Jason Griffiths

• PhD
• PostDoc Position at The University of Sheffield

In early-stage estrogen receptor-positive (ER + ) breast cancer, resistance to endocrine therapy (ET) and CDK4/6 inhibitors (CDK4/6i) often involve a shift away from estrogen-driven proliferation. The nature and source of compensatory growth signals driving cancer proliferation remain unknown but represent direct therapeutic targets of resistant ce...

Advanced estrogen receptor positive (ER+) breast cancers are typically treated with endocrine therapy (ET) plus cell cycle inhibitors (CCI); however, nearly 20% of these cancers recur due to treatment resistance. Our previous study of tumor intrinsic properties during CCI plus ET treatment found that CCI-resistant cancer cells are associated with d...

Estrogen receptor-positive breast cancer (ER+BC) represent about 70% of all breast cancer cases. Approximately 30-50% of ER+BCs eventually develop resistance to primary endocrine therapy and progress to metastatic disease. The addition of cyclin-dependent kinases 4 and 6 inhibitors (CDK4/6i) to endocrine therapy has improved disease control in adva...

Immune evasion by cancer cells involves reshaping the tumor microenvironment (TME) via communication with non-malignant cells. However, resistance-promoting interactions during treatment remain lesser known. Here we examine the composition, communication, and phenotypes of tumor-associated cells in serial biopsies from stage II and III high-risk es...

The rapid evolution of machine learning has led to a proliferation of sophisticated models for predicting therapeutic responses in cancer. While many of these show promise in research, standards for clinical evaluation and adoption are lacking. Here, we propose seven hallmarks by which predictive oncology models can be assessed and compared. These...

A time-series analysis of serum Cancer Antigen 125 (CA-125) levels was performed in 791 patients with high-grade serous ovarian cancer (HGSOC) from the Australian Ovarian Cancer Study to evaluate the development of chemoresistance and response to therapy. To investigate chemoresistance and better predict the treatment effectiveness, we examined two...

Fibroblast growth factors (FGFs) control various cellular functions through fibroblast growth factor receptor (FGFR) activation, including proliferation, differentiation, migration, and survival. FGFR amplification in ER + breast cancer patients correlate with poor prognosis, and FGFR inhibitors are currently being tested in clinical trials. By com...

Breast cancer is the most common malignancy in women and estrogen receptor positive (ER+) breast cancers represent nearly 75% of all breast tumors. Everolimus, an mTORC1 inhibitor, in combination with exemestane has been approved for patients with metastatic ER+ breast cancer. However, many patients eventually develop resistance to everolimus and l...

Metastatic breast cancers show variable clinical responses due to inherent heterogeneity, both within tumors and among patients. Studies mainly examine molecular diversity across different patients' tumors and genetic variance within a single tumor. Yet, the variability among multiple tumors or metastases in a single patient remains underexplored....

Tumors are comprised of subpopulations of cancer cells that harbor distinct genetic profiles and phenotypes that evolve over time and during treatment. By reconstructing the course of cancer evolution, we can understand the acquisition of the malignant properties that drive tumor progression. Unfortunately, recovering the evolutionary relationships...

The interplay of positive and negative interactions between drug-sensitive and resistant cells influences the effectiveness of treatment in heterogeneous cancer cell populations. Here, we study interactions between estrogen receptor-positive breast cancer cell lineages that are sensitive and resistant to ribociclib-induced cyclin-dependent kinase 4...

While endocrine therapy (ET) has considerably improved Stage II/III ER+ breast cancer survival rates, resistance emerges in 30-50% of patients. Recent advances have uncovered numerous cancer intrinsic and tumor-microenvironment mediated mechanisms contributing to ET resistance. However, the predominant mechanisms that prevent cure and ultimately le...

By corrupting signals for growth and survival, evolving cancer cells can engineer the tumor microenvironment (TME) to promote treatment resistance. However, the specific interactions between malignant and non-malignant cells that predispose drug resistance and their changes during treatment remain widely unknown. Here we examine the composition, co...

Breast cancer is a leading cause of global cancer-related mortality. About 75% of breast tumors are estrogen receptor-positive (ER+). Nearly 30-50% of ER+ breast cancers eventually become refractory to multiple lines of therapy and progress to an uncurable metastatic stage despite positive 5-year results on primary endocrine therapy. To uncover the...

Recent advances in single cell RNA sequencing (scRNA-seq) technologies have been invaluable in the study of the diversity of cancer cells and the tumor microenvironment. While scRNA-seq platforms allow processing of a high number of cells, uneven read quality and technical artifacts hinder the ability to identify and classify biologically relevant...

Tumors are comprised of subpopulations of cancer cells that harbor distinct genetic profiles and phenotypes that evolve over time and during treatment. By reconstructing the course of cancer evolution, we can understand the acquisition of the malignant properties that drive tumor progression. Unfortunately, recovering the evolutionary relationship...

Cancer cells evolve, acquire resistance to therapy and change their environment. One resistance mechanism involves altering communication with non-malignant cells in the tumor microenvironment (TME). By corrupting the signals for growth and survival, evolving cancer cells can engineer a pro-tumor TME. However, the specific interactions between mali...

The interplay of positive and negative interactions between drug sensitive and resistant cells determines the efficacy of treatment in heterogeneous cancer cell populations. While competition between different cell lineages within tumors has been considered in cancer evolution and progression, cooperative interactions receive far less study. We hav...

Despite high response rates to initial chemotherapy, the majority of women diagnosed with High-Grade Serous Ovarian Cancer (HGSOC) ultimately develop drug resistance within 1–2 years of treatment. We previously identified the most common mechanism of acquired resistance in HGSOC to date, transcriptional fusions involving the ATP-binding cassette (A...

Competition between different lineages of cells within a tumor has been included in thinking about cancer evolution and progression, but positive interactions like cooperation have received far less study. We have developed isogenic estrogen positive breast cancer cell lineages sensitive and resistant to CDK4/6 inhibition in order to investigate th...

Combining cyclin-dependent kinase (CDK) inhibitors with endocrine therapy improves outcomes for patients with metastatic estrogen receptor-positive breast cancer but its value in earlier-stage patients is unclear. We examined evolutionary trajectories of early-stage breast cancer tumors, using single-cell RNA sequencing of serial biopsies from the...

Combining cyclin-dependent kinase (CDK) inhibitors with endocrine therapy improves outcomes for metastatic estrogen receptor positive (ER+), HER2 negative, breast cancer patients. However, the value of this combination in potentially curable earlier stage patients is not clear. Using single cell transcriptomic profiling, we examined the evolutionar...

The interplay of positive and negative interactions between drug sensitive and resistant cells determines the efficacy of treatment in heterogeneous cancer cell populations. We developed isogenic estrogen receptor positive (ER+) breast cancer cell lineages sensitive and resistant to ribociclib-induced CDK4/6 inhibition to investigate cell interacti...

Combining cyclin-dependent kinase (CDK) inhibitors with endocrine therapy improves outcomes for metastatic estrogen receptor positive (ER+), HER2 negative, breast cancer patients. However, the value of this combination in potentially curable earlier stage patients is not clear. Using single cell transcriptomic profiling, we examined the evolutionar...

Background Accurately determining changes in tumor size during therapy is essential to evaluating response or progression. However, individual imaging methodologies often poorly reflect pathologic response and long-term treatment efficacy in patients with estrogen receptor positive (ER+) early-stage breast cancer. Mathematical models that measure t...

Significance The evolution of peripheral immune cell abundance and signaling over time, as well as how these immune cells interact with the tumor, may impact a cancer patient’s response to therapy. By developing an ecological population model, we provide evidence of a dynamic predator–prey-like relationship between circulating immune cell abundance...

Significance Demonstrating asymmetric competition in natural systems is difficult, as the effect of large individuals on small ones has to be measured, and vice versa. Numerous experiments have quantified one side of the interaction, typically the effect of large individuals on small ones. Here, we demonstrate, using a long-term study of guppies, t...

The extent that immune cell phenotypes in the peripheral blood reflect within-tumor immune activity prior to and early in cancer therapy is unclear. To address this question, we studied the population dynamics of tumor and immune cells, and immune phenotypic changes, using clinical tumor and immune cell measurements and single cell genomic analyses...

Current cancer therapies target a limited set of tumor features, rather than considering the tumor as a whole. Systems biology aims to reveal therapeutic targets associated with a variety of facets in an individual's tumor, such as genetic heterogeneity and its evolution, cancer cell–autonomous phenotypes, and microenvironmental signaling. These di...

Losses and gains in species diversity affect ecological stability1–7 and the sustainability of ecosystem functions and services8–13. Experiments and models have revealed positive, negative and no effects of diversity on individual components of stability, such as temporal variability, resistance and resilience2,3,6,11,12,14. How these stability com...

Intraspecific trait change, including altered behaviour or morphology, can drive temporal variation in interspecific interactions and population dynamics. In turn, variation in species’ interactions and densities can alter the strength and direction of trait change. The resulting feedback between species’ traits and abundance permits a wide range o...

The development of video-based monitoring methods allows for rapid, dynamic and accurate monitoring of individuals or communities, compared to slower traditional methods, with far reaching ecological and evolutionary applications. Large amounts of data are generated using video-based methods, which can be effectively processed using machine learnin...

Scatterplot of trajectories in principal component space from videos of three experimental units (Tetra = Tetrahymena thermophila, none = control (no ciliates), and Loxo = Loxocephalus sp.). A 90% confidence interval ellipse is fitted to each of the three experimental units to identify background noise in component space. The observations that fall...

Morphological boundaries for training data. (PDF)

Output model 1. (PDF)

Output model 4. (PDF)

Sensitivity and specificity of alternative classifiers such as support vector machines (SVM) and Naive Bayes (NB), compared to random forest (RF) and manual classifiers. All provide similar classification success for the ciliate species. SVM and NB are even slightly better than RF in terms of classifying noise. (TIF)

A single frame of one video, with particles labeled by their trajectory ID. For each trajectory, we obtained morphology and movement properties that were later used for classification into the respective species. (JPG)

In each panel, a point is a trajectory, with its position on PC1 corresponding to overall size, and PC2 to variability in size, and turning behaviour. Trajectories from microcosms containing ciliates are shown in black, yellow dots are trajectories from the controls (no ciliates). Panel codes: Colp = Colpidium striatum, Dexio = Dexiostoma campylum,...

Initial densities (individuals mL−1) for different richness treatments. (PDF)

Scatterplot of trajectories in principal component space from videos of three experimental units. Trajectories reclassified as noise by the Gaussian Mixture Model (GMM) are outlined in black. In this example, only some of the trajectories from the Tetrahymena thermophila culture were classified as noise (i.e. are outlined in black and have their co...

Output model 2. (PDF)

Output model 3. (PDF)

1. Technological advances have greatly simplified to take and analyze digital images and videos, and ecologists increasingly use these techniques for trait, behavioral and taxonomic analyses. The development of techniques to automate biological measurements from the environment opens up new possibilities to infer species numbers, observe presence/a...

The recent description of potentially generic early warning signals is a promising development that may help conservationists to anticipate a population's collapse prior to its occurrence. So far, the majority of such warning signals documented have been in highly controlled laboratory systems or in theoretical models. Data from wild populations, h...

Multiple aspects of the environment often change at the same time, influencing populations directly by modifying their physiology, but also indirectly by influencing other interacting species. The impacts of each environmental change upon population dynamics are usually assumed be independent of the state of other aspects of the environment, despit...