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Churchman, M.

Publications and source records attributed to Churchman, M..

8 recordsLinked to original sources

Defining biologically directed therapy target signatures in urothelial carcinoma: A transcriptomic framework for precision therapy

IntroductionNectin-4 targeting antibody-drug conjugate (ADC) enfortumab vedotin (EV), in combination with pembrolizumab, is the first-line treatment for patients with locally advanced or metastatic urothelial carcinoma (UC). Optimal treatment strategies for patients who are non-responders or progress on EV with pembrolizumab remain an unmet clinical need. We sought to characterize ADC and immunotherapy (IO)-associated target expression profiles to identify candidate therapeutic vulnerabilities beyond EV. MethodsWe conducted a literature review to identify ADC and IO targets with approved or investigational relevance in UC. Unsupervised hierarchical clustering was used to identify clusters of target gene expression in RNA-seq data. Transcriptomic clustering analyses were performed in 434 patients from The Cancer Genome Atlas Bladder Urothelial Carcinoma cohort (TCGA-BLCA) and validated in an independent cohort of 478 patients from the Oncology Research Information Exchange Network (ORIEN) consortium. Proteomic interrogation of these targets was performed using mass spectrometry data from additional cohort of 116 patients. Differential gene expression analyses evaluated associations between target expression patterns, histologic variants, and consensus molecular subtypes of muscle-invasive bladder cancer (CMIBC). ResultsWe identified 13 ADC and 10 IO-associated targets with translational relevance in UC. Transcriptomic analyses revealed three reproducible clusters of overexpressed target genes across independent cohorts: 1) a luminal/epithelial-associated cluster enriched for VTCN1, SLITRK6, FGFR3, NECTIN4, TACSTD2, ERBB2, and ERBB3; 2) an immune target predominant cluster enriched for BTLA, LAG3, PDCD1, TIGIT, CTLA4, TNFRSF9, TNFRSF18, TNFRSF4; and 3) a basal/neuroendocrine-associated cluster characterized by CD274, F3, NT5E, EGFR, MET and DLL3. Similar clusters were largely conserved at the proteomic level. Adenocarcinomas overexpressed ERBB3 compared to neuroendocrine and squamous cell carcinomas. Pure squamous cell carcinomas overexpressed TACSTD2 compared to adenocarcinomas. In CMIBC subtypes, basal/squamous tumors expressed higher levels of CD274, EGFR, F3, LAG3, NT5E, and TNFRSF18, whereas luminal tumors demonstrated higher ERBB2 and ERBB3 expression. Neuroendocrine-like tumors showed higher DLL3 expression compared to all other subtypes. Tumors with low expression of NECTIN4, TACSTD2, and FGFR3 were enriched for alternative targets including DLL3, CD274, and CD276. Our findings provide a framework for hypothesis-driven therapeutic prioritization in advanced UC. Conclusions: UC is characterized by reproducible, biologically distinct patterns of ADC and IO target expressions. The degree of expression of NECTIN4 was positively associated with TACSTD2, FGFR3 and inversely associated with DLL3, CD276, and CD274, supporting alternative biologically informed treatment strategies besides EV . Histologic variants and molecular subtypes of UC also display distinct patterns of target expression. This study provides the first integrated transcriptomic framework linking ADC and IO target co-expression patterns for hypothesis-driven therapeutic prioritization. These findings provide a basis for rational ADC and immunotherapy development in advanced UC and support prospective proteomic validation in treatment stratified cohorts. Statement of Translational RelevanceEnfortumab vedotin plus pembrolizumab has redefined first-line therapy for advanced urothelial carcinoma, yet treatment selection following resistance or progression remains undefined. In this study, we integrate transcriptomic and proteomic analyses across independent cohorts to define reproducible patterns of antibody-drug conjugate (ADC) and immunotherapy target co-expression in urothelial carcinoma. We identify biologically distinct target-expression patterns that are associated with histologic and molecular subtypes and demonstrate coordinated and, in some cases, mutually exclusive relationships among therapeutically actionable targets. These findings have direct translational implications. First, they provide biologic rationale for rational sequencing and combination strategies based on co-expressed targets in NECTIN4-enriched tumors. Second, they identify alternative therapeutic vulnerabilities, including DLL3- and CD274-associated pathways, in tumors with low NECTIN4 expression, a population potentially enriched for resistance to EV-based therapy. Finally, this framework establishes a foundation for biomarker-driven clinical trials in urothelial carcinoma and supports the development of precision therapeutic approaches beyond current standards.

cancer biology↗

Candida albicans infiltrates colon and rectal cancers causing therapeutic resistance and decreased survival

The microbiome is increasingly recognized as a modifier of cancer progression and therapy response, yet the role of intratumoral fungi remains poorly defined. Here, we identify Candida albicans colonization within human colorectal tumors as a predictor of reduced survival and impaired radiation response. Leveraging the Oncology Research Information Exchange Network (ORIEN) cohort, we show that high intratumoral Candida burden is associated with decreased survival across multiple gastrointestinal cancers, with the strongest treatment-specific effect in rectal cancer patients receiving radiotherapy. This observation was validated in independent rectal cancer cohorts using RNA sequencing and quantitative PCR. In immune-competent murine colorectal cancer models, oral gavage of C. albicans resulted in intratumoral colonization, accelerated tumor growth, and radiation resistance, effects not observed with Saccharomyces cerevisiae or PBS controls. Colonized tumors exhibited increased hypoxia, altered metabolic and transcriptional programs, and distinct expression of genes linked to cytokine signaling and cell survival. Hypoxia conditioned C. albicans secreted metabolites that directly conferred radiation resistance to colorectal cancer cells in vitro, implicating a cancer cell intrinsic mechanism independent of immune signaling. Untargeted metabolomics revealed enrichment of nucleosides and lipid oxidation intermediates under hypoxia, suggesting that C. albicans metabolites may provide substrates facilitating tumor recovery after irradiation. These findings establish C. albicans as a causal modifier of tumor biology and radiation response, highlighting intratumoral fungi as future potential therapeutic targets. Modulating fungal colonization or metabolism may improve radiotherapy outcomes and broaden our understanding of interactions between microbes and tumors.

cancer biology↗

Primary tumor microbiomes predict distant metastasis of colorectal cancer

Metastasis causes most cancer-related deaths in colorectal carcinoma (CRC), and microbiome markers may have prognostic value. We hypothesized that primary tumor microbiomes predict distant metastases. We analyzed 5-year metastasis-free survival (MFS) in a retrospective cohort of 900 ORIEN CRC tumor microbiomes (RNAseq). ORIEN findings were validated on an independent cohort using 16S rDNA sequencing and pathobiont-specific qPCR. Microbiome alpha diversity was higher in primary tumors than metastases and positively correlated with metastasis risk. Microbiome beta diversity distinguished primary vs. metastasis and predicted 5-year MFS. High primary tumor abundance of B. fragilis and low F. nucleatum were associated with short MFS. Enterobacteriaceae, including E. coli, were enriched in metastases. qPCR identified increased enterotoxigenic B. fragilis and pks+ E. coli detection in CRC metastasizers. Microbial co-occurrence analysis identified a 3-species clique that predicts metastasis (OR 1.9 [1.4-2.6]). Results suggest that primary tumor microbiomes and specific pathobionts are precision markers for metastasis risk.

cancer biology↗

Combined genomic and molecular analysis defines prognostic markers of relapse in stage IA-IC1 clear cell ovarian carcinoma

ObjectiveClear cell ovarian carcinoma (CCOC) is generally associated with a favourable prognosis, but up to 30% of low-stage cases relapse within five years. The benefit of adjuvant chemotherapy for low-stage CCOC (FIGO stage IA-IC1) remains uncertain. This study aimed to identify molecular and immune markers associated with relapse in a well-characterized CCOC cohort. MethodsUsing the Edinburgh Ovarian Cancer Database, we identified 85 CCOC cases. Targeted DNA sequencing assessed genomic alterations and tumour immune infiltration was evaluated using CD3 and CD8 immunohistochemistry on tissue microarrays. Tumours were stratified by stage (IA-IC1, IC2-II, III-IV), and both univariate and multivariate analysis applied for progression-free survival (PFS) included stage, age, genomic features, and immune markers. ResultsCommon genomic alterations included ARID1A (49%) and PIK3CA (42%) mutations, PIK3-AKT pathway perturbations (60%), and mismatch repair-related mutational signatures (25.9%). Genomic and molecular features were not significantly associated with tumour stage; however, low-stage tumours (IA-IC1) were enriched in CD3+ (40% cases) and CD8+ (29% cases) tumour-infiltrating lymphocytes (TILs) compared to higher-stage tumours (IC2-II: 13%/7%; III-IV: 9%/0% cases). In univariate analysis, low CD3+ TIL levels were significantly associated with reduced progression-free survival (HR = 4.4, P = 0.042, 95% CI 1.1-18). ARID1A wild-type status was linked to poorer PFS but only in low-stage tumours HR = 7.2, P = 0.088; 95% CI 0.74-72). Notably, the combination of ARID1A wild-type status and CD3+ depletion identified a high-risk subgroup among low-stage CCOC cases (HR = 11.7, P = 0.050; 95% CI 1-138), highlighting potential as a composite risk marker set. ConclusionsCombined ARID1A mutation and low CD3+ve TIL levels are suggestive of higher recurrence risk in low-stage CCOC patients. These findings support further investigation of targeted therapies or immune checkpoint inhibitors in larger CCOC cohorts. HighlightsO_LIWe report a well-characterized CCOC cohort with rich clinical, genomic and molecular data. C_LIO_LICommon mutations included ARID1A (49%) and PIK3CA (42%), with MSI in 9%, showing no significant enrichment across tumour stages. C_LIO_LILow-stage CCOC has higher levels of CD3+ & CD8+ tumour infiltrating leukocytes than in advanced-stage disease. C_LIO_LIARID1A wild-type tumours with CD3+ TIL depletion represent a high-risk subgroup of low-stage CCOC. C_LIO_LIFindings support further study and highlight potential markers for recurrence risk. C_LI

cancer biology↗

Rapid Identification of Genomic Alterations in Tumors affecting lymphocyte Infiltration (RIGATonI)

Tumor genomic alterations have been associated with altered tumor immune microenvironments and therapeutic outcomes. These studies raise a critical question: are there additional genomic variations altering the immune microenvironment in tumors that can provide insight into mechanisms of immune evasion? This question is the backbone of precision immuno-oncology. Current computational approaches to estimate immunity in bulk RNA sequencing (RNAseq) from tumors include gene set enrichment analysis and cellular deconvolution, but these techniques do not consider the spatial organization of lymphocytes or connect immune phenotypes with gene activity. Our new software package, Rapid Identification of Genomic Alterations in Tumors affecting lymphocyte Infiltration (RIGATonI), addresses these two gaps in separate modules: the Immunity Module and the Function Module. Using pathologist-reviewed histology slides and paired bulk RNAseq expression data, we trained a machine learning algorithm to detect high, medium, and low levels of immune infiltration (Immunity Module). We validated this technique using a subset of pathologist-reviewed slides not included in the training data, multiplex immunohistochemistry, flow cytometry, and digital staining of The Cancer Genome Atlas (TCGA). In addition to immune infiltrate classification, RIGATonI leverages another novel machine learning algorithm for the prediction of gain- and loss-of-function genomic alterations (Function Module). We validated this approach using clinically relevant and function-impacting genomic alterations from the OncoKB database. Combining these two modules, we analyzed all genomic alterations present in solid tumors in TCGA for their resulting protein function and immune phenotype. We visualized these results on a publicly available website. To illustrate RIGATonIs potential to identify novel genomic variants with associated altered immune phenotypes, we describe increased anti-tumor immunity in renal cell carcinoma tumors harboring 14q deletions and confirmed these results with previously published single-cell RNA sequencing. Thus, we present our R package and online database, RIGATonI: an innovative software for precision immuno-oncology research.

bioinformatics↗

Divergent trajectories to structural diversity impact patient survival in high grade serous ovarian cancer

Deciphering the structural variation across tumour genomes is crucial to determine the events driving tumour progression and better understand tumour adaptation and evolution. High grade serous ovarian cancer (HGSOC) is an exemplar tumour type showing extreme, but poorly characterised structural diversity. We comprehensively describe the mutational landscape driving HGSOC, exploiting a large (N=324), deeply whole genome sequenced dataset. We reveal two divergent evolutionary trajectories, affecting patient survival and involving differing genomic environments. One involves homologous recombination repair deficiency (HRD) while the other is dominated by whole genome duplication (WGD) with frequent chromothripsis, breakage-fusion-bridges and extra-chromosomal DNA. These trajectories contribute to structural variation hotspots, containing novel candidate driver genes with significantly altered expression. While structural variation predominantly drives tumorigenesis, we also find high mtDNA mutation loads associated with shorter patient survival, and acting in combination with alterations in the nuclear genome to impact prognosis and suggesting new strategies for patient stratification.

cancer biology↗

Loss of the endocytic tumor suppressor HD-PTP phenocopies LKB1 and promotes RAS-driven oncogenesis.

Abstract/SummaryOncogenic RAS mutations drive aggressive cancers that are difficult to treat in the clinic, and while direct inhibition of the most common KRAS variant in lung adenocarcinoma (G12C) is undergoing clinical evaluation, a wide spectrum of oncogenic RAS variants together make up a large percentage of untargetable lung and GI cancers. Here we report that loss-of-function alterations (mutations and deep deletions) in the gene that encodes HD-PTP (PTPN23) occur in up to 14% of lung cancers in the ORIEN Avatar lung cancer cohort, associate with adenosquamous histology, and occur alongside an altered spectrum of KRAS alleles. Furthermore, we show that in publicly available early-stage NSCLC studies loss of HD-PTP is mutually exclusive with loss of LKB1, which suggests they restrict a common oncogenic pathway in early lung tumorigenesis. In support of this, knockdown of HD-PTP in RAS-transformed lung cancer cells is sufficient to promote FAK-dependent invasion. Lastly, knockdown of the Drosophila homolog of HD-PTP (dHD-PTP/Myopic) synergizes to promote RAS-dependent neoplastic progression. Our findings highlight a novel tumor suppressor that can restrict RAS-driven lung cancer oncogenesis and identify a targetable pathway for personalized therapeutic approaches for adenosquamous lung cancer.

cancer biology↗

Structural variants at the BRCA1/2 loci are a common source of homologous repair deficiency in high grade serous ovarian carcinoma

Around half of high grade serous ovarian carcinomas (HGSOC) show homologous recombination repair deficiency (HRD), often caused by germline or somatic single nucleotide variant (SNV) mutations or small indels disrupting BRCA1/2. We have uniformly processed the largest collection of whole genome sequencing (WGS) data from HGSOC samples to date (N=205), comprehensively characterising the somatic mutational landscape, and expression at the BRCA1/2 loci. We discover that large structural variants (SV) are a frequent but unappreciated source of BRCA1/2 disruption in these tumours. Somatic structural variation at these loci is dominated by multi-megabase deletions that span the entirety of BRCA1 (median = 4.9Mb) or BRCA2 (median = 6.2Mb), independently affecting a substantial proportion of patients (16%) in addition to those affected by damaging germline or somatic short variants, within the BRCA1/2 coding sequences (24%). In common with previous studies, we show that the presence of damaging somatic SNVs or short indels in BRCA1 (OR=10, 95% CI 1.8-103, p=0.002, adj p=0.027 and BRCA2 (OR=17, 95% CI 2.1-816), p=0.002, adj.p=0.021) was found to influence HRD. For the first time we also study the compound effect of SV and SNV or short indel mutations at both loci, demonstrating that SVs often contribute to compound deficiencies involving SNVs or indels, with large somatic deletions contributing to these compound deficiencies in 15/205 (7%) of samples. Notably the strongest risk of HRD (OR=19 (2.4-896), p=6.6x10-3, adj P=8.5x10-3) is generated by combined large deletions at BRCA1 and BRCA2 in the absence of SNVs or indels, affecting 3% of patients. Overall, we show that HRD is a complex phenotype in HGSOC tumours, affected by the patterns of shorter variants such as SNVs and indels, SVs, methylation and expression seen at multiple loci, and we construct a successful (ROC AUC = 0.75) predictive model of HRD using such variables. In addition, HRD impacts patient survival when conferred by mechanisms other than through the well-understood short variants at BRCA1/2, currently exploited in the clinic. These results alter our understanding of the mutational landscape at the BRCA1/2 loci in highly rearranged tumours, and increase the number of patients predicted to benefit from therapies exploiting HRD in tumours such as PARP inhibition.

cancer biology↗