Biology subjects

Gallagher, F. A.

Publications and source records attributed to Gallagher, F. A..

4 recordsLinked to original sources

bioRxiv2024

Angiogenic and Immune Predictors of Neoadjuvant Axitinib Response in Renal Cell Carcinoma with Venous Tumour Thrombus

Venous tumour thrombus (VTT), where the primary tumour invades the renal vein and inferior vena cava, affects 10-15% of renal cell carcinoma (RCC) patients. Curative surgery for VTT is high-risk, but neoadjuvant therapy may improve outcomes. The NAXIVA trial demonstrated a 35% VTT response rate after 8 weeks of neoadjuvant axitinib, a VEGFR-directed therapy. However, understanding non-response is critical for better treatment. We conducted a multiparametric investigation of samples collected during NAXIVA using digital pathology, flow cytometry, plasma cytokine profiling and RNA sequencing. Responders had higher baseline microvessel density and increased induction of VEGF-A and PlGF during treatment. A multi-modal machine learning model integrating features predicted response with an AUC of 0.868, improving to 0.945 when using features from week 3. Key predictive features included plasma CCL17 and IL-12. These findings may guide future treatment strategies for VTT, improving the clinical management of this challenging scenario. One Sentence SummaryA comprehensive multiparametric assessment of the effect of neoadjuvant axitinib in renal cell carcinoma patients with venous tumour thrombus was performed on tissue and peripheral blood, including an integrative machine learning model, which identified both angiogenic and immune determinants of response to therapy.

cancer biology↗

bioRxiv2019

Multi-site clonality analyses uncovers pervasive subclonal heterogeneity and branching evolution across melanoma metastases

Metastatic melanoma carries a poor prognosis despite modern systemic therapies. Understanding the evolution of the disease could help inform patient management. Through whole-genome sequencing of 13 melanoma metastases sampled at autopsy from a treatment naive patient and by leveraging the analytical power of multi-sample analyses, we reveal that metastatic cells may depart the primary tumour very early in the disease course and follow a branched pattern of evolution. Truncal UV-induced mutations that often swamp downstream analyses of heterogeneity, were found to be replaced by APOBEC-associated mutations in the branches of the evolutionary tree. Multi-sample analyses from a further 7 patients confirmed that branched evolution was pervasive, representing an important mode of melanoma dissemination. Our analyses illustrate that combining cancer cell fraction estimates across multiple metastases provides higher resolution phylogenetic reconstructions relative to single sample analyses and highlights the limitations of accurately inferring inter-tumoural heterogeneity from a single biopsy.

genomics↗

bioRxiv2019

High-sensitivity monitoring of ctDNA by patient-specific sequencing panels and integration of variant reads

Circulating tumor-derived DNA (ctDNA) can be used to monitor cancer dynamics noninvasively. Patients with small tumors have few copies of ctDNA in plasma, resulting in limited sensitivity to detect low-volume or residual disease. We show that sampling limitations can be overcome and sensitivity for ctDNA detection can be improved by massively parallel sequencing when hundreds to thousands of mutations are identified by tumor genotyping. We describe the INtegration of VAriant Reads (INVAR) analysis pipeline, which combines patient-specific mutation lists with both custom error-suppression methods and signal enrichment based on biological features of ctDNA. In this framework, the sensitivity can be estimated independently for each sample based on the number of informative reads, which is the product of the number of mutations analyzed and the average depth of unique sequencing reads. We applied INVAR to deep sequencing data generated by custom hybrid-capture panels, and showed that when ~106 informative reads were obtained INVAR allowed detection of tumor-derived DNA fractions to parts per million (ppm). In serial samples from patients with advanced melanoma on treatment, we detected ctDNA when imaging confirmed tumor volume of ~1cm3. In patients with resected early-stage melanoma, ctDNA was detected in 40% of patients who later relapsed, with higher rates of detection when more informative reads were obtained. We further demonstrated that INVAR can be generalized and allows improved detection of ctDNA from whole-exome and low-depth whole-genome sequencing data.

cancer biology↗

bioRxiv2019

3D-printed moulds of renal tumours for image-guided tissue sampling in the clinical setting

PURPOSESpatial heterogeneity of tumours is a major challenge in precision oncology. The relationship between molecular and imaging heterogeneity is still poorly understood, as it relies on the accurate co-registration of medical images and tissue biopsies. tumour moulds can guide the localization of biopsies, but their creation is time consuming, technologically challenging, and difficult to interface with routine clinical practice. These hurdles have so far hindered the progress in the area of multiscale integration of tumour heterogeneity data. METHODSWe have developed an open source computational framework to automatically produce patient-specific 3D-printed moulds that can be used in the clinical setting. Our approach achieves accurate co-registration of sampling location between tissue and imaging, and integrates seamlessly with clinical, imaging and pathology workflows. RESULTSWe applied our framework to patients with renal cancer undergoing radical nephrectomy. We created personalised moulds for five patients, obtaining Dice similarity coefficients between imaging and tissue sections ranging from 0.86 to 0.93 for tumour regions, and between 0.70 and 0.76 for healthy kidney. The framework required minimal manual intervention, producing the final mould design in just minutes, while automatically taking into account clinical considerations such as a preference for specific cutting planes. CONCLUSIONOur work provides a robust and automated interface between imaging and tissue samples, enabling the development of clinical studies to probe tumour heterogeneity on multiple spatial scales.

bioengineering↗