The genetic evolutionary features of solid tumour growth are becoming increasingly well described, but the spatial and physical nature of subclonal growth remains unclear. Here, we utilize 102 ...macroscopic whole-tumour images from clear cell renal cell carcinoma patients, with matched genetic and phenotypic data from 756 biopsies. Utilizing a digital image processing pipeline, a renal pathologist marked the boundaries between tumour and normal tissue and extracted positions of boundary line and biopsy regions to X and Y coordinates. We then integrated coordinates with genomic data to map exact spatial subclone locations, revealing how genetically distinct subclones grow and evolve spatially. We observed a phenotype of advanced and more aggressive subclonal growth in the tumour centre, characterized by an elevated burden of somatic copy number alterations and higher necrosis, proliferation rate and Fuhrman grade. Moreover, we found that metastasizing subclones preferentially originate from the tumour centre. Collectively, these observations suggest a model of accelerated evolution in the tumour interior, with harsh hypoxic environmental conditions leading to a greater opportunity for driver somatic copy number alterations to arise and expand due to selective advantage. Tumour subclone growth is predominantly spatially contiguous in nature. We found only two cases of subclone dispersal, one of which was associated with metastasis. The largest subclones spatially were dominated by driver somatic copy number alterations, suggesting that a large selective advantage can be conferred to subclones upon acquisition of these alterations. In conclusion, spatial dynamics is strongly associated with genomic alterations and plays an important role in tumour evolution.
Genetic intra-tumour heterogeneity fuels clonal evolution, but our understanding of clinically relevant clonal dynamics remain limited. We investigated spatial and temporal features of clonal ...diversification in clear cell renal cell carcinoma through a combination of modelling and real tumour analysis. We observe that the mode of tumour growth, surface or volume, impacts the extent of subclonal diversification, enabling interpretation of clonal diversity in patient tumours. Specific patterns of proliferation and necrosis explain clonal expansion and emergence of parallel evolution and microdiversity in tumours. In silico time-course studies reveal the appearance of budding structures before detectable subclonal diversification. Intriguingly, we observe radiological evidence of budding structures in early-stage clear cell renal cell carcinoma, indicating that future clonal evolution may be predictable from imaging. Our findings offer a window into the temporal and spatial features of clinically relevant clonal evolution.
Abstract
Introduction: Intra-tumor heterogeneity (ITH) is a major driver of treatment resistance. ITH also affects anti-tumor immunity, with immune cell infiltration, neo-antigen expression and T ...cell receptor (TCR) profiles differing between separate regions of an individual tumor. However, the extent to which separate tumor subclones differ in their capacity for immune evasion, the tumor-intrinsic mechanisms underlying any such heterogeneity, and its impact on cancer immunosurveillance remain largely unexplored. We have previously developed personalized models of anti-tumor immunity, based on co-cultures of cancer organoids and autologous T-cells. These co-culture systems can be used to evaluate the efficacy of cancer immunosurveillance at the level of an individual patient.
Approach: Here, we leverage the multi-region TRACERx lung cancer evolution study to generate a patient-derived study platform that allows the evaluation of T-cell responses to individual cancer subclones. We generated libraries of >20 separate non-small cell lung cancer (NSCLC) organoid lines, based on isolating individual (clonal) organoids established from multiple spatially separated tumor regions. Each organoid subline was co-cultured with autologous tumor infiltrating lymphocytes (TIL) to evaluate how they differ in their capacity to elicit a T-cell response.
Results: Our data reveal heterogeneity between individual clonal organoid sublines in their capacity to stimulate TIL. The proportion of TIL being activated by a particular subclone, as measured by 4-1BB (CD137) expression, ranged from 5 to 42%. These differences could not be explained by differences in MHC class I or PD-L1 expression. We are currently using DNA, RNA and TCR sequencing to characterize ‘immune evading’ and ‘non-immune evading’ sublines. Data will be updated on emerging subclonal immune evasion mechanisms inferred through DNA/RNA/TCR sequencing.
Conclusion: Individual cancer subclones show differences in the degree of immune evasion. This patient-derived study platform allows moving beyond descriptive analyses of the heterogeneity of anti-tumor immunity, allowing fine-grained functional studies of how ITH affects cancer immunosurveillance.
Citation Format: Krijn K. Dijkstra, Roberto Vendramin, Robert E. Hynds, David R. Pearce, Despoina Karagianni, Felipe Gálvez-Cancino, Oriol Pich, Mark S. Hill, Vittorio Barbè, Andrew Rowan, Selvaraju Veeriah, Cristina Naceur-Lombardelli, Antonia Toncheva, Supreet Bola, Mariam Jamal-Hanjani, Crispin Hiley, Kevin Litchfield, James Reading, Sergio A. Quezada, Charles Swanton, TRACERx consortium. Patient-derived co-cultures of TRACERx lung cancer organoids and autologous T-cells reveal heterogeneity in immune evasion between cancer subclones abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 692.
Abstract
Background: Lung adenocarcinoma (LUAD) is a morphologically and genetically diverse disease. The prognostic impact of LUAD histological patterns have been described, such as solid growth ...pattern and poor outcomes, though their underlying biology is poorly understood. Furthermore, the genomic characteristics and evolutionary constraints in relation to the inter- and intra- tumoral variance of histological patterns in primary and metastatic disease are unknown.
Methods: Pathological classification of 246 patients with LUAD from the TRACERx 421 cohort was performed at the whole tumor (diagnostic samples) and multi-regional sample level (matched for tumor whole exome sequencing and RNA sequencing). Circulating tumor DNA (ctDNA) data was also integrated to determine the relationship between pathological subtypes and ctDNA detection.
Results: Chromosomal instability, characterized by fraction of the genome affected by subclonal copy number alterations was significantly correlated with proportion of high-grade patterns, namely solid, cribriform and micropapillary (Spearman’s Rho 0.27, p<0.001). Analysis of somatic copy number alterations (SCNAs) and driver mutation profiles showed that specific SCNAs were associated with a predominant growth pattern, such as 3q arm gains in predominantly cribriform and solid pattern tumors. Multiregional analysis of tumors with mixed patterns showed higher grade regions to be associated with a higher frequency of LOH and expression of proliferation-related pathway genes, suggesting intra-tumoral sequential evolution from low to high grade growth patterns. No recurrent subclonal mutations or SCNAs were found to associate with progression from low to high grade patterns. The growth pattern in metastatic tumors tended to show similar or a higher-grade pattern compared with primary tumor regions harboring metastasizing clones (seeding regions). The growth pattern of the seeding regions in the primary tumor was not necessarily higher grade compared with their non-seeding counterparts. Finally, the proportion of solid pattern in the primary tumor and the presence of necrosis were found to be strongly associated with pre-operative ctDNA detection, while histological ‘spread through air spaces’ (STAS) was identified in 92% (12/13) of pre-operative ctDNA-negative tumors that subsequently were associated with recurrence. Patients with both pre-operative detectable ctDNA and STAS had a particularly poor prognosis.
Conclusion: These data reveal insights into the association between morphological and molecular heterogeneity in LUAD, describe key features of tumor evolutionary tendencies and demonstrate the utility of detailed tumor morphological assessment integrated with molecular characterization and ctDNA detection.
Citation Format: Takahiro Karasaki, David A. Moore, Selvaraju Veeriah, Cristina Naceur-Lombardelli, Antonia Toncheva, Maise Al Bakir, Thomas B. Watkins, Oriol Pich, Alexander M. Frankell, Emilia Lim, Mark S. Hill, Kristiana Grigoriadis, Carlos Martinez-Ruiz, James R. Black, Clare Puttick, Dhruva Biswas, Ariana Huebner, Michelle Dietzen, Emma Colliver, Claudia Lee, Nnenna Kanu, Sadegh Mohammad Saghafinia, Francisco Gimeno Valiente, Christopher Abbosh, Crispin T. Hiley, Simone Zaccaria, Nicolai J. Birkbak, Allan Hackshaw, TRACERx Consortium, Teresa Marafioti, Roberto Salgado, John Le Quesne, Andrew G. Nicholson, Nicholas McGranahan, Charles Swanton, Mariam Jamal-Hanjani. Evolutionary characterisation of lung adenocarcinoma pathological subtypes in TRACERx abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6091.
EuroKUP (Urine and Kidney Proteomics; www.eurokup.org) is a COST (European Cooperation in the field of Scientific and Technical research: www.cost.esf.org Action fostering a multi‐disciplinary ...network of investigators from 25 countries and focusing on facilitating translational proteomic research in kidney diseases. Four Working Groups focusing respectively on defining clinically important research questions in kidney diseases, kidney tissue proteomics, urine proteomics and bioinformatics have been generated. The EuroKUP members had their second combined Working Group and Management Committee (MC) meeting in Nafplio, Greece from March 29 to 30, 2009. This report summarizes the main presentations, discussions and agreed action points during this meeting. These refer to the design of collaborative projects and clinical center networks for specific kidney diseases; establishment of guidelines for kidney tissue proteomics analysis by laser‐based imaging‐ and laser capture microdissection‐MS; development and characterization of a “standard” urine specimen to be used for assessment of platform capability and data comparability in clinical proteomics applications; definition of statistical requirements in biomarker discovery studies; and development of a specialized kidney and urine ontology. Various training activities are planned involving training schools on laser capture microdissection‐ and imaging‐MS, workshops on ontologies as well as short‐term travel grants for junior investigators.
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