Had a fantastic week in beautiful Toledo for @ecmtb2024! Thanks to all of the organisers for the opportunity to present my recent work on ecDNA in human GBM, and for such a fun and well-organised conference. See you in 2026! https://t.co/PhQxVf8emo

📢 Want to read more about our recent @JHepatology paper where we delved into the origins of homeostatic liver cell renewal? Have a read here! 🔎https://t.co/Gfav3z1sC0

Thanks @gliomath and @ara_anderson and the rest of the organising team for #MathOnc23. What a pleasure to meet so many other cancer modellers and learn about their incredible work! https://t.co/9re2wmzYNS

Sunrise on day 1 in Phoenix. Looking forward to 3 fantastic days of cancer modelling at #MathOnc23! Excited to see some old faces and make new connections. Let's go! https://t.co/uq62KZdN49

An absolute pleasure to contribute to this great work & very pleased that it is out now! Congrats to the whole team 🎊 https://t.co/P1WA9nITiB

This work was a joint effort with @AleixBassolas and supervised by @huang_weini, representing a collaboration between @QMULMaths, @QMBCI & @CEC_ICR. Thanks to all the other authors @sandrofsousa, Ann-Marie Baker, @trevoragraham, @KatolaZ! 7/7

Using a spatial agent-based model of growing tumours, we then showed that the CMFPT can distinguish between tumours with varying sub-clonal selection strength, s, mutation time, n_mut, and cell pushing strength, q, through the resulting patterns of sub-clonal mixing. 4/7 https://t.co/8gQZij6UTV

Class mean first passage time (CMFPT), τ_AB, the average length of a random walk between any pair of node types/colours A and B, can distinguish between patterns of different population abundances and underlying pattern structures in an artificial model of cell mixing. 3/7 https://t.co/njsLk96Rrx

We sought to find out if the geometry of mixing patterns of wild-type and mutated tumour cells encodes information about how they expanded. To quantify these patterns, we explored using an established metric in network science – first passage times of random walks. 2/7 https://t.co/N073QaQkfV

Do spatial patterns of tumour cells hold clues about sub-clonal evolution? We developed a random walk-based method to describe the dynamics of mutant sub-clones in human colorectal cancer using only their spatial arrangement. 🧵 https://t.co/VtGSlq4weI 1/7

In our new preprint, we demonstrate how spatially resolved sub-clonal boundaries can be used to study past/present sub-clonal evolution in cancer. Very pleased to share! Great collaboration between @QMULMaths & @bciqmul https://t.co/Ur4c1GlmPx @AleixBassolas