Cancer progression is fundamentally a process of clonal selection and expansion.
Clonal populations of tumor cells evolution over time
Clonal populations of tumor cells evolve over time, with certain clones gaining dominance under selective pressures in TME, such as hypoxia, limited nutrient availability, stromal interactions, and immune surveillance.
Metastasis exemplifies this evolutionary process: a subclone may acquire traits that enable dissemination, survival in circulation, and colonization of distant organs. These metastatic subclones often diverge significantly from their primary counterparts, generating spatial heterogeneity across tumor sites. Advances in next-generation sequencing, particularly single cell sequencing, now allow researchers to reconstruct these clonal trajectories in detail. Biocomputational tools further model clonal structure and infer evolutionary history from both bulk and single cell data.
Early in cancer development, mutations in key genes such as TP53, KRAS, and SMAD4 enable uncontrolled cell proliferation and resistance to apoptosis. As cancer cells continue to replicate, they accumulate additional mutations that drive further heterogeneity and adaptation. Beyond genetic variation, epigenetic alterations also play a critical role in clonal evolution. Compared to normal cells, cancer cells are generally hypomethylated; however, promoter regions of tumor suppressor genes often become hypermethylated, leading to cell cycle dysregulation, enhanced invasion, and ultimately metastasis. A known driver of intratumoral heterogeneity is cell-cell fusion, a genome-doubling process where cancer cells fuse with other cells generating a new hybrid tumor clone with a distinct phenotype. These hybrids display new features like stem-cell’s self-renewal, immune escape, and resistance to apoptosis. Moreover they contribute to epithelial-mesenchymal transition (EMT), further promoting metastasis.
Mechanisms underlying the competition between expanding clones
Tumor clones compete for resources, space, nutrients, oxygen, and growth factors are all present in the TME. As these clones accumulate mutations, some will acquire selective advantage (metabolic adaptation, immune evasion, etc).
Therapeutic interventions are one of the strongest selective pressures as they eliminate sensitive clones, allowing resistant ones to survive and expand. The emergence of drug resistance is indeed a well known phenomenon in cancer treatment.
To develop novel and effective drugs, researchers now have multi-omic and bioinformatic tools to dissect tumor diversity and develop new therapeutic strategies, such as targeted and combination therapies, and immune therapies. Recently, encouraging results have been published about an otherwise fatal cancer, Multiple Myeloma (MM). Using scRNA-seq with combinatorial barcoding and biochemical assays, researchers demonstrated that SKP2 causes MM cells to become resistant to bortezomib, a first line MM therapy. This resistance can be reversed by inhibiting SKP2 with a promising new compound, SkpinC1.
How expression of immune checkpoint molecules vary among different clonal populations, and its impact on immune evasion
As clones survive and thrive in the TME, they express different levels of immune checkpoints molecules like PD-L1 that will grant them a selective advantage.
In the TME, immune suppressive T cells like the Tregs accumulate and secrete immune suppressive cytokines and growth factors like TGF-beta and IL-10 (the immune suppressive milieu), that limit the anti-tumor activation of CD4, CD8, and NK cells, and inhibition of production of pro-inflammatory cytokines by macrophages and dendritic cells.
Immune checkpoint molecules are critical regulators of immune responses and in normal tissues their inhibitory signals prevent excessive immune activation and autoimmunity. Tumor cells exploit them to escape immune surveillance. Key immune checkpoints like PD-L1 and CTLA-4 are frequently overexpressed in both tumor and immune cells within the TME. Their engagement suppresses T cell activation and proliferation, dampening anti-tumor immunity.
Checkpoint expression is regulated by oncogenic signaling and pro-inflammatory cytokines. For instance, activation of the PI3K/AKT pathway in tumor cells can drive upregulation of PD-L1.
Additionally, interferon-γ can induce PD-L1 as part of a negative feedback loop aimed at limiting immune-mediated tissue damage.
Beyond PD-1/PD-L1 and CTLA-4, emerging immune checkpoints are gaining attention for their roles in immune resistance.
Lymphocyte-activation gene 3 (LAG-3), a co-inhibitory receptor generally expressed on exhausted T cells. LAG-3 binds to MHC class II molecules, transmitting inhibitory signals that limit T cell proliferation and cytokine production, thus contributing to immune escape. Dual blockade of PD-1 and LAG-3 has been shown to improve T cell function.
Another emerging checkpoint is T cell immunoglobulin and mucin-domain containing-3 (TIM-3). Its expression is typically elevated in exhausted T cells and is associated with resistance to PD-1 blockade, making it a promising candidate for combination immunotherapy.
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Tracking Tumor Clonal Expansion with scRNA-seq
Cancer begins with cumulating mutations in somatic cells that enable them to escape homeostasis and proliferate uncontrollably creating cancer clones that grow, evolve, migrate, and become resistant to therapy. Monitoring these ever evolving subclones at the single cell resolution reveals the underlying drivers of metastasis, predict prognosis, and inform the development of more effective therapies.
Clonal Evolution and Gene Expression Dynamics in Tumor Progression
- How genetically diverse is the tumor, and what clones are present?
- How do clones evolve over time or across tumor regions?
- What are the gene expression dynamics underlying clonal transitions?
- How does TME influence their behavior?
Mechanisms underlying the competition between expanding clones
- Which clones exhibit transcriptional signatures associated with higher fitness
- What resources or environmental niches are being competed for?
- How do proliferative and quiescent states influence competitive outcomes?
- What are the early indicators of a clone gaining competitive dominance?
How expression of immune checkpoint molecules vary among different clonal populations, and its impact on immune evasion
- Which clones rely on immune checkpoint upregulation as their dominant immune evasion strategy?
- Are differences in immune checkpoint expression genetically encoded or state-driven?
- How does the tumor microenvironment influence checkpoint expression in distinct clones?
- Which checkpoint molecules are potential therapeutic targets for specific clones?
TLDR: Cancer progression is driven by the rise and fall of competing tumor clones under constant selective pressure. Small differences in genetic, epigenetic, or transcriptional programs can determine which clones expand, persist, or seed metastases. These evolutionary dynamics shape intratumoral heterogeneity, treatment resistance, and disease recurrence. Single cell RNA sequencing makes clonal competition visible, linking gene expression states to fitness, adaptation, and dominance over time. This chapter examines how tracking clonal expansion reveals the evolutionary forces that drive tumor progression.
