Hani Goodarzi
@genophoria.bsky.social
Core Investigator @ Arc Institute | Associate Professor @ UCSF | {Computational, Systems, Cancer, RNA} biologist | Co-founder @exaibio @vevo_ai
Finally, we used double-knockdown for in vivo lung colonization assays to confirm the expected epistatic interaction between RBMS3 and TXNIP.
June 9, 2025 at 1:33 PM
Finally, we used double-knockdown for in vivo lung colonization assays to confirm the expected epistatic interaction between RBMS3 and TXNIP.
We confirmed that TXNIP is correlated with RBMS3, and similarly its expression is associated with better outcomes. Then we looked at TXNIP expression in a cohort of 96 breast cancer samples in-house, stratified by stage, that confirmed reduced expression as disease progresses.
June 9, 2025 at 1:33 PM
We confirmed that TXNIP is correlated with RBMS3, and similarly its expression is associated with better outcomes. Then we looked at TXNIP expression in a cohort of 96 breast cancer samples in-house, stratified by stage, that confirmed reduced expression as disease progresses.
To figure out which, if any, of the targets of RBMS3 that we identified are responsible for this phenotype, we performed an in vivo CRISPR screen. Among the targets tested, we found that silencing TXNIP increases metastatic lung colonization.
June 9, 2025 at 1:33 PM
To figure out which, if any, of the targets of RBMS3 that we identified are responsible for this phenotype, we performed an in vivo CRISPR screen. Among the targets tested, we found that silencing TXNIP increases metastatic lung colonization.
To turn this clinical association into causation, we took advantage of metastasis assays in xenografted mice. We showed that silencing and over-expressing RBMS3 modulates metastasis in vivo in two independent models.
June 9, 2025 at 1:33 PM
To turn this clinical association into causation, we took advantage of metastasis assays in xenografted mice. We showed that silencing and over-expressing RBMS3 modulates metastasis in vivo in two independent models.
Interestingly, this association was most notable in the basal and Claudin-low subtypes of breast cancer, which are known to be aggressive subtypes.
June 9, 2025 at 1:33 PM
Interestingly, this association was most notable in the basal and Claudin-low subtypes of breast cancer, which are known to be aggressive subtypes.
We consistently observed that reduced expression of RBMS3 is associated with poor clinical outcomes in breast cancer patients, in multiple datasets.
June 9, 2025 at 1:33 PM
We consistently observed that reduced expression of RBMS3 is associated with poor clinical outcomes in breast cancer patients, in multiple datasets.
To gain insight into the functional consequences and phenotypic effects of this regulon, we looked at pathways and complexes that may be enriched among the RBMS3 target. We saw a significant enrichment for TGFb and VEGF signaling that are associated with metastatic progression in breast cancer.
June 9, 2025 at 1:33 PM
To gain insight into the functional consequences and phenotypic effects of this regulon, we looked at pathways and complexes that may be enriched among the RBMS3 target. We saw a significant enrichment for TGFb and VEGF signaling that are associated with metastatic progression in breast cancer.
Finally, we demonstrated the requirement and sufficiency of RBMS3 binding sites for this RBSM3-mediated transcript stabilization. We cloned binding sites from 13 high confidence mRNA targets into a reporter assay, which showed RBMS3-dependent increase in reporter expression.
June 9, 2025 at 1:33 PM
Finally, we demonstrated the requirement and sufficiency of RBMS3 binding sites for this RBSM3-mediated transcript stabilization. We cloned binding sites from 13 high confidence mRNA targets into a reporter assay, which showed RBMS3-dependent increase in reporter expression.
Replacing AUA-carrying mRNAs with these empirical RBMS3 CLIP targets confirmed that RBMS3 direct binding drives transcript stabilization.
June 9, 2025 at 1:33 PM
Replacing AUA-carrying mRNAs with these empirical RBMS3 CLIP targets confirmed that RBMS3 direct binding drives transcript stabilization.
To show that this effect results from a direct interaction between RBMS3 and its target mRNAs, we performed CLIP-seq (UV crosslinking followed by immuno-precipitation and sequencing). We observed pervasive 3’UTR binding, and also a strong enrichment for the AUA element we had identified.
June 9, 2025 at 1:33 PM
To show that this effect results from a direct interaction between RBMS3 and its target mRNAs, we performed CLIP-seq (UV crosslinking followed by immuno-precipitation and sequencing). We observed pervasive 3’UTR binding, and also a strong enrichment for the AUA element we had identified.
Silencing RBMS3, as expected, resulted in a significant decrease in the stability and expression of the mRNAs that contain AUA-elements in their 3’UTRs.
June 9, 2025 at 1:33 PM
Silencing RBMS3, as expected, resulted in a significant decrease in the stability and expression of the mRNAs that contain AUA-elements in their 3’UTRs.
Among these, we chose RBMS3 for further characterization, simply because it was the highest ranking RBP for correlated expression with its putative regulon—identified based on the AUA cis-regulatory element, which was determined by analysis of GreyHound’s sequence importance scores.
June 9, 2025 at 1:33 PM
Among these, we chose RBMS3 for further characterization, simply because it was the highest ranking RBP for correlated expression with its putative regulon—identified based on the AUA cis-regulatory element, which was determined by analysis of GreyHound’s sequence importance scores.
Applying GreyHound to our breast cancer mRNA stability dataset, we uncovered a network of RBPs associated, and their cognate cis-regulatory elements, as a major determinant of variation in the RNA dynamics of breast cancer.
June 9, 2025 at 1:33 PM
Applying GreyHound to our breast cancer mRNA stability dataset, we uncovered a network of RBPs associated, and their cognate cis-regulatory elements, as a major determinant of variation in the RNA dynamics of breast cancer.
To help decipher the regulatory grammar of context-specific mRNA dynamics, we developed GreyHound: a multimodal deep-learning model that integrates RNA sequences and RNA-binding protein (RBP) expression to predict mRNA stability.
June 9, 2025 at 1:33 PM
To help decipher the regulatory grammar of context-specific mRNA dynamics, we developed GreyHound: a multimodal deep-learning model that integrates RNA sequences and RNA-binding protein (RBP) expression to predict mRNA stability.
For this, we performed SLAM-seq (metabolic RNA labeling) in six breast cancer cell lines (3 major subtypes). Our findings revealed variations in mRNA dynamics, especially subtype-specific differences, suggesting RNA stability as a major factor in breast cancer heterogeneity.
June 9, 2025 at 1:33 PM
For this, we performed SLAM-seq (metabolic RNA labeling) in six breast cancer cell lines (3 major subtypes). Our findings revealed variations in mRNA dynamics, especially subtype-specific differences, suggesting RNA stability as a major factor in breast cancer heterogeneity.
We performed a systematic analysis to measure variations in mRNA dynamics across diverse models of breast cancer. We observed that a substantial portion of gene expression variation in breast cancer cannot be explained by transcriptional control alone.
June 9, 2025 at 1:33 PM
We performed a systematic analysis to measure variations in mRNA dynamics across diverse models of breast cancer. We observed that a substantial portion of gene expression variation in breast cancer cannot be explained by transcriptional control alone.
Sharing our lab’s latest preprint, led by @heatherkarner.bsky.social and @tabeamittmann.bsky.social. Our study describes a post-transcriptional network that governs mRNA dynamics contributing to breast cancer heterogeneity.
June 9, 2025 at 1:33 PM
Sharing our lab’s latest preprint, led by @heatherkarner.bsky.social and @tabeamittmann.bsky.social. Our study describes a post-transcriptional network that governs mRNA dynamics contributing to breast cancer heterogeneity.
We are excited about this work because it introduces:
• A locus-specific regulator of Pol III transcription
• A new chromatin-based axis of tRNA control
• A codon-level mechanism linking translation to cancer progression
It’s the first direct evidence for a tRNA-targeting TF
• A locus-specific regulator of Pol III transcription
• A new chromatin-based axis of tRNA control
• A codon-level mechanism linking translation to cancer progression
It’s the first direct evidence for a tRNA-targeting TF
April 30, 2025 at 11:49 PM
We are excited about this work because it introduces:
• A locus-specific regulator of Pol III transcription
• A new chromatin-based axis of tRNA control
• A codon-level mechanism linking translation to cancer progression
It’s the first direct evidence for a tRNA-targeting TF
• A locus-specific regulator of Pol III transcription
• A new chromatin-based axis of tRNA control
• A codon-level mechanism linking translation to cancer progression
It’s the first direct evidence for a tRNA-targeting TF
Systematic analysis of clinical datasets, including TCGA and METABRIC revealed that:
• Low ZZEF1 expression is associated with poor prognosis in breast cancer
• This is true across subtypes and multiple datasets
• STK3 protein levels show similar associations
• Low ZZEF1 expression is associated with poor prognosis in breast cancer
• This is true across subtypes and multiple datasets
• STK3 protein levels show similar associations
April 30, 2025 at 11:49 PM
Systematic analysis of clinical datasets, including TCGA and METABRIC revealed that:
• Low ZZEF1 expression is associated with poor prognosis in breast cancer
• This is true across subtypes and multiple datasets
• STK3 protein levels show similar associations
• Low ZZEF1 expression is associated with poor prognosis in breast cancer
• This is true across subtypes and multiple datasets
• STK3 protein levels show similar associations
• ZZEF1 or tRNA-LysUUU knockdown promotes lung colonization in vivo
• STK3 overexpression or tRNA-LysUUU rescue inhibits metastasis
• STK3 overexpression or tRNA-LysUUU rescue inhibits metastasis
April 30, 2025 at 11:49 PM
• ZZEF1 or tRNA-LysUUU knockdown promotes lung colonization in vivo
• STK3 overexpression or tRNA-LysUUU rescue inhibits metastasis
• STK3 overexpression or tRNA-LysUUU rescue inhibits metastasis
The ZZEF1-tRNA-LysUUU translational regulon showed a significant enrichment for metastasis associated genes in breast cancer. Of note, STK3, a known metastasis suppressor, is part of this regulon. Taking advantage of xenograft mouse models of metastasis we confirmed that:
April 30, 2025 at 11:49 PM
The ZZEF1-tRNA-LysUUU translational regulon showed a significant enrichment for metastasis associated genes in breast cancer. Of note, STK3, a known metastasis suppressor, is part of this regulon. Taking advantage of xenograft mouse models of metastasis we confirmed that:
This ZZEF1-mediated regulation of tRNA-LysUUU has codon-dependent translational consequences:
• Reduced translational efficiency of AAR codon-rich mRNAs upon ZZEF1 KD
• Rescue of translation by overexpressing tRNA-LysUUU
• Increased ribosome dwelling on AAR codons
• Reduced translational efficiency of AAR codon-rich mRNAs upon ZZEF1 KD
• Rescue of translation by overexpressing tRNA-LysUUU
• Increased ribosome dwelling on AAR codons
April 30, 2025 at 11:49 PM
This ZZEF1-mediated regulation of tRNA-LysUUU has codon-dependent translational consequences:
• Reduced translational efficiency of AAR codon-rich mRNAs upon ZZEF1 KD
• Rescue of translation by overexpressing tRNA-LysUUU
• Increased ribosome dwelling on AAR codons
• Reduced translational efficiency of AAR codon-rich mRNAs upon ZZEF1 KD
• Rescue of translation by overexpressing tRNA-LysUUU
• Increased ribosome dwelling on AAR codons
• binds DNA across the genome but also specifically to tRNA-Lys-TTT-3 loci (ChIP-seq)
• has an affinity for distinct DNA motifs at these loci
• interacts with CHD6, a chromatin remodeler
• Together, they enhance chromatin accessibility to promote tRNA transcription
• has an affinity for distinct DNA motifs at these loci
• interacts with CHD6, a chromatin remodeler
• Together, they enhance chromatin accessibility to promote tRNA transcription
April 30, 2025 at 11:49 PM
• binds DNA across the genome but also specifically to tRNA-Lys-TTT-3 loci (ChIP-seq)
• has an affinity for distinct DNA motifs at these loci
• interacts with CHD6, a chromatin remodeler
• Together, they enhance chromatin accessibility to promote tRNA transcription
• has an affinity for distinct DNA motifs at these loci
• interacts with CHD6, a chromatin remodeler
• Together, they enhance chromatin accessibility to promote tRNA transcription
Among the regulatory interactions in common between the two, we focused on ZZEF1, nominated as a regulator of tRNA-Lys expression. First we showed that CRISPRi-mediated ZZEF1 knockdown led to reduced expression of tRNA-LysUUU, confirmed by both tRNA-seq and Northern blot.
April 30, 2025 at 11:49 PM
Among the regulatory interactions in common between the two, we focused on ZZEF1, nominated as a regulator of tRNA-Lys expression. First we showed that CRISPRi-mediated ZZEF1 knockdown led to reduced expression of tRNA-LysUUU, confirmed by both tRNA-seq and Northern blot.
So, we used TCGA-BRCA to carry out an integrated network analysis using matched RNA-seq and small RNA-seq datasets. The small RNA-seq data captures tRNA fragments, which have been previously shown to be highly correlated with tRNA expression level.
April 30, 2025 at 11:49 PM
So, we used TCGA-BRCA to carry out an integrated network analysis using matched RNA-seq and small RNA-seq datasets. The small RNA-seq data captures tRNA fragments, which have been previously shown to be highly correlated with tRNA expression level.