Sensitive and robust liquid biopsy-based detection of PIK3CA mutations in hormone-receptor-positive metastatic breast cancer patients.

BACKGROUND: The benefit of alpelisib in hormone-receptor-positive (HR+) metastatic breast cancer patients provided clinical evidence for the increasing importance of PIK3CA testing. We performed a comparison of liquid biopsy and tissue-based detection of PIK3CA mutations. MATERIALS AND METHODS: PIK3CA hotspot mutation analysis using a high-resolution SiMSen-Seq assay was performed in plasma from 93/99 eligible patients with HR+/HER2- breast cancer. Additionally, mFAST-SeqS was used to estimate the tumour fractions in plasma samples. In 72/93 patients, matched tissue was available and analysed using a customised Ion Torrent panel. RESULTS: PIK3CA mutations were detected in 48.6% of tissue samples and 47.3% of plasma samples, with identical PIK3CA mutation detected in 24/72 (33.3%) patients both in tissue and plasma. In 10 (13.9%) patients, mutations were only found in plasma, and in 6 (8.3%) patients, PIK3CA mutations found in tissue were not detectable in ctDNA. In 49/93 plasma samples without detectable PIK3CA mutations, 22 (44.9%) samples had elevated tumour fractions, implying true negative results. CONCLUSION: SiMSen-Seq-based detection of PIK3CA mutations in plasma shows advantageous concordance with the tissue analyses. A combination with an untargeted approach for detecting ctDNA fractions may confirm a negative PIK3CA result and enhance the performance of the SiMSen-Seq test.

Comparing linear discriminant analysis and supervised learning algorithms for binary classification-A method comparison study.

In psychology, linear discriminant analysis (LDA) is the method of choice for two-group classification tasks based on questionnaire data. In this study, we present a comparison of LDA with several supervised learning algorithms. In particular, we examine to what extent the predictive performance of LDA relies on the multivariate normality assumption. As nonparametric alternatives, the linear support vector machine (SVM), classification and regression tree (CART), random forest (RF), probabilistic neural network (PNN), and the ensemble k conditional nearest neighbor (EkCNN) algorithms are applied. Predictive performance is determined using measures of overall performance, discrimination, and calibration, and is compared in two reference data sets as well as in a simulation study. The reference data are Likert-type data, and comprise 5 and 10 predictor variables, respectively. Simulations are based on the reference data and are done for a balanced and an unbalanced scenario in each case. In order to compare the algorithms' performance, data are simulated from multivariate distributions with differing degrees of nonnormality. Results differ depending on the specific performance measure. The main finding is that LDA is always outperformed by RF in the bimodal data with respect to overall performance. Discriminative ability of the RF algorithm is often higher compared to LDA, but its model calibration is usually worse. Still LDA mostly ranges second in cases it is outperformed by another algorithm, or the differences are only marginal. In consequence, we still recommend LDA for this type of application.

Sensitive and broadly applicable residual disease detection in acute myeloid leukemia using flow cytometry-based leukemic cell enrichment followed by mutational profiling.

Persistent measurable residual disease (MRD) is an increasingly important prognostic marker in acute myeloid leukemia (AML). Currently, MRD is determined by multi-parameter flow cytometry (MFC) or PCR-based methods detecting leukemia-specific fusion transcripts and mutations. However, while MFC is highly operator-dependent and difficult to standardize, PCR-based methods are only available for a minority of AML patients. Here we describe a novel, highly sensitive and broadly applicable method for MRD detection by combining MFC-based leukemic cell enrichment using an optimized combinatorial antibody panel targeting CLL-1, TIM-3, CD123 and CD117, followed by mutational analysis of recurrently mutated genes in AML. In dilution experiments this method showed a sensitivity of 10-4 to 10-5 for residual disease detection. In prospectively collected remission samples this marker combination allowed for a median 67-fold cell enrichment with sufficient DNA quality for mutational analysis using next generation sequencing (NGS) or digital PCR in 39 out of 41 patients. Twenty-one samples (53.8%) tested MRD positive, whereas 18 (46.2%) were negative. With a median follow-up of 559 days, 71.4% of MRD positive (15/21) and 27.8% (5/18) of MRD negative patients relapsed (P = .007). The cumulative incidence of relapse (CIR) was higher for MRD positive patients (5-year CIR: 90.5% vs 28%, P < .001). In multivariate analysis, MRD positivity was a prominent factor for CIR. Thus, MFC-based leukemic cell enrichment using antibodies against CLL-1, TIM-3, CD123 and CD117 followed by mutational analysis allows high sensitive MRD detection and is informative on relapse risk in the majority of AML patients.

G protein-coupled receptor GPR55 promotes colorectal cancer and has opposing effects to cannabinoid receptor 1.

The putative cannabinoid receptor GPR55 has been shown to play a tumor-promoting role in various cancers, and is involved in many physiological and pathological processes of the gastrointestinal (GI) tract. While the cannabinoid receptor 1 (CB1 ) has been reported to suppress intestinal tumor growth, the role of GPR55 in the development of GI cancers is unclear. We, therefore, aimed at elucidating the role of GPR55 in colorectal cancer (CRC), the third most common cancer worldwide. Using azoxymethane (AOM)- and dextran sulfate sodium (DSS)-driven CRC mouse models, we found that GPR55 plays a tumor-promoting role that involves alterations of leukocyte populations, i.e. myeloid-derived suppressor cells and T lymphocytes, within the tumor tissues. Concomitantly, expression levels of COX-2 and STAT3 were reduced in tumor tissue of GPR55 knockout mice, indicating reduced presence of tumor-promoting factors. By employing the experimental CRC models to CB1 knockout and CB1 /GPR55 double knockout mice, we can further show that GPR55 plays an opposing role to CB1 . We report that GPR55 and CB1 mRNA expression are differentially regulated in the experimental models and in a cohort of 86 CRC patients. Epigenetic methylation of CNR1 and GPR55 was also differentially regulated in human CRC tissue compared to control samples. Collectively, our data suggest that GPR55 and CB1 play differential roles in colon carcinogenesis where the former seems to act as oncogene and the latter as tumor suppressor.

Genomic alterations in plasma DNA from patients with metastasized prostate cancer receiving abiraterone or enzalutamide.

In patients with metastatic castrate-resistant prostate cancer (mCRPC), circulating tumor DNA (ctDNA) analysis offers novel opportunities for the development of non-invasive biomarkers informative of treatment response with novel agents targeting the androgen-receptor (AR) pathway, such as abiraterone or enzalutamide. However, the relationship between ctDNA abundance, detectable somatic genomic alterations and clinical progression of mCRPC remains unexplored. Our study aimed to investigate changes in plasma DNA during disease progression and their associations with clinical variables in mCRPC patients. We analyzed ctDNA in two cohorts including 94 plasma samples from 25 treatment courses (23 patients) and 334 plasma samples from 125 patients, respectively. We conducted whole-genome sequencing (plasma-Seq) for genome-wide profiling of somatic copy number alterations and targeted sequencing of 31 prostate cancer-associated genes. The combination of plasma-Seq with targeted AR analyses identified prostate cancer-related genomic alterations in 16 of 25 (64%) treatment courses in the first cohort, in which we demonstrated that AR amplification does not always correlate with poor abiraterone and enzalutamide therapy outcome. As we observed a wide variability of ctDNA levels, we evaluated ctDNA levels and their association with clinical parameters and included the second, larger cohort for these analyses. Employing altogether 428 longitudinal plasma samples from 148 patients, we identified the presence of bone metastases, increased lactate dehydrogenase and prostate-specific antigen (PSA) as having the strongest association with high ctDNA levels. In summary, ctDNA alterations are observable in the majority of patients with mCRPC and may eventually be useful to guide clinical decision-making in this setting.

Residual disease detection using targeted parallel sequencing predicts relapse in cytogenetically normal acute myeloid leukemia.

Despite achieving complete remission after intensive therapy, most patients with cytogenetically normal (CN) AML relapse due to the persistence of submicroscopic residual disease. In this pilot study, we hypothesized that detection of leukemia-specific mutations following consolidation treatment using a targeted parallel sequencing approach predicts relapse. We included 34 AML patients of whom diagnostic material and remission bone marrow slides after at least one cycle of consolidation were available. Isolated DNA was screened for mutations in 19 genes using an Ion Torrent sequencing platform. Furthermore, the variant allelic frequency of distinct mutations was validated by digital PCR and sequencing using a barcoding approach. Twenty-seven out of 34 patients could be analyzed for mutation clearance. We identified 68 somatic mutations at diagnosis (median, 3 mutations per patient; range 1-5) and 22 of these were still detected in 16 patients after consolidation therapy with a reliable sensitivity of 0.5% (median, 1 mutation; range 0-3). The most frequent noncleared mutations were found in DNMT3A. However, as persistence of these mutations has recently been shown to be without any impact on relapse risk, we performed survival and relapse risk analysis excluding DNMT3A mutations. Importantly, persistence of non-DNMT3A mutations was associated with a higher risk of AML relapse (7/8 pts versus 6/19 pts; P = .013) and with a shorter relapse-free survival (333 days vs. not reached; log-rank P = .0219). Detection of residual disease by routine targeted parallel sequencing proved feasible and effective as persistence of somatic mutations other than DNMT3A were prognostic for relapse in CN AML.

Differential survival trends of stage II colorectal cancer patients relate to promoter methylation status of PCDH10, SPARC, and UCHL1.

Surgical excision of colorectal cancer at early clinical stages is highly effective, but 20-30% of patients relapse. Therefore, it is of clinical relevance to identify patients at high risk for recurrence, who would benefit from adjuvant chemotherapy. The objective of this study was to identify prognostic and/or predictive methylation markers in stage II colorectal cancer patients. Therefore, we selected six gene promoters (FZD9, PCDH10 (protocadherin 10), SFRP2, SPARC (secreted protein acidic and rich in cysteine), UCHL1 (ubiquitin carboxyl-terminal hydrolase 1), and WIF1) for methylation analysis in formalin-fixed, paraffin-embedded primary tumor samples of colorectal cancer patients (n=143) who were enrolled in a prospective randomized phase III trial of the Austrian Breast and Colorectal cancer Study Group. Patients were randomized to adjuvant chemotherapy with 5-fluorouracil and leucovorin or surveillance only. Survival analyses revealed that combined evaluation of three promoters (PCDH10, SPARC, and UCHL1) showed differential effects with regard to disease-free survival and overall survival in the two treatment groups (significance level 0.007). In the chemotherapy arm, a statistically insignificant trend for patients without methylation toward longer survival was observed (P=0.069 for disease-free survival and P=0.139 for overall survival). Contrary, patients in the surveillance arm without methylation in their gene promoters had shorter disease-free survival and overall survival (P=0.031 for disease-free survival and P=0.003 for overall survival), indicating a prognostic effect of methylation in this group (test for interaction, P=0.006 for disease-free survival and P=0.018 for overall survival). These results indicate that promoter methylation status of PCDH10, SPARC, and UCHL1 may be used both as prognostic and predictive molecular marker for colorectal cancer patients and, therefore, may facilitate treatment decisions for stage II colorectal cancer.

Persistence of ctDNA in Patients with Breast Cancer During Neoadjuvant Treatment Is a Significant Predictor of Poor Tumor Response.

PURPOSE: Accurate response assessment during neoadjuvant systemic treatment (NST) poses a clinical challenge. Therefore, a minimally invasive assessment of tumor response based on cell-free circulating tumor DNA (ctDNA) may be beneficial to guide treatment decisions. EXPERIMENTAL DESIGN: We profiled 93 genes in tissue from 193 patients with early breast cancer. Patient-specific assays were designed for 145 patients to track ctDNA during NST in plasma. ctDNA presence and levels were correlated with complete pathological response (pCR) and residual cancer burden (RCB) as well as clinicopathologic characteristics of the tumor to identify potential proxies for ctDNA release. RESULTS: At baseline, ctDNA could be detected in 63/145 (43.4%) patients and persisted in 25/63 (39.7%) patients at mid-therapy (MT) and 15/63 (23.8%) patients at the end of treatment. ctDNA detection at MT was significantly associated with higher RCB (OR = 0.062; 95% CI, 0.01-0.48; P = 0.0077). Of 31 patients with detectable ctDNA at MT, 30 patients (96.8%) were nonresponders (RCB II, n = 8; RCB III, n = 22) and only one patient responded to the treatment (RCB I). Considering all 145 patients with baseline (BL) plasma, none of the patients with RCB 0 and only 6.7% of patients with RCB I had ctDNA detectable at MT, whereas 30.6% and 29.6% of patients with RCB II/III, respectively, had a positive ctDNA result. CONCLUSIONS: Overall, our results demonstrate that the detection and persistence of ctDNA at MT may have the potential to negatively predict response to neoadjuvant treatment and identify patients who will not achieve pCR or be classified with RCB II/III.

Blocking STAT3/5 through direct or upstream kinase targeting in leukemic cutaneous T-cell lymphoma.

Leukemic cutaneous T-cell lymphomas (L-CTCL) are lymphoproliferative disorders of skin-homing mature T-cells causing severe symptoms and high mortality through chronic inflammation, tissue destruction, and serious infections. Despite numerous genomic sequencing efforts, recurrent driver mutations have not been identified, but chromosomal losses and gains are frequent and dominant. We integrated genomic landscape analyses with innovative pharmacologic interference studies to identify key vulnerable nodes in L-CTCL. We detected copy number gains of loci containing the STAT3/5 oncogenes in 74% (n = 17/23) of L-CTCL, which correlated with the increased clonal T-cell count in the blood. Dual inhibition of STAT3/5 using small-molecule degraders and multi-kinase blockers abolished L-CTCL cell growth in vitro and ex vivo, whereby PAK kinase inhibition was specifically selective for L-CTCL patient cells carrying STAT3/5 gains. Importantly, the PAK inhibitor FRAx597 demonstrated encouraging anti-leukemic activity in vivo by inhibiting tumor growth and disease dissemination in intradermally xenografted mice. We conclude that STAT3/5 and PAK kinase interaction represents a new therapeutic node to be further explored in L-CTCL.

Longitudinal tumor fraction trajectories predict risk of progression in metastatic HR+ breast cancer patients undergoing CDK4/6 treatment.

Despite improved clinical outcomes, intrinsic or acquired resistance to CDK4/6 inhibitor treatment has limited the success of this treatment in HR+ HER2- metastatic breast cancer patients. Biomarkers are urgently needed, and longitudinal biomarker measurements may harbor more dynamic predictive and prognostic information compared to single time point measurements. The aim of this study was to explore the longitudinal evolution of circulating tumor fractions within cell-free DNA assessed by an untargeted sequencing approach during CDK4/6 therapy and to quantify the potential association between longitudinal z-score measurements and clinical outcome by using joint models. Forty-nine HR+ HER2- metastatic breast cancer patients were enrolled, and z-score levels were measured at baseline and during 132 follow-up visits (median number of measurements per patient = 3, 25th -75th percentile: 3-5, range: 1-8). We observed higher baseline z-score levels (estimated difference 0.57, 95% CI: 0.147-0.983, P-value = 0.008) and a constant increase of z-score levels over follow-up time (overall P-value for difference in log z-score over time = 0.024) in patients who developed progressive disease. Importantly, the joint model revealed that elevated z-score trajectories were significantly associated with higher progression risk (HR of log z-score at any time of follow-up = 3.3, 95% CI, 1.44-7.55, P = 0.005). In contrast, single z-score measurement at CDK4/6 inhibitor treatment start did not predict risk of progression. In this prospective study, we demonstrate proof-of-concept that longitudinal z-score trajectories rather than single time point measurements may harbor important dynamic information on the development of disease progression in HR+ HER2- breast cancer patients undergoing CDK4/6 inhibitor treatment.

Dynamic Changes of Circulating Tumor DNA Predict Clinical Outcome in Patients With Advanced Non-Small-Cell Lung Cancer Treated With Immune Checkpoint Inhibitors.

PURPOSE: Immune checkpoint inhibitors (ICIs) are increasingly being used in non-small-cell lung cancer (NSCLC), yet biomarkers predicting their benefit are lacking. We evaluated if on-treatment changes of circulating tumor DNA (ctDNA) from ICI start (t0) to after two cycles (t1) assessed with a commercial panel could identify patients with NSCLC who would benefit from ICI. PATIENTS AND METHODS: The molecular ctDNA response was evaluated as a predictor of radiographic tumor response and long-term survival benefit of ICI. To maximize the yield of ctDNA detection, de novo mutation calling was performed. Furthermore, the impact of clonal hematopoiesis (CH)-related variants as a source of biologic noise was investigated. RESULTS: After correction for CH-related variants, which were detected in 75 patients (44.9%), ctDNA was detected in 152 of 167 (91.0%) patients. We observed only a fair agreement of the molecular and radiographic response, which was even more impaired by the inclusion of CH-related variants. After exclusion of those, a ≥ 50% molecular response improved progression-free survival (10 v 2 months; hazard ratio [HR], 0.55; 95% CI, 0.39 to 0.77; P = .0011) and overall survival (18.4 v 5.9 months; HR, 0.44; 95% CI, 0.31 to 0.62; P < .0001) compared with patients not achieving this end point. After adjusting for clinical variables, ctDNA response and STK11/KEAP1 mutations (HR, 2.08; 95% CI, 1.4 to 3.0; P < .001) remained independent predictors for overall survival, irrespective of programmed death ligand-1 expression. A landmark survival analysis at 2 months (n = 129) provided similar results. CONCLUSION: On-treatment changes of ctDNA in plasma reveal predictive information for long-term clinical benefit in ICI-treated patients with NSCLC. A broader NSCLC patient coverage through de novo mutation calling and the use of a variant call set excluding CH-related variants improved the classification of molecular responders, but had no significant impact on survival.

On-treatment measurements of circulating tumor DNA during FOLFOX therapy in patients with colorectal cancer.

We addressed a significant unknown feature of circulating tumor DNA (ctDNA), i.e., how ctDNA levels change during chemotherapy, by serially monitoring ctDNA in patients with colorectal cancer during the 48-h application of FOLFOX. Surprisingly, we did not observe a spike in ctDNA as a sign of a responsive tumor, but instead ctDNA levels initially decreased and remained low in patients with stable disease or partial response. Our observations reveal further insights into cell destruction during chemotherapy with important implications for the management of patients.

Comparison of three commercial decision support platforms for matching of next-generation sequencing results with therapies in patients with cancer.

OBJECTIVE: Precision oncology depends on translating molecular data into therapy recommendations. However, with the growing complexity of next-generation sequencing-based tests, clinical interpretation of somatic genomic mutations has evolved into a formidable task. Here, we compared the performance of three commercial clinical decision support tools, that is, NAVIFY Mutation Profiler (NAVIFY; Roche), QIAGEN Clinical Insight (QCI) Interpret (QIAGEN) and CureMatch Bionov (CureMatch). METHODS: In order to obtain the current status of the respective tumour genome, we analysed cell-free DNA from patients with metastatic breast, colorectal or non-small cell lung cancer. We evaluated somatic copy number alterations and in parallel applied a 77-gene panel (AVENIO ctDNA Expanded Panel). We then assessed the concordance of tier classification approaches between NAVIFY and QCI and compared the strategies to determine actionability among all three platforms. Finally, we quantified the alignment of treatment suggestions across all decision tools. RESULTS: Each platform varied in its mode of variant classification and strategy for identifying druggable targets and clinical trials, which resulted in major discrepancies. Even the frequency of concordant actionable events for tier I-A or tier I-B classifications was only 4.3%, 9.5% and 28.4% when comparing NAVIFY with QCI, NAVIFY with CureMatch and CureMatch with QCI, respectively, and the obtained treatment recommendations differed drastically. CONCLUSIONS: Treatment decisions based on molecular markers appear at present to be arbitrary and dependent on the chosen strategy. As a consequence, tumours with identical molecular profiles would be differently treated, which challenges the promising concepts of genome-informed medicine.

Exome sequence analysis in consanguineous Pakistani families inheriting Bardet-Biedle syndrome determined founder effect of mutation c.299delC (p.Ser100Leufs*24) in BBS9 gene.

BACKGROUND: Bardet-Biedl syndrome (BBS) is characterized by a heterogeneous phenotypic spectrum of retinopathy, intellectual disability (ID), obesity, polydactyly, and kidney dysfunctions as the major clinical features. Genetic investigations have reported 21 BBS genes, the products of which are mostly located at the centrosome, basal body or the ciliary transition zone. METHODS: In the present genetic report, we analyzed two apparently unrelated consanguineous BBS families from Dera Ismail Khan (D.I.Khan) district, Pakistan. Genetic mapping was performed using Whole exome sequencing and Sanger sequencing. RESULTS: Whole exome sequencing identified a recently reported single base deletion NM_001033604.1:c.299delC in the fourth exon of BBS9 in both families. The identified frameshift mutation is predicted to cause premature truncation of the expressed protein (p.Ser100Leufs*24). This mutation has previously been mapped in a consanguineous Pakistani family; therefore this is the second report of this particular mutation in two additional BBS families originating from different locations. CONCLUSION: We speculate the evolutionary significance of this mutation and assume its strong founder effect in the Khaisoori tribe of D.I.Khan. Based on these findings, we suggest developing a molecular diagnostic test that may be used for premarital and prenatal screening of families at risk of BBS.

Whole-genome plasma sequencing reveals focal amplifications as a driving force in metastatic prostate cancer.

Genomic alterations in metastatic prostate cancer remain incompletely characterized. Here we analyse 493 prostate cancer cases from the TCGA database and perform whole-genome plasma sequencing on 95 plasma samples derived from 43 patients with metastatic prostate cancer. From these samples, we identify established driver aberrations in a cancer-related gene in nearly all cases (97.7%), including driver gene fusions (TMPRSS2:ERG), driver focal deletions (PTEN, RYBP and SHQ1) and driver amplifications (AR and MYC). In serial plasma analyses, we observe changes in focal amplifications in 40% of cases. The mean time interval between new amplifications was 26.4 weeks (range: 5-52 weeks), suggesting that they represent rapid adaptations to selection pressure. An increase in neuron-specific enolase is accompanied by clonal pattern changes in the tumour genome, most consistent with subclonal diversification of the tumour. Our findings suggest a high plasticity of prostate cancer genomes with newly occurring focal amplifications as a driving force in progression.

Inferring expressed genes by whole-genome sequencing of plasma DNA.

The analysis of cell-free DNA (cfDNA) in plasma represents a rapidly advancing field in medicine. cfDNA consists predominantly of nucleosome-protected DNA shed into the bloodstream by cells undergoing apoptosis. We performed whole-genome sequencing of plasma DNA and identified two discrete regions at transcription start sites (TSSs) where nucleosome occupancy results in different read depth coverage patterns for expressed and silent genes. By employing machine learning for gene classification, we found that the plasma DNA read depth patterns from healthy donors reflected the expression signature of hematopoietic cells. In patients with cancer having metastatic disease, we were able to classify expressed cancer driver genes in regions with somatic copy number gains with high accuracy. We were able to determine the expressed isoform of genes with several TSSs, as confirmed by RNA-seq analysis of the matching primary tumor. Our analyses provide functional information about cells releasing their DNA into the circulation.