Biology subjects

Jamal-Hanjani, M.

Publications and source records attributed to Jamal-Hanjani, M..

6 recordsLinked to original sources

bioRxiv2025

JAK1/2 Inhibition Delays Cachexia and Improves Survival through Increased Food Intake

Lung cancer is the leading cause of cancer-related death and is frequently accompanied by reduced food intake and cachexia, a debilitating syndrome characterized by weight loss and skeletal muscle wasting. We sought to identify contributors to cachexia using a murine model of lung cancer that reproduces key features of this syndrome. A multiplex cytokine screening approach, integrated with western blot and transcriptomic analyses, identified tumor-derived inflammatory mediators and downstream signaling pathways associated with cachexia. Notably, IL-6 superfamily members were elevated in the tumor and plasma of mice and patients with cachexia. The JAK-STAT3 signaling was upregulated in liver and skeletal muscle, driving the acute phase response and impairing lipid metabolism. Pharmacologic inhibition of JAK1/2 with ruxolitinib improved body weight, fat mass, and overall survival without altering tumor burden. These effects were driven primarily by blunted hypothalamic leptin receptor signaling, which increased food intake early in the disease course. In the liver, JAK inhibition reduced STAT3 activity, restored fatty acid oxidation, and decreased the production of acute-phase proteins. These findings support JAK inhibition as a therapeutic strategy for lung cancer-associated cachexia. Statement of SignificanceCancer cachexia is a lethal complication of lung cancer that lacks effective treatment. We show that JAK inhibition by ruxolitinib restores weight, fat mass, and prolongs survival in murine models of lung cancer. These effects were independent of tumor burden, underscoring the relevance of addressing cachexia to improve survival in cancer patients and supporting clinical testing of JAK inhibition for cancer cachexia

cancer biology↗

bioRxiv2024

Extrachromosomal DNA driven oncogene spatial heterogeneity and evolution in glioblastoma

Oncogene amplification on extrachromosomal DNA (ecDNA) is strongly associated with treatment resistance and shorter survival for patients with cancer, including patients with glioblastoma. The non-chromosomal inheritance of ecDNA during cell division is a major contributor to intratumoral genetic heterogeneity. At present, the spatial dynamics of ecDNA, and the impact on tumor evolutionary trajectories, are not well understood. Here, we investigate the spatial-temporal evolution of ecDNA and its clinical impact by analyzing tumor samples from 94 treatment-naive human IDH-wildtype glioblastoma patients. We developed a spatial-temporal computational model of ecDNA positive tumors ( SPECIES) that integrates whole-genome sequencing, multi-region DNA FISH, and nascent RNAscope, to provide unique insight into the spatial dynamics of ecDNA evolution. Random segregation in combination with positive selection of ecDNAs induce large, predictable spatial patterns of cell-to-cell ecDNA copy number variation that are highly dependent on the oncogene encoded on the circular DNA. EGFR ecDNAs often reach high mean copy number (mean of 50 copies per tumor cell), are under strong positive selection (mean selection coefficient, s > 2) and do not co-amplify other oncogenes on the same ecDNA particles. In contrast, PDGFRA ecDNAs have lower mean copy number (mean of 15 copies per cell), are under weaker positive selection and frequently co-amplify other oncogenes on the same ecDNA. Evolutionary modeling suggests that EGFR ecDNAs often accumulate prior to clonal expansion. EGFR structural variants, including vIII and c-terminal deletions are under strong positive selection, are found exclusively on ecDNA, and are intermixed with wild-type EGFR ecDNAs. Simulations show EGFRvIII ecDNA likely arises after ecDNA formation in a cell with high wild-type EGFR copy number (> 10) before the onset of the most recent clonal expansion. This remains true even in cases of co-selection and co-amplification of multiple oncogenic ecDNA species in a subset of patients. Overall, our results suggest a potential time window in which early ecDNA detection may provide an opportunity for more effective intervention. HighlightsO_LIecDNA is the most common mechanism of focal oncogene amplification in IDHwt glioblastoma. C_LIO_LIEGFR and its variants on ecDNA are particularly potent, likely arising early in tumor development, providing a strong oncogenic stimulus to drive tumorigenesis. C_LIO_LIWild-type and variant EGFR ecDNA heteroplasmy (co-occurrence) is common with EGFRvIII or c-terminal deletions being derived from EGFR wild-type ecDNA prior to the most recent clonal expansion. C_LIO_LITumors with ecDNA amplified EGFR versus PDGFRA exhibit different evolutionary trajectories. C_LIO_LISPECIES model can infer spatial evolutionary dynamics of ecDNA in cancer. C_LIO_LIA delay between ecDNA accumulation and subsequent oncogenic mutation may give a therapeutic window for early intervention. C_LI

cancer biology↗

bioRxiv2023

Genomic evolution of non-small cell lung cancer patient-derived xenograft models

Patient-derived xenograft (PDX) models of cancer, developed through injection of patient tumour cells into immunocompromised mice, have been widely adopted in preclinical studies, as well as in precision oncology approaches. However, the extent to which PDX models represent the underlying genetic diversity of a patients tumour and the extent of on-going genomic evolution in PDX models are incompletely understood, particularly in the context of heterogeneous cancers such as non-small cell lung cancer (NSCLC). To investigate the depiction of intratumour heterogeneity by PDX models, we derived 47 new subcutaneous multi-region PDX models from 22 patients with primary NSCLC enrolled in the clinical longitudinal cohort study TRACERx. By analysing whole exome sequencing data from primary tumours and PDX models, we find that PDX establishment creates a genomic bottleneck, with 76% of PDX models being derived from a single primary tumour subclone. Despite this, multiple primary tumour subclones were capable of PDX establishment in regional PDX models, indicating that PDX libraries derived from multiple tumour regions can capture intratumour heterogeneity. Acquisition of somatic mutations continued during PDX model expansion, and was associated with APOBEC- or mismatch repair deficiency-induced mutational signatures in a subset of models. Overall, while NSCLC PDX models retain truncal genomic alterations, the absence of subclonal heterogeneity representative of the primary tumour is a major limitation. Our results emphasise the importance of characterising and monitoring intratumour heterogeneity in the context of pre-clinical cancer studies.

cancer biology↗

bioRxiv2020

Copy number-aware deconvolution of tumor-normal DNA methylation profiles

Aberrant methylation is a hallmark of cancer, but bulk tumor data is confounded by admixed normal cells and copy number changes. Here, we introduce Copy number-Aware Methylation Deconvolution Analysis of Cancers (CAMDAC; https://github.com/VanLoo-lab/CAMDAC), which outputs tumor purity, allele-specific copy number and deconvolved methylation estimates. We apply CAMDAC to 122 multi-region samples from 38 TRACERx non-small cell lung cancers profiled by reduced representation bisulfite sequencing. CAMDAC copy number profiles parallel those derived from genome sequencing and highlight widespread chromosomal instability. Deconvolved polymorphism-independent methylation rates enable unbiased tumor-normal and tumor-tumor differential methylation calling. Read-phasing validates CAMDAC methylation rates and directly links genotype and epitype. We show increased epigenetic instability in adenocarcinoma vs. squamous cell carcinoma, frequent hypermethylation at sites carrying somatic mutations, and parallel copy number losses and methylation changes at imprinted loci. Unlike bulk methylomes, CAMDAC profiles recapitulate tumor phylogenies and evidence distinct patterns of epigenetic heterogeneity in lung cancer.

genomics↗

bioRxiv2020

Transcriptome analysis of IPF fibroblastic foci identifies key pathways involved in fibrogenesis

Fibroblastic foci (FF) represent the cardinal pathogenic lesion in idiopathic pulmonary fibrosis (IPF) and comprise activated fibroblasts and myofibroblasts, the key effector cells responsible for dysregulated extracellular matrix deposition in multiple fibrotic conditions. The aim of this study was to define the major transcriptional programmes involved in fibrogenesis in IPF by profiling un-manipulated myo/fibroblasts within FF in situ by laser capture microdissection. The challenges associated with deriving gene calls from low amounts of RNA and the absence of a meaningful comparator cell type were overcome by adopting novel data mining strategies and by using weighted gene co-expression network analysis (WGCNA), as well as an eigengene-based approach to identify transcriptional signatures which correlate with fibrillar collagen gene expression. WGCNA identified prominent clusters of genes associated with cell cycle, inflammation/differentiation, translation and cytoskeleton/cell adhesion. Collagen eigengene analysis revealed that TGF-{beta}1, RhoA kinase and the TSC2/RHEB axis formed major signalling clusters associated with collagen gene expression. Functional studies using CRISPR-Cas9 gene edited cells demonstrated a key role for the TSC2/RHEB axis in regulating TGF-{beta}1-induced mTORC1 activation and collagen I deposition in mesenchymal cells reflecting IPF and other disease settings, including cancer-associated fibroblasts. These data provide strong support for the human tissue-based and bioinformatics approaches adopted to identify critical transcriptional nodes associated with the key pathogenic cell responsible for fibrogenesis in situ and further identifies the TSC2/RHEB axis as a potential novel target for interfering with excessive matrix deposition in IPF and other fibrotic conditions. What is the key question?Can we identify a transcriptional signature associated with collagen gene expression in the fibrotic focus, the cardinal fibrotic lesion in IPF? What is the bottom line?We herein define the major transcriptional programmes involved in fibrogenesis in IPF by profiling myo/fibroblasts within FF in situ by laser capture microdissection. Why read on?The data provide strong support for a human tissue-based approach to identify critical transcriptional nodes associated with fibrogenesis in situ and further identifies the TSC2/RHEB axis as a potential novel target for interfering with excessive matrix deposition in IPF and other fibrotic conditions.

cell biology↗

bioRxiv2019

Whole Genome Doubling mitigates Muller’s Ratchet in Cancer Evolution

Whole genome doubling (WGD) is a prevalent macro-evolutionary event in cancer, involving a doubling of the entire chromosome complement. However, despite its prevalence and clinical prognostic relevance, the evolutionary selection pressures for WGD have not been investigated. Here, we explored whether WGD may act to mitigate the irreversible, inexorable ratchet-like, accumulation of deleterious mutations in essential genes. Utilizing 1050 tumor regions from 816 non-small cell lung cancers (NSCLC), we temporally dissect mutations to determine their temporal acquisition in relation to WGD. We find evidence for strong negative selection against homozygous loss of essential cancer genes prior to WGD. However, mutations in essential genes occurring after duplication were not subject to significant negative selection, consistent with WGD providing a buffering effect, decreasing the likelihood of homozygous loss. Finally, we demonstrate that loss of heterozygosity and temporal dissection of mutations can be exploited to identify signals of positive selection in lung, breast, colorectal cancer and other cancer types, enabling the elucidation of novel tumour suppressor genes and a deeper characterization of known cancer genes.

genomics↗