The Christie School of Oncology: Christie Research Publications Repository
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Frontline treatment of follicular lymphoma: what will it take to change current practice?
No full textFollicular lymphoma is the most common subtype of indolent lymphoma. Despite multiple trials over the past decades showing improved progression-free survival with new first-line therapeutic strategies, such as anti-CD20 maintenance therapy and new glycoengineered anti-CD20 antibodies, no standardized approach has been widely adopted in routine clinical practice. Several factors may explain this, including the increased incidence of infectious adverse events associated with these therapies, particularly during the COVID-19 pandemic, and the lack of overall survival benefit despite long-term follow-up. A consensus has emerged acknowledging the high prognostic variability of follicular lymphoma, which complicates the adoption of a one-size-fits-all first-line treatment strategy. A plethora of prognostic scores (Follicular Lymphoma International Prognostic Index [FLIPI], FLIPI2, PRIMA-Prognostic Index, m7-FLIPI, FLEX [Follicular Lymphoma Evaluation Index], 23-gene score, etc) has been proposed but none can reliably identify the ∼20% of patients who will die within 10 years of first-line immunochemotherapy and for whom a critical medical need remains despite recent therapeutic improvements. Consequently, current prognostic models mainly serve as tools to cross-compare and stratify clinical trials. In this review, we highlight current and future strategies aimed at reshaping frontline treatment paradigms to improve outcomes, including tailored approaches based on risk- or response-adapted designs, development of new predictive, rather than prognostic, tools, approaches to reduce adverse events to enhance health-related quality of life, and the potential use of T-cell-engaging therapies to improve survival in the highest risk patients
Somatic evolution following cancer treatment in normal tissue
No full textThe extent to which exogenous sources, including cancer treatment, contribute to somatic evolution in normal tissue remains unclear. Here we used high-depth duplex sequencing1 (more than 30,000x coverage) to analyse 168 cancer-free samples representing 16 organs from 22 patients with metastatic cancer enroled in the PEACE research autopsy study. In every sample, we identified somatic mutations (range 305-2,854 mutations) at low variant allele frequencies (median 0.0000323). We extracted 16 distinct single-base substitution mutational signatures, reflecting processes that have moulded the genomes of normal cells. We identified alcohol-induced mutation acquisition in liver, smoking-induced mutagenesis in lung and cardiac tissue, and multiple treatment-induced processes, which correlated with therapy type and duration. Exogenous sources, including treatment, underpinned, on average, more than 40% of mutations in liver but less than 10% of mutations in brain samples. Finally, we observed tissue-specific selection, with positive selection in tissues such as lung (PTEN and PIK3CA), liver (NF2L2) and spleen (BRAF and NOTCH2), and limited selection in others, such as brain and cardiac tissue. More than 25% of driver mutations in normal tissue exposed to systemic anti-cancer therapy, including in TP53, could be attributed to treatment. Immunotherapy, although not associated with increased mutagenesis, was linked to driver mutations in PPM1D and TP53, illustrating how non-mutagenic treatment can sculpt somatic evolution. Our study reveals the rich tapestry of mutational processes and driver mutations in normal tissue, and the profound effect of lifetime exposures, including cancer treatment, on somatic evolution
Prophylactic pelvic nodal radiation therapy in high-risk node-negative prostate cancer: the case against
No full textGenomic landscape of diffuse glioma revealed by whole genome sequencing
No full textDiffuse gliomas are the commonest malignant primary brain tumour in adults. Herein, we present analysis of the genomic landscape of adult glioma, by whole genome sequencing of 403 tumours (256 glioblastoma, 89 astrocytoma, 58 oligodendroglioma; 338 primary, 65 recurrence). We identify an extended catalogue of recurrent coding and non-coding genetic mutations that represents a source for future studies and provides a high-resolution map of structural variants, copy number changes and global genome features including telomere length, mutational signatures and extrachromosomal DNA. Finally, we relate these to clinical outcome. As well as identifying drug targets for treatment of glioma our findings offer the prospect of improving treatment allocation with established targeted therapies
Olaparib Monotherapy or in Combination with Abiraterone for the Treatment of Patients with Metastatic Castration-Resistant Prostate Cancer (mCRPC) and a BRCA Mutation
No full textTreatment strategies to improve outcomes in patients with metastatic castration-resistant prostate cancer (mCRPC) are evolving. Of particular interest are therapies that target DNA damage responses in tumor cells by inhibiting poly(ADP-ribose) polymerase (PARP) activity. Several PARP inhibitors have recently received regulatory approval for the treatment of patients with mCRPC, of which olaparib was the first for prostate cancer. Olaparib received approval as a monotherapy following the PROfound study (NCT02987543) and in combination with abiraterone following the PROpel study (NCT03732820) for mCRPC. Both PROfound (homologous recombination repair mutation biomarker-selected) and PROpel (biomarker unselected) patients demonstrated statistically significant longer radiographic progression-free survival (rPFS) with olaparib versus their respective control arms in the intention-to-treat population. In both studies, the greatest clinical benefit with olaparib was seen in patients with BRCA1 and/or BRCA2 mutations (BRCAm): PROfound rPFS hazard ratio (HR) 0.22 (95% confidence interval [CI] 0.15-0.32); PROpel rPFS HR 0.23 (95% CI 0.12-0.43). Clinical benefit was also observed in terms of overall survival: PROfound HR 0.63 (95% CI 0.42-0.95); PROpel HR 0.29 (95% CI 0.14-0.56). We provide a comprehensive overview of the utility of olaparib for patients with mCRPC harboring a BRCAm. Key clinical and safety data in BRCAm subgroup populations are discussed, predominantly based on findings from PROfound and PROpel, as well as investigator-initiated studies, to help inform treatment decision-making in this patient population. We also discuss the importance of genetic testing to identify patients who may optimally benefit from treatment with olaparib, either as a monotherapy or in combination with abiraterone
Managing patients with head and neck cancer and advanced age or comorbidities
No full textThe dominant treatment paradigm for locoregionally advanced head and neck squamous cell carcinoma (HNSCC) involves postoperative or definitive radiotherapy with concurrent cisplatin chemotherapy. Despite years of research investigating de-intensified treatment, cisplatin-based chemoradiotherapy remains the standard, yet it is associated with significant acute and chronic toxicity. However, due to shared risk factors, such as advanced age, and tobacco and alcohol use, patients with HNSCC frequently have comorbid illnesses that impact treatment tolerability, adding complexity to treatment-related decision-making. In addition, many patients have medical contraindications to cisplatin, requiring alternative treatment strategies. It is thus important to consider how well patients are likely to tolerate treatment, and how to adapt treatment in response to a patient's condition, when weighing treatment options. In this review, we aim to offer readers guidance in managing the elderly or comorbid patient with HNSCC, with particular attention to (i) approaching comorbidity and fragility assessment to make determinations on intensity of treatment, (ii) considering primary treatment modality (eg, surgery vs radiotherapy, chemo-radiotherapy vs radiotherapy alone) and (iii) choice of concurrent systemic therapy agent
External validation of the early-stage classic Hodgkin lymphoma (cHL) international prognostication index (E-HIPI) in the german Hodgkin study group (GHSG) unfavorable clinical trials
No full textDefinition of resectable stage III non-small cell lung cancer (NSCLC) for inclusion in clinical trials: a clinical case review by a pan-European multidisciplinary expert panel led by the EORTC lung cancer group
No full textINTRODUCTION: Stage III non-small cell lung cancer (NSCLC) is a heterogeneous disease, leading to ambiguity in resectability criteria. This has prompted the EORTC Lung Cancer Group to establish a standardized definition of resectability for clinical trials. A Delphi consensus process was initiated, including a systematic review, survey, and clinical cases review. Here, we report exclusively the results of the clinical cases review, aimed to categorize cases based on tumor and lymph node factors, to identify those deemed surgically resectable upfront. METHODS: Consecutive patients with clinical stage III NSCLC (8th TNM edition) treated at Institut Jules Bordet between 2016-2021 were identified. These cases underwent evaluation by multidisciplinary panels (MDT), comprising thoracic surgeons, radiation oncologists, medical oncologists/pulmonologists and imaging specialists. The MDT determined the resectability of each tumor, and non-consensual cases underwent a second and a third discussion rounds. A TNM-subset was classified as 'resectable' if ≥75 % of cases within that category were deemed 'resectable' following multiple rounds of review. RESULTS: Among 105 cases, 52 % of tumors were stage IIIA, 36 % stage IIIB and 11 % stage IIIC. After the first two review rounds, 13 % of cases were classified as 'no consensus' and moved to a third round. The main reasons were suboptimal imaging (n = 8), incomplete invasive mediastinal staging to assess the N factor (n = 3), and disagreement on the resectability of T4 tumors invading thoracic structures or with multi-station/bulky N2 disease (n = 3). After the third review round, T3-T4 tumors based on size/satellite nodules and/or with N1-N2 single-station involvement were considered resectable. In contrast, many invasive T4-tumors were considered unresectable, especially if combined with N2-N3 disease. N2-multi-station, N2-bulky or N3 involvement were generally considered unresectable (100 %/95 %/95 % respectively). CONCLUSIONS: After a multiple-round multidisciplinary review of real-world cases, consensus was reached for most TNM-subsets, except for invasive T4N0 tumors. This case review informed the Consensual Definition of Resectable stage III NSCLC in clinical trials
Spatial transcriptomics of the tumor microenvironment discriminates inflamed tumors responsive or resistant to atezolizumab plus bevacizumab in patients with advanced HCC
No full textThe suitability of radiomics extracted from 4DCT motion-compensated reconstruction
No full textPURPOSE: The most appropriate 4DCT image for radiomics analysis remains uncertain, with options including individual respiratory phases and motion-compensated (MC) reconstructions. This study compares radiomic features derived from MC reconstructions and patient-specific, 4D phases, evaluating their influence on feature selection, robustness to registration algorithms and implications for radiomics analysis. METHODS: This study included 223 NSCLC patients. MC reconstructions (MC(mean) and MC(median)) were generated using three different registration algorithms and compared to a patient-specific optimal 4D phase (TOp), defined as the phase where radiomic feature values exhibited the smallest variability. Ninety-three features, extracted from the tumor region, underwent unsupervised selection to assess how image type influenced feature selection and redundancy. The impact of image type on distant failure prediction was evaluated using bootstrapped univariable Cox regression (p < 0.05) and multivariable modeling. Model performance was assessed across 500 bootstrap resamples, with feature selection frequency, concordance index (CI), and Akaike Information Criterion (AIC) recorded. RESULTS: Over 60% of selected features differed between 4D phases and MC reconstructions, indicating image type influences feature selection. The proportion of remaining features varied: 11.8% (TOp), 15.1% (MC(mean)), and 12.9% (MC(median)). The single-phase model, TOp, achieved a CI of 0.72 [0.64-0.77] and an AIC of 267.53, but did not demonstrate clear superiority over MC-based models. Both MC(median) and TOp showed modest improvements over the clinical model, suggesting both image types offer comparable prognostic potential. MC reconstructions were largely robust across registration algorithms, but MC(mean) and MC(median) reconstructions should not be used interchangeably. CONCLUSION: This study highlights differences in radiomic feature selection and predictive performance between MC reconstructions and individual 4DCT phases. MC reconstructions were a viable alternative, demonstrating robustness across registration algorithms. Both approaches can be integrated into radiomics pipelines, but image type selection should be carefully considered