In our previous exploration, we uncovered the deep evolutionary roots of cancer, linking it to the ancient mechanisms of unicellular life. This perspective reshaped our understanding, highlighting how cancer is not merely a rogue disease but a reawakening of ancient cellular programs.
Now, we take a broader view, delving into the evolving paradigms that have shaped our understanding of cancer over the decades. Historically, cancer was viewed simply as uncontrolled growth, an aberration in the body's tightly regulated processes. This perspective later gave way to the genetic mutation theory, emphasizing the role of DNA damage in driving malignancy. However, as research has advanced, a third paradigm has emerged: cancer as an evolutionary phenomenon, deeply connected to our unicellular ancestry.
In this blog, we’ll dissect these three paradigms, tracing the evolution of our understanding from the earliest theories to the cutting-edge perspectives that challenge conventional thinking. By contextualizing these shifts, we aim to illuminate not only where our knowledge stands today but also the exciting directions it is poised to take. Join us as we journey through the past, present, and future of cancer biology, uncovering insights that redefine how we combat this ancient yet ever-relevant disease.
Paradigm 1: The “Uncontrolled Growth” Theory
The earliest paradigm of cancer viewed it as uncontrolled cell proliferation caused by local disturbances. The focus was on removing or destroying the rapidly dividing cells through:
Surgery: Physically removing tumors.
Radiation: Targeting cancer cells with high-energy rays.
Chemotherapy: Using cytotoxic drugs to kill dividing cells.
Pitfalls and Inefficiencies
Non-Specificity: Treatments harmed healthy cells along with cancer cells, leading to debilitating side effects.
Incomplete Solutions: These methods addressed symptoms, not causes.
Resistance and Recurrence: Cancers often returned, sometimes more aggressively, due to surviving resistant cells.
Quality of Life: The toxic nature of treatments diminished patients’ well-being without guaranteeing a cure.
Band-Aid Approach
These treatments, though life-saving in some cases, were ultimately reactive rather than proactive. They didn’t address the underlying mechanisms causing cells to become cancerous. Without targeting the root cause—whether it be genetic instability, metabolic dysfunction, or immune evasion—patients often experienced relapse. The quest to uncover deeper causes laid the groundwork for the genetic paradigm, though it, too, faced challenges.
Paradigm 2: The Genetic Mutation Theory (1970s–2000s)
The second paradigm shifted focus from uncontrolled growth to genetic mutations as the drivers of cancer. Researchers identified oncogenes and tumor suppressor genes, leading to treatments targeting these mutations. Early successes, such as Imatinib (Gleevec) and Trastuzumab (Herceptin), offered hope for a genetic cure.
However, by 2018, nearly six million unique mutations in protein-coding regions and close to twenty million unique mutations in protein-coding regions, across cancers were identified. Targeting these mutations through genetic therapy becomes an infeasible endeavor. The sheer number and diversity of mutations present a fundamental challenge—how does one determine which mutations to target, and in what order? Additionally, new mutations arise as cancer evolves, making it impossible to devise a universal or lasting strategy. This variability proved overwhelming:
Some tumors had hundreds of mutations; others had none.
Different patients with the same cancer had entirely distinct mutations.
Even within a single patient, tumors from different sites showed diverse mutations.
This underscores the futility of solely relying on genetic therapy to combat cancer effectively. Instead, it highlights the need to address the underlying drivers of cancer, such as metabolic dysfunction and the microenvironment that fuels its progression.
Total contents in version 86 of the COSMIC database (August 2018)
Category | Number | Description |
Tumor Samples | 1,391,372 | Cancer samples analyzed in the COSMIC database |
Coding Mutations | 5,977,977 | Mutations in protein-coding regions |
Manually Curated Publications | 26,251 | Research articles reviewed for data |
Gene Fusions | 19,368 | Fusions between genes contributing to cancer |
Whole Genomes/Exomes | 35,480 | Sequenced genomes/exomes from studies |
Copy Number Variants | 1,179,545 | Changes in gene copy numbers |
Gene Expression Variants | 9,147,833 | Alterations in gene activity levels |
Differentially Methylated CpGs | 7,879,142 | Epigenetic changes affecting gene regulation |
Non-coding Variants | 19,721,019 | Mutations outside coding regions |
The Denominator Problem
A significant challenge to the genetic model emerged when researchers discovered that many people with cancer-associated mutations did not develop cancer.
A 2012 Nature Genomics study found that 90% of individuals carrying mutations in known oncogenes never developed cancer.
Another study revealed that, as people age, they accumulate mutations, yet most never result in cancer.
Even in individuals with 1,000-2,000 mutations per cell in their later years, cancer remains rare.
Finding drugs to target each mutation became impossible. Despite initial promise, the genetic paradigm faltered. The question lingered: Why were these mutations occurring in the first place? The randomness theory also fell apart. For instance, a colorectal cancer in a Indian woman from the 1920s and a Hispanic woman in the U.S. a century later would appear identical under a microscope, despite vastly different environments and genetics. This suggested cancer followed a predictable, non-random pathway, contradicting the idea of purely random mutations.
Thus, the theory that “mutations cause cancer” lacked nuance. Mutations might contribute to cancer development, but they alone were insufficient. This finding unraveled the somatic mutation theory, shifting the focus toward understanding why cells mutate and how the microenvironment enables malignancy.The realization set the stage for a more holistic paradigm centered on cancer’s metabolic and environmental drivers.
Paradigm 3: Cancer's Evolutionary Roots – A Journey Back to Single-Cell Origins
While Paradigm 2 highlighted the inadequacies of the genetic mutation theory, it left open a deeper question: why do these mutations lead to cancer at all? The answer lies in the ancient biological roots of life. Cancer, more than being a disease of modern life, represents a fundamental breakdown in the cooperative principles that define multicellular organisms.
Evolution of Cancer: A Deep Time Perspective
Cancer is not a uniquely human disease—it predates humanity and is found across various species, including dogs, cats, and even simple organisms. To understand its origins, it is necessary to explore the evolution of life itself, particularly two major milestones:
From Prokaryotes to Eukaryotes: The transition from primitive, single-celled life forms to more complex cells with organelles.
From Single-Celled to Multi-Celled Organisms: This shift introduced fundamental changes in how cells functioned.
Key Differences Between Single-Celled and Multi-Celled Organisms
Feature | Single-Celled Organism | Cancer Cell | Multi-Celled Organism |
Growth Control | Exponential, unchecked growth | Unchecked, exponential growth | Highly controlled, cooperative |
Lifespan | Immortal, divides indefinitely | Immortal-like behaviour | Limited by telomere shortening |
Movement | Mobile, uses mechanisms like swarming/twitching | Mobile (metastasis) | Fixed in place, uses adhesion |
Energy Use | Glycolysis (fermentation) | Glycolysis even in oxygen presence | Oxidative phosphorylation in oxygen |
Behavior | Competes for resources, focuses on survival | Competes, invades and destroys host | Cells cooperate for the organism’s survival |
Specialization | No specialization | De-differentiated, non-specialized | Highly specialized, organized functions |
Genomic Stability | Genetically unstable to adapt | Genomic instability | Genetically stable |
Cancer as a Reversion to a Primitive State
Cancer behaves much like a single-celled organism, prioritizing its survival over the host's. This reversion includes:
Invasive Behaviour: Cancer invades new tissues, much like bacteria or viruses.
Exponential Growth: It replicates uncontrollably, competing for resources.
Resistance: Just as bacteria evolve resistance to antibiotics, cancer cells develop resistance to therapies.
Table: Mechanisms Supporting Indefinite Life in Single-Celled Organisms
Mechanism | Explanation |
Symmetrical Division | The "parent" cell divides into two equal cells, redistributing DNA, cytoplasm, and organelles evenly. Neither is a parent or child; both are functionally and structurally new. |
Dilution of Damage | Damaged proteins and cellular components are diluted during division, ensuring the daughter cells have minimal wear and tear. |
Rejuvenation | Cellular components are effectively "reset" during division, keeping the resulting cells free from aging-associated decline. |
Asymmetrical Division | In some cases (e.g., budding yeast), one cell inherits older components, while the other remains younger, allowing the lineage to maintain vitality. |
Avoidance of Aging | Single-celled organisms bypass the aging process by continuously creating "new" cells during division rather than retaining damage. |
Environmental Pressures | While theoretically immortal, factors like starvation, toxins, or predators ultimately limit their survival in practice. |
This table outlines how single-celled organisms sustain their potential for indefinite survival through biological and evolutionary strategies.
Backward Evolution: The Hidden Playbook of Cancer
Cancer represents a regression to ancient, unicellular behaviour embedded within the genetic code of every multicellular organism. The process is not one of adding new mutations but rather stripping away layers of control that block primitive cellular functions like unchecked growth, immortality, and mobility. This reveals an ancient genetic "kernel", which represents a fundamental, ancient set of genetic instructions or capabilities inherent in all living cells. This "kernel" embodies the primitive survival mechanisms and behaviours that are thought to have been inherited from our unicellular ancestors. It includes the core genetic and metabolic programming necessary for basic cellular functions, such as energy generation, reproduction, and survival in harsh environments. This is present in all living cells—a throwback to single-celled ancestors. Pathologists describe cancer as dedifferentiated or anaplastic—terms reflecting this backward evolution, or atavism, toward a primitive state. Every cell retains this dormant potential, explaining cancer’s universality across tissues and species.
Image Credit: British Journal of Cancer
Every cell in our body is potentially cancerous! This explains why cancer can arise in any cell type (e.g., breast, lung, or cervix) and why every multicellular organism is susceptible. Cancer essentially reflects a backward evolution, where cells revert from their cooperative multicellular state, with necessary controls in place, to a primitive single-cell-like behaviour, mirroring our unicellular origins.
Cancer Growth and Metastasis: The Evolutionary Path
Metastasis, the process by which cancer spreads to distant parts of the body, is not a late-stage phenomenon as previously believed but begins early in tumor development. Even before a tumor becomes detectable, it releases cancer cells into the bloodstream. Most of these circulating tumor cells (CTCs) perish due to immune attack, turbulence, or inability to adapt to new environments. Occasionally, a genetically diverse cell survives this hostile journey.
This surviving cell, selected for its resilience, may return to its original tumor site in a phenomenon known as tumor self-seeding. There, it thrives in familiar surroundings, integrating into the tumor and contributing to its genetic heterogeneity. Over time, cycles of sending out CTCs, selecting for survival, and reseeding enrich the tumor with multiple clones, each more evolutionarily adapted to thrive. Through these cycles, cancer not only grows locally but also refines its ability to metastasize, setting the stage for eventual colonization of distant tissues.
Image Credit: Nature Medicine
Genetic heterogeneity in the context of cancer refers to the diverse and variable genetic alterations that occur within and between cancer cells in a tumor. This variability influences the behavior, progression, and treatment resistance of cancer. Genetic heterogeneity can be broadly categorized into inter-tumoral heterogeneity (differences between tumors in different patients or locations) and intra-tumoral heterogeneity (differences within a single tumor).
Types of Genetic Heterogeneity in Cancer:
Inter-Tumoral Heterogeneity:
Refers to the genetic differences between tumors in different patients or even between primary and metastatic tumors within the same patient.
It explains why patients with the same type of cancer may respond differently to the same treatments.
Examples include variations in driver mutations (e.g., mutations in EGFR in lung cancer) or differences in tumor micro-environments.
Intra-Tumoral Heterogeneity:
Refers to the genetic diversity among cancer cells within a single tumor.
Subclones of cells with distinct mutations can coexist in a tumor, contributing to its complexity.
This type of heterogeneity can arise due to:
Mutations: Accumulated genetic changes during tumor growth.
Epigenetic modifications: Changes in gene expression without altering the DNA sequence.
Selective pressures: Environmental factors, such as hypoxia or treatment, that favor the survival of certain clones.
Implications of Genetic Heterogeneity in Cancer:
Treatment Resistance:
Heterogeneity allows for the presence of resistant subclones that can survive therapy and cause relapse or metastasis.
Targeting one mutation may not eliminate other genetically distinct clones.
Diagnosis and Prognosis:
Genetic variability complicates the identification of reliable biomarkers for cancer detection and treatment prediction.
A single biopsy may not capture the full genetic landscape of a tumor.
Cancer Progression and Metastasis:
Genetic heterogeneity drives the evolution of aggressive subclones that can spread to distant sites.
It plays a role in the adaptability of cancer cells to new environments.
Addressing Genetic Heterogeneity:
Combination Therapies: Targeting multiple pathways to overcome resistance.
Liquid Biopsies: Detecting circulating tumor DNA (ctDNA) to capture a broader genetic snapshot.
Adaptive Treatment Strategies: Adjusting therapies based on the evolving genetic profile of the tumor.
Genetic heterogeneity underscores the complexity of cancer and highlights the need for personalized and dynamic treatment approaches. It reflects the evolutionary nature of cancer, where diverse genetic changes provide a survival advantage in the face of environmental challenges, including therapies.
Conclusion: Shifting the Lens on Cancer
Throughout this blog, we’ve explored how the traditional genetic paradigm of cancer has evolved and how new perspectives, particularly the metabolic and evolutionary theories, are reshaping our understanding. We delved into how cancer is not solely driven by genetic mutations but by underlying metabolic reprogramming, a survival mechanism that harkens back to ancient cellular behaviors. This shift in focus highlights the importance of considering the environment, lifestyle, and metabolic dysfunctions in understanding cancer development and progression.
Additionally, we examined the complexity of cancer's genetic heterogeneity, which presents a significant challenge to therapies targeting mutations. The sheer number of mutations in cancer cells makes traditional genetic therapies difficult to implement, prompting the need for alternative approaches that take into account the underlying evolutionary processes that govern cancer behaviour.
As we conclude, it is clear that cancer is a manifestation of an evolutionary process rooted in the ancient behaviours of unicellular organisms, with profound implications for how we approach treatment and prevention. In the next blog, we will continue this exploration by diving deeper into the evolutionary link between unicellular ancestors and cancer cells, the role of gene expression in cancer, and how elements like promoters and enhancers orchestrate cellular behaviour. We’ll uncover how these ancient genetic "blueprints", activated under certain conditions, allow cancer cells to thrive in a way that mirrors the evolution from unicellular to multicellular organisms, setting the stage for a broader understanding of cancer biology.
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