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Kirane, A. R.

Publications and source records attributed to Kirane, A. R..

6 recordsLinked to original sources

A Pan-Cancer Single-Cell Atlas to Evaluate Tumor Identity, Cell Line Concordance, and Dependency Mapping

Bulk RNA sequencing enables pan-cancer transcriptional analyses, but obscures cancer cell-specific programs due to admixture with nonmalignant cells, thereby limiting direct comparison between experimental models and primary tumors. Single-cell RNA sequencing (scRNA-seq) overcomes these limitations; however, the biological interpretability of public datasets is often compromised by variable data quality, inconsistent annotation, and atlas-scale aggregation strategies that prioritize data volume over biological coherence. We therefore developed a stringent integration framework that prioritizes representative malignant transcriptional states. Using Mahalanobis distance-based selection within batch-corrected latent space, we constructed a pan-cancer atlas comprising 135,424 high-quality malignant cells from 499 samples across 36 adult and pediatric cancers. Atlas-derived cancer signatures were used to determine tumor-cell line concordance and project ElasticNet models trained on DepMap CRISPR screens to infer cancer-specific gene dependencies. The scTumor Atlas establishes a scalable framework for tumor identity inference, cancer cell line benchmarking, and systematic identification of genetic vulnerabilities.

cancer biology↗

Multidimensional Single-Cell Transcriptomic Profiling of Uterine Leiomyosarcomas Identifies Molecular Subtypes with Distinct Therapeutic Vulnerabilities

Uterine leiomyosarcoma (ULMS) is an orphan disease that frequently recurs and metastasizes, with patients undergoing multiple lines of chemotherapy due to lack of effective therapeutic targets. To address this gap, we used single-cell RNA sequencing and spatial transcriptomic analysis to comprehensively profile ULMS. We uncovered multiple states of tumor cells, including tumor cells with mesenchyme-like features, ischemic tumor cells defined by a MYC program, inflammatory tumor cells with active interferon signaling, and stem cell-like hormone receptor-positive cells. The inferred spatial correlates of these tumor cell states demonstrated unique localization patterns. By correlating these signatures to bulk RNA sequencing data, we demonstrate the relevance of these findings to clinical outcomes. Finally, using the single-cell integration and drug response prediction algorithm (scIDUC), we propose drug predictions that may target specific tumor states. Our findings suggest new avenues for further exploration of individualized and multifaceted therapeutic strategies to treat ULMS.

cancer biology↗

AXL tyrosine kinase inhibition rescues immune checkpoint blockade-resistant melanoma in a tumor microenvironment-dependent fashion

BackgroundImmune checkpoint blockade (ICB) achieves durable responses in approximately half of patients with advanced melanoma, but the mechanistic basis for resistance in the remaining patients remains incompletely defined. AXL tyrosine kinase has emerged as a candidate resistance mediator, yet clinical development of AXL inhibitors has yielded heterogeneous results in unselected patient populations, suggesting that cell-type and tumor microenvironment context may critically govern therapeutic response. MethodsWe characterized AXL expression across cell types in ICB-resistant melanoma using publicly available single-cell RNA sequencing datasets and The Cancer Genome Atlas (TCGA). In vivo efficacy was assessed in the YUMM1.7 PD-1-resistant syngeneic melanoma model using three pharmacologically distinct AXL inhibitors (warfarin, bemcentinib, and cabozantinib) as monotherapy and in combination with anti-PD-1 therapy. Tumor-associated macrophage (TAM) context-dependency was established using anti-CSF1R and anti-F4/80 depletion strategies. Functional PD-L1:PD-1 checkpoint interactions were quantified in tumor sections by immune Forster Resonance Energy Transfer (iFRET). TAM secretome reprogramming was characterized by 40-plex Luminex immunoassay in polarized RAW264.7 macrophages. ResultsAXL expression in ICB-resistant melanoma was predominantly localized to TAMs rather than tumor cells by single-cell analysis, with AXL+ TAMs distributed across both M1-like and M2-like phenotypic compartments. AXL inhibition significantly reduced tumor burden and synergized with anti-PD-1 therapy in vivo; however, efficacy was abolished by depletion of the monocyte-derived myeloid compartment (anti-CSF1R) and enhanced by depletion of tissue-resident TAMs (anti-F4/80), establishing TAM-context dependency. iFRET revealed a paradoxical gain of PD-L1:PD-1 interaction efficiency in anti-PD-1-treated resistant tumors, a functional resistance signature detectable by iFRET but not by PD-L1 expression that was reversed by AXL combination therapy. In vitro secretome profiling demonstrated that combination therapy reprograms macrophage secretome in a polarization-context-dependent manner, amplifying pro-inflammatory cytokines including IL-6 and GM-CSF in M2-like macrophages while selectively dampening T cell chemokine production. ConclusionsThese findings establish AXL as a TAM-resident immune target in ICB-resistant melanoma whose therapeutic relevance is governed by tumor-immune micronenvironment (TiME) macrophage composition rather than tumor cell AXL expression. TAM polarization contexture represents a candidate stratification axis for AXL inhibitor-based combination strategies, and iFRET-measured checkpoint interaction offers a functional complement to PD-L1 expression for monitoring resistance and response. Key MessagesO_ST_ABSWhat is already known on this topicC_ST_ABSO_LIAXL tyrosine kinase has been studied predominantly as a tumor-intrinsic mesenchymal marker and therapeutic target in melanoma, with prior clinical development of AXL inhibitors predicated on tumor cell AXL expression as the primary biomarker; the contribution of TAM-expressed AXL to ICB resistance and the dependence of therapeutic response on TiME composition have not been defined. C_LI What this study addsO_LIAXL expression in ICB-resistant melanoma is predominantly localized to tumor-associated macrophages distributed across both M1-like and M2-like phenotypic compartments, reframing AXL as a TAM immune target whose therapeutic relevance is governed by TiME macrophage composition rather than tumor cell AXL expression. C_LIO_LICombination AXL inhibition and anti-PD-1 reprograms the macrophage secretome in a polarization-context-dependent manner and reverses a paradoxical gain of functional PD-L1:PD-1 checkpoint interaction in resistant tumors -- a resistance signature detectable by spatial iFRET but not by PD-L1 expression. C_LI How this study might affect research, practice or policyO_LIThe context-dependent effects of AXL inhibition (immunostimulatory in M2-heavy TiMEs, potentially counterproductive in M1-heavy TiMEs) indicate that TAM polarization profiling should be incorporated into clinical trial design for AXL inhibitor-based combinations, and that unselected enrollment may obscure meaningful efficacy signals in the subset most likely to benefit. C_LIO_LIiFRET-based quantification of functional checkpoint interaction represents a candidate dynamic biomarker for ICB resistance monitoring that is orthogonal to PD-L1 immunohistochemistry and may identify resistant patients who retain immunosuppressive checkpoint interactions that can be disrupted by AXL targeting. C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=170 HEIGHT=200 SRC="FIGDIR/small/667666v2_ufig1.gif" ALT="Figure 1"> View larger version (90K): org.highwire.dtl.DTLVardef@521de1org.highwire.dtl.DTLVardef@127a933org.highwire.dtl.DTLVardef@d56132org.highwire.dtl.DTLVardef@e03ef9_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

Functional Spatial Mapping of the Tumour Immune Microenvironment In Advanced Melanoma Patients

IntroductionCurrent spatial proteomic approaches quantify immune checkpoint expression but do not directly measure functional receptor/ligand (PD-1/PD-L1) interactions within the tumor immune microenvironment (TiME). Therapeutic antibodies disrupt receptor-ligand interactions and do not target protein abundance. Methods that resolve functional checkpoint interactions provide biologically distinct insight beyond expression-based assays MethodsWe combined computation and quantitative spatial imaging, FuncO:TiME, [Functional Oncology Mapping (FuncOmap)], to map PD-1/PD-L1 interaction states to spatially defined regions of the TiME, in clinically annotated melanoma specimens, collected before and after neoadjuvant immune checkpoint blockade (ICB), ResultsFuncOmap spatially quantified millions of per-pixel PD-1/PD-L1 interactions demonstrated spatial heterogeneity in checkpoint interaction, not reflected by PD-1 expression levels alone. Post-treatment tissues exhibited increased PD-1/PD-L1 interaction states despite no corresponding increase in expression, indicating persistent or augmented functional checkpoint interaction despite therapy. Integration with spatial immune profiling further demonstrated that checkpoint interaction intensity can be contextualized within distinct immune cell populations. ConclusionWe have established the feasibility of spatially resolved functional checkpoint mapping in human melanoma tissues. We demonstrate that receptor-ligand interactions diverge from protein expression patterns. By enabling direct interrogation of functional checkpoint interaction dynamics within intact tissue architecture, FuncO:TiME advances a functional paradigm for studying immune regulation in cancer.

cancer biology↗

Predicting targeted- and immunotherapeutic response outcomes in melanoma with single-cell Raman Spectroscopy and AI

PURPOSEIdentifying reliable predictors of immunotherapeutic response in melanoma remains an outstanding challenge. Existing transcriptomic and proteomic profiling methods for the tumor-immune microenvironment (TIME) are costly and may not faithfully capture modifications actively impacting tumor behavior. Here, we present a non-destructive, single-cell approach combining Raman spectroscopy and machine learning (ML) that enables rapid cell profiling and therapeutic response prediction. METHODSWe analyzed single-cell Raman spectra of mouse and human melanoma cell lines alongside nine melanoma patient-derived samples with known resistance profiles to targeted and immunotherapeutic inhibitors bemcentinib, cabozantinib, dabrafenib, nivolumab, and a combination of nivolumab and relatlimab. We assessed cell phenotyping classification and treatment resistance using random forests and feature importance analysis. For patient samples, we constructed a two-stage evaluation workflow to determine clinical drug resistance through aggregated single-cell predictions and identified corresponding highly variant spectral signatures using computational methods adapted from single-cell RNA sequencing methods. RESULTSIn cell lines, our approach achieved >96% differentiation accuracy across tumor microenvironment cell types and induced functional phenotypes. Persistent (drug-resistant) cells formed subclusters based on genetic mutations rather than sample origin, with Raman signatures reflecting biochemical changes relevant to therapeutic pathways. For patient samples, our workflow correctly inferred resistance likelihoods for 30 of 33 clinically-relevant patient-drug combinations (91% accuracy). CONCLUSIONSingle-cell Raman spectroscopy combined with machine learning offers a scalable, prognostic platform to predict therapeutic resistance likelihood, with further potential to advance clinical, multi-omic biomarker efforts for melanoma. Our approach may improve first-and second-line therapy selection assessments for precision medicine by providing rapid, non-destructive prediction of therapeutic response based on cellular spectral profiles. Context SummaryO_ST_ABSKey objectiveC_ST_ABSCan label-free, single-cell Raman spectroscopy and machine learning approach accurately profile melanoma cell states and therapeutic resistance likelihood to targeted and immunotherapeutic agents? Knowledge generatedRaman spectroscopy with machine learning differentiated tumor microenvironment cell types and functional phenotypes with >96% accuracy in cell lines. When applied to patient-derived metastatic melanoma samples, the approach correctly inferred patient response to a panel of targeted and immunotherapeutic inhibitors with 91% accuracy (30 of 33 cases). High-likelihood persistent and sensitive cells across diverse patients exhibited recurrent spectral features. RelevanceSingle-cell Raman-based profiling supports functional-diagnostic assessment or resistance likelihood and may contribute to improved therapeutic selection and precision oncology strategies for melanoma patients.

cancer biology↗

Antibody-Free Immunopeptide Nano-Conjugates for Brain-Targeted Drug Delivery in Glioblastoma Multiforme

Glioblastoma Multiforme (GBM) represents a significant clinical challenge amongst central nervous system (CNS) tumors, with a dismal mean survival rate of less than 8 months, a statistic that has remained largely unchanged for decades (National Brain Society, 2022). The specialized intricate anatomical features of the brain, notably the blood-brain barrier (BBB), pose significant challenges to effective therapeutic interventions, limiting the potential reach of modern advancements in immunotherapy to impact these types of tumors. This study introduces an innovative, actively targeted immunotherapeutic nanoconjugate (P12/AP-2/NCs) designed to serve as an immunotherapeutic agent capable of traversing the BBB via LRP-1 receptor-mediated transcytosis. P12/AP-2/NCs exert its immune-modulating effects by inhibiting the PD-1/PD-L1 axis through a small-size PD-L1/ PD-L2 antagonist peptide Aurigene NP-12 (P12). P12/AP-2/NCs are synthesized from completely biodegradable, functionalized high molecular weight {beta}-poly(L-malic acid) (PMLA) polymer, conjugated with P12 and Angiopep-2 (AP2) to yield P12/AP-2/NCs. Evaluating nanoconjugates for BBB permeability and 3-D tumor model efficacy using an in vitro BBB-Transwell spheroid based model demonstrating successful crossing of the BBB and internalization in brain 3D tumor environments. In addition, the nanoconjugate mediated T cells cytotoxicity on 3D tumor region death in a U87 GBM 3-D spheroid model. AP2/P12/NCs is selectively inhibited in PD1/PDL1 interaction on T cells and tumor site, increasing inflammatory cytokine secretion and T cell proliferation. In an in-vivo murine brain environment, rhodamine fluorophore-labeled AP2/P12/NCs displayed significantly increased accumulation in the brain during 2-6 h time intervals post-injection with a prolonged bioavailability over unconjugated peptides. AP2/P12/NCs demonstrated a safety profile at both low and high doses based on major organ histopathology evaluations. Our findings introduce a novel, programmable nanoconjugate platform capable of penetrating the BBB for directed delivery of small peptides and significant immune environment modulation without utilizing antibodies, offering promise for treating challenging brain diseases like glioblastoma multiforme and beyond.

immunology↗