Biology subjects

Sahni, S.

Publications and source records attributed to Sahni, S..

7 recordsLinked to original sources

bioRxiv2026

(E,E)-bisantrene suppresses MYC expression and displays anti-leukemic activity in acute myeloid leukemia

Background: Acute myeloid leukemia (AML) is genetically diverse with a high unmet clinical need for improved treatment options. Dysregulation of the transcription factor MYC plays a central role in AML progression and therapeutic resistance. (E,E)-bisantrene was recently found to inhibit MYC transcription and downstream activity via G-quadruplex DNA stabilization. This study aimed to evaluate the mechanism of action and preclinical activity of (E,E)-bisantrene in AML. Methods: The in vitro and in vivo activity of (E,E)-bisantrene was determined in a variety of AML models (cell lines, xenograft mouse models, and ex vivo human AML mononuclear cells). Transcriptomic, proteomic and phosphoproteomic analyses were performed after treatment with (E,E)-bisantrene. Analyses of -omics data to identify enriched pathways and upstream regulators were performed. Results: (E,E)-bisantrene demonstrated potent anti-proliferative activity across a panel of AML cell lines, inducing apoptosis and reducing S phase proportions. (E,E)-bisantrene significantly prolonged survival in cell- and patient-derived xenograft models of AML. Mechanistically, RNA-seq and proteomic analysis of MOLM13 and MV4-11 cells treated with (E,E)-bisantrene showed significant reductions in the activity of MYC and E2F, together with the cell cycle regulators CDK1/2/4/5. Transcript and protein levels of MYC were reduced in a dose- and time-dependent manner. TP53 and inflammation-associated transcript signatures were also observed. Conclusion: Anti-proliferative activity of (E,E)-bisantrene in preclinical AML models was associated with a downregulation of MYC, CDK1/2/4/5 and E2F. This study supports the ongoing clinical evaluation of (E,E)-bisantrene in AML where MYC is a clinically relevant driver of disease aggressiveness and therapy resistance.

cancer biology↗

bioRxiv2025

Bisantrene potentiates tyrosine kinase inhibitor activity in clear cell renal cell carcinoma

Clear Cell Renal Cell Carcinoma (ccRCC) is the most prevalent kidney cancer and often develops resistance to standard therapies. This study aimed to assess if bisantrene, a multi-mechanistic agent with broad anticancer activity, can enhance the activity of standard of care ccRCC treatments. A panel of ccRCC cell lines were treated with bisantrene alone and in combination with common ccRCC drugs. Bisantrene showed moderate activity as a single agent, but strongly synergized with several ccRCC treatments, especially the tyrosine kinase inhibitors (TKIs) lenvatinib, pazopanib and cabozantinib. Cellular signaling pathways assessed by immunoblotting revealed the TKIs inhibit MET as well as downstream AKT and ERK signaling pathways as single agents. Combination of these TKIs with bisantrene was able to induce sustained downstream AKT inhibition and negate the rebound effect seen with TKI resistance. Overall, bisantrene shows promise as a new therapeutic agent for ccRCC in combination with TKIs.

cancer biology↗

bioRxiv2024

IMMClock reveals immune aging and T cell function at single-cell resolution

The aging of the immune system substantially impacts individual immune responses, yet accurately quantifying immune age remains a complex challenge. Here we developed IMMClock, a novel immune aging clock that uses gene expression data to predict the biological age of individual CD8 T cells, CD4 T cells, and NK cells. The accuracy of IMMClock is first validated across multiple independent datasets, demonstrating its robustness. Second, utilizing the IMMClock, we find that intrinsic cellular aging processes are more strongly altered during immune aging than differentiation processes. Thirdly, our analysis confirms the strong associations between immune aging and established processes such as cellular senescence, exhaustion, and telomere length at the single cell level. Furthermore, immune aging is accelerated under several disease conditions such as type 2 diabetes, heart disease, and cancer. Finally, we apply IMMClock to analyze a perturb-seq gene activation screen of T cell functionality. We find that the post-perturbation immune age of individual T cells is strongly correlated with their pre-perturbation immune age. Furthermore, the immune age at resting state of individual T cells is strongly predictive of their post-stimulation activation state. Overall, IMMClock advances our understanding of immune aging by providing precise, single-cell level age estimations. Its future applications hold promise for identifying interventions that concomitantly rejuvenate and activate T cells, potentially enhancing efforts to counteract age-related immune decline.

bioinformatics↗

bioRxiv2024

The expression patterns of different cell types and their interactions in the tumor microenvironment are predictive of breast cancer patient response to neoadjuvant chemotherapy

The tumor microenvironment (TME) is a complex ecosystem of diverse cell types whose interactions govern tumor growth and clinical outcome. While multiple studies have extensively charted the TMEs impact on immunotherapy, its role in chemotherapy response remains less explored. To address this, we developed DECODEM (DEcoupling Cell-type-specific Outcomes using DEconvolution and Machine learning), a generic computational framework leveraging cellular deconvolution of bulk transcriptomics to associate gene expression of individual cell types in the TME with clinical response. Employing DECODEM to analyze gene expression of breast cancer patients treated with neoadjuvant chemotherapy across three bulk cohorts, we find that the expression of specific immune cells (myeloid, plasmablasts, B-cells) and stromal cells (endothelial, normal epithelial, CAFs) are highly predictive of chemotherapy response, achieving the same prediction levels as the expression of malignant cells. Notably, ensemble models integrating the estimated expression of different cell types perform best and outperform models built on the original tumor bulk expression. These findings and the models generalizability are further tested and validated in two single-cell (SC) cohorts of triple negative breast cancer. To investigate the possible role of immune cell-cell interactions (CCIs) in mediating chemotherapy response, we extended DECODEM to DECODEMi to identify such key functionally important CCIs, validated in SC data. Our findings highlight the importance of active pre-treatment immune infiltration for chemotherapy success. DECODEM and DECODEMi are made publicly available to facilitate studying the role of the TME in mediating response in a wide range of cancer indications and treatments.

bioinformatics↗

bioRxiv2023

Deactivation of ligand-receptor interactions enhancing lymphocyte infiltration drives melanoma resistance to Immune Checkpoint Blockade

Immune checkpoint blockade (ICB) is a promising cancer therapy; however, resistance often develops. To learn more about ICB resistance mechanisms, we developed IRIS (Immunotherapy Resistance cell-cell Interaction Scanner), a machine learning model aimed at identifying candidate ligand-receptor interactions (LRI) that are likely to mediate ICB resistance in the tumor microenvironment (TME). We developed and applied IRIS to identify resistance-mediating cell-type-specific ligand-receptor interactions by analyzing deconvolved transcriptomics data of the five largest melanoma ICB therapy cohorts. This analysis identifies a set of specific ligand-receptor pairs that are deactivated as tumors develop resistance, which we refer to as resistance deactivated interactions (RDI). Quite strikingly, the activity of these RDIs in pre-treatment samples offers a markedly stronger predictive signal for ICB therapy response compared to those that are activated as tumors develop resistance. Their predictive accuracy surpasses the state-of-the-art published transcriptomics biomarker signatures across an array of melanoma ICB datasets. Many of these RDIs are involved in chemokine signaling. Indeed, we further validate on an independent large melanoma patient cohort that their activity is associated with CD8+ T cell infiltration and enriched in hot/brisk tumors. Taken together, this study presents a new strongly predictive ICB response biomarker signature, showing that following ICB treatment resistant tumors turn inhibit lymphocyte infiltration by deactivating specific key ligand-receptor interactions.

bioinformatics↗

bioRxiv2023

Length-dependent RNA foci formation and RAN translation are associated with SCA12 disorder

Spinocerebellar ataxia type-12 (SCA-12) is a neurodegenerative disease caused by tandem CAG repeat expansion in the 5-UTR/non-coding region of PPP2R2B. Molecular pathology of SCA12 has not been studied in the context of CAG repeats and no appropriate models exist. We found in human SCA12-iPSC derived neuronal lineage that expanded CAG in PPP2R2B transcript forms nuclear RNA foci and were found to sequester variety of proteins. Further, the ectopic expression of transcript containing varying length of CAG repeats exhibits non-canonical Repeat Associated Non-AUG (RAN) translation in multiple frames in HEK293T cells, which was further validated in patient-derived neural stem cells using specific antibodies. mRNA sequencing of the SCA12 and control neurons have shown a network of crucial transcription factors affecting neural fate, in addition to alteration of various signaling pathways involved in neurodevelopment. Altogether, this study identifies the molecular signatures of spinocerebellar ataxia type-12 disorder using patient-derived neuronal cell lines.

neuroscience↗

bioRxiv2022

Accurate and simple FXN-GAA repeats (Friedreich ataxia loci) estimation by long read targeted sequencing.

Friedreich ataxia, an autosomal recessive disorder is caused by tandem GAA nucleotide repeats expansion in intron 1 of the FXN (frataxin gene). The GAA repeats above 66 in length are considered as pathogenic and commonly occurring repeats are 600-1200. Clinically the spectrum of the features is confined mainly to the neurological tissue, however, cardiomyopathy and diabetes mellitus has been observed in 60% and 30% of the subjects. The accurate detection of GAA repeats count is of utmost importance for clinical genetic correlation as no study has attempted an approach which is of high throughput nature and defines the sequence of GAA repeats. Largely, the method for detection of GAA repeats so far is either conventional PCR based screening and southern blot which is the gold standard method. We describe for the first time a method of long read sequencing wherein we utilized approach of long range targeted amplification of FXN-GAA repeats and sequencing on oxford MinION platform. We were able to achieve the successful amplification of GAA repeats ranging from 180-1200 at 250x coverage. The total throughput achievable for 96 samples can be less than 24 hours on one flow cell as per our protocol and is scalable and deployable at clinical day to sequencing.

genetics↗