Centre for Cancer Research - Research Publications
Permanent URI for this collection
Search Results
1 - 10 of 12
-
ItemNo Preview AvailableThe landscape of cell-free mitochondrial DNA in liquid biopsy for cancer detection(BMC, 2023-10-12)BACKGROUND: Existing methods to detect tumor signal in liquid biopsy have focused on the analysis of nuclear cell-free DNA (cfDNA). However, non-nuclear cfDNA and in particular mitochondrial DNA (mtDNA) has been understudied. We hypothesize that an increase in mtDNA in plasma could reflect the presence of cancer, and that leveraging cell-free mtDNA could enhance cancer detection. RESULTS: We survey 203 healthy and 664 cancer plasma samples from three collection centers covering 12 cancer types with whole genome sequencing to catalogue the plasma mtDNA fraction. The mtDNA fraction is increased in individuals with cholangiocarcinoma, colorectal, liver, pancreatic, or prostate cancer, in comparison to that in healthy individuals. We detect almost no increase of mtDNA fraction in individuals with other cancer types. The mtDNA fraction in plasma correlates with the cfDNA tumor fraction as determined by somatic mutations and/or copy number aberrations. However, the mtDNA fraction is also elevated in a fraction of patients without an apparent increase in tumor-derived cfDNA. A predictive model integrating mtDNA and copy number analysis increases the area under the curve (AUC) from 0.73 when using copy number alterations alone to an AUC of 0.81. CONCLUSIONS: The mtDNA signal retrieved by whole genome sequencing has the potential to boost the detection of cancer when combined with other tumor-derived signals in liquid biopsies.
-
ItemDenosumab and invasive cervical root resorption: a case report(WILEY, 2022-06)
-
ItemNo Preview AvailableAlpelisib Monotherapy for PI3K-Altered, Pretreated Advanced Breast Cancer: A Phase II Study(AMER ASSOC CANCER RESEARCH, 2022-09-02)UNLABELLED: There is limited knowledge on the benefit of the α-subunit-specific PI3K inhibitor alpelisib in later lines of therapy for advanced estrogen receptor-positive (ER+) HER2- and triple-negative breast cancer (TNBC). We conducted a phase II multicohort study of alpelisib monotherapy in patients with advanced PI3K pathway mutant ER+HER2- and TNBC. In the intention-to-treat ER+ cohort, the overall response rate was 30% and the clinical benefit rate was 36%. A decline in PI3K pathway mutant circulating tumor DNA (ctDNA) levels from baseline to week 8 while on therapy was significantly associated with a partial response, clinical benefit, and improved progression-free-survival [HR 0.24; 95% confidence interval (CI), 0.083-0.67, P = 0.0065]. Detection of ESR1 mutations at baseline in plasma was also associated with clinical benefit and improved progression-free survival (HR 0.22; 95% CI, 0.078-0.60, P = 0.003). SIGNIFICANCE: Alpelisib monotherapy displayed efficacy in heavily pretreated ER+ breast cancer with PIK3CA mutations. PIK3CA mutation dynamics in plasma during treatment and ESR1 mutations detected in plasma at baseline were candidate biomarkers predictive of benefit from alpelisib, highlighting the utility of ctDNA assays in this setting. This article is highlighted in the In This Issue feature, p. 2007.
-
ItemClinical validation and implementation of droplet digital PCR for the detection of BRAF mutations from cell-free DNA(ELSEVIER, 2022-10)Droplet digital PCR (ddPCR) has been demonstrated in many research studies to be a sensitive method in the analysis of circulating tumour DNA (ctDNA) for identifying mutations and tracking disease. The transition of ddPCR into the diagnostic setting requires a number of critical steps including the assessment of accuracy and precision and ultimately implementation into clinical use. Here we present the clinical validation of ddPCR for the detection of BRAF mutations (V600E and V600K) from plasma. We describe the performance characteristics assessed including the limit of blank, limit of detection, ruggedness, accuracy, precision and the effect of the matrix. Overall, each assay could achieve a limit of detection of 0.5% variant allele fraction and was highly accurate, with 100% concordance of results obtained from routine diagnostic testing of formalin fixed tumour samples or reference controls (n=36 for BRAF V600E and n=30 for BRAF V600K). Inter-laboratory reproducibility across 12 plasma samples for each assay was also assessed and results were 100% concordant. Overall, we report the successful validation and translation of a ddPCR assay into clinical routine practice.
-
ItemNo Preview AvailableInhibition of the CtBP complex and FBXO11 enhances MHC class II expression and anti-cancer immune responses(CELL PRESS, 2022-10-10)There is increasing recognition of the prognostic significance of tumor cell major histocompatibility complex (MHC) class II expression in anti-cancer immunity. Relapse of acute myeloid leukemia (AML) following allogeneic stem cell transplantation (alloSCT) has recently been linked to MHC class II silencing in leukemic blasts; however, the regulation of MHC class II expression remains incompletely understood. Utilizing unbiased CRISPR-Cas9 screens, we identify that the C-terminal binding protein (CtBP) complex transcriptionally represses MHC class II pathway genes, while the E3 ubiquitin ligase complex component FBXO11 mediates degradation of CIITA, the principal transcription factor regulating MHC class II expression. Targeting these repressive mechanisms selectively induces MHC class II upregulation across a range of AML cell lines. Functionally, MHC class II+ leukemic blasts stimulate antigen-dependent CD4+ T cell activation and potent anti-tumor immune responses, providing fundamental insights into the graft-versus-leukemia effect. These findings establish the rationale for therapeutic strategies aimed at restoring tumor-specific MHC class II expression to salvage AML relapse post-alloSCT and also potentially to enhance immunotherapy outcomes in non-myeloid malignancies.
-
ItemTargeting Menin disrupts the KMT2A/B and polycomb balance to paradoxically activate bivalent genes(NATURE PORTFOLIO, 2023-02)Precise control of activating H3K4me3 and repressive H3K27me3 histone modifications at bivalent promoters is essential for normal development and frequently corrupted in cancer. By coupling a cell surface readout of bivalent MHC class I gene expression with whole-genome CRISPR-Cas9 screens, we identify specific roles for MTF2-PRC2.1, PCGF1-PRC1.1 and Menin-KMT2A/B complexes in maintaining bivalency. Genetic loss or pharmacological inhibition of Menin unexpectedly phenocopies the effects of polycomb disruption, resulting in derepression of bivalent genes in both cancer cells and pluripotent stem cells. While Menin and KMT2A/B contribute to H3K4me3 at active genes, a separate Menin-independent function of KMT2A/B maintains H3K4me3 and opposes polycomb-mediated repression at bivalent genes. Release of KMT2A from active genes following Menin targeting alters the balance of polycomb and KMT2A at bivalent genes, facilitating gene activation. This functional partitioning of Menin-KMT2A/B complex components reveals therapeutic opportunities that can be leveraged through inhibition of Menin.
-
Item
-
ItemPotential Clinical Utility of a Targeted Circulating Tumor DNA Assay in Esophageal Adenocarcinoma(LIPPINCOTT WILLIAMS & WILKINS, 2022-08)OBJECTIVE: To explore the clinical utility of circulating tumor DNA (ctDNA) in esophageal adenocarcinoma (EAC) by developing a cost-effective and rapid technique utilising targeted amplicon sequencing. SUMMARY OF BACKGROUND DATA: Emerging evidence suggests that levels of ctDNA in the blood can be used to monitor treatment response and in the detection of disease recurrence in various cancer types. Current staging modalities for EAC such as computerised tomography of the chest/abdomen/pelvis (CT) and positron emission tomography (PET) do not reliably detect occult micro-metastatic disease, the presence of which signifies a poor prognosis. After curative-intent treatment, some patients are still at high risk of recurrent disease, and there is no widely accepted optimal surveillance tool for patients with EAC. METHODS: Sixty-two patients with EAC were investigated for the presence of ctDNA using a tumor-informed approach. We designed a custom targeted amplicon sequencing panel of target specific primers covering mutational foci in 9 of the most commonly mutated genes in EAC. Serial blood samples were taken before and after neoadjuvant treatment (NAT), and during surveillance. RESULTS: Somatic mutations were detected in pre-treatment biopsy samples of 55 out of 62 (89%) EAC patients. Mutations in TP53 (80%) were the most common. Out of these 55 patients, 20 (36%) had detectable ctDNA at baseline. The majority (90%) of patients with detectable ctDNA had either locally advanced tumors, nodal involvement or metastatic disease. In patients with locally advanced tumors, disease free survival (DFS) was more accurately stratified using pre-treatment ctDNA status [HR 4.34 (95% CI 0.93-20.21); P = 0.05] compared to nodal status on PET-CT. In an exploratory subgroup analysis, patients who are node negative but ctDNA positive have inferior DFS [HR 11.71 (95% CI 1.16-118.80) P = 0.04]. In blood samples taken before and following NAT, clearance of ctDNA after NAT was associated with a favourable response to treatment. Furthermore, patients who are ctDNA positive during post-treatment surveillance are at high risk of relapse. CONCLUSIONS: Our study shows that ctDNA has potential to provide additional prognostication over conventional staging investigation such as CT and PET. It may also have clinical utility in the assessment of response to NAT and as a biomarker for the surveillance of recurrent disease.
-
ItemModeling the Prognostic Impact of Circulating Tumor Cells Enumeration in Metastatic Breast Cancer for Clinical Trial Design Simulation(OXFORD UNIV PRESS, 2022-07-05)Despite the strong prognostic stratification of circulating tumor cells (CTCs) enumeration in metastatic breast cancer (MBC), current clinical trials usually do not include a baseline CTCs in their design. This study aimed to generate a classifier for CTCs prognostic simulation in existing datasets for hypothesis generation in patients with MBC. A K-nearest neighbor machine learning algorithm was trained on a pooled dataset comprising 2436 individual MBC patients from the European Pooled Analysis Consortium and the MD Anderson Cancer Center to identify patients likely to have CTCs ≥ 5/7 mL blood (StageIVaggressive vs StageIVindolent). The model had a 65.1% accuracy and its prognostic impact resulted in a hazard ratio (HR) of 1.89 (Simulatedaggressive vs SimulatedindolentP < .001), similar to patients with actual CTCs enumeration (HR 2.76; P < .001). The classifier's performance was then tested on an independent retrospective database comprising 446 consecutive hormone receptor (HR)-positive HER2-negative MBC patients. The model further stratified clinical subgroups usually considered prognostically homogeneous such as patients with bone-only or liver metastases. Bone-only disease classified as Simulatedaggressive had a significantly worse overall survival (OS; P < .0001), while patients with liver metastases classified as Simulatedindolent had a significantly better prognosis (P < .0001). Consistent results were observed for patients who had undergone CTCs enumeration in the pooled population. The differential prognostic impact of endocrine- (ET) and chemotherapy (CT) was explored across the simulated subgroups. No significant differences were observed between ET and CT in the overall population, both in terms of progression-free survival (PFS) and OS. In contrast, a statistically significant difference, favoring CT over ET was observed among Simulatedaggressive patients (HR: 0.62; P = .030 and HR: 0.60; P = .037, respectively, for PFS and OS).
-
ItemMulti-omic machine learning predictor of breast cancer therapy response(NATURE PORTFOLIO, 2022-01-27)Breast cancers are complex ecosystems of malignant cells and the tumour microenvironment1. The composition of these tumour ecosystems and interactions within them contribute to responses to cytotoxic therapy2. Efforts to build response predictors have not incorporated this knowledge. We collected clinical, digital pathology, genomic and transcriptomic profiles of pre-treatment biopsies of breast tumours from 168 patients treated with chemotherapy with or without HER2 (encoded by ERBB2)-targeted therapy before surgery. Pathology end points (complete response or residual disease) at surgery3 were then correlated with multi-omic features in these diagnostic biopsies. Here we show that response to treatment is modulated by the pre-treated tumour ecosystem, and its multi-omics landscape can be integrated in predictive models using machine learning. The degree of residual disease following therapy is monotonically associated with pre-therapy features, including tumour mutational and copy number landscapes, tumour proliferation, immune infiltration and T cell dysfunction and exclusion. Combining these features into a multi-omic machine learning model predicted a pathological complete response in an external validation cohort (75 patients) with an area under the curve of 0.87. In conclusion, response to therapy is determined by the baseline characteristics of the totality of the tumour ecosystem captured through data integration and machine learning. This approach could be used to develop predictors for other cancers.