carcinoma (HGSOC) including frequent TP53 and BRCA mutations, high genomic instability and the prolific growth and metastatic behavior of MDA-MB-231 cell line. Consistent with the response observed in OVCAR8 tumors, systemic retro-orbital injections of siFXRl -LNA also significantly inhibited tumor growth of MDA-MB-231 tumors compared to the unmodified siFXRl treatment (Fig. 18c-18e). Furthermore, histological analysis of lymph nodes used as indicators of early metastasis also revealed no signs of metastasis in the mice were treated with siFXRl -LNA unlike those were treated with control siRNA-treated mice (FIG. 181).

[0206] In the foregoing description, it will be readily apparent to one skilled in the art that varying substitutions and modifications may be made to the invention disclosed herein without departing from the scope and spirit of the invention. The invention illustratively described herein suitably may be practiced in the absence of any element or elements, limitation or limitations which is notAtty. Dkt. No. 650053.01226 specifically disclosed herein. The terms and expressions which have been employed are used as terms of description and not of limitation, and there is no intention that in the use of such terms and expressions of excluding any equivalents of the features shown and described or portions thereof, but it is recognized that various modifications are possible within the scope of the invention. Thus, it should be understood that although the present invention has been illustrated by specific embodiments and optional features, modification and / or variation of the concepts herein disclosed may be resorted to by those skilled in the art, and that such modifications and variations are considered to be within the scope of this invention.

[0207] Citations to a number of patent and non-patent references may be made herein. The cited references are incorporated by reference herein in their entireties. In the event that there is an inconsistency between a definition of a term in the specification as compared to a definition of the term in a cited reference, the term should be interpreted based on the definition in the specification.References1. Cancer Genome Atlas Research N. Integrated genomic analyses of ovarian carcinoma. Nature 474, 609-615 (2011 ).2. Chaluvally-Raghavan P, et al. Copy number gain of hsa-miR-569 at 3q26.2 leads to loss of TP53INP1 and aggressiveness of epithelial cancers. Cancer Cell 26, 863-879 (2014).3. Macintyre G, et al. Copy number signatures and mutational processes in ovarian carcinoma. Nat Genet 50, 1262-1270 (2018).4. Shayesteh L, et al. PIK3CA is implicated as an oncogene in ovarian cancer. Nature genetics 21. 99-102 (1999).5. Wang W, etal. 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Claims

Atty. Dkt. No. 650053.01226CLAIMS1. A dsRNA comprising: a polynucleotide selected from one of SEQ ID NOs: 3-6, 1,2, or 7-10, or a sequence with at least 95% identity to one of SEQ ID NOs: 3-6, 1, 2, or 7- 10, and wherein the dsRNA comprises one or more modified nucleic acids.

2. The dsRNA of claim 1, wherein the polynucleotide is one of SEQ ID NOs: 3-6, or a sequence with at least 95% identity to one of SEQ ID NOs: 3-6.

3. The dsRNA of claim 1, wherein the polynucleotide is SEQ ID NO: 3 or 4, or a sequence with at least 95% identity' to SEQ ID NO: 3 or 4.

4. The dsRNA of claim 1, wherein the polynucleotide is SEQ ID NO: 5 or 6, or a sequence with at least 95% identity’ to SEQ ID NO: 5 or 6.

5. The dsRNA of claim 3, wherein the polynucleotide is SEQ ID NO: 3 or 4.

6. The dsRNA of claim 4. wherein the polynucleotide is SEQ ID NO: 5 or 6.

7. The dsRNA of claim 1, wherein the one or more modified nucleic acids are one or more 2’-O-methyl nucleotides, one or more 2 ’-fluoro nucleotides, one or more 2- methoxy ethyl nucleotides.

8. The dsRNA of claim 1, w herein the one or more modified nucleic acids comprise a phosphorothioate modification.

9. The dsRNA of claim 1, wherein the one or more modified nucleotides comprise a locked nucleic acid (LNA).

10. The dsRNA of claim 9, wherein the polynucleotide is selected from SEQ ID NOs: 21-24, or a sequence with at least 95% identity’ to one of SEQ ID NOs: 21-24.

11. The dsRNA of claim 10, wherein the polynucleotide is SEQ ID NO: 23 or 24.

12. The dsRNA of claim 1, wherein the dsRNA comprises at least one nucleotide overhang, optionally, wherein the nucleotide overhang is a deoxynucleotide overhang.

13. A pharmaceutical composition comprising the dsRNA of claim 1.Atty. Dkt. No. 650053.0122614. A nanoparticle comprising the dsRNA of claim 1.

15. The nanoparticle of claim 14, wherein the nanoparticle comprises a liposome.

16. The nanoparticle of claim 14 or 15, wherein the nanoparticle comprises l,2-di-(9Z- octadecenoyl)-sn-glycero-3-phosphocholine (DOPC) or polyethyleneimine (PEI).

17. A pharmaceutical composition comprising the nanoparticle of claim 14.

18. A method of treating a disease or disorder associated with FXR1 expression in a subject in need thereof, the method comprising: administering the pharmaceutical composition of claim 13 or 17 to the subject to treat the disease or disorder associated w ith FXR1 expression in the subject.

19. The method of claim 18, wherein the disease or disorder associated FXR1 expression is associated with an increase in the copy number of FXR1.

20. The method of claim 18, wherein the disease or disorder is a cell proliferative disease or disorder.

21. The method of claim 20, wherein the cell proliferative disease or disorder is a cancer.

22. The method of claim 21, wherein the cancer is selected from lung cancer, ovarian cancer, cervical cancer, esophageal cancer, or breast cancer.

23. The method of claim 22, wherein the cancer is ovarian cancer.

24. A method of treating ovarian cancer in a subject in need thereof, the method comprising: administering the pharmaceutical composition of claim 17 to a subject to treat ovarian cancer in the subject.

25. The method of claim 24, wherein the subject has been diagnosed with an ovarian tumor, and wherein the ovarian tumor expresses FXR1.

26. The method of claim 24, wherein the ovarian tumor comprises at least one tumor cells comprising additional genetic copies of FXR1.

27. The method of claim 24, wherein the method causes apoptosis in transformed or cancerous cells of the subject.Atty. Dkt. No. 650053.0122628. A method of increasing immune cell infiltration into a tumor in a subj ect, the method comprising administering a therapeutically effective amount of the pharmaceutical composition of claim 17 to the subject to increase immune cell infiltration into the tumor.

29. The method of claim 28, wherein the immune cell infiltration comprises infiltration of T cells, B cells, natural killer (NK) cells, or dendritic cells (DCs).

30. The method of claim 28, wherein the immune infiltration comprises infiltration of T cells.

31. The method of claim 30, wherein the T cells are effector T cells.

32. The method of claim 31, wherein the T cells are CD8+or CD4+T cells.

33. The method of claim 32, wherein the CD8+or CD4+T cells are cytotoxic T cells.

34. The method of claim 28, wherein the immune infiltration comprises infiltration ofNK cells.

35. The method of claim 28, wherein the immune infiltration comprises infiltration of B cells.

36. The method of claim 29, wherein the DCs are plasmacytoid DCs (pDCs).

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