Biology subjects

Khandekar, A.

Publications and source records attributed to Khandekar, A..

13 recordsLinked to original sources

bioRxiv2025

Revealing the Drivers Underlying Distinct Evolutionary Trajectories in Lung Adenocarcinoma

Elucidating the evolution of cancers allows us to understand their key events, and the order in which they occur. To chart and interpret these evolutionary trajectories, we leverage whole-genome sequencing of lung tumours, including those from the largest cohort to date of lung cancers in subjects who have never smoked. Through ordering frequent genomic alterations, we discover three distinct evolutionary paths taken by lung adenocarcinomas; two dominated by tumours from people who have never smoked (NS-LUAD), and one followed by the vast majority of those who have smoked (S-LUAD). However, one in six NS-LUAD follow the smoking-dominant trajectory. These tumours, surprisingly, have fewer somatic alterations than the other NS-LUAD, and have shorter latency. They are strongly enriched for KRAS mutations. Our results suggest that gaining KRAS mutations allows these tumours to evolve more rapidly, acquiring a set of smoking-associated key alterations, with less need for genomic instability to progress. These tumours are three times more frequent in subjects of European vs. East Asian ancestry. These findings could shape clinical management strategies for lung adenocarcinoma patients, particularly for tumours driven by smoking-like evolutionary trajectories.

cancer biology↗

bioRxiv2025

A prognostic signature for lung adenocarcinoma in people who have never smoked

Knowledge of tumor cell dynamics can inform prognosis and treatment yet is largely lacking for lung adenocarcinoma in people who have never smoked (NS-LUAD). With RNA-seq data from 684 NS-LUAD and validation in an independent dataset, we identified three subtypes with distinct phenotypic traits and cell compositions. Additional genomic and histological data further characterized the subtypes. Steady, marked by low proliferation, high alveolar cell fraction, moderate-to-well differentiation, and fewer driver genes alterations, is linked to prolonged survival and low immune evasion. Proliferative shows high proliferation markers, TP53 mutations, and gene fusions. Chaotic, with high epithelial-to-mesenchymal transition markers, has the worst prognosis even within stage I tumors. Lacking known molecular or histological characteristics, this aggressive subtype is solely identified by transcriptomic data. A 60-gene signature recapitulates the overall classification and strongly predicts survival even within subgroups based on tumor stage or known genomic features, emphasizing its potential for improving NS-LUAD prognostication in clinical settings. SignificanceThe transcriptome of 684 lung adenocarcinomas in people who have never smoked (NS-LUAD) identifies three subtypes with different cellular dynamics, and genomic and morphologic features. A 60-gene signature accurately stratifies subjects for mortality risk, even in stage I, offering a clinically applicable tool for treatment decision making in NS-LUAD patients.

genomics↗

bioRxiv2025

Copper-Containing ROS-Scavenging Nanozyme Paradoxically Drives Alpha-Synucleinopathy by Amplifying Nitrosative Stress

Reactive oxygen and nitrogen species (RONS) are implicated in neurodegeneration, but their specific pathogenic roles remain unclear. Here, we developed a pair of iridium-based nanozymes with opposing functionalities to dissect these pathways. We show that a copper-tuned iridium nanozyme (Ir{square}Cu), despite being a superior ROS scavenger, paradoxically and dramatically exacerbated -synuclein (Syn) pathology in vivo. This pathology was causally linked to its ability to amplify RNS, as pharmacological inhibition of nitric oxide synthase (NOS) with L-NAME completely abrogated the pathology and reversed a human Parkinsons disease (PD)-like transcriptomic signature. In contrast, a copper-free, broad-spectrum RONS-scavenging iridium (Ir) nanozyme demonstrated substantial therapeutic efficacy across diverse brain-first, body-first, and Alzheimers disease with Lewy body co-pathology models. Our findings uncover the importance of the RNS pathway in driving -synucleinopathies and establish a critical design principle for nanomedicine, mandating caution in the use of redox-active copper for neuroprotective applications.

pathology↗

bioRxiv2025

Examining the Role of Extrachromosomal DNA in 1,216 Lung Cancers

The role of extrachromosomal DNA (ecDNA) in lung cancer, particularly in subjects who never smoked (LCINS), remains unclear. Examination of over 1200 whole-genome-sequenced lung cancers identified ecDNA in 18.9% of patients. Recurrent amplification of MDM2 and other oncogenes via ecDNA possibly drives a LCINS subset. Tumors harboring ecDNA showed worse overall survival than tumors harboring other focal amplifications. A strong association with whole-genome doubling suggests most ecDNA reflects genomic instability in treatment-naive lung cancer.

bioinformatics↗

bioRxiv2025

In vivo single-cell CRISPR screening for microproteins identifies a critical ribosomal component

The dark proteome includes a rapidly expanding catalog of microproteins with unknown functions that have been historically ignored in genome annotations. Here, we exploit an in vivo single-cell CRISPR screening strategy in the mouse epidermis to systematically investigate the tissue-wide function of microproteins. We document the global and cell-type-specific roles of microproteins during epidermal development and homeostasis at single-cell transcriptomic resolution. Focusing on select candidates, we identify a novel microprotein on Gm10076, identical to the ribosomal intersubunit bridge protein RPL41, whose perturbation strongly impairs proliferation and protein synthesis. Employing ribosome profiling and RNA sequencing, we show that Gm10076 perturbation profoundly reshapes the translational landscape. Contrary to its prior classification as nonessential, we find that the ribosomal protein RPL41 is essential for cellular proliferation, warranting further investigation into its role as an intersubunit bridge in the translational machinery. Together, our study comprehensively charts the tissue-wide functional landscape of the dark proteome, uncovers a second Rpl41 gene critical for ribosome function and establishes a basis for exploring the impact of microproteins on disease pathogenesis.

genetics↗

bioRxiv2025

Deciphering lung adenocarcinoma evolution and the role of LINE-1 retrotransposition

Understanding lung cancer evolution can identify tools for intercepting its growth. In a landscape analysis of 1024 lung adenocarcinomas (LUAD) with deep whole-genome sequencing integrated with multiomic data, we identified 542 LUAD that displayed diverse clonal architecture. In this group, we observed an interplay between mobile elements, endogenous and exogenous mutational processes, distinct driver genes, and epidemiological features. Our results revealed divergent evolutionary trajectories based on tobacco smoking exposure, ancestry, and sex. LUAD from smokers showed an abundance of tobacco-related C:G>A:T driver mutations in KRAS plus short subclonal diversification. LUAD in never smokers showed early occurrence of copy number alterations and EGFR mutations associated with SBS5 and SBS40a mutational signatures. Tumors harboring EGFR mutations exhibited long latency, particularly in females of European-ancestry (EU_N). In EU_N, EGFR mutations preceded the occurrence of other driver genes, including TP53 and RBM10. Tumors from Asian never smokers showed a short clonal evolution and presented with heterogeneous repetitive patterns for the inferred mutational order. Importantly, we found that the mutational signature ID2 is a marker of a previously unrecognized mechanism for LUAD evolution. Tumors with ID2 showed short latency and high L1 retrotransposon activity linked to L1 promoter demethylation. These tumors exhibited an aggressive phenotype, characterized by increased genomic instability, elevated hypoxia scores, low burden of neoantigens, propensity to develop metastasis, and poor overall survival. Re-activated L1 retrotransposition-induced mutagenesis can contribute to the origin of the mutational signature ID2, including through the regulation of the transcriptional factor ZNF695, a member of the KZFP family. The complex nature of LUAD evolution creates both challenges and opportunities for screening and treatment plans.

genomics↗

bioRxiv2024

In vivo single-cell ribosome profiling reveals cell-type-specific translational programs during aging

Somatic stem cells are characterized by their low overall protein synthesis rates, a feature implicated in driving their stemness. However, how aging reshapes the translational landscape of stem cells and how these changes impact their regenerative capacity remains poorly understood. Here, we present an in vivo single-cell ribosome profiling strategy to monitor tissue-wide translational landscapes of the young and aged mouse epidermis. By implementing ribosomal elongation-inhibited cell isolation and switching to RNase I ribonuclease for generating ribosomal footprints, we expand the applicability of single-cell ribosome profiling to in vivo systems and facilitate the evaluation of triplet periodicity, a hallmark of high-quality ribosome profiling data. Leveraging this strategy and integrating ribosome profiling with single-cell RNA sequencing, we document the in vivo translational landscapes of the major epidermal cell types, outline cell-type-specific translational efficiencies and capture heterogeneity in differentiation commitment within stem cell populations. Notably, we identify a pronounced translational reprogramming of AP-1 subunits specifically in aged epidermal stem cells, with functional consequences for keratinocyte behavior. Our study illustrates the power of in vivo single-cell ribosome profiling to map cell-type-specific translational programs and offers a scalable strategy for tissue-wide interrogation of translational landscapes at single-cell resolution.

genomics↗

bioRxiv2023

In vivo single-cell CRISPR uncovers distinct TNF-alphaprograms in clonal expansion and tumorigenesis

The tumor evolution model posits that malignant transformation is preceded by randomly distributed driver mutations in cancer genes, which cause clonal expansions in phenotypically normal tissues. Although clonal expansions occur frequently in human epithelia and can remodel almost entire tissues, the mechanisms behind why only a small number of clones transform into malignant tumors remain enigmatic. Here, we develop an in vivo single-cell CRISPR strategy to systematically investigate tissue-wide clonal dynamics of the 150 most frequently mutated squamous cell carcinoma genes. We couple ultrasound-guided in utero lentiviral microinjections, single-cell RNA sequencing, guide capture and spatial transcriptomics to longitudinally monitor cell type-specific clonal expansions, document their underlying gene programs and contrast clonal expansions from tumor initiation. We uncover a TNF- signaling module that acts as a generalizable driver of clonal expansions in epithelial tissues. Conversely, during tumorigenesis, the TNF- signaling module is downregulated, and instead, we identify a subpopulation of invasive cancer cells that switch to an autocrine TNF- gene program. By analyzing clonally expanded perturbations and their frequency in tumors, we demonstrate that the autocrine TNF- gene program is associated with epithelial-mesenchymal transition (EMT) and is preexistent in a subpopulation of expanded epidermal stem cells, contributing to the predisposition for tumor initiation. Finally, we provide in vivo evidence that the epithelial TNF- gene program is sufficient to mediate invasive properties of epidermal stem cells and show that the TNF- signature correlates with shorter overall survival in human squamous cell carcinoma patients. Collectively, our study demonstrates the power of applying in vivo single-cell CRISPR screening to mammalian tissues and unveils distinct TNF- programs in tumor evolution. Understanding the biology of clonal expansions in phenotypically normal epithelia and the mechanisms governing their transformation will guide the development of novel strategies for early cancer detection and therapy.

cancer biology↗

bioRxiv2023

Visualizing and exploring patterns of large mutational events with SigProfilerMatrixGenerator

BackgroundAll cancers harbor somatic mutations in their genomes. In principle, mutations affecting between one and fifty base pairs are generally classified as small mutational events. Conversely, large mutational events affect more than fifty base pairs, and, in most cases, they encompass copy-number and structural variants affecting many thousands of base pairs. Prior studies have demonstrated that examining patterns of somatic mutations can be leveraged to provide both biological and clinical insights, thus, resulting in an extensive repertoire of tools for evaluating small mutational events. Recently, classification schemas for examining large-scale mutational events have emerged and shown their utility across the spectrum of human cancers. However, there has been no standard bioinformatics tool that allows visualizing and exploring these large-scale mutational events ResultsHere, we present a new version of SigProfilerMatrixGenerator that now delivers integrated capabilities for examining large mutational events. The tool provides support for examining copy-number variants and structural variants under two previously developed classification schemas and it supports data from numerous algorithms and data modalities. SigProfilerMatrixGenerator is written in Python with an R wrapper package provided for users that prefer working in an R environment. ConclusionsThe new version of SigProfilerMatrixGenerator provides the first standardized bioinformatics tool for optimized exploration and visualization of two previously developed classification schemas for copy number and structural variants. The tool is freely available at https://github.com/AlexandrovLab/SigProfilerMatrixGenerator with an extensive documentation at https://osf.io/s93d5/wiki/home/.

bioinformatics↗

bioRxiv2021

Disentangling heterogeneity of Malignant Pleural Mesothelioma through deep integrative omics analyses

Malignant Pleural Mesothelioma (MPM) is an aggressive cancer with rising incidence and challenging clinical management. Using the largest series of whole-genome sequencing data integrated with transcriptomic and epigenomic data using multi-omic factor analysis, we demonstrate that MPM heterogeneity arises from four sources of variation: tumor cell morphology, ploidy, adaptive immune response, and CpG island methylator phenotype. Previous genomic studies focused on describing only the tumor cell morphology factor, although we robustly find the three other sources in all publicly available cohorts. We prove how these sources of variation explain the biological functions performed by the cancer cells, and how genomic events shape MPM molecular profiles. We show how these new sources of variation help understand the heterogeneity of the clinical behavior of MPM and drug responses measured in cell lines. These findings unearth the interplay between MPM functional biology and its genomic history, and ultimately, inform classification, prognostication and treatment. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/461908v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@b6c43corg.highwire.dtl.DTLVardef@10d45a9org.highwire.dtl.DTLVardef@58746eorg.highwire.dtl.DTLVardef@143f880_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2021

Signatures of copy number alterations in human cancer

The gains and losses of DNA that emerge as a consequence of mitotic errors and chromosomal instability are prevalent in cancer. These copy number alterations contribute to cancer initiaition, progression and therapeutic resistance. Here, we present a conceptual framework for examining the patterns of copy number alterations in human cancer using whole-genome sequencing, whole-exome sequencing, and SNP6 microarray data making it widely applicable to diverse datasets. Deploying this framework to 9,873 cancers representing 33 human cancer types from the TCGA project revealed a set of 19 copy number signatures that explain the copy number patterns of 93% of TCGA samples. 15 copy number signatures were attributed to biological processes of whole-genome doubling, aneuploidy, loss of heterozygosity, homologous recombination deficiency, and chromothripsis. The aetiology of four copy number signatures are unexplained and some cancer types have unique patterns of amplicon signatures associated with extrachromosomal DNA, disease-specific survival, and gains of proto-oncogenes such as MDM2. In contrast to base-scale mutational signatures, no copy number signature associated with known cancer risk factors. The results provide a foundation for exploring patterns of copy number changes in cancer genomes and synthesise the global landscape of copy number alterations in human cancer by revealing a diversity of mutational processes giving rise to copy number changes.

cancer biology↗

bioRxiv2020

Uncovering novel mutational signatures by de novo extraction with SigProfilerExtractor

Mutational signature analysis is commonly performed in genomic studies surveying cancer and normal somatic tissues. Here we present SigProfilerExtractor, an automated tool for accurate de novo extraction of mutational signatures for all types of somatic mutations. Benchmarking with a total of 34 distinct scenarios encompassing 2,500 simulated signatures operative in more than 60,000 unique synthetic genomes and 20,000 synthetic exomes demonstrates that SigProfilerExtractor outperforms thirteen other tools across all datasets with and without noise. For genome simulations with 5% noise, reflecting high-quality genomic datasets, SigProfilerExtractor outperforms other approaches by elucidating between 20% and 50% more true positive signatures while yielding more than 5-fold less false positive signatures. Applying SigProfilerExtractor to 4,643 whole-genome sequenced and 19,184 whole-exome sequenced cancers reveals four previously missed mutational signatures. Two of the signatures are confirmed in independent cohorts with one of these signatures associating with tobacco smoking. In summary, this report provides a reference tool for analysis of mutational signatures, a comprehensive benchmarking of bioinformatics tools for extracting mutational signatures, and several novel mutational signatures including a signature putatively attributed to direct tobacco smoking mutagenesis in bladder cancer and in normal bladder epithelium.

bioinformatics↗

bioRxiv2018

Microridges are apical projections formed of branched F-actin networks that organize the glycan layer

Apical projections are integral functional units of epithelial cells. Microvilli and stereocilia are cylindrical apical projections that are formed of bundled actin. Microridges on the other hand, grow laterally long, forming labyrinthine patterns on surfaces of various kinds of squamous epithelial cells. So far, the structural organization and functions of microridges have remained elusive. We have analyzed microridges on zebrafish epidermal cells using confocal and electron microscopy methods including electron tomography, to show that a microridge is formed of a network of F-actin and requires the function of the Arp2/3 complex for its maintenance. During development, microridges begin as F-actin punctae showing signatures of branching and requiring an active Arp2/3 complex. Using inhibitors of actin polymerization and the Arp2/3 complex, we show that microridges organize the surface glycan layer. Our analyses have unraveled the F-actin organization supporting the most abundant and evolutionarily conserved apical projection, which functions in glycan organization.

cell biology↗