The Christie School of Oncology: Christie Research Publications Repository
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Retinal determination network reactivation drives chemoresistance and blocks myeloid differentiation in acute myeloid leukemia
No full textAcute myeloid leukemia (AML) is a heterogeneous malignancy driven by abnormal transcriptional programs that block myeloid differentiation and sustain self-renewal. Despite treatment advances over the last 30 years, refractory responses remain common, underscoring the need for new therapies. Here, we reveal the reactivation of retinal determination gene network (RDGN) members SIX1 and EYA1 in MOZ- and MLL-rearranged AMLs. We demonstrate that the SIX1-EYA1 complex enhances HOXA9-driven transformation, reinforcing differentiation blocks and maintaining leukemic blast morphology. RDGN members are expressed in both mouse and human AML cells, within discrete subpopulations that inversely correlate with MEIS1/HOXA9 expression. We demonstrate that the expression of RDGN members contributes to chemoresistance via enhanced DNA damage repair. Genetic ablation of SIX1 and pharmacological disruption of the SIX1/EYA1 interaction impair AML maintenance and resensitize cells to DNA-damaging therapies. These findings establish RDGN as a promising therapeutic target in AML and potentially in solid tumors marked by SIX1/RDGN re-expression
Cigarette Smoke Skews T Cells to Promote Pancreatic Cancer
No full textIn this issue, Griffith and colleagues describe a novel mechanism by which exposure to the carcinogen 2,3,7,8-tetrachlorodibenzo-p-dioxin through cigarette smoking promotes pancreatic tumorigenesis via the orchestration of a tumor-permissive local T-cell compartment. By stimulating aryl hydrocarbon receptors in CD4+ T cells, 2,3,7,8-tetrachlorodibenzo-p-dioxin skews the pancreatic immune landscape toward tolerance by promoting the expansion of IL22-secreting Th22 cells and regulatory T cells while simultaneously depleting tumor-targeting CD8+ T cells, thereby accelerating pancreatic dysplasia and tumor progression
Feasibility study exploring the effect of pelvic radiotherapy on the intestinal microbiome and metabolome to improve the detection and management of gastrointestinal toxicity
No full textAIMS: Eighty percent patients develop gastrointestinal (GI) symptoms during pelvic radiotherapy. The triggering event is a known enabling identification of pathophysiological changes. The focus of this study was feasibility (identification, recruitment, and retention), however, exploratory microbiome and metabolome analyses were performed. MATERIALS AND METHODS: Patients undergoing pelvic radiotherapy underwent faecal sampling (baseline, week 4, and 6 months), with assessment of GI toxicity using the Imflammatory Bowel Disease Questionnaire (IBDQ) bowel (IBDQB) subset. Participants were split into 2 groups based on IBDQB at week-4. Exploratory analysis was performed to identify differences in metabolome (gas chromatography-mass spectrometry) and microbiome (16s rRNA sequencing). RESULTS: Two hundred twenty-seven patients were screened, 69 were approached, and 17 were recruited over 18 months (mean age: 61.6 ± 15.3 years; 14 female; 1 withdrawal). Metabolome analysis showed lower heptanal and octanal in baseline samples of patients with higher GI toxicity; lower (methyltrisulfanyl)methane in week-4 samples of patients with higher GI toxicity; and higher butanoic acid and benzaldehyde in month 6 samples in patients with higher GI toxicity. Whole-group microbiome analysis showed a trend towards decreased alpha diversity at 4 weeks; no differences in beta diversity; and a trend towards increase in Lachnoclostridium and decrease in Ruminococcaceae Incertae sedis at week 4. Microbiome analysis split by GI toxicity showed lower alpha diversity for the high GI toxicity group (each timepoint); no significant difference in beta diversity between groups; more genera differentially abundant between the GI toxicity groups at 4 weeks, than at other timepoints. CONCLUSION: Recruitment was lower than anticipated. Attrition was low. Exploratory analysis suggests heptanal and octanal may have a role as a biomarker for GI toxicity, and lower alpha diversity may predict GI toxicity, with Lachnoclostridium and Ruminococcaceae Incertae sedis as bacteria of interest
Long-term outcomes from a multicentre study of HDR monotherapy with a single fraction of 19 Gy for localized prostate cancer
No full textOBJECTIVES: To evaluate long-term clinical outcomes, toxicity, and prognostic factors in patients with localized prostate cancer treated with single-fraction high-dose-rate (HDR) brachytherapy. METHODS: This multicentre retrospective study included patients from five UK centres who received a single 19 Gy HDR brachytherapy fraction under a standardized protocol. Kaplan-Meier estimates were calculated at median 5 and 8 years for biochemical progression-free survival (bPFS), local recurrence-free survival (LRFS), nodal recurrence-free survival (NRFS), distant metastasis-free survival (DMFS), and overall survival (OS). Prognostic factors were assessed using Cox regression. Toxicities were graded using CTCAEv3.0. Quality of life (QoL) was evaluated using IPSS, IIEF, and FACT-P questionnaires. RESULTS: A total of 320 patients were included, with a median follow-up of 94 months. Five- and 8-year rates were: bPFS 77.1%/66.5%, LRFS 96.1%/90.9%, NRFS 98.3%/97.3%, DMFS 95.9%/93.8%, and OS 91.4%/87.0%. Low-risk patients had significantly better bPFS than intermediate and high-risk (HR12.55, 95%CI:1.74-90.05,p = 0.012), though no significant differences were seen in other outcomes. Subcentimetre pelvic lymph nodes on MR scan were associated with poorer bPFS, LRFS, DMFS, and OS. GS ≥ 8 predicted worse OS. Acute and late ≥ grade 2 GU toxicities occurred in 3.1% and 19.3% of patients, respectively; GI toxicities in 0.8% and 1.5%. QoL scores worsened post-treatment: IPSS + 7 points (p < 0.001), IIEF -9 points (p = 0.043), and FACT-P -3 points (p = 0.02) and returned to baseline. CONCLUSION: Single-fraction 19 Gy HDR brachytherapy was tolerable and provided disease control, though contemporary practice favors active surveillance for most low-risk patients. For higher-risk disease, a single fraction is not equivalent to standard multifraction regimens, indicating its role should remain limited
Are we far from getting it right? Contemporary practices in culturing urine pre-ureteroscopy
No full textInvited Commentary:"free functional gracilis muscle opponensplasty for thenar reconstruction: indications, technique, and long-term outcomes" and reflections on Prof Ninkovic's career and contributions to plastic surgery
No full textGenomic risk model to implement precision prostate cancer screening in clinical care: the ProGRESS study
No full textPrecision healthcare aims to tailor disease prevention and early detection to individual risk. Prostate cancer screening may benefit from genomics-informed approaches. We developed and validated the P-CARE model, a prostate cancer risk prediction tool combining a polygenic score, family history and genetic ancestry, using data from over 585,000 male participants in the Million Veteran Program. The model was externally validated in diverse cohorts and implemented via a blended genome-exome assay for clinical use. Here we show that the P-CARE model identifies clinically meaningful gradients of prostate cancer risk among men, with higher scores associated with increased risk of any, metastatic and fatal prostate cancer. The model is now being used in a clinical trial of precision prostate cancer screening. This work demonstrates the potential for genomics-enabled health systems to improve prostate cancer screening and prevention in men. ClinicalTrials.gov registration: NCT05926102
Spatial-Spectral Deep Learning for Prostate Cancer Tissue Classification in Infrared Spectroscopy
No full textModern methods of infrared (IR) spectroscopy yield full IR absorbance spectra in arrays, forming hyperspectral images. End-to-end processing of these images via deep learning seems ideal for exploiting their high dimensionality and wealth of spatial and spectral information, but recent research suggests that convolution-based architectures may have a spatial bias. Toward the goal of improved prostate cancer tissue classification, we compare a variety of deep learning classifiers for IR spectroscopy and probe the impact of a bottleneck which compresses the spectral dimension. We find a strong correlation between model spatial receptive field and classification performance, with the highest performance achieved by a modified Vision Transformer model. Conversely, we find only limited correlation between spectral information and deep learning model performance: we find that a spectral bottleneck of just 16 features has only a negligible effect on all neural network models, including convolution-eschewing transformer architectures and a multilayer perceptron model utilizing no spatial information. Rather than any particular network component inducing a spatial bias, the breadth of architectures exhibiting little dependence on spectral information implies that tissue classification itself is characterized by only a small set of spectral features. This, in turn, suggests that success at tissue classification may be a poor benchmark in the development of deep learning models designed to effectively utilize the spectral dimension
An ESTRO-EPTN Delphi consensus on robustness evaluation in proton therapy
No full textBackground and purpose: Robustness evaluation (RE) is vital for proton treatment planning, but lacks international consensus or guidelines, with clinics using varied, self-developed methods focused on selected uncertainties. This ESTRO project surveys expert opinions on clinical RE methods to inform future treatment planning system (TPS) development. Materials and methods: A study within the European Particle Therapy Network (EPTN) involved 24 European proton therapy centres, with one radiation oncologist and one medical physicist per centre. The goal was to reach a consensus on transitioning from Planning Target Volume (PTV)-based planning to robustly optimized planning, including uncertainties, methods, and reporting of robustness evaluations. An internal committee drafted 39 statements, reviewed by an independent committee. Following a two-round Delphi procedure, consensus was set at a 75% agreement threshold. Results: Twenty of 24 contacted centers (83.0%) responded to both questionnaire rounds. Consensus was reached on 26 of 39 statements (66.7%), with 5 being high-priority. Strong agreement emerged regarding which uncertainties to include in RE (range, setup, intra-fraction, anatomy changes), methodologies (e.g., for moving targets, combining setup and range), and how to report RE results clinically. Disagreement was found on using the PTV for both planning and dose reporting. The results also offer important implications for TPS vendors and future software development. Conclusions: The ESTRO Delphi consensus may serve as practical guidance on points where a clear consensus was achieved. For remaining points, the development of guidelines is recommended to standardize methodologies and reporting. Furthermore, TPS vendors are encouraged to align their developments with the community's articulated requirements
KRAS p.G12C mutated-targeted treatments in metastatic colorectal cancer: a systematic review and meta-analysis
No full textBackground Colorectal cancer (CRC) is a leading cause of cancer-related mortality worldwide. The presence of the KRAS G12C mutation in patients with CRC is associated with poor responses to standard therapies and worse outcomes. This study systematically reviewed and analyzed the existing evidence on the efficacy of KRAS G12C inhibitors. Methods PubMed, Scopus, and ISI Web of Knowledge were searched, along with conference proceedings, posters, and major oncology journals. Eligibility criteria included clinical trials involving adult patients with KRAS G12C-mutant CRC. Data on treatment outcomes, study design, and patient demographics were extracted and analyzed using a random-effects model, with heterogeneity assessed via I2 statistics. Results Seventeen trials, comprising 663 patients with KRAS G12C-mutant metastatic CRC, were included. Monotherapy with KRAS G12C inhibitors demonstrated an objective response rate of 23%, while combination therapies with agents such as cetuximab and panitumumab showed a higher response rate of 43%. Stable disease rates were also higher in monotherapy (62%) compared to combination therapy (44%). The highest disease control rates were observed with combination therapies (96%). The overall progressive disease rate was lower with combination therapies (1%) than with monotherapies (10%). Conclusions The results indicate that KRAS G12C inhibitors, particularly in combination with other agents, show promising efficacy in treating metastatic CRC. High heterogeneity across studies suggests variability due to small sample sizes and early-phase trial designs. While preliminary data are promising, further large-scale phase III trials are essential to establish these inhibitors as a standard treatment for KRAS G12C-mutant CRC