Characteristics, origin, and potential for cancer diagnostics of ultrashort plasma cell-free DNA.

Current evidence suggests that plasma cell-free DNA (cfDNA) is fragmented around a mode of 166 bp. Data supporting this view has been mainly acquired through the analysis of double-stranded cfDNA. The characteristics and diagnostic potential of single-stranded and damaged double-stranded cfDNA in healthy individuals and cancer patients remain unclear. Here, through a combination of high-affinity magnetic bead-based DNA extraction and single-stranded DNA sequencing library preparation (MB-ssDNA), we report the discovery of a large proportion of cfDNA fragments centered at ∼50 bp. We show that these "ultrashort" cfDNA fragments have a greater relative abundance in plasma of healthy individuals (median = 19.1% of all sequenced cfDNA fragments, n = 28) than in plasma of patients with cancer (median = 14.2%, n = 21, P < 0.0001). The ultrashort cfDNA fragments map to accessible chromatin regions of blood cells, particularly in promoter regions with the potential to adopt G-quadruplex (G4) DNA secondary structures. G4-positive promoter chromatin accessibility is significantly enriched in ultrashort plasma cfDNA fragments from healthy individuals relative to patients with cancers (P < 0.0001), in whom G4-cfDNA enrichment is inversely associated with copy number aberration-inferred tumor fractions. Our findings redraw the landscape of cfDNA fragmentation by identifying and characterizing a novel population of ultrashort plasma cfDNA fragments. Sequencing of MB-ssDNA libraries could facilitate the characterization of gene regulatory regions and DNA secondary structures via liquid biopsy. Our data underline the diagnostic potential of ultrashort cfDNA through classification for cancer patients.

Symptom-triggered testing detects early stage and low volume resectable advanced stage ovarian cancer.

OBJECTIVE: Symptom-triggered testing for ovarian cancer was introduced to the UK whereby symptomatic women undergo an ultrasound scan and serum CA125, and are referred to hospital within 2 weeks if these are abnormal. The potential value of symptom-triggered testing in the detection of early-stage disease or low tumor burden remains unclear in women with high grade serous ovarian cancer. In this descriptive study, we report on the International Federation of Gynecology and Obstetrics (FIGO) stage, disease distribution, and complete cytoreduction rates in women presenting via the fast-track pathway and who were diagnosed with high grade serous ovarian cancer. METHODS: We analyzed the dataset from Refining Ovarian Cancer Test accuracy Scores (ROCkeTS), a single-arm prospective diagnostic test accuracy study recruiting from 24 hospitals in the UK. The aim of ROCkeTS is to validate risk prediction models in symptomatic women. We undertook an opportunistic analysis for women recruited between June 2015 to July 2022 and who were diagnosed with high grade serous ovarian cancer via the fast-track pathway. Women presenting with symptoms suspicious for ovarian cancer receive a CA125 blood test and an ultrasound scan if the CA125 level is abnormal. If either of these is abnormal, women are referred to secondary care within 2 weeks. Histology details were available on all women who underwent surgery or biopsy within 3 months of recruitment. Women who did not undergo surgery or biopsy at 3 months were followed up for 12 months as per the national guidelines in the UK. In this descriptive study, we report on patient demographics (age and menopausal status), WHO performance status, FIGO stage at diagnosis, disease distribution (low/pelvic confined, moderate/extending to mid-abdomen, high/extending to upper abdomen) and complete cytoreduction rates in women who underwent surgery. RESULTS: Of 1741 participants recruited via the fast-track pathway, 119 (6.8%) were diagnosed with high grade serous ovarian cancer. The median age was 63 years (range 32-89). Of these, 112 (94.1%) patients had a performance status of 0 and 1, 30 (25.2%) were diagnosed with stages I/II, and the disease distribution was low-to-moderate in 77 (64.7%). Complete and optimal cytoreduction were achieved in 73 (61.3%) and 18 (15.1%). The extent of disease was low in 43 of 119 (36.1%), moderate in 34 of 119 (28.6%), high in 32 of 119 (26.9%), and not available in 10 of 119 (8.4%). Nearly two thirds, that is 78 of 119 (65.5%) women with high grade serous ovarian cancer, underwent primary debulking surgery, 36 of 119 (30.3%) received neoadjuvant chemotherapy followed by interval debulking surgery, and 5 of 119 (4.2%) women did not undergo surgery. CONCLUSION: Our results demonstrate that one in four women identified with high grade serous ovarian cancer through the fast-track pathway following symptom-triggered testing was diagnosed with early-stage disease. Symptom-triggered testing may help identify women with a low disease burden, potentially contributing to high complete cytoreduction rates.

CXCR4 inhibition in human pancreatic and colorectal cancers induces an integrated immune response.

Inhibition of the chemokine receptor CXCR4 in combination with blockade of the PD-1/PD-L1 T cell checkpoint induces T cell infiltration and anticancer responses in murine and human pancreatic cancer. Here we elucidate the mechanism by which CXCR4 inhibition affects the tumor immune microenvironment. In human immune cell-based chemotaxis assays, we find that CXCL12-stimulated CXCR4 inhibits the directed migration mediated by CXCR1, CXCR3, CXCR5, CXCR6, and CCR2, respectively, chemokine receptors expressed by all of the immune cell types that participate in an integrated immune response. Inhibiting CXCR4 in an experimental cancer medicine study by 1-wk continuous infusion of the small-molecule inhibitor AMD3100 (plerixafor) induces an integrated immune response that is detected by transcriptional analysis of paired biopsies of metastases from patients with microsatellite stable colorectal and pancreatic cancer. This integrated immune response occurs in three other examples of immune-mediated damage to noninfected tissues: Rejecting renal allografts, melanomas clinically responding to anti-PD1 antibody therapy, and microsatellite instable colorectal cancers. Thus, signaling by CXCR4 causes immune suppression in human pancreatic ductal adenocarcinoma and colorectal cancer by impairing the function of the chemokine receptors that mediate the intratumoral accumulation of immune cells.

Comparison of two targeted ultra-deep sequencing technologies for analysis of plasma circulating tumour DNA in endocrine-therapy-resistant breast cancer patients.

PURPOSE: There is growing interest in the application of circulating tumour DNA (ctDNA) as a sensitive tool for monitoring tumour evolution and guiding targeted therapy in patients with cancer. However, robust comparisons of different platform technologies are still required. Here we compared the InVisionSeq™ ctDNA Assay with the Oncomine™ Breast cfDNA Assay to assess their concordance and feasibility for the detection of mutations in plasma at low (< 0.5%) variant allele fraction (VAF). METHODS: Ninety-six plasma samples from 50 patients with estrogen receptor (ER)-positive metastatic breast cancer (mBC) were profiled using the InVision Assay. Results were compared to the Oncomine assay in 30 samples from 26 patients, where there was sufficient material and variants were covered by both assays. Longitudinal samples were analysed for 8 patients with endocrine resistance. RESULTS: We detected alterations in 59/96 samples from 34/50 patients analysed with the InVision assay, most frequently affecting ESR1, PIK3CA and TP53. Complete or partial concordance was found in 28/30 samples analysed by both assays, and VAF values were highly correlated. Excellent concordance was found for most genes, and most discordant calls occurred at VAF < 1%. In longitudinal samples from progressing patients with endocrine resistance, we detected consistent alterations in sequential samples, most commonly in ESR1 and PIK3CA. CONCLUSION: This study shows that both ultra-deep next-generation sequencing (NGS) technologies can detect genomic alternations even at low VAFs in plasma samples of mBC patients. The strong agreement of the technologies indicates sufficient reproducibility for clinical use as prognosic and predictive biomarker.

Detection of ctDNA from Dried Blood Spots after DNA Size Selection.

BACKGROUND: Recent advances in the study and clinical applications of circulating tumor DNA (ctDNA) are limited by practical considerations of sample collection. Whole-genome sequencing (WGS) is increasingly used for analysis of ctDNA, identifying copy-number alterations and fragmentation patterns. We hypothesized that low-depth/shallow WGS (sWGS) data may be generated from minute amounts of cell-free DNA, and that fragment-size selection may remove contaminating genomic DNA from small blood volumes. Dried blood spots have practical advantages for sample collection, may facilitate serial sampling, and could support novel study designs in humans and animal models. METHODS: We developed a protocol for the isolation and analysis of cell-free DNA from dried blood spots using filter paper cards and bead-based size selection. DNA extracted and size-selected from dried spots was analyzed using sWGS and polymerase chain reaction (PCR). RESULTS: Analyzing a 50 µL dried blood spot from frozen whole blood of a patient with melanoma, we identified ctDNA based on the presence of tumor-specific somatic copy-number alterations, and found a fragment-size profile similar to that observed in plasma DNA. We found alterations in different chromosomes in blood spots from 2 patients with high-grade serous ovarian carcinoma. Extending this approach to serial dried blood spots from mouse xenograft models, we detect tumor-derived cell-free DNA and identified ctDNA from the originally grafted ascites. CONCLUSION: Our data suggest that ctDNA can be detected and monitored in dried blood spots from archived and fresh blood samples, enabling new approaches for sample collection and novel study/trial designs for both patients and in vivo models.

Non-invasive analysis of acquired resistance to cancer therapy by sequencing of plasma DNA.

Cancers acquire resistance to systemic treatment as a result of clonal evolution and selection. Repeat biopsies to study genomic evolution as a result of therapy are difficult, invasive and may be confounded by intra-tumour heterogeneity. Recent studies have shown that genomic alterations in solid cancers can be characterized by massively parallel sequencing of circulating cell-free tumour DNA released from cancer cells into plasma, representing a non-invasive liquid biopsy. Here we report sequencing of cancer exomes in serial plasma samples to track genomic evolution of metastatic cancers in response to therapy. Six patients with advanced breast, ovarian and lung cancers were followed over 1-2 years. For each case, exome sequencing was performed on 2-5 plasma samples (19 in total) spanning multiple courses of treatment, at selected time points when the allele fraction of tumour mutations in plasma was high, allowing improved sensitivity. For two cases, synchronous biopsies were also analysed, confirming genome-wide representation of the tumour genome in plasma. Quantification of allele fractions in plasma identified increased representation of mutant alleles in association with emergence of therapy resistance. These included an activating mutation in PIK3CA (phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit alpha) following treatment with paclitaxel; a truncating mutation in RB1 (retinoblastoma 1) following treatment with cisplatin; a truncating mutation in MED1 (mediator complex subunit 1) following treatment with tamoxifen and trastuzumab, and following subsequent treatment with lapatinib, a splicing mutation in GAS6 (growth arrest-specific 6) in the same patient; and a resistance-conferring mutation in EGFR (epidermal growth factor receptor; T790M) following treatment with gefitinib. These results establish proof of principle that exome-wide analysis of circulating tumour DNA could complement current invasive biopsy approaches to identify mutations associated with acquired drug resistance in advanced cancers. Serial analysis of cancer genomes in plasma constitutes a new paradigm for the study of clonal evolution in human cancers.

Exploratory Analysis of TP53 Mutations in Circulating Tumour DNA as Biomarkers of Treatment Response for Patients with Relapsed High-Grade Serous Ovarian Carcinoma: A Retrospective Study.

BACKGROUND: Circulating tumour DNA (ctDNA) carrying tumour-specific sequence alterations may provide a minimally invasive means to dynamically assess tumour burden and response to treatment in cancer patients. Somatic TP53 mutations are a defining feature of high-grade serous ovarian carcinoma (HGSOC). We tested whether these mutations could be used as personalised markers to monitor tumour burden and early changes as a predictor of response and time to progression (TTP). METHODS AND FINDINGS: We performed a retrospective analysis of serial plasma samples collected during routine clinical visits from 40 patients with HGSOC undergoing heterogeneous standard of care treatment. Patient-specific TP53 assays were developed for 31 unique mutations identified in formalin-fixed paraffin-embedded tumour DNA from these patients. These assays were used to quantify ctDNA in 318 plasma samples using microfluidic digital PCR. The TP53 mutant allele fraction (TP53MAF) was compared to serum CA-125, the current gold-standard response marker for HGSOC in blood, as well as to disease volume on computed tomography scans by volumetric analysis. Changes after one cycle of treatment were compared with TTP. The median TP53MAF prior to treatment in 51 relapsed treatment courses was 8% (interquartile range [IQR] 1.2%-22%) compared to 0.7% (IQR 0.3%-2.0%) for seven untreated newly diagnosed stage IIIC/IV patients. TP53MAF correlated with volumetric measurements (Pearson r = 0.59, p < 0.001), and this correlation improved when patients with ascites were excluded (r = 0.82). The ratio of TP53MAF to volume of disease was higher in relapsed patients (0.04% per cm3) than in untreated patients (0.0008% per cm3, p = 0.004). In nearly all relapsed patients with disease volume > 32 cm3, ctDNA was detected at ≥20 amplifiable copies per millilitre of plasma. In 49 treatment courses for relapsed disease, pre-treatment TP53MAF concentration, but not CA-125, was associated with TTP. Response to chemotherapy was seen earlier with ctDNA, with a median time to nadir of 37 d (IQR 28-54) compared with a median time to nadir of 84 d (IQR 42-116) for CA-125. In 32 relapsed treatment courses evaluable for response after one cycle of chemotherapy, a decrease in TP53MAF of >60% was an independent predictor of TTP in multivariable analysis (hazard ratio 0.22, 95% CI 0.07-0.67, p = 0.008). Conversely, a decrease in TP53MAF of ≤60% was associated with poor response and identified cases with TTP < 6 mo with 71% sensitivity (95% CI 42%-92%) and 88% specificity (95% CI 64%-99%). Specificity was improved when patients with recent drainage of ascites were excluded. Ascites drainage led to a reduction of TP53MAF concentration. The limitations of this study include retrospective design, small sample size, and heterogeneity of treatment within the cohort. CONCLUSIONS: In this retrospective study, we demonstrated that ctDNA is correlated with volume of disease at the start of treatment in women with HGSOC and that a decrease of ≤60% in TP53MAF after one cycle of chemotherapy was associated with shorter TTP. These results provide evidence that ctDNA has the potential to be a highly specific early molecular response marker in HGSOC and warrants further investigation in larger cohorts receiving uniform treatment.

Analysis of circulating tumor DNA to monitor metastatic breast cancer.

BACKGROUND: The management of metastatic breast cancer requires monitoring of the tumor burden to determine the response to treatment, and improved biomarkers are needed. Biomarkers such as cancer antigen 15-3 (CA 15-3) and circulating tumor cells have been widely studied. However, circulating cell-free DNA carrying tumor-specific alterations (circulating tumor DNA) has not been extensively investigated or compared with other circulating biomarkers in breast cancer. METHODS: We compared the radiographic imaging of tumors with the assay of circulating tumor DNA, CA 15-3, and circulating tumor cells in 30 women with metastatic breast cancer who were receiving systemic therapy. We used targeted or whole-genome sequencing to identify somatic genomic alterations and designed personalized assays to quantify circulating tumor DNA in serially collected plasma specimens. CA 15-3 levels and numbers of circulating tumor cells were measured at identical time points. RESULTS: Circulating tumor DNA was successfully detected in 29 of the 30 women (97%) in whom somatic genomic alterations were identified; CA 15-3 and circulating tumor cells were detected in 21 of 27 women (78%) and 26 of 30 women (87%), respectively. Circulating tumor DNA levels showed a greater dynamic range, and greater correlation with changes in tumor burden, than did CA 15-3 or circulating tumor cells. Among the measures tested, circulating tumor DNA provided the earliest measure of treatment response in 10 of 19 women (53%). CONCLUSIONS: This proof-of-concept analysis showed that circulating tumor DNA is an informative, inherently specific, and highly sensitive biomarker of metastatic breast cancer. (Funded by Cancer Research UK and others.).

Spatial and temporal heterogeneity in high-grade serous ovarian cancer: a phylogenetic analysis.

BACKGROUND: The major clinical challenge in the treatment of high-grade serous ovarian cancer (HGSOC) is the development of progressive resistance to platinum-based chemotherapy. The objective of this study was to determine whether intra-tumour genetic heterogeneity resulting from clonal evolution and the emergence of subclonal tumour populations in HGSOC was associated with the development of resistant disease. METHODS AND FINDINGS: Evolutionary inference and phylogenetic quantification of heterogeneity was performed using the MEDICC algorithm on high-resolution whole genome copy number profiles and selected genome-wide sequencing of 135 spatially and temporally separated samples from 14 patients with HGSOC who received platinum-based chemotherapy. Samples were obtained from the clinical CTCR-OV03/04 studies, and patients were enrolled between 20 July 2007 and 22 October 2009. Median follow-up of the cohort was 31 mo (interquartile range 22-46 mo), censored after 26 October 2013. Outcome measures were overall survival (OS) and progression-free survival (PFS). There were marked differences in the degree of clonal expansion (CE) between patients (median 0.74, interquartile range 0.66-1.15), and dichotimization by median CE showed worse survival in CE-high cases (PFS 12.7 versus 10.1 mo, p = 0.009; OS 42.6 versus 23.5 mo, p = 0.003). Bootstrap analysis with resampling showed that the 95% confidence intervals for the hazard ratios for PFS and OS in the CE-high group were greater than 1.0. These data support a relationship between heterogeneity and survival but do not precisely determine its effect size. Relapsed tissue was available for two patients in the CE-high group, and phylogenetic analysis showed that the prevalent clonal population at clinical recurrence arose from early divergence events. A subclonal population marked by a NF1 deletion showed a progressive increase in tumour allele fraction during chemotherapy. CONCLUSIONS: This study demonstrates that quantitative measures of intra-tumour heterogeneity may have predictive value for survival after chemotherapy treatment in HGSOC. Subclonal tumour populations are present in pre-treatment biopsies in HGSOC and can undergo expansion during chemotherapy, causing clinical relapse.

Clinical and pathological impact of VHL, PBRM1, BAP1, SETD2, KDM6A, and JARID1c in clear cell renal cell carcinoma.

VHL is mutated in the majority of patients with clear cell renal cell carcinoma (ccRCC), with conflicting clinical relevance. Recent studies have identified recurrent mutations in histone modifying and chromatin remodeling genes, including BAP1, PBRM1, SETD2, KDM6A, and JARID1c. Current evidence suggests that BAP1 mutations are associated with aggressive disease. The clinical significance of the remaining genes is unknown. In this study, targeted sequencing of VHL and JARID1c (entire genes) and coding regions of BAP1, PBRM1, SETD2, and KDM6A was performed on 132 ccRCCs and matched normal tissues. Associations between mutations and clinical and pathological outcomes were interrogated. Inactivation of VHL (coding mutation or promoter methylation) was seen in 75% of ccRCCs. Somatic noncoding VHL alterations were identified in 29% of ccRCCs and may be associated with improved overall survival. BAP1 (11%), PBRM1 (33%), SETD2 (16%), JARID1c (4%), and KDM6A (3%) mutations were identified. BAP1-mutated tumors were associated with metastatic disease at presentation (P = 0.023), advanced clinical stage (P = 0.042) and a trend towards shorter recurrence free survival (P = 0.059) when compared with tumors exclusively mutated for PBRM1. Our results support those of recent publications pointing towards a role for BAP1 and PBRM1 mutations in risk stratifying ccRCCs. Further investigation of noncoding alterations in VHL is warranted.

Second Primary Lung Cancer - An Emerging Issue in Lung Cancer Survivors.

As a result of an increased focus on early detection including lung cancer screening, combined with more curative treatment options, the 5-year survival rates for lung cancer are improving. Welcome though this is, it brings new, hitherto unseen challenges. As more patients are cured and survive longer, they are at risk of developing second primary cancers, particularly lung cancer. In this review, we examine the challenges that surveillance, diagnosis, and management of second primary lung cancer (SPLC) bring and how these can be addressed. Recent data from prospective follow-up studies suggests that the incidence of SPLC may be higher than previously appreciated, partly due to an increase in multi-focal adenocarcinoma spectrum disease. Over 5 years, up to 1 in 6 long-term lung cancer survivors may develop a SPLC. Although not routinely used in clinical practice at present, genomic approaches for differentiating SPLC from intrapulmonary metastases of the first primary are emerging, and we highlight how this could be used to help differentiate lesions. An accurate distinction between SPLC and the recurrence of the first primary is of paramount importance due to the very different management strategies that may be required. Wrongly classifying an SPLC as a recurrence of the first primary may have significant consequences for patient management and overall survival. Updated approaches to the classification of SPLC combining clinical history, histopathological assessment, and genomic profiling are needed. Finally, we review the potential role of early detection biomarkers in the identification of SPLC, focusing in particular on blood-based biomarkers that are being examined in a multi-center prospective study recruiting lung cancer survivors.

Dynamics of the p53-Mdm2 feedback loop in individual cells.

The tumor suppressor p53, one of the most intensely investigated proteins, is usually studied by experiments that are averaged over cell populations, potentially masking the dynamic behavior in individual cells. We present a system for following, in individual living cells, the dynamics of p53 and its negative regulator Mdm2 (refs. 1,4-7): this system uses functional p53-CFP and Mdm2-YFP fusion proteins and time-lapse fluorescence microscopy. We found that p53 was expressed in a series of discrete pulses after DNA damage. Genetically identical cells had different numbers of pulses: zero, one, two or more. The mean height and duration of each pulse were fixed and did not depend on the amount of DNA damage. The mean number of pulses, however, increased with DNA damage. This approach can be used to study other signaling systems and suggests that the p53-Mdm2 feedback loop generates a 'digital' clock that releases well-timed quanta of p53 until damage is repaired or the cell dies.

Integrated radiogenomics models predict response to neoadjuvant chemotherapy in high grade serous ovarian cancer.

High grade serous ovarian carcinoma (HGSOC) is a highly heterogeneous disease that typically presents at an advanced, metastatic state. The multi-scale complexity of HGSOC is a major obstacle to predicting response to neoadjuvant chemotherapy (NACT) and understanding critical determinants of response. Here we present a framework to predict the response of HGSOC patients to NACT integrating baseline clinical, blood-based, and radiomic biomarkers extracted from all primary and metastatic lesions. We use an ensemble machine learning model trained to predict the change in total disease volume using data obtained at diagnosis (n = 72). The model is validated in an internal hold-out cohort (n = 20) and an independent external patient cohort (n = 42). In the external cohort the integrated radiomics model reduces the prediction error by 8% with respect to the clinical model, achieving an AUC of 0.78 for RECIST 1.1 classification compared to 0.47 for the clinical model. Our results emphasize the value of including radiomics data in integrative models of treatment response and provide methods for developing new biomarker-based clinical trials of NACT in HGSOC.

Comparison of tumor-informed and tumor-naïve sequencing assays for ctDNA detection in breast cancer.

Analysis of circulating tumor DNA (ctDNA) to monitor cancer dynamics and detect minimal residual disease has been an area of increasing interest. Multiple methods have been proposed but few studies have compared the performance of different approaches. Here, we compare detection of ctDNA in serial plasma samples from patients with breast cancer using different tumor-informed and tumor-naïve assays designed to detect structural variants (SVs), single nucleotide variants (SNVs), and/or somatic copy-number aberrations, by multiplex PCR, hybrid capture, and different depths of whole-genome sequencing. Our results demonstrate that the ctDNA dynamics and allele fractions (AFs) were highly concordant when analyzing the same patient samples using different assays. Tumor-informed assays showed the highest sensitivity for detection of ctDNA at low concentrations. Hybrid capture sequencing targeting between 1,347 and 7,491 tumor-identified mutations at high depth was the most sensitive assay, detecting ctDNA down to an AF of 0.00024% (2.4 parts per million, ppm). Multiplex PCR targeting 21-47 tumor-identified SVs per patient detected ctDNA down to 0.00047% AF (4.7 ppm) and has potential as a clinical assay.

High- or low-dose preoperative ipilimumab plus nivolumab in stage III urothelial cancer: the phase 1B NABUCCO trial.

Cohort 1 of the phase 1B NABUCCO trial showed high pathological complete response (pCR) rates with preoperative ipilimumab plus nivolumab in stage III urothelial cancer (UC). In cohort 2, the aim was dose adjustment to optimize responses. Additionally, we report secondary endpoints, including efficacy and tolerability, in cohort 2 and the association of presurgical absence of circulating tumor DNA (ctDNA) in urine and plasma with clinical outcome in both cohorts. Thirty patients received two cycles of either ipilimumab 3 mg kg-1 plus nivolumab 1 mg kg-1 (cohort 2A) or ipilimumab 1 mg kg-1 plus nivolumab 3 mg kg-1 (cohort 2B), both followed by nivolumab 3 mg kg-1. We observed a pCR in six (43%) patients in cohort 2A and a pCR in one (7%) patient in cohort 2B. Absence of urinary ctDNA correlated with pCR in the bladder (ypT0Nx) but not with progression-free survival (PFS). Absence of plasma ctDNA correlated with pCR (odds ratio: 45.0; 95% confidence interval (CI): 4.9-416.5) and PFS (hazard ratio: 10.4; 95% CI: 2.9-37.5). Our data suggest that high-dose ipilimumab plus nivolumab is required in stage III UC and that absence of ctDNA in plasma can predict PFS. ClinicalTrials.gov registration: NCT03387761 .

Variability and memory of protein levels in human cells.

Protein expression is a stochastic process that leads to phenotypic variation among cells. The cell-cell distribution of protein levels in microorganisms has been well characterized but little is known about such variability in human cells. Here, we studied the variability of protein levels in human cells, as well as the temporal dynamics of this variability, and addressed whether cells with higher than average protein levels eventually have lower than average levels, and if so, over what timescale does this mixing occur. We measured fluctuations over time in the levels of 20 endogenous proteins in living human cells, tagged by the gene for yellow fluorescent protein at their chromosomal loci. We found variability with a standard deviation that ranged, for different proteins, from about 15% to 30% of the mean. Mixing between high and low levels occurred for all proteins, but the mixing time was longer than two cell generations (more than 40 h) for many proteins. We also tagged pairs of proteins with two colours, and found that the levels of proteins in the same biological pathway were far more correlated than those of proteins in different pathways. The persistent memory for protein levels that we found might underlie individuality in cell behaviour and could set a timescale needed for signals to affect fully every member of a cell population.

The future of early cancer detection.

A proactive approach to detecting cancer at an early stage can make treatments more effective, with fewer side effects and improved long-term survival. However, as detection methods become increasingly sensitive, it can be difficult to distinguish inconsequential changes from lesions that will lead to life-threatening cancer. Progress relies on a detailed understanding of individualized risk, clear delineation of cancer development stages, a range of testing methods with optimal performance characteristics, and robust evaluation of the implications for individuals and society. In the future, advances in sensors, contrast agents, molecular methods, and artificial intelligence will help detect cancer-specific signals in real time. To reduce the burden of cancer on society, risk-based detection and prevention needs to be cost effective and widely accessible.

Refined characterization of circulating tumor DNA through biological feature integration.

Circulating tumor DNA (ctDNA) in blood plasma is present at very low concentrations compared to cell-free DNA (cfDNA) of non-tumor origin. To enhance ctDNA detection, recent studies have been focused on understanding the non-random fragmentation pattern of cfDNA. These studies have investigated fragment sizes, genomic position of fragment end points, and fragment end motifs. Although these features have been described and shown to be aberrant in cancer patients, there is a lack of understanding of how the individual and integrated analysis of these features enrich ctDNA fraction and enhance ctDNA detection. Using whole genome sequencing and copy number analysis of plasma samples from 5 high grade serious ovarian cancer patients, we observed that (1) ctDNA is enriched not only in fragments shorter than mono-nucleosomes (~ 167 bp), but also in those shorter than di-nucleosomes (~ 240-330 bp) (28-159% enrichment). (2) fragments that start and end at the border or within the nucleosome core are enriched in ctDNA (5-46% enrichment). (3) certain DNA motifs conserved in regions 10 bp up- and down- stream of fragment ends (i.e. cleavage sites) could be used to detect tumor-derived fragments (10-44% enrichment). We further show that the integrated analysis of these three features resulted in a higher enrichment of ctDNA when compared to using fragment size alone (additional 7-25% enrichment after fragment size selection). We believe these genome wide features, which are independent of genetic mutational changes, could allow new ways to analyze and interpret cfDNA data, as significant aberrations of these features from a healthy state could improve its utility as a diagnostic biomarker.

Longitudinal monitoring of disease burden and response using ctDNA from dried blood spots in xenograft models.

Whole-genome sequencing (WGS) of circulating tumour DNA (ctDNA) is now a clinically important biomarker for predicting therapy response, disease burden and disease progression. However, the translation of ctDNA monitoring into vital preclinical PDX models has not been possible owing to low circulating blood volumes in small rodents. Here, we describe the longitudinal detection and monitoring of ctDNA from minute volumes of blood in PDX mice. We developed a xenograft Tumour Fraction (xTF) metric using shallow WGS of dried blood spots (DBS), and demonstrate its application to quantify disease burden, monitor treatment response and predict disease outcome in a preclinical study of PDX mice. Further, we show how our DBS-based ctDNA assay can be used to detect gene-specific copy number changes and examine the copy number landscape over time. Use of sequential DBS ctDNA assays could transform future trial designs in both mice and patients by enabling increased sampling and molecular monitoring.