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Home NEWS Science News Cancer

Young Scientists Map the Next Quarter-Century of Cancer Research

Bioengineer by Bioengineer
September 12, 2026
in Cancer
Reading Time: 6 mins read
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Cancer research stands at a turning point. Over the past 25 years, the field has been transformed by genomic sequencing, immunotherapy and a vastly deeper understanding of tumour biology, yet cancer still claims millions of lives each year. As the journal Nature Reviews Cancer marks its 25th anniversary, it has taken the unusual step of handing the microphone to the scientists who will define the field’s next quarter-century. In a viewpoint article published in September 2026, six emerging investigators — a medical oncologist, a genomicist, a cancer neuroscientist, a tumour immunologist, an expert in non-genetic drug resistance and a computational biologist — were asked to identify the conceptual opportunities, outdated paradigms and emerging technologies they believe will most powerfully shape cancer research through 2050.

The decision to centre emerging investigators rather than established luminaries is itself a statement about how science should evolve. The authors argue that researchers early in their careers are uniquely positioned to challenge prevailing assumptions, adopt interdisciplinary approaches and redirect priorities that may have calcified over decades. The resulting collection of perspectives spans an unusually wide technical range, from neoadjuvant immunotherapy in colorectal cancer to somatic mosaicism in healthy tissues, from the nervous system’s role in tumour progression to artificial intelligence models that predict cellular responses to genetic perturbation. Together, the six contributions sketch a research agenda that is more integrated, more prevention-focused and more computationally ambitious than anything the field has attempted before.

One thread running through the article is the remarkable maturation of cancer immunotherapy, particularly when treatment is moved earlier in the disease course. Myriam Chalabi, a medical oncologist and physician scientist at the Netherlands Cancer Institute in Amsterdam, has built her research programme around immunotherapy delivered in the neoadjuvant setting, using novel treatment combinations within innovative trial designs. The clinical evidence underpinning this shift is striking: recent work has demonstrated neoadjuvant immunotherapy in mismatch-repair-proficient colon cancers, while separate research has shown that non-operative management of mismatch repair deficient tumours can produce durable responses, in some cases allowing patients with rectal cancer to avoid surgery entirely. These results suggest that the immune system, when engaged before a tumour has been removed, can eliminate disease that conventional staging would consider established, and they raise the prospect of organ-preserving treatment as a realistic goal rather than an aspirational one.

Yet immunotherapy has also exposed the limits of tumour-centric thinking, and several of the authors argue that the next 25 years must focus on the host as much as the tumour. James L. Reading, an associate professor of cancer immunology at UCL who leads the Pre-cancer Immunology Laboratory, studies T cell-driven cancer interception — the idea of detecting and eliminating tumours before they become clinically invasive. His work builds on the discovery that reservoirs of stem-like CD8-positive T cells in tumour-draining lymph nodes sustain ongoing antitumor immune responses, and that conventional type I dendritic cells maintain pools of proliferative, tumour-antigen-specific TCF1-positive CD8-positive T cells in those same nodes. Understanding how these immune reservoirs are established and maintained during pre-invasive disease, he argues, could transform early detection from passive imaging into active, immune-guided interception, catching malignancy at a stage when cure rates approach certainty.

The genomic dimension of this preventive agenda is developed most fully by Tim H. H. Coorens, a group leader at the European Bioinformatics Institute who studies how somatic mutations accumulate in normal cells. Twenty-five years ago, cancer genomes were largely studied in isolation from the tissues that produced them. Today, it is clear that essentially every cell in the body accrues mutations over a lifetime, and that clones of mutant cells — some harmless, some pre-malignant — expand and compete in otherwise healthy tissue. Coorens contributed to the Somatic Mosaicism Across Human Tissues network, an effort to catalogue this variation systematically, and recent analyses have shown that age itself can distinguish selective clonal expansion from simple mutational causation in cancer genomes. Meanwhile, the real-world clinical utility of tumour whole-genome sequencing in solid cancers has now been demonstrated at scale, suggesting that comprehensive genomic profiling is moving from research luxury to standard of care. The conceptual shift is profound: cancer becomes not a foreign invader but one possible endpoint of a lifelong evolutionary process, and the levers for prevention may lie in the dynamics of normal tissue.

Perhaps the most visually striking frontier is cancer neuroscience. Leanne Li, a group leader at the Francis Crick Institute in London, combines cancer genetics with neurotechnologies to decipher the logic of interactions between tumours and the nervous system in mouse models. The field’s roots reach back more than a century to observations of nerves within tumours made using methylene blue vital staining, but modern cancer neuroscience has exploded in the past decade. Recent single-neuron sequencing has revealed how individual neurons are reprogrammed by pancreatic cancer, and comprehensive reviews have mapped the past, present and future of the discipline. Li also leads InteroCANCEption, a multidisciplinary team funded by Cancer Grand Challenges to tackle the broader question of how interoception — the body’s sensing and regulation of its own internal signals, a concept elaborated in modern neuroscience — shapes tumour initiation, growth and response to therapy. If tumours co-opt neural circuitry the way they co-opt blood vessels, then neuromodulatory drugs already approved for other conditions could become unexpected additions to the oncology arsenal.

Resistance to therapy, the stubborn core of cancer mortality, is the focus of Shensi Shen, associate professor at West China Hospital, Sichuan University. His work centres on drug-tolerant persister cells — a subpopulation of cancer cells that survives initial treatment not through genetic mutation but through reversible shifts in cell state. Reviews have traced the journey of persister cell biology from basic questions to clinical opportunities, and single-cell analyses have shown that genetically homogeneous cancer cells can diverge into multiple distinct clonal fates when exposed to the same drug. Shen’s particular interest is in layered translational control: the regulation of how messenger RNA is decoded into protein, which allows cancer cells to deploy hidden protein functions and switch states under therapeutic pressure. Because these transitions are non-genetic, they are also potentially reversible, which makes the persister state an attractive target for combination strategies designed to block the escape routes that tumours use to survive targeted therapy and immunotherapy alike.

Underpinning all of these biological questions is a computational revolution, examined by Ewa Szczurek, associate professor at the University of Warsaw and director of the Institute of AI for Health at Helmholtz Munich. Szczurek develops artificial intelligence models for molecular biology and medicine, and her perspective is notably sober about the current state of the field. While foundation models promise to predict how cells respond to genetic and pharmacological perturbations — an ambition exemplified by recent preprint work on state-based prediction of cellular responses — independent evaluations have shown that deep-learning-based gene perturbation effect prediction does not yet outperform simple linear baselines in many settings. Her message is that the next 25 years of AI in cancer research will be defined not by model size but by data quality, experimental validation and careful benchmarking. If the field heeds that warning, machine learning could genuinely accelerate target discovery and personalised treatment; if it does not, hype risks outrunning biology.

Woven together, the six perspectives describe a field in mid-revolution. The tumour-as-isolated-entity model is giving way to a systems view in which cancer is embedded in the evolutionary dynamics of normal tissues, the immune landscape of pre-invasive disease, the neural circuitry of the host body and the non-genetic plasticity of individual cells. Clinical paradigms are shifting in parallel: treatment is moving earlier, surgery is sometimes becoming optional, and molecular residual disease monitoring — exemplified by analyses of adjuvant osimertinib in resected EGFR-mutated lung cancer — is becoming a guide for post-operative decisions. The anniversary article also translates premalignant biology into strategies for intercepting non-small-cell lung cancer, illustrating how laboratory insight can be converted directly into prevention trials.

What emerges most clearly is a demand for interdisciplinarity as a structural principle rather than a slogan. The authors themselves embody it: a clinician designing immunotherapy trials, a bioinformatician decoding mutation accumulation, a neuroscientist engineering tools to interrogate tumour-nerve crosstalk, an immunologist chasing T cells before invasion, a molecular biologist tracking protein-level resistance and a computer scientist stress-testing the field’s newest models. Their collective wager is that the major killers of the next quarter-century will not be defeated by any single breakthrough but by the deliberate integration of genomics, immunology, neuroscience, developmental biology and computation — and by the willingness of a new generation to ask questions their predecessors did not think to ask.

Subject of Research: Emerging investigators’ perspectives on the future priorities of cancer research over the next 25 years

Article Title: The next 25 years of cancer research: emerging perspectives and priorities

Article References: Chalabi, M., Coorens, T. H. H., Li, L., Reading, J. L., Shen, S., & Szczurek, E. (2026). The next 25 years of cancer research: emerging perspectives and priorities. Nature Reviews Cancer. https://doi.org/10.1038/s41568-026-00975-3

Image Credits: AI Generated

DOI: 10.1038/s41568-026-00975-3

Keywords: cancer research, Nature Reviews Cancer, immunotherapy, neoadjuvant therapy, somatic mosaicism, cancer neuroscience, cancer interception, drug-tolerant persister cells, tumour heterogeneity, whole-genome sequencing, artificial intelligence, early detection

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Nathaniel Bowman. (September 12, 2026). Young Scientists Map the Next Quarter-Century of Cancer Research. Scienmag. https://scienmag.com/young-scientists-map-the-next-quarter-century-of-cancer-research/

Nathaniel Bowman. “Young Scientists Map the Next Quarter-Century of Cancer Research.” Scienmag, 12 September 2026, https://scienmag.com/young-scientists-map-the-next-quarter-century-of-cancer-research/. Accessed 12 September 2026.

Nathaniel Bowman. “Young Scientists Map the Next Quarter-Century of Cancer Research.” Scienmag. September 12, 2026. https://scienmag.com/young-scientists-map-the-next-quarter-century-of-cancer-research/

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Tags: Artificial Intelligencecancer interceptioncancer neurosciencecancer researchcancer research future predictionscancer resistance mechanismsdrug-tolerant persister cellsearly detectionearly-career cancer scientistsemerging cancer research technologiesfuture challenges in cancer treatmentgenomic sequencing in cancerImmunotherapyimmunotherapy advancementsinterdisciplinary approaches in oncologyNature Reviews Cancerneoadjuvant therapyneuro-oncology and tumor interactionsnext-generation cancer therapiessomatic mosaicismtumor biology insightstumor microenvironmenttumour heterogeneitywhole genome sequencing

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