The research, led by Biao Zhang, Shujun Yang, Su Zhang and corresponding author Panfeng Shang, drew on the Surveillance, Epidemiology, and End Results database, the large population-based cancer registry maintained by the United States National Cancer Institute. The investigators identified patients diagnosed with UTUC between 2004 and 2015 and divided them into two groups: 2,694 early-onset patients and 4,144 elderly patients. The first analytical step was a head-to-head comparison of clinicopathological characteristics between the age groups, followed by survival analyses in both cohorts. The early-onset patients were then split into a training set of 1,886 individuals and an internal validation set of 808 individuals, in a seven-to-three ratio, providing the statistical backbone for model construction and testing.

At the heart of the study is a statistical instrument known as a nomogram. A nomogram is a graphical calculating device that translates the results of a multivariable regression model into a point-based scoring system. Each patient characteristic, such as tumor stage or age, is assigned a number of points proportional to its statistical weight, and the summed total maps onto an estimated probability of surviving for a given number of years. For decades nomograms have been prized in oncology because they outperform crude stage groupings: they integrate continuous variables, weigh each factor according to its independent contribution, and produce individualized estimates rather than population averages. In this study the team built two separate nomograms, one predicting overall survival, which counts deaths from any cause, and one predicting cancer-specific survival, which counts only deaths attributable to the cancer itself.

To determine which variables deserved a place on those nomograms, the researchers used Cox proportional hazards regression, the standard method for modeling the time until an event such as death occurs. For overall survival, the analysis identified age, tumor size, T stage, N stage, M stage, histologic subtype and chemoradiotherapy as independent risk factors. For cancer-specific survival, the independent predictors were age, tumor grade, tumor size, T stage, N stage, M stage, histologic subtype and radiotherapy. The overlap is instructive: the anatomical staging variables that describe how far the tumor has invaded and spread dominate both models, while treatment variables enter in different forms depending on whether the endpoint is death from any cause or death from cancer. Tumor grade, a measure of how abnormal the cancer cells look under the microscope, appears only in the cancer-specific model, which makes biological sense because grade reflects the inherent lethality of the tumor rather than the general health of the patient.

The performance of the two nomograms was assessed with a battery of complementary statistical tests, each answering a different question. The concordance index measures whether the model correctly ranks patients by risk, a value of 0.5 indicating coin-flip accuracy and 1.0 indicating perfect discrimination. Receiver operating characteristic curves and their areas under the curve, or AUC values, quantify how well the model separates patients who die within a fixed time window from those who survive it. Calibration plots compare predicted survival probabilities against observed survival, revealing whether the model is systematically too optimistic or too pessimistic. Decision curve analysis, a more recent addition to the prognostic modeling toolkit, estimates the net clinical benefit of using the model to guide decisions across a range of risk thresholds, weighing the costs of false alarms against the costs of missed high-risk patients.

The reported discrimination figures are strong for a population-based model. For overall survival, the AUC values at one, three, five and eight years were 0.807, 0.774, 0.760 and 0.736 in the training cohort, 0.811, 0.793, 0.763 and 0.752 in the internal validation cohort, and 0.793, 0.767, 0.754 and 0.730 in the external validation cohort. For cancer-specific survival the numbers were even higher: 0.834, 0.822, 0.816 and 0.792 in the training cohort, 0.863, 0.833, 0.811 and 0.820 in internal validation, and 0.819, 0.815, 0.806 and 0.780 in external validation. In practical terms, an AUC above 0.8 is generally considered good discrimination, meaning the cancer-specific model correctly distinguished young patients who died of their disease from those who did not in roughly four out of five pairwise comparisons. The modest decline in accuracy at longer horizons is expected, since competing causes of death and evolving treatments accumulate over time and blur the predictive signal.

Crucially, the team did not rely on internal validation alone, which can flatter a model by testing it on data drawn from the same source population. External validation was performed using an independent cohort of 255 early-onset UTUC patients, and the nomograms retained their accuracy in this outside sample. This step matters because a model that only works within the registry used to build it has limited clinical value. The investigators also plotted Kaplan-Meier survival curves to compare outcomes across risk subgroups defined by the nomogram scores, and these curves showed statistically significant differences in both overall and cancer-specific survival. In other words, when the tool sorts patients into risk categories, those categories genuinely correspond to different survival trajectories, which is the property that would allow a clinician to use the score to triage follow-up intensity or treatment escalation.

Why does early-onset UTUC deserve its own prognostic model in the first place? Younger patients differ from elderly ones in ways that can distort predictions borrowed from general models. They tend to have fewer competing causes of death, so cancer-specific outcomes dominate their survival statistics, and their disease biology, genetic background and exposure profiles may differ from the typical older patient with a smoking history and decades of environmental exposure. By comparing early-onset and elderly patients directly and then modeling the young cohort separately, the Lanzhou team produced estimates that reflect the actual risk landscape facing a forty-five-year-old with a renal pelvis tumor rather than a seventy-five-year-old. The inclusion of histologic subtype as a predictor is also notable, since variants of urothelial carcinoma carry different prognoses and are increasingly recognized as important modifiers of outcome.

The study does carry the limitations inherent to its design. SEER data, while vast and population-based, lack granular clinical details such as lymphovascular invasion, molecular markers, performance status and the specific surgical approach, all of which influence outcomes in modern practice. The diagnostic window of 2004 to 2015 predates the routine use of checkpoint inhibitor immunotherapy in metastatic urothelial carcinoma, so the models cannot account for survival gains from newer systemic therapies. As a registry-based study, it captures what was recorded at the population level, not the full nuance of individual clinical decision-making. The authors acknowledge that the tool is intended to aid prognostic assessment and guide clinical treatment, not to replace clinical judgment, and external validation in contemporary cohorts treated with modern regimens would strengthen confidence in its current applicability.

Nevertheless, the work represents a concrete step toward precision prognostication in a neglected patient subgroup. For a young patient facing a diagnosis of upper tract urothelial carcinoma, an evidence-based estimate of one-, three-, five- and eight-year survival probabilities can inform decisions about the aggressiveness of surgery, the use of perioperative chemotherapy or radiotherapy, and the intensity of surveillance. For researchers, the nomogram provides a risk-stratification framework that future studies of biomarkers and targeted therapies can build upon. As prognostic models in oncology evolve from static stage groupings toward dynamic, individualized calculators, studies like this one demonstrate that even rare cancers in atypical populations can be modeled rigorously when sufficiently large registry data are combined with disciplined statistical validation.

Subject of Research: Development of a SEER-based prognostic nomogram predicting survival in early-onset upper tract urothelial carcinoma

Article Title: Development and validation of a SEER-based prognostic nomogram for patients with early-onset upper tract urothelial carcinoma

Article References: Zhang, B., Yang, S., Wang, C., Chang, W., Zhang, H., Zhang, S., & Shang, P. (2026). Development and validation of a SEER-based prognostic nomogram for patients with early-onset upper tract urothelial carcinoma. BMC Cancer. https://doi.org/10.1186/s12885-026-17114-8

Image Credits: AI Generated

DOI: 10.1186/s12885-026-17114-8

Keywords: upper tract urothelial carcinoma, nomogram, SEER database, prognosis, overall survival, cancer-specific survival, Cox regression, early-onset cancer, urological cancer, risk stratification, BMC Cancer, survival prediction

The research, published in Supportive Care in Cancer, involved twelve adults with advanced bladder or renal cancer receiving immune checkpoint inhibitor therapy at a tertiary cancer centre in London. Through individual semi-structured interviews lasting between 34 and 69 minutes, the team led by Nicola Peat of Guy’s and St Thomas’ Hospital NHS Foundation Trust explored how patients perceive and experience physical activity during immunotherapy. The interviews were transcribed verbatim and analysed using Braun and Clarke’s six-phase thematic analysis, a rigorous framework for identifying patterns across qualitative data. Four main themes emerged: the purpose of physical activity participation, the factors that help or hinder it, the striking lack of support from healthcare professionals, and the kind of support patients actually want.

The scientific rationale for the study is compelling. Physical activity is known to mitigate many cancer treatment side-effects, including fatigue and anxiety, and is associated with improved physical function and health-related quality of life across cancer populations. More intriguingly, emerging evidence suggests exercise may exert immunomodulatory effects that contribute directly to tumour control. In preclinical research, moderate-intensity exercise has been shown to reduce tumour size by mobilising highly differentiated natural killer cells and increasing the infiltration of CD8-positive T cells into tumours, the very immune mechanisms that checkpoint inhibitors are designed to enhance. This has led researchers to propose that exercise may have both a conditioning effect and a tumour immune surveillance effect, potentially amplifying the benefits of immunotherapy itself.

Current guidelines recommend that adults with cancer engage in at least 150 minutes of moderate-intensity or 75 minutes of vigorous-intensity aerobic exercise per week, plus two resistance-training sessions. Yet physical activity levels typically decline after a cancer diagnosis, with fewer than 30 percent of individuals meeting these recommendations. The new study reveals how this gap plays out in the lives of patients on immunotherapy. Most participants described a decline in activity following diagnosis, driven by frequent hospital visits, debilitating side-effects, and a simple lack of knowledge about what was safe or beneficial. Fatigue emerged as the dominant barrier, with one participant describing having absolutely no energy, and another attributing profound exhaustion to treatment-induced pituitary and thyroid dysfunction, telling researchers they were more worn out than during their army days.

Pain also limited movement, particularly where cancer had spread to bones in the hip and leg, while nausea, vomiting, skin rash and itchiness added further obstacles. Psychological factors mattered too. One participant described falling into a dark period after diagnosis, spending most days in bed with the blanket over their head, and reflected that help to snap out of it might have changed everything. Notably, the study identified barriers unique to checkpoint inhibitor therapy: endocrine-related fatigue, nausea and skin symptoms that fluctuate across treatment cycles, creating a moving target for both patients and anyone prescribing exercise. Social support cut both ways, with some patients encouraged by family members to walk to the shops, and others told by worried relatives to cancel gym memberships and rest.

Against these barriers, participants described powerful motivations. Physical activity represented independence, normalcy and control, a way of living life on their own terms. Walking was the most common activity, woven into daily routines such as commuting, shopping and playing with grandchildren. Immunotherapy itself acted as a beacon of hope, with one patient describing the treatment as a last chance of survival and a reason to be as fit and well as possible. Participants also credited exercise with lifting mood, managing comorbidities such as pre-diabetes, and easing fatigue and pain, with one describing how supervised treadmill sessions at the cancer centre gym restored the ability to walk at a good pace and take grandchildren to the park. Several described physical activity as their therapy place, a source of routine, sanctuary and a happiness factor.

The most striking finding, however, was the silence of the clinical team. Every participant reported receiving little or no physical activity advice during routine appointments. Some recalled only vague encouragement to keep doing what they were doing, while the majority received nothing at all. When asked whether advice would have helped, all but one said yes, with one patient noting that information about exercise would totally have changed the way they felt about it. Several said that simply reading the study information sheet sparked a desire to become more active, and argued that such information should be given to patients at the start of treatment. Participants perceived that clinicians prioritised drug-based management of side-effects over conversations about movement, and physiotherapy referrals, when they occurred, focused on managing impairments rather than broader activity benefits.

What patients want, the study found, is structured, personalised and expert-led support rather than leaflets or generic exhortations. They wanted someone to show them the right exercises for their specific tumour sites and limitations, trusted professionals with knowledge of both cancer and exercise, clear targets and progress tracking, and flexible programmes that accommodate the good and bad days of treatment cycles. Walking and strength training were the most favoured activities, followed by cycling and swimming, and participants favoured hybrid models combining supervised hospital or gym sessions with home-based activity. Crucially, they endorsed a periodised, auto-regulated approach, doing less during treatment weeks and more in the weeks after, an approach consistent with research showing that chemotherapy-periodised exercise improves adherence and symptom management compared with linear progression.

The authors argue that structured physical activity is a promising but underutilised strategy for managing cancer and treatment-related side-effects during checkpoint inhibitor therapy, and that these patients have distinct needs requiring personalised support. Their recommendations include embedding professionals with cancer-specific exercise expertise, such as physiotherapists, directly into cancer clinics and care pathways, improving referral routes to rehabilitation specialists, and training healthcare professionals to close knowledge and confidence gaps. Prior research suggests only between 6 and 44 percent of cancer patients receive physical activity information during oncology appointments, and this study suggests immunotherapy patients are no exception. Given exercise’s potential to enhance both quality of life and possibly immunotherapy response, the researchers call for future studies to evaluate which checkpoint inhibitor side-effects can be mitigated through activity, and to test accessible, scalable interventions across patient groups.

The study has limitations. Recruitment came from a single UK tertiary centre with a relatively homogeneous group of bladder and renal cancer patients, all receiving checkpoint inhibitors, which may limit generalisability to broader populations or other treatments. The supportive context of the specialist unit and good transport links may also have under-represented socioeconomic and environmental barriers reported elsewhere. Nevertheless, the methodology was rigorous, reported against the COREQ checklist, with ethical approval, member-checked transcripts and reflexive analysis. For patients whose treatment is their last hope of survival, the message from this research is clear: they want to move, they believe movement helps, and the healthcare system needs to start telling them how.

Subject of Research: Patient perspectives and experiences of physical activity during immune checkpoint inhibitor treatment for advanced urological cancers

Article Title: Physical activity in advanced urological cancers undergoing immune checkpoint inhibitor treatment: a qualitative study exploring patient perspectives and experiences

Article References: Peat, N., Jones, G. D., Veal, I., Kinsella, N., Karagiannis, S. N., & Van Hemelrijck, M. (2026). Physical activity in advanced urological cancers undergoing immune checkpoint inhibitor treatment: a qualitative study exploring patient perspectives and experiences. Supportive Care in Cancer, 34(10), Article 963. https://doi.org/10.1007/s00520-026-11195-8

Image Credits: AI Generated

DOI: 10.1007/s00520-026-11195-8

Keywords: physical activity, immune checkpoint inhibitors, immunotherapy, bladder cancer, renal cancer, urological cancer, qualitative research, exercise oncology, cancer rehabilitation, fatigue, supportive care, patient perspectives

The messenger RNA in question encodes CENPA, or centromere protein A, a specialized histone variant that performs a task no dividing cell can do without: it marks the centromere, the chromosomal anchor point that spindle fibers grip during mitosis to ensure chromosomes are partitioned faithfully between daughter cells. CENPA has long been known to be elevated in a range of tumors, where excess levels contribute to chromosomal instability, aberrant cell division, and aggressive behavior. The new study adds an important layer to that picture by showing that in bladder urothelial carcinoma, CENPA abundance is not simply a matter of how much mRNA is transcribed from the gene, but how long that mRNA survives once it is made—and that survival is controlled by a discrete epitranscriptomic mark.

That mark is N6-methyladenosine, or m6A, the most prevalent internal modification in eukaryotic messenger RNA. Rather than changing the genetic sequence itself, m6A tags act like postal codes, dictating how each transcript is folded, exported, translated, or degraded. The system depends on reader proteins that recognize the tag and act on it. Among the most consequential readers is the IGF2BP family, and in particular IGF2BP3, also known as IMP3, an oncofetal RNA-binding protein that is largely silenced in adult tissues but re-emerges in many cancers, including glioma, hepatocellular carcinoma, renal cell carcinoma, and bladder cancer. Prior work had already linked IGF2BP3 to tumor progression and stem-like behavior in bladder cancer, but its precise contribution to chemotherapy resistance had remained murky.

To dissect that contribution, the research team turned to a pair of well-characterized human bladder urothelial carcinoma cell lines, UMUC3 and T24, alongside a purposefully derived paclitaxel-resistant counterpart of T24, designated T24/R. Paclitaxel works by stabilizing microtubules, throwing a wrench into the mitotic spindle and triggering cell death in rapidly dividing cells. Resistant cells must therefore either alter their division machinery or blunt the death pathways that spindle catastrophe activates. Using a battery of molecular assays—RNA immunoprecipitation to capture physical protein-RNA interactions, methylated RNA immunoprecipitation followed by quantitative PCR to detect the m6A mark itself, and dual-luciferase reporter assays to confirm sequence-specific binding—the researchers established that IGF2BP3 directly recognizes m6A-modified CENPA mRNA in bladder cancer cells.

The functional consequences of that recognition were striking. When the team silenced IGF2BP3, levels of CENPA messenger RNA and its encoded protein fell sharply, an effect the researchers traced to destabilization of the transcript. Actinomycin D chase experiments, a classic method for measuring mRNA half-life, revealed that without IGF2BP3 standing guard, the CENPA message decayed far more rapidly. In practical terms, IGF2BP3 acts as a molecular bodyguard: by docking onto the m6A tag, it shields CENPA mRNA from the cellular degradation machinery, keeping the centromere protein continuously stocked in the tumor cell. Loss of that bodyguard leaves the cancer cell with diminished CENPA supplies and, crucially, a heightened vulnerability to paclitaxel.

That vulnerability translated into measurable changes in tumor behavior. IGF2BP3 knockdown not only increased paclitaxel sensitivity but also curtailed the migration, invasion, and clonogenic capacity of the cancer cells—the repertoire of traits that makes tumors hard to remove and prone to spread. To test whether CENPA was the critical downstream effector rather than an incidental passenger, the researchers ran a rescue experiment: they forced CENPA overexpression in IGF2BP3-silenced cells and found that the malignant capabilities returned, allowing the cells to migrate, invade, and form colonies even under paclitaxel pressure. The m6A dependency of the whole circuit was confirmed with an elegant control. When the researchers mutated the specific m6A site on CENPA mRNA, the rescue effect evaporated, demonstrating that the epitranscriptomic mark is not decorative but essential to the IGF2BP3-CENPA axis.

The story then moved from the dish to the living animal. In xenograft mouse models implanted with paclitaxel-resistant T24/R cells, silencing IGF2BP3 suppressed tumor growth and made the tumors significantly more responsive to paclitaxel treatment. Reintroducing CENPA partially reversed this effect, blunting the gains in drug sensitivity and tumor control. The in vivo results are important because they suggest that the mechanism operates not merely as a cell-culture artifact but as a genuine driver of treatment failure in a physiological setting. They also reinforce the notion that the IGF2BP3-CENPA axis sits upstream of chemoresistance rather than downstream of it, making it a plausible intervention point.

The significance of these findings lies in the convergence of two hot areas of cancer biology: epitranscriptomics and drug resistance. Over the past decade, m6A modification has emerged as a master regulator of cancer-relevant gene expression, with writers, erasers, and readers each offering potential drug targets. IGF2BPs, in particular, have been shown to stabilize transcripts supporting stemness, hypoxia adaptation, metabolism, and immune evasion in tumors. By identifying CENPA mRNA as a specific m6A-dependent target of IGF2BP3 in bladder cancer, the Nanchang-led team has connected this regulatory logic to a clinically painful problem: paclitaxel resistance in urothelial carcinoma, where poor prognosis and chemoresistance remain defining features of advanced disease. CENPA itself has already been implicated in resistance to EGFR inhibitors in lung adenocarcinoma and in suppressing ferroptosis in liver tumors, hinting that epitranscriptomic control of the centromere machinery may be a recurrent theme across cancer types.

The therapeutic implications are twofold. First, IGF2BP3 or its interaction with m6A-tagged CENPA mRNA could serve as a biomarker, helping clinicians identify patients whose tumors are likely to resist paclitaxel and who might benefit from alternative regimens or combination strategies. Second, pharmacologically disrupting the IGF2BP3-CENPA axis—whether by blocking the protein-RNA interaction, depleting IGF2BP3, or targeting upstream m6A machinery—could resensitize resistant tumors to existing chemotherapy, effectively converting nonresponders into responders. The study’s authors, led by HanJie Yi, YongQing Han, and corresponding author ShanFeng Li, suggest that targeting this axis may provide a novel strategy to overcome chemoresistance in bladder urothelial carcinoma. Substantial work remains before such strategies reach patients: the findings derive from cell lines and xenografts, and candidate inhibitors of m6A readers are only beginning to enter clinical development. Yet the study offers a clear mechanistic narrative for how bladder cancer cells weaponize a chemical tag on their own messenger RNA to endure one of medicine’s oldest spindle poisons—and in doing so, it hands researchers a precise molecular handle to pry that endurance apart.

Subject of Research: m6A-dependent stabilization of CENPA mRNA by IGF2BP3 as a mechanism of paclitaxel resistance in bladder urothelial carcinoma

Article Title: IGF2BP3 enhances paclitaxel resistance in bladder urothelial carcinoma by recognizing m6A-modified CENPA mRNA

Article References: Yi, H., Han, Y., Wang, X., Li, Q., Xiong, L., & Li, S. (2026). IGF2BP3 enhances paclitaxel resistance in bladder urothelial carcinoma by recognizing m6A-modified CENPA mRNA. Medical Oncology, 43(10), Article 278. https://doi.org/10.1007/s12032-026-03383-7

Image Credits: AI Generated

DOI: 10.1007/s12032-026-03383-7

Keywords: bladder urothelial carcinoma, IGF2BP3, CENPA, m6A modification, paclitaxel resistance, mRNA stability, chemoresistance, epitranscriptomics, RNA-binding protein, cancer therapeutic resistance, urological cancer, xenograft models