13/13
There are so many people to thank for their contributions to this work. Most importantly my advisor Adam Palmer. I'd also like to thank @unclineberger.bsky.social and @unc-phco.bsky.social (and a lot of other individuals and organizations not on bluesky).

12/n
This model provides quantitative insight into how combination therapy can overcome heterogeneity within and between tumors to cure many patients with Large B-Cell Lymphoma.

We hope it is a practical tool to explore new combinations based on clinical data on new drugs.

11/n
Importantly, we had predicted the success of Pola-R-CHP *before* the trial read out, as she reported from the model prototype back in 2021:
www.amypomeroy.com/post/predict...

10/n
Looking at ‘RCHOP+X’ trials, we used clinical data on each ‘drug X’ to predict the clinical trial results.
Only Pola-R-CHP, and Tucidinostat + R-CHOP, were expected to succeed, and indeed they did
www.asco.org/abstracts-presentations/ABSTRACT451754
www.nejm.org/doi/full/10.1056/NEJMoa2115304

9/n
We calibrated the model to reproduce Progression-Free Survival for the CHOP and RCHOP regimens for Diffuse Large B-Cell Lymphoma.

Simulated tumor population shrinkage agreed well with observed changes in circulating tumor DNA after the first cycle of RCHOP:

8/n
From this ‘bottom-up’ model of tumor heterogeneity, simulating treatment responses in a cohort of patients produces a Kaplan-Meier curve of Progression-Free Survival:

7/n
This extends to combination therapy by using a different dimension of heterogeneity for each drug

This way, patients and cells vary in their sensitivity to different drugs; for example, some patients can be more sensitive to one drug than another, or sensitive to both, etc.

6/n
Extending to patient variability, a group of patients - say in a clinical trial - also have a distribution of drug response phenotypes, with each patient’s cancer containing a range of cellular heterogeneity around the average drug sensitivity of that individual.

5/n
In this model of heterogeneity as a distribution of states, each cycle of chemotherapy progressively shifts the distribution to increasingly drug-resistant states

4/n
Many insightful models of tumor heterogeneity described drug-sensitive and drug-resistant subpopulations.

Based on clone-tracing, we modelled cellular heterogeneity as a distribution of sensitivity phenotypes, reflecting many complex influences on drug response

3/n
We built a model that unifies intra-tumor and inter-patient heterogeneity in drug sensitivity to understand the clinical efficacy of curative-intent combination therapy for Large B-Cell Lymphoma.

2/n
Cell-to-cell and patient-to-patient heterogeneity both have a role in the success of drug combinations.

While inter-patient variation can explain better response rates of combos for incurable cancers, CURES need a regimen to overcome cellular heterogeneity and evolution.

An impressive result from their work - their model would have been able to predict from single treatment trials what would have happened in the combination trials