Biology subjects

Salari, K.

Publications and source records attributed to Salari, K..

7 recordsLinked to original sources

bioRxiv2026

Genomic analysis of BCG unresponsive non-muscle-invasive bladder cancer identifies drivers of sensitivity to intravesical Gemcitabine/Docetaxel

Background and ObjectivesIntravesical gemcitabine/docetaxel (Gem/Doce) is an effective therapy for Bacillus Calmette- Guerin (BCG)-unresponsive non-muscle-invasive bladder cancer (NMIBC), achieving 50% complete responses at 2 years. However, the genomic determinants underlying response and resistance to Gem/Doce remain poorly defined. Our objective was to define the mutational landscape of BCG-unresponsive NMIBC and nominate genomic features associated with response or resistance Gem/Doce. MethodsPatients with BCG-unresponsive NMIBC treated with Gem/Doce were classified as responders (recurrence-free survival [RFS] >12 months) or non-responders (RFS <12 months). Whole-exome sequencing was performed on tumors prior to Gem/Doce treatment (n=23). Single nucleotide variants were identified and annotated using a Cancer Genome Analysis pipeline. Copy number alterations were inferred with ABSOLUTE, and clonal architecture was reconstructed using PhylogicNDT. Key Findings and LimitationsResponders demonstrated significantly prolonged time to high-grade recurrence (3.5 vs 42 months, p<0.001) and cystectomy compared with non-responders (9.5 months vs not reached; p<0.001). Non-responders exhibited higher tumor mutational burden (13.66 vs 8.71; p=0.02) and more frequent whole-genome doubling (2/2 non-responders vs 0/1 responders; p=0.33). Phylogenetic analyses revealed clonal BAP1 and subclonal BRCA2 mutations in responders, whereas non-responders harbored clonal FGFR3 mutations. Limitations include small sample size and retrospective design. Conclusions and Clinical ImplicationsDistinct genomic features underlie differential response to Gem/Doce in BCG-unresponsive NMIBC. In responders, alterations in DNA repair pathways (e.g., BRCA2) may sensitize tumors to chemotherapy, while non-responders with FGFR3 mutations may benefit from alternative targeted strategies. These findings warrant validation in larger cohorts and support the development of biomarker-driven clinical trials. Patient summaryIn this report we analyzed bladder tumors and found that some tumors respond well to treatment because they have defects in repairing DNA, making them more vulnerable to chemotherapy. In contrast, tumors that do not respond to chemotherapy harbor different genetic changes that help them survive and grow. These findings may help physicians choose more effective and personalized treatments in the future.

genomics↗

bioRxiv2025

Immune Spatial Organization Predicts Metastasis Risk in Aggressive Localized Prostate Cancer

Risk stratification in localized prostate cancer (PCa) remains imprecise. Computational pathology has emerged as an attractive option for improving risk stratification, but current approaches either lack interpretability or focus solely on tumor morphology. Here, we identify, validate, and provide interpretability for an immune microenvironment-derived computational pathology biomarker for high-grade PCa. Using digitized hematoxylin and eosin-stained (H&E) slides from two independent cohorts of patients treated with radical prostatectomy (n=490), we found that spatial clustering of immune clusters, but not immune cell abundance, was independently associated with reduced risk of distant metastasis for high-grade disease but not low-grade. Joint analysis of H&E images and RNA sequencing (n=326) revealed that in high-grade disease, high-cluster samples were enriched in CD8+ T cells, activated memory CD4+ T cells, and Tregs, as well as clonal T cell populations, overall suggestive of an underlying T cell-mediated antitumor response. No such enrichment was found in low-grade tumors. These findings establish immune spatial architecture as a novel, interpretable computational pathology biomarker and provide insight into the immune landscape of high-grade PCa.

bioinformatics↗

bioRxiv2025

Oncogene SETDB1s Dual Role in Endometrial Cancer: Driving Tumor Progression and Immune Escape

Oncogene SETDB1, an H3K9 methyltransferase, drives tumorigenesis in various cancers. Using endometrial cancer (EC) as a model, we discovered SETDB1s dual mechanisms in driving EC tumorigenesis and mediating immune evasion. SETDB1 knockout (SETDB1-/-) tumor-bearing mice exhibited prolonged survival of up to 100 days. Transcriptomic profiling of SETDB1-/- EC cells revealed decreased expression of oncogenes (POLR2A, MSH6, FLNA) and increased expression of tumor suppressor genes (PGR, RERG, ZNF582), which indicates that SETDB1 intrinsically promotes EC tumor proliferation by regulating these downstream genes. SETDB1 repressed repeat elements and the interferon pathway, mediating immune evasion extrinsically by inhibiting anti-tumor macrophage infiltration. ChIP-seq analysis showed SETDB1 binding at pericentromeric regions on many chromosomes and numerous ZNFs. Loss of SETDB1 resulted in abnormal cell division. SETDB1-/- tumors displayed reduced proliferation markers (Ki67, pHH3) and increased macrophage infiltration. Mechanistically, SETDB1 promotes CD47 (a dont-eat-me signal) and represses CCL5 and CXCL9 (macrophage and T-cell recruiting chemokines), contributing to immune evasion. M1-like macrophages killed more SETDB1-/- cells in co-culture. Additionally, SETDB1 knockout in mouse EC cells reduced tumor growth in C57BL/6 mice, with increased macrophage and CD4+ T-cell infiltration. Our results indicates that elevated SETDB1 and its target genes can predict higher tumor grade and worse survival, suggesting that targeting SETDB1 could be a promising therapeutic strategy for EC.

cancer biology↗

bioRxiv2023

Analysis of evolutionary dynamics and clonal architecture in prostate cancer

The extent to which clinical and genomic characteristics associate with prostate cancer clonal architecture, tumor evolution, and therapeutic response remains unclear. Here, we reconstructed the clonal architecture and evolutionary trajectories of 845 prostate cancer tumors with harmonized clinical and molecular data. We observed that tumors from patients who self-reported as Black had more linear and monoclonal architectures, despite these men having higher rates of biochemical recurrence. This finding contrasts with prior observations relating polyclonal architecture to adverse clinical outcomes. Additionally, we utilized a novel approach to mutational signature analysis that leverages clonal architecture to uncover additional cases of homologous recombination and mismatch repair deficiency in primary and metastatic tumors and link the origin of mutational signatures to specific subclones. Broadly, prostate cancer clonal architecture analysis reveals novel biological insights that may be immediately clinically actionable and provide multiple opportunities for subsequent investigation. Statement of significanceTumors from patients who self-reported as Black demonstrate linear and monoclonal evolutionary trajectories yet experience higher rates of biochemical recurrence. In addition, analysis of clonal and subclonal mutational signatures identifies additional tumors with potentially actionable alterations such as deficiencies in mismatch repair and homologous recombination.

cancer biology↗

bioRxiv2022

Integrated single-cell and spatial transcriptomic analyses unravel the heterogeneity of the prostate tumor microenvironment

The treatment of primary prostate cancer delicately balances an active surveillance approach for low-risk disease with multimodal treatment including surgery, radiation therapy, and hormonal therapy for high-risk disease. Recurrence and development of metastatic disease remains a clinical problem, without a clear understanding of what drives immune escape and tumor progression. Here, we sought to comprehensively describe the tumor microenvironment of localized prostate cancer contrasting this with adjacent normal samples and healthy controls. We performed single-cell RNA sequencing and high-resolution spatial transcriptomic analysis. This revealed tumor context dependent changes in gene expression. Our data point towards an immune suppressive tumor microenvironment associated with suppressive myeloid populations and exhausted T-cells, in addition to high stromal angiogenic activity. We inferred cell-to-cell relationships at an unprecedented scale for ligand-receptor interactions within undissociated tissue sections. Our work provides a highly detailed and comprehensive resource of the prostate tumor microenvironment as well as tumor-stromal cell interactions. HighlightsO_LICharacterization of prostate cancer by combined scRNA-seq and spatial transcriptomic analysis C_LIO_LIPrimary prostate cancer establishes a suppressive immune microenvironment C_LIO_LIThe prostate tumor microenvironment exhibits a high angiogenic gene expression pattern C_LIO_LIA new computational analysis pipeline to deconvolute context-specific differential gene expression C_LI

cancer biology↗

bioRxiv2020

Biologically informed deep neural network for prostate cancer classification and discovery

Determination of molecular features that mediate clinically aggressive phenotypes in prostate cancer (PrCa) remains a major biological and clinical challenge. Here, we developed a biologically informed deep learning model (P-NET) to stratify PrCa patients by treatment resistance state and evaluate molecular drivers of treatment resistance for therapeutic targeting through complete model interpretability. Using a molecular cohort of 1,238 prostate cancers, we demonstrated that P-NET can predict cancer state using molecular data that is superior to other modeling approaches. Moreover, the biological interpretability within P-NET revealed established and novel molecularly altered candidates, such as MDM4 and FGFR1, that were implicated in predicting advanced disease and validated in vitro. Broadly, biologically informed fully interpretable neural networks enable preclinical discovery and clinical prediction in prostate cancer and may have general applicability across cancer types.

bioinformatics↗

bioRxiv2019

Integrative genomic, transcriptomic, and epigenomic analyses of benign prostatic hyperplasia reveal new options for therapy

Benign prostatic hyperplasia (BPH), a nonmalignant enlargement of the prostate, is one of the most common diseases affecting aging men, but the underlying molecular features of BPH remain poorly understood, and therapeutic options are limited. Here we employed a comprehensive molecular investigation of BPH, including genomic, transcriptomic and epigenetic profiling of 18 BPH cases. At the molecular level, we found no evidence of neoplastic features in BPH: no evidence of driver genomic alterations, including low coding mutation rates, mutational signatures consistent with aging tissues, minimal copy number alterations, and no genomic rearrangements. Similarly at the epigenetic level, we found global hypermethylation was the dominant process (unlike most neoplastic processes). By integrating transcriptional and methylation signatures, we identified two BPH subgroups with distinct clinical features and associated signaling pathways, which were validated in two independent cohorts. Finally, our analyses nominated mTOR inhibitors as a potential subtype-specific therapeutic option. Supporting this, a cohort of men exposed to mTOR inhibitors showed a significant decrease in prostate size. Our results demonstrate that BPH consists of distinct molecular subgroups, with potential for subtype-specific precision therapy via mTOR inhibition.

genomics↗