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Mills, I. G.

Publications and source records attributed to Mills, I. G..

17 recordsLinked to original sources

Assessing the effects of a 3D pathology tissue-processing workflow on downstream molecular analyses

Non-destructive 3D pathology methods have emerged in recent years with the potential to enhance standard 2D histopathology by greatly increasing the amount of tissue sampled by imaging and by providing volumetric morphological context. Another key advantage is that tissues remain intact, allowing re-embedding after imaging for potential long-term storage and future histological or molecular analyses. However, the impact of 3D pathology protocols on biomolecules -- including DNA, RNA, and proteins -- and their compatibility with downstream assays, has not been systematically evaluated. Here, we applied a previously optimized 3D pathology protocol -- involving deparaffinization, fluorescent H&E-analog staining, optical clearing, and open-top light-sheet microscopy -- to formalin-fixed paraffin-embedded (FFPE) specimens of breast, prostate, and head and neck cancer. Following the protocol, tissues were re-embedded in paraffin and compared with paired FFPE controls that did not undergo 3D pathology processing. DNA and RNA were extracted and subjected to quality assessments. Amplifiability was tested by PCR and reverse transcription quantitative PCR (RT-qPCR) of housekeeping genes. Although the results showed a slight decrease in the average yield and increased fragmentation of both DNA and RNA, amplifiability was largely preserved. Sanger sequencing of the PCR products confirmed accurate sequence determinations, while total RNA sequencing indicated that the global transcriptomic profile was largely unchanged. IHC staining of common biomarkers produced comparable signals, suggesting those proteins are well preserved after the 3D pathology workflow. These results demonstrate the feasibility of combining 3D pathology with downstream molecular applications.

pathology↗

3D pathology-guided microdissection

Traditional micro- and macro-dissection techniques enable the extraction of localized regions in thin tissue sections for molecular analysis. Despite the growing use of 3D microscopy, analogous methods for volumetric microdissection are lacking. We have developed a 3D microdissection method based on computer numerical controlled (CNC) milling integrated with open-top light-sheet microscopy. We demonstrate the ability to study tumor evolution along convoluted 3D branching architectures, which is inaccessible to 2D methods.

bioengineering↗

IRE1 activity regulates tumour and microenvironment cell lineage states while stratifying localised and metastatic prostate cancer.

Prostate cancer (PCa) is an androgen receptor (AR) driven, high-incidence disease significantly contributing to cancer mortality. PCa is in need of better risk stratification at diagnosis and treatment outcomes in patients at high risk of metastasis. The unfolded protein response (UPR) is an AR-dependent process. However, the impact of the UPR transducer IRE1 on AR-dependent biology and treatment resistance has not been defined. We use diverse pre-clinical models of stress response to describe IRE1 activity impact on multiple disease stages and demonstrate its involvement with poor prognosis (RB1 loss), and cell lineage determination (club phenotypes). Integrating clinical transcriptomic datasets, we chart IRE1 activity throughout PCa evolution by developing a PCa-specific, IRE1 activity gene set (IRE1_18) reflecting both tumoral and micro-environmental niches. IRE1_18 can determine tumoral identity, inform androgen deprivation treatment suitability, prognosticate localised and metastatic disease independently from AR activity, and guide IRE1 modulation as a novel combination therapeutic. Graphical Abstract created using Biorender.com O_FIG O_LINKSMALLFIG WIDTH=197 HEIGHT=200 SRC="FIGDIR/small/643042v3_ufig1.gif" ALT="Figure 1"> View larger version (49K): org.highwire.dtl.DTLVardef@18edd6aorg.highwire.dtl.DTLVardef@6a759eorg.highwire.dtl.DTLVardef@14ff3fborg.highwire.dtl.DTLVardef@1ae77d_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

IGFs regulate cancer cell immune evasion in prostate cancer

Insulin-like growth factor-1 (IGF-1) promotes prostate cancer (PCa) development and lethality, with immunosuppressive properties in other disease models. These studies investigated the tumor-intrinsic immune effects of IGF-1 in PCa to understand mechanisms underlying its poor immunotherapy response. Transcriptional profiling of human (DU145, 22Rv1) and murine (Myc-CaP) PCa cells revealed, through pathway enrichment, that cytokine signalling, antigen processing and presentation, and other immune regulatory pathways, were most suppressed by IGF-1. We went on to investigate changes in the expression of components of two key pathways responsible for cancer cell recognition by immune cells and immune evasion: antigen processing and presentation, and PD-L1 checkpoint expression. These pathways are crucial for determining immunotherapy response. IGF-1 downregulated transporters associated with antigen processing (TAPs), endoplasmic reticulum aminopeptidase-1 (ERAP-1), and Class I component {beta}2-microglobulin, without major changes in Class I allele expression. These effects were associated with reduced presentation of Class I complexes on the Myc-CaP cell surface suggesting altered peptide transport, processing, and/or presentation. In contrast, IGF-1 upregulated immune checkpoint CD274 (PD-L1) via IGF receptor/AKT/ERK-dependent signaling. Analysis of public data (TCGA Firehose Legacy PCa) revealed increased CD274 expression in PCa with high endogenous IGF1 and IGFBP5, markers of high IGF axis activity. Additionally, in primary PCa (n=32), multiplex immunofluorescence revealed higher PD-L1 expression in the central tumor of men with high serum IGF-1 promoting cancer cell immune evasion in PCa. These findings indicate a novel mechanism by which IGF-1 mediates immunosuppressive effects in malignant prostate epithelium, potentially explaining the poor responsiveness of PCa to immunotherapy and highlighting the complex interplay between IGF signaling and immune evasion.

cancer biology↗

Mitochondrial metabolism is a key determinant of chemotherapy sensitivity in Colorectal Cancer

Therapy resistance is attributed to over 80% of cancer deaths per year emphasizing the urgent need to overcome this challenge for improved patient outcomes. Despite its widespread use in colorectal cancer (CRC) treatment, resistance to 5-fluorouracil (5FU) remains poorly understood. Here, we investigate the transcriptional responses of CRC cells to 5FU treatment, revealing significant metabolic reprogramming towards heightened mitochondrial activity. Utilizing CRC models, we demonstrate sustained enhancement of mitochondrial biogenesis and function following 5FU treatment, leading to resistance in both in vitro and in vivo settings. Furthermore, we show that targeting mitochondrial metabolism, specifically by inhibiting Complex I (CI), sensitizes CRC cells to 5FU, resulting in delayed tumour growth and prolonged survival in preclinical models. Additionally, our analysis of patient data suggests that oxidative metabolism signatures may predict responses to 5FU-based chemotherapy. These findings shed light on mechanisms underlying 5FU resistance and propose a rational strategy for combination therapy in CRC, emphasizing the potential clinical benefit of targeting mitochondrial metabolism to overcome resistance and enhance patient outcomes.

cancer biology↗

Androgen deprivation therapy-resistant club cells are linked to myeloid cell-driven immunosuppression in the prostate tumor microenvironment

Prostate cancer treatment resistance is a significant challenge facing the field. Genomic and transcriptomic profiling have partially elucidated the mechanisms through which cancer cells escape treatment, but their relation toward the tumor microenvironment (TME) remains elusive. Here we present a comprehensive transcriptomic landscape of the prostate TME at multiple points in the standard treatment timeline employing single-cell RNA-sequencing and spatial transcriptomics data from 110 patients. We identify club-like cells as a key epithelial cell subtype that acts as an interface between the prostate and the immune system. Tissue areas enriched with club-like cells have depleted androgen signaling and upregulated expression of luminal progenitor cell markers. Club-like cells display a senescence-associated secretory phenotype and their presence is linked to increased polymorphonuclear myeloid-derived suppressor cell (PMN-MDSC) activity. Our results indicate that club-like cells partake in inducing myeloid inflammation previously associated with androgen deprivation therapy resistance, providing a rationale for their therapeutic targeting.

cancer biology↗

Molecular analysis of archival diagnostic prostate cancer biopsies identifies genomic similarities in cases with progression post-radiotherapy, and those with de novo metastatic disease.

PurposeIt is important to identify molecular features that improve prostate cancer (PCa) risk stratification before radical treatment with curative intent. Molecular analysis of historical diagnostic formalin-fixed paraffin-embedded (FFPE) prostate biopsies from cohorts with post-radiotherapy (RT) long-term clinical follow-up has been limited. Utilizing parallel sequencing modalities, we performed a proof-of-principle sequencing analysis of historical diagnostic FFPE prostate biopsies. We compared patients with i) stable PCa post-primary or salvage RT (sPCa), ii) progressing PCa post-RT (pPCa), and iii) de novo metastatic PCa (mPCa). Experimental DesignA cohort of 19 patients with diagnostic prostate biopsies (n=6 sPCa, n=5 pPCa, n=8 mPCa) and mean 4 years 10 months follow-up (diagnosed 2009-2016) underwent nucleic acid extraction from demarcated malignancy. Samples underwent 3RNA sequencing (3RNAseq) (n=19), nanoString analysis (n=12) and Illumina 850k methylation (n=8) sequencing. Bioinformatic analysis was performed to coherently identify differentially expressed genes (DEGs) and methylated genomic regions (MGRs). Results18 of 19 samples provided useable 3RNAseq data. Principal Component Analysis (PCA) demonstrated similar expression profiles between pPCa and mPCa cases, versus sPCa. Coherently differentially methylated probes between these groups identified [~]600 differentially MGRs. The top 50 genes with increased expression in pPCa patients were associated with reduced progression-free survival post-RT (p<0.0001) in an external cohort. Conclusions3RNAseq, nanoString and 850K-methylation analyses are each achievable from historical FFPE diagnostic pre-treatment prostate biopsies, unlocking the potential to utilize large cohorts of historic clinical samples. Profiling similarities between individuals with pPCa and mPCa suggests biological similarities and historical radiological staging limitations, which warrant further investigation.

genomics↗

Spatial transcriptomic analysis of virtual prostate biopsy reveals confounding effect of heterogeneity on genomic signature scoring

Genetic signatures have added a molecular dimension to prognostics and therapeutic decision-making. However, tumour heterogeneity in prostate cancer and current sampling methods could confound accurate assessment. Based on previously published spatial transcriptomic data from multifocal prostate cancer, we created virtual biopsy models that mimic conventional biopsy placement and core size. We then analysed the gene expression of different prognostic signatures (OncotypeDx(R), Decipher(R), Prostadiag(R)) using a step-wise approach increasing resolution from pseudo-bulk analysis of the whole biopsy, to differentiation by tissue subtype (benign, stroma, tumour), followed by distinct tumour grade and finally clonal resolution. The gene expression profile of virtual tumour biopsies revealed clear differences between grade groups and tumour clones, compared to a benign control, which were not reflected in bulk analyses. This suggests that bulk analyses of whole biopsies or tumour-only areas, as used in clinical practice, may provide an inaccurate assessment of gene profiles. The type of tissue, the grade of the tumour and the clonal composition all influence the gene expression in a biopsy. Clinical decision making based on biopsy genomics should be made with caution while we await more precise targeting and cost-effective spatial analyses. Patient summaryProstate cancers are very variable, including within a single tumour. Current genetic scoring systems, which are sometimes used to make decisions for how to treat patients with prostate cancer, are based on sampling methods which do not reflect these variations. We found, using state-of-the-art spatial genetic technology to simulate accurate assessment of variation in biopsies, that the current approaches miss important details which could negatively impact clinical decisions. Take home messageVirtual biopsies from spatial transcriptomic analysis of a whole prostate reveal that current genomic risk scores potentially deliver misleading results as they are based on bulk analysis of prostate biopsies and ignore tumour heterogeneity.

genomics↗

Clonal phylogenies inferred from bulk, single cell, and spatial transcriptomic analysis of cancer

Epithelial cancers are typically heterogeneous with primary prostate cancer being a typical example of histological and genomic variation. Prostate cancer is the second most common male cancer in western industrialized countries. Prior studies of primary prostate cancer tumor genetics revealed extensive inter and intra-patient tumor heterogeneity. Recent advances have enabled extensive single-cell and spatial transcriptomic profiling of tissue specimens. The ability to resolve accurate prostate cancer tumor phylogenies at high spatial resolution would provide tools to address questions in tumorigenesis, disease progression, and metastasis. Recent advances in machine learning have enabled the inference of ground-truth genomic single-nucleotide and copy number variant status from transcript data. The inferred SNV and CNV states can be used to resolve clonal phylogenies, however, it is still unknown how faithfully transcript-based tumor phylogenies reconstruct ground truth DNA-based tumor phylogenies. We sought to study the accuracy of inferred-transcript to recapitulate DNA-based tumor phylogenies. We first performed in-silico comparisons of inferred and directly resolved SNV and CNV status, from single cancer cells, from three different cell lines. We found that inferred SNV phylogenies accurately recapitulate DNA phylogenies (entanglement = 0.097). We observed similar results in iCNV and CNV based phylogenies (entanglement = 0.11). Analysis of published prostate cancer DNA phylogenies and inferred CNV, SNV and transcript based phylogenies demonstrated phylogenetic concordance. Finally, a comparison of pseudo-bulked spatial transcriptomic data to adjacent sections with WGS data also demonstrated recapitulation of ground truth (entanglement = 0.35). These results suggest that transcript-based inferred phylogenies recapitulate conventional genomic phylogenies. Further work will need to be done to increase accuracy, genomic, and spatial resolution.

bioinformatics↗

Intra-prostatic tumour evolution, steps in metastatic spread and histogenomic associations revealed by integration of multi-region whole genome sequencing with histopathological features

Extension of prostate cancer beyond the primary site into the surrounding organs by local invasion or nodal metastasis is associated with poor prognosis. The emergence and evolution of cancer clones at this early stage of expansion and spread has not been studied in detail. We performed whole genome sequencing on 42 prostate cancer samples from the prostate, seminal vesicles and regional lymph nodes of five treatment-naive patients with locally advanced disease who underwent radical prostatectomy. Using cancer cell fractions computed from single nucleotide variants and copy number alterations, we reconstructed the tumour phylogenies, which in turn allowed us to infer key molecular steps in the progression of prostate cancer in these individuals. We mapped the clonal composition of cancer sampled across the prostate in each individual and inferred the routes of spread of cancer cells within the prostate and to seminal vesicles and lymph nodes. Based on these data, we delineated the route of tumour progression and metastasis following the transformation of adenocarcinoma to amphicrine morphology, the molecular events leading to whole genome duplication associated with a single clonal expansion and identified putative driver events associated with local invasion and lymph node metastasis. We also correlated genomic changes associated with differences in morphology and identified putative driver events associated with spread to seminal vesicle invasion and lymph node metastasis. Taken together, these findings have implications for diagnosis and risk stratification, in addition to providing a rationale for further studies to characterise the genetic changes associated with morphological transformation. Our results demonstrate the value of integrating multi-region sequencing with histopathological data to study tumour evolution and identify mechanisms of prostate cancer spread.

cancer biology↗

Peroxisomal β-oxidation enzyme, DECR2, regulates lipid metabolism and promotes treatment resistance in advanced prostate cancer

Peroxisomes are central metabolic organelles that have key roles in fatty acid homeostasis, including {beta}-oxidation, and emerging evidence has linked aberrant peroxisome metabolism to cancer development and progression. While targeting mitochondrial {beta}-oxidation in prostate cancer (PCa) has gained significant attention in recent years, the contribution of peroxisomal {beta}-oxidation (perFAO) to PCa tumorigenesis is comparatively unexplored. Herein, we explored the therapeutic efficacy of targeting perFAO in PCa cells and clinical prostate tumours, and subsequently identified peroxisomal 2,4-dienoyl CoA reductase 2 (DECR2), as a key therapeutic target. DECR2 is markedly upregulated in clinical PCa, most notably in metastatic castrate-resistant PCa. Depletion of DECR2 significantly suppressed proliferation, migration, and 3D growth of a range of CRPC and enzalutamide-resistant PCa cell lines, and inhibited LNCaP tumour growth and proliferation in vivo. Using transcriptomic and lipidomic analyses, we determined that DECR2 influences cell cycle progression and lipid metabolism to enable tumour cell proliferation. We further demonstrated a novel role for perFAO in driving resistance to standard-of-care androgen receptor pathway inhibition, using genetic and pharmacological approaches to alter DECR2/perFAO in treatment-resistant PCa cells. Our findings highlight a need to focus on peroxisomes to suppress tumour cell proliferation and reveal new therapeutic targets for advanced, treatment-resistant PCa.

cancer biology↗

The spatial landscape of clonal somatic mutations in benign and malignant tissue

Defining the transition from benign to malignant tissue is fundamental to improve early diagnosis of cancer. Here, we provide an unsupervised approach to study spatial genome integrity in situ to gain molecular insight into clonal relationships. We employed spatially resolved transcriptomics to infer spatial copy number variations in >120 000 regions across multiple organs, in benign and malignant tissues. We demonstrate that genome-wide copy number variation reveals distinct clonal patterns within tumours and in nearby benign tissue. Our results suggest a model for how genomic instability arises in histologically benign tissue that may represent early events in cancer evolution. We highlight the power of an unsupervised approach to capture the molecular and spatial continuums in a tissue context and challenge the rationale for treatment paradigms, including focal therapy.

genomics↗

Single-cell ATAC and RNA sequencing reveal pre-existing and persistent subpopulations of cells associated with relapse of prostate cancer

Prostate cancer is profoundly heterogeneous and patients would benefit from methods that stratify clinically indolent from more aggressive forms of the disease. We employed single-cell assay for transposase-accessible chromatin (ATAC) and RNA sequencing in models of early treatment response and resistance to enzalutamide. In doing so, we identified pre-existing and treatment-persistent cell subpopulations that possess transcriptional stem-like features and regenerative potential when subjected to treatment. We found distinct chromatin landscapes associated with enzalutamide treatment and resistance that are linked to alternative transcriptional programs. Transcriptional profiles characteristic of persistent stem-like cells were able to stratify the treatment response of patients. Ultimately, we show that defining changes in chromatin and gene expression in single-cell populations from pre-clinical models can reveal hitherto unrecognized molecular predictors of treatment response. This suggests that high analytical resolution of pre-clinical models may powerfully inform clinical decision-making.

cancer biology↗

Tumor irradiation combined with vascular-targeted photodynamic therapy enhances anti-tumor effects in preclinical prostate cancer.

RationaleThere is an important clinical need to improve the treatment of high risk localized and locally advanced prostate cancer (PCa), and to reduce the side effects of these treatments. We hypothesized that multi-modality therapy combining radiotherapy and vascular-targeted photodynamic therapy (VTP) could PCa tumour control compared against monotherapy with each of these treatments alone. This could provide proof-of-concept to take to the clinic. VTP is a focal therapy for localized PCa, which rapidly destroys targeted tumors through vascular disruption. Tumor vasculature is characterized by vessel immaturity, increased permeability, aberrant branching and inefficient flow. Fractionated radiotherapy (FRT) alters the tumor microenvironment and promotes transient vascular normalization. ObjectiveWe investigated whether sequential delivery of FRT followed by VTP 7 days later improves PCa tumor control compared to monotherapy with FRT or VTP alone. FindingsFRT induced vascular normalization changes in PCa flank tumor allografts, improving vascular function as demonstrated using dynamic contrast enhanced magnetic resonance imaging. FRT followed by VTP significantly delayed tumor growth in flank PCa allograft pre-clinical models, compared with monotherapy with FRT or VTP alone, and improved overall survival. ConclusionTaken together, these results suggest that combining FRT and VTP could become a promising multimodal clinical strategy in PCa therapy. This provides proof-of-concept for this multi-modality therapy approach to take forward to early phase clinical trials.

cancer biology↗

A feedback loop between the androgen receptor and 6-phosphogluoconate dehydrogenase (6PGD) drives prostate cancer growth

Alterations to androgen receptor (AR) signalling and cellular metabolism are hallmarks of prostate cancer. This study uncovers a novel link between AR and the pentose phosphate pathway (PPP) through 6-phosphogluoconate dehydrogenase (6PGD), an androgen-regulated gene that is upregulated in prostate cancer. Knockdown of 6PGD impairs growth and elicits death of prostate cancer cells, at least in part due to oxidative stress. Targeting 6PGD using 2 specific inhibitors, physcion and S3, was efficacious in multiple models of prostate cancer, including aggressive castration-resistant models. Importantly, S3 also suppressed proliferation of clinical patient-derived explants (PDEs). Mechanistically, 6PGD decreased expression and activity of AR in cell lines and PDEs, revealing a novel positive feedback loop between these factors. The enhanced efficacy of co-targeting AR and 6PGD further supported the biological relevance of this feedback. This work provides insight into the dysregulated metabolism of prostate cancer and supports investigation of co-targeting AR and the PPP.

cancer biology↗

Targeting CXCR1 and CXCR2 to overcome radiotherapy resistance in PTEN-deficient prostate carcinoma

ABSTRACTFunctional impairment of the tumour-suppressor PTEN is common in primary-prostate cancer and has been linked to relapse post-radiotherapy (RT). Pre-clinical modelling supports elevated CXC-chemokine signaling as a critical mediator of PTEN-depleted disease progression and therapeutic resistance. We assessed the correlation of PTEN-deficiency with CXC-chemokine signaling and its association with clinical outcomes. Gene expression analysis characterized a PTENLOW/CXCR1HIGH/CXCR2HIGH cluster of tumors that associates with earlier time-to-biochemical recurrence (HR 5.87 and HR 2.65 respectively) and development of systemic metastasis (HR 3.51). In vitro, CXCL-signaling was further amplified following exposure of PTEN-deficient prostate cancer cell lines to ionizing radiation (IR). Inhibition of CXCR1/2-signaling in PTEN-depleted cell-based models increased IR-sensitivity. In vivo, administration of a CXCR1/2-targeted pepducin (x1/2pal-i3), or CXCR2-specific antagonist (AZD5069), in combination with IR to PTEN-deficient xenografts attenuated tumor growth and progression compared to control or IR alone. Post-mortem analysis confirmed that x1/2pal-i3 administration attenuated IR-induced CXCL-signaling and anti-apoptotic protein expression. Interventions targeting CXC-chemokine signaling may provide an effective strategy to combine with radiotherapy, in both locally-advanced and oligometastatic-prostate cancers, with known presence of PTEN-deficient foci.

cancer biology↗

Mining human prostate cancer datasets: The "camcAPP" shiny app

Obtaining access to robust, well-annotated human genomic datasets is an important step in demonstrating relevance of experimental findings and, often, in generating the hypotheses that led to those experiments being conducted in the first place. We recently published data from two cohorts of men with prostate cancer who had undergone prostatectomy, men from Cambridge, UK and Stockholm, Sweden.1 We considered how we might best share our output with those who wish to interrogate the data with their own ideas, gene lists and clinical questions. We recognised that finding, down-loading, processing and assimilating any such dataset into a usable format is daunting and may put off even the more persistent researcher. We also felt that interrogation tools generated to date (e.g. cBioPortal) lack functionality as they either cover too many organ types, or fall short in terms of clinical annotation. We therefore determined to produce an accessible web-based platform ...

cancer biology↗