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Advances in therapeutic approaches for melanoma urge the need for biomarkers that can identify patients at risk for recurrence and to guide treatment. The potential use of liquid biopsies in identifying biomarkers is increasingly being recognized. Here, we present a head‐to‐head comparison of several techniques to analyze circulating tumor cells (CTCs) and cell‐free DNA (cfDNA) in 20 patients with metastatic melanoma. In this study, we investigated whether diagnostic leukapheresis (DLA) combined with multimarker flow cytometry (FCM) increased the detection of CTCs in blood compared to the CellSearch platform. Additionally, we characterized cfDNA at the level of somatic mutations, extent of aneuploidy and genome‐wide DNA methylation. Both CTCs and cfDNA measures were compared to tumor markers and extracranial tumor burden on radiological imaging. Compared to the CellSearch method applied on peripheral blood, DLA combined with FCM increased the proportion of patients with detectable CTCs from 35% to 70% (P = 0.06). However, the median percentage of cells that could be recovered by the DLA procedure was 29%. Alternatively, cfDNA mutation and methylation analysis detected tumor load in the majority of patients (90% and 93% of samples successfully analyzed, respectively). The aneuploidy score was positive in 35% of all patients. From all tumor measurements in blood, lactate dehydrogenase (LDH) levels were significantly correlated to variant allele frequency (P = 0.004). Furthermore, the presence of CTCs in DLA was associated with tumor burden (P

Abstract Background In breast cancer, the advent of anti-HER2 therapies has made HER2+ tumors a highly relevant subgroup. However, the exact characteristics which prohibit clinical response to anti-HER2 therapies and drive disease progression are not yet fully known. Integrative whole-genome and transcriptomic sequencing data from both primary and metastatic HER2-positive breast cancer will enhance our understanding of underlying biological processes. Methods Here, we used WGS and RNA sequencing data of 700 metastatic breast tumors, of which 68 being HER2+, to search for specific genomic features of HER2+ disease and therapy resistance. Furthermore, we integrated results with transcriptomic data to associate tumors exhibiting a HER2+-specific gene expression profile with ERBB2 mutation status, prior therapy and relevant gene expression signatures. Results Overall genomic profiles of primary and metastatic HER2+ breast cancers were similar, and no specific acquired genomics traits connected to prior anti-HER2 treatment were observed. However, specific genomic features were predictive of progression-free survival on post-biopsy anti-HER2 treatment. Furthermore, a HER2-driven expression profile grouped HER2-amplified tumors with ERBB2-mutated cases and cases without HER2 alterations. The latter were reported as ER positive in primary disease, but the metastatic biopsy showed low ESR1 expression and upregulation of the MAPK pathway, suggesting transformation to ER independence. Conclusions In summary, although the quantity of variants increased throughout HER2-positive breast cancer progression, the genomic composition remained largely consistent, thus yielding no new major processes beside those already operational in primary disease. Our results suggest that integrated genomic and transcriptomic analyses may be key in establishing therapeutic options.

Multiple prognostic biomarkers, including circulating tumour cell (CTC) counts, exist in metastatic castration‐resistant prostate cancer (mCRPC) patients, but none of them have been implemented into daily clinical care. The modified fast aneuploidy screening test‐sequencing system (mFast‐SeqS), which yields a genome‐wide aneuploidy score, is able to reflect the fraction of cell‐free tumour DNA (ctDNA) within cell‐free DNA (cfDNA) and may be a promising biomarker in mCRPC. In this study, we investigated the prognostic value of dichotomized aneuploidy scores (

Abstract This prospective cohort study reports aneuploidy score by mFast-SeqS as a strong prognostic marker in MBC patients. mFAST-SeqS is an affordable and easily implementable method for the assessment of total ctDNA levels and, as such, provides an alternative prognostic tool. One mixed cohort (cohort A, n = 45) starting any type of treatment in any line of therapy and one larger cohort (cohort B, n = 129) consisting of patients starting aromatase inhibitors (AI) as first-line therapy were used. mFAST-SeqS was performed using plasma of blood in which CTCs (CellSearch) were enumerated. The resulting aneuploidy score was correlated with categorized CTC count and associated with outcome. The aneuploidy score was significantly correlated with CTC count, but discordance was observed in 31.6% when applying cut-offs of 5. In both cohorts, aneuploidy score was a significant prognostic marker for both PFS and OS. In the Cox regression models, the HR for aneuploidy score for PFS was 2.52 (95% CI: 1.56–4.07), and the HR for OS was 2.37 (95% CI: 1.36–4.14). Results presented here warrant further investigations into the clinical utility of this marker in MBC patients.

Abstract Next generation sequencing of cell-free DNA (cfDNA) is a promising method for treatment monitoring and therapy selection in metastatic breast cancer (MBC). However, distinguishing tumor-specific variants from sequencing artefacts and germline variation with low false discovery rate is challenging when using large targeted sequencing panels covering many tumor suppressor genes. To address this, we built a machine learning model to remove false positive variant calls and augmented it with additional filters to ensure selection of tumor-derived variants. We used cfDNA of 70 MBC patients profiled with both the small targeted Oncomine breast panel (Thermofisher) and the much larger Qiaseq Human Breast Cancer Panel (Qiagen). The model was trained on the panels’ common regions using Oncomine hotspot mutations as ground truth. Applied to Qiaseq data, it achieved 35% sensitivity and 36% precision, outperforming basic filtering. For 20 patients we used germline DNA to filter for somatic variants and obtained 245 variants in total, while our model found seven variants, of which six were also detected using the germline strategy. In ten tumor-free individuals, our method detected in total one (potentially germline) variant, in contrast to 521 variants detected without our model. These results indicate that our model largely detects somatic variants.

Intrapatient tumour heterogeneity is likely a major determinant of clinical outcome in cancer patients. To assess heterogeneity in a minimally invasive manner, methods to perform single circulating tumour cell (CTC) genomics at high resolution are necessary. However, due to the rarity of CTCs, development of such methods is challenging. Here, we developed a modular single CTC analysis pipeline to assess intrapatient heterogeneity by copy number (CN) profiling. To optimize this pipeline, spike‐in experiments using MCF‐7 breast cancer cells were performed. The VyCAP puncher system was used to isolate single cells. The quality of whole genome amplification (WGA) products generated by REPLI‐g and Ampli1™ methods, as well as the results from the Illumina Truseq and the Ampli1™ LowPass library preparation techniques, was compared. Moreover, a bioinformatic pipeline was designed to generate CN profiles from single CTCs. The optimal combination of Ampli1™ WGA and Illumina Truseq library preparation was successfully validated on patient‐derived CTCs. In conclusion, we developed a novel modular pipeline to isolate single CTCs and subsequently generate detailed patient‐derived CN profiles that allow assessment of intrapatient heterogeneity in future studies.

Second‐line treatment with immune checkpoint inhibition in patients with metastatic urothelial cancer (mUC) has a low success rate (~ 20%). Circulating tumour‐derived DNA (ctDNA) levels may guide patient stratification, provided that an affordable and robust assay is available. Here, we investigate whether the modified fast aneuploidy screening test‐sequencing system (mFast‐SeqS) may provide such an assay. To this end, mFast‐SeqS was performed on cell‐free DNA (cfDNA) from 74 patients with mUC prior to treatment with pembrolizumab. Results were associated with corresponding tissue‐based profiles, plasma‐based variant allele frequencies (VAFs) and clinical response. We found that plasma‐derived mFast‐SeqS‐based aneuploidy scores significantly correlated with those observed in the corresponding tumour tissue as well as with the ctDNA level in the plasma. In multivariate logistic regression analysis, a high aneuploidy score was independently associated with lack of clinical benefit from treatment with pembrolizumab. In conclusion, mFast‐SeqS provides a patient‐friendly, high‐throughput and affordable method to estimate ctDNA level. Following independent validation, this test could be used to stratify mUC patients for response prior to the initiation of treatment with pembrolizumab.

Circulating tumour DNA (ctDNA) is a potential biomarker that could contribute to more judicious patient selection for personalised treatment. This review and meta-analysis gives an overview of the current knowledge in the literature investigating the value of ctDNA in patients with colorectal liver metastases (CRLM). A systematic search was conducted in electronic databases for studies published prior to the 26th of May 2023. Studies investigating the association between ctDNA and oncological outcomes in patients undergoing curative-intent local therapy for CRLM were included. Meta-analyses were performed to pool hazard ratios (HR) for the recurrence-free survival (RFS) and overall survival (OS). A total of eleven studies were included and nine were eligible for meta-analyses. Patients with detectable ctDNA after surgery experienced a significantly higher chance of recurrence (HR 3.12, 95% CI 2.27–4.28, p < 0.000010) and shorter OS (HR 5.04, 95% CI 2.53–10.04, p < 0.00001) compared to patients without detectable ctDNA. A similar association for recurrence was found in patients with detectable ctDNA after the completion of adjuvant therapy (HR 6.39, 95% CI 2.13–19.17, p < 0.0009). The meta-analyses revealed no association between detectable ctDNA before surgery and the RFS and OS. These meta-analyses demonstrate the strong association between detectable ctDNA after treatment and oncological outcomes in CRLM patients.

BackgroundCirculating tumour DNA (ctDNA) has been established as a promising (prognostic) biomarker with the potential to personalise treatment in cancer patients. The objective of this systematic review is to provide an overview of the current literature and the future perspectives of ctDNA in non-metastatic rectal cancer.MethodsA comprehensive search for studies published prior to the 4th of October 2022 was conducted in Embase, Medline, Cochrane, Google scholar, and Web of Science. Only peer-reviewed original articles and ongoing clinical trials investigating the association between ctDNA and oncological outcomes in non-metastatic rectal cancer patients were included. Meta-analyses were performed to pool hazard ratios (HR) for recurrence-free survival (RFS).ResultsA total of 291 unique records were screened, of which 261 were original publications and 30 ongoing trials. Nineteen original publications were reviewed and discussed, of which seven provided sufficient data for meta-analyses on the association between the presence of post-treatment ctDNA and RFS. Results of the meta-analyses demonstrated that ctDNA analysis can be used to stratify patients into very high and low risk groups for recurrence, especially when detected after neoadjuvant treatment (HR for RFS: 9.3 [4.6 – 18.8]) and after surgery (HR for RFS: 15.5 [8.2 – 29.3]). Studies investigated different types of assays and used various techniques for the detection and quantification of ctDNA.ConclusionsThis literature overview and meta-analyses provide evidence for the strong association between ctDNA and recurrent disease. Future research should focus on the feasibility of ctDNA-guided treatment and follow-up strategies in rectal cancer. A blueprint for agreed-upon timing, preprocessing, and assay techniques is needed to empower adaptation of ctDNA into daily practice.

Consensus molecular subtypes (CMSs) can guide precision treatment of colorectal cancer (CRC). We aim to identify methylation markers to distinguish between CMS2 and CMS3 in patients with CRC, for which an easy test is currently lacking. To this aim, fresh‐frozen tumor tissue of 239 patients with stage I‐III CRC was analyzed. Methylation profiles were obtained using the Infinium HumanMethylation450 BeadChip. We performed adaptive group‐regularized logistic ridge regression with post hoc group‐weighted elastic net marker selection to build prediction models for classification of CMS2 and CMS3. The Cancer Genome Atlas (TCGA) data were used for validation. Group regularization of the probes was done based on their location either relative to a CpG island or relative to a gene present in the CMS classifier, resulting in two different prediction models and subsequently different marker panels. For both panels, even when using only five markers, accuracies were > 90% in our cohort and in the TCGA validation set. Our methylation marker panel accurately distinguishes between CMS2 and CMS3. This enables development of a targeted assay to provide a robust and clinically relevant classification tool for CRC patients.

Molecular landscapes of metastatic colorectal cancers (mCRC) have often been restricted to coding regions or low numbers of patients. Here the authors present a whole-genome landscape of 429 mCRC patients, revealing the mutational impact of prior therapies and potential actionable targets.

Cervical screening by high-risk HPV (hrHPV) testing requires additional risk stratification (triage), as most infections are transient and only a subset of hrHPV-positive women harbours clinically relevant disease. Molecular triage markers such as microRNAs (miRNAs) and DNA methylation markers are particularly promising, as they can be objectively tested directly on hrHPV-positive scrapes and cervicovaginal self-samples. Here, we evaluated the marker potential of 10 candidate miRNAs in 209 hrHPV-positive scrapes of women with underlying precancer (cervical intraepithelial neoplasia, grade 2–3 (CIN2-3)), cancer, or without disease (CIN0/1). A predictive miRNA classifier for CIN3 detection was built using logistic regression, which was compared to and combined with DNA methylation marker FAM19A4. Markers were correlated to histology parameters and hrHPV genotype. A miRNA classifier consisting of miR-149, miR-20a, and miR-93 achieved an area under the curve (AUC) of 0.834 for CIN3 detection, which was not significantly different to that of FAM19A4 methylation (AUC: 0.862, p = 0.591). Combining miRNA and methylation analysis demonstrated complementarity between both marker types (AUC: 0.939). While the miRNA classifier seemed more predictive for CIN2, FAM19A4 methylation was particularly high in HPV16-positive and histologically advanced CIN3, i.e. CIN3 with high lesion volume. The miRNA classifier, FAM19A4 methylation, and the miRNA/methylation combination were highest in cancer-associated scrapes. In conclusion, a panel of three miRNAs is discriminatory for CIN3 in hrHPV-positive scrapes and can complement DNA methylation analysis for the efficient detection of cervical disease. Combined analysis of the two marker types warrants further evaluation as triage strategy in hrHPV-based screening.

The emerging interest in circulating tumor DNA (ctDNA) analyses for clinical trials has necessitated the development of a high‐throughput method for fast, reproducible, and efficient isolation of ctDNA. Currently, the majority of ctDNA studies use the manual QIAamp (QA) platform to isolate DNA from blood. The purpose of this study was to compare two competing automated DNA isolation platforms [Maxwell (MX) and QIAsymphony (QS)] to the current ‘gold standard’ QA to facilitate high‐throughput processing of samples in prospective trials. We obtained blood samples from healthy blood donors and metastatic cancer patients for plasma isolation. Total cell‐free DNA (cfDNA) quantity was assessed by TERT quantitative PCR. Recovery efficiency was investigated by quantitative PCR analysis of spiked‐in synthetic plant DNA. In addition, a β‐actin fragmentation assay was performed to determine the amount of contamination by genomic DNA from lysed leukocytes. ctDNA quality was assessed by digital PCR for somatic variant detection. cfDNA quantity and recovery efficiency were lowest using the MX platform, whereas QA and QS showed a comparable performance. All platforms preferentially isolated small (136 bp) DNA fragments over large (420 and 2000 bp) DNA fragments. Detection of the number variant and wild‐type molecules was most comparable between QA and QS. However, there was no significant difference in variant allele frequency comparing QS and MX to QA. In summary, we show that the QS platform has comparable performance to QA, the ‘gold standard’, and outperformed the MX platform depending on the readout used. We conclude that the QS can replace the more laborious QA platform, especially when high‐throughput cfDNA isolation is needed.

Abstract Vulvar squamous cell carcinoma (VSCC) and precancerous vulvar intraepithelial neoplasia (VIN) can develop through human papillomavirus (HPV)‐dependent and ‐independent pathways, indicating a heterogeneous disease. Only a minority of VIN progress, but current clinicopathological classifications are insufficient to predict the cancer risk. Here we analyzed copy number alterations (CNA) to assess the molecular heterogeneity of vulvar lesions in relation to HPV and cancer risk. HPV‐status and CNA by means of whole‐genome next‐generation shallow‐sequencing were assessed in VSCC and VIN. The latter included VIN of women with associated VSCC (VINVSCC) and women who did not develop VSCC during follow‐up (VINnoVSCC). HPV‐testing resulted in 41 HPV‐positive (16 VINVSCC, 14 VINnoVSCC, and 11 VSCC) and 24 HPV‐negative (11 VINVSCC and 13 VSCC) lesions. HPV‐positive and ‐negative VSCC showed a partially overlapping pattern of recurrent CNA, including frequent gains of 3q and 8q. In contrast, amplification of 11q13/cyclinD1 was exclusively found in HPV‐negative lesions. HPV‐negative VINVSCC had less CNA than HPV‐negative VSCC (P = .009), but shared chromosome 8 alterations. HPV‐positive VINnoVSCC had less CNA than VINVSCC (P = .022). Interestingly, 1pq gain was detected in 81% of HPV‐positive VINVSCC and only in 21% of VINnoVSCC (P = .001). In conclusion, HPV‐dependent and ‐independent vulvar carcinogenesis is characterized by distinct CNA patterns at the VIN stage, while more comparable patterns are present at the cancer stage. Cancer risk in VIN seems to be reflected by the extent of CNA, in particular chromosome 1 gain in HPV‐positive cases.

Abstract Background Current normalization methods for RNA-sequencing data allow either for intersample comparison to identify differentially expressed (DE) genes or for intrasample comparison for the discovery and validation of gene signatures. Most studies on optimization of normalization methods typically use simulated data to validate methodologies. We describe a new method, GeTMM, which allows for both inter- and intrasample analyses with the same normalized data set. We used actual (i.e. not simulated) RNA-seq data from 263 colon cancers (no biological replicates) and used the same read count data to compare GeTMM with the most commonly used normalization methods (i.e. TMM (used by edgeR), RLE (used by DESeq2) and TPM) with respect to distributions, effect of RNA quality, subtype-classification, recurrence score, recall of DE genes and correlation to RT-qPCR data. Results We observed a clear benefit for GeTMM and TPM with regard to intrasample comparison while GeTMM performed similar to TMM and RLE normalized data in intersample comparisons. Regarding DE genes, recall was found comparable among the normalization methods, while GeTMM showed the lowest number of false-positive DE genes. Remarkably, we observed limited detrimental effects in samples with low RNA quality. Conclusions We show that GeTMM outperforms established methods with regard to intrasample comparison while performing equivalent with regard to intersample normalization using the same normalized data. These combined properties enhance the general usefulness of RNA-seq but also the comparability to the many array-based gene expression data in the public domain.

Abstract Background Primary testing for high-risk HPV (hrHPV) is increasingly implemented in cervical cancer screening programs. Many hrHPV-positive women, however, harbor clinically irrelevant infections, demanding additional disease markers to prevent over-referral and over-treatment. Most promising biomarkers reflect molecular events relevant to the disease process that can be measured objectively in small amounts of clinical material, such as miRNAs. We previously identified eight miRNAs with altered expression in cervical precancer and cancer due to either methylation-mediated silencing or chromosomal alterations. In this study, we evaluated the clinical value of these eight miRNAs on cervical scrapes to triage hrHPV-positive women in cervical screening. Results Expression levels of the eight candidate miRNAs in cervical tissue samples (n = 58) and hrHPV-positive cervical scrapes from a screening population (n = 187) and cancer patients (n = 38) were verified by quantitative RT-PCR. In tissue samples, all miRNAs were significantly differentially expressed (p

Abstract Background Prediction in high dimensional settings is difficult due to the large number of variables relative to the sample size. We demonstrate how auxiliary ‘co-data’ can be used to improve the performance of a Random Forest in such a setting. Results Co-data are incorporated in the Random Forest by replacing the uniform sampling probabilities that are used to draw candidate variables by co-data moderated sampling probabilities. Co-data here are defined as any type information that is available on the variables of the primary data, but does not use its response labels. These moderated sampling probabilities are, inspired by empirical Bayes, learned from the data at hand. We demonstrate the co-data moderated Random Forest (CoRF) with two examples. In the first example we aim to predict the presence of a lymph node metastasis with gene expression data. We demonstrate how a set of external p-values, a gene signature, and the correlation between gene expression and DNA copy number can improve the predictive performance. In the second example we demonstrate how the prediction of cervical (pre-)cancer with methylation data can be improved by including the location of the probe relative to the known CpG islands, the number of CpG sites targeted by a probe, and a set of p-values from a related study. Conclusion The proposed method is able to utilize auxiliary co-data to improve the performance of a Random Forest.

Cervical cancer is initiated by high-risk types of the human papillomavirus (hrHPV) and develops via precursor stages, called cervical intraepithelial neoplasia (CIN). High-grade CIN lesions are considered true precancerous lesions when the viral oncogenes E6 and E7 are aberrantly expressed in the dividing cells. This results in abolishment of normal cell cycle control via p53 and pRb degradation. However, it has become clear that these viral oncogenes possess additional oncogenic properties, including interference with the DNA methylation machinery and mitotic checkpoints. Identification of the resulting molecular events leading to high-grade neoplasia will 1) increase our understanding of cervical carcinogenesis, 2) yield biomarkers for early diagnosis, and 3) identify therapeutic targets for HPV-induced (pre) cancerous lesions.This review will briefly summarise current advances in our understanding of the molecular alterations in the host cell genome that occur during HPV-induced carcinogenesis.

Squamous cell carcinoma (SCC) and adenocarcinoma (AC) represent the major cervical cancer histotypes. Both histotypes are caused by infection with high-risk HPV (hrHPV) and are associated with deregulated microRNA expression. Histotype-dependent expression has been observed for miR-9-5p, showing increased expression in SCC and low expression in AC. Here, we studied the regulation and functionality of miR-9-5p in cervical SCCs and ACs using cervical tissue samples and hrHPV-containing cell lines. Expression and methylation analysis of cervical tissues revealed that low levels of miR-9-5p in ACs are linked to methylation of its precursor genes, particularly miR-9-1. Stratification of tissue samples and hrHPV-containing cell lines suggested that miR-9-5p depends on both histotype and hrHPV type, with higher expression in SCCs and HPV16-positive cells. MiR-9-5p promoted cell viability and anchorage independence in cervical cancer cell lines SiHa (SCC, HPV16) and CaSki (metastasized SCC, HPV16), while it played a tumor suppressive role in HeLa (AC, HPV18). TWIST1, a transcription factor involved in epithelial-to-mesenchymal transition (EMT), was established as a novel miR-9-5p target. Our results show that miR-9-5p plays a dual role in cervical cancer in a histotype- and hrHPV type-dependent manner. MiR-9-5p mediated silencing of TWIST1 suggests two distinct mechanisms towards EMT in cervical cancer.

Summary: CGHcall achieves high calling accuracy for array CGH data by effective use of breakpoint information from segmentation and by inclusion of several biological concepts that are ignored by existing algorithms. The algorithm is validated for simulated and verified real array CGH data. By incorporating more than three classes, CGHcall improves detection of single copy gains and amplifications. Moreover, it allows effective inclusion of chromosome arm information.Availability: An R-package (GUI), a manual and an example data set are available at http://www.few.vu.nl/~mavdwiel/CGHcall.html.Contact:mark.vdwiel@vumc.nlSupplementary information: Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]