Within recent years, many precision cancer medicine initiatives have been developed. Most of these have focused on solid cancers, while the potential of precision medicine for patients with hematological malignancies, especially in the relapse situation, are less elucidated. Here, we present a demographic unbiased and observational prospective study at Aalborg University Hospital Denmark, referral site for 10% of the Danish population. We developed a hematological precision medicine workflow based on sequencing analysis of whole exome tumor DNA and RNA. All steps involved are outlined in detail, illustrating how the developed workflow can provide relevant molecular information to multidisciplinary teams. A group of 174 hematological patients with progressive disease or relapse was included in a non-interventional and population-based study, of which 92 patient samples were sequenced. Based on analysis of small nucleotide variants, copy number variants, and fusion transcripts, we found variants with potential and strong clinical relevance in 62% and 9.5% of the patients, respectively. The most frequently mutated genes in individual disease entities were in concordance with previous studies. We did not find tumor mutational burden or micro satellite instability to be informative in our hematologic patient cohort.

Thanks to personalized medicine trends and collaborations between industry, clinical research groups and regulatory agencies, next generation sequencing (NGS) is turning into a common practice faster than one could have originally expected. When considering clinical applications of NGS in oncology, a rapid workflow for DNA extraction from formalin-fixed paraffin-embedded (FFPE) tissue samples, as well as producing high quality library preparation, can be real challenges. Here we consider these targets and how applying effective automation technology to NGS workflows may help improve yield, timing and quality-control. We firstly evaluated DNA recovery from archived FFPE blocks from three different manual extraction methods and two automated extraction workstations. The workflow was then implemented to somatic (lung/colon panel) and germline (BRCA1/2) library preparation for NGS analysis exploiting two automated workstations. All commercial kits gave good results in terms of DNA yield and quality. On the other hand, the automated workstation workflow has been proven to be a valid automatic extraction system to obtain high quality DNA suitable for NGS analysis (lung/colon Ampli-seq panel). Moreover, it can be efficiently integrated with an open liquid handling platform to provide high-quality libraries from germline DNA with more reproducibility and high coverage for targeted sequences in less time (BRCA1/2). The introduction of automation in routine workflow leads to an improvement of NGS standardization and increased scale up of sample preparations, reducing labor and timing, with optimization of reagents and management.

Next Generation Sequencing (NGS)-based methods are high-throughput and cost-effective molecular genetic diagnostic tools. Targeted gene panel and whole exome sequencing (WES) are applied in clinical practice for assessing mutations of pheochromocytoma/paraganglioma (PPGL) associated genes, but the best strategy is debated. Germline mutations of at the least 18 PPGL genes are present in approximately 20-40% of patients, thus molecular genetic testing is recommended in all cases. We aimed to evaluate the analytical and clinical performances of NGS methods for mutation detection of PPGL-associated genes. WES (three different library preparation and bioinformatics workflows) and an in-house, hybridization based gene panel (endocrine-onco-gene-panel- ENDOGENE) was evaluated on 37 (20 WES and 17 ENDOGENE) samples with known variants. After optimization of the bioinformatic workflow, 61 additional samples were tested prospectively. All clinically relevant variants were validated with Sanger sequencing. Target capture of PPGL genes differed markedly between WES platforms and genes tested. All known variants were correctly identified by all methods, but methods of library preparations, sequencing platforms and bioinformatical settings significantly affected the diagnostic accuracy. The ENDOGENE panel identified several pathogenic mutations and unusual genotype-phenotype associations suggesting that the whole panel should be used for identification of genetic susceptibility of PPGL.

Immunopeptidomics is used to identify novel epitopes for (therapeutic) vaccination strategies in cancer and infectious disease. Various false discovery rates (FDRs) are applied in the field when converting liquid chromatography-tandem mass spectrometry (LC-MS/MS) spectra to peptides. Subsequently, large efforts have recently been made to rescue peptides of lower confidence. However, it remains unclear what the overall relation is between the FDR threshold and the percentage of obtained HLA-binders. We here directly evaluated the effect of varying FDR thresholds on the resulting immunopeptidomes of HLA-eluates from human cancer cell lines and primary hepatocyte isolates using HLA-binding algorithms. Additional peptides obtained using less stringent FDR-thresholds, although generally derived from poorer spectra, still contained a high amount of HLA-binders and confirmed recently developed tools that tap into this pool of otherwise ignored peptides. Most of these peptides were identified with improved confidence when cell input was increased, supporting the validity and potential of these identifications. Altogether, our data suggest that increasing the FDR threshold for peptide identification in conjunction with data filtering by HLA-binding prediction, is a valid and highly potent method to more efficient exhaustion of immunopeptidome datasets for epitope discovery and reveals the extent of peptides to be rescued by recently developed algorithms.

There is increased interest in the use of magnetic resonance imaging (MRI) for guiding radiation therapy (RT) in the clinical setting. In this regard, preclinical studies can play an important role in understanding the added value of MRI in RT planning. In the present study, we developed and validated a clinically relevant integrated workflow for MRI-guided volumetric arc therapy (VMAT) in a VX2 rabbit neck tumor model of HNSCC. In addition to demonstrating safety and feasibility, we examined the therapeutic impact of MR-guided VMAT using a single high dose to obtain proof-of-concept and compared the response to conventional 2D-RT. Contrast-enhanced MRI (CE-MRI) provided excellent soft tissue contrast for accurate tumor segmentation for VMAT. Notably, MRI-guided RT enabled improved tumor targeting ability and minimal dose to organs at risk (OAR) compared to 2D-RT, which resulted in notable morbidity within a few weeks of RT. Our results highlight the value of integrating MRI into the workflow for VMAT for improved delineation of tumor anatomy and optimal treatment planning. The model combined with the multimodal imaging approach can serve as a valuable platform for the conduct of preclinical RT trials.

A multicenter study was performed to determine an optimal workflow for liquid biopsy in a clinical setting. In total, 549 plasma samples from 234 non-small cell lung cancer (NSCLC) patients were collected. Epidermal Growth Factor Receptor (EGFR) circulating cell-free tumor DNA (ctDNA) mutational analysis was performed using digital droplet PCR (ddPCR). The influence of (pre-) analytical variables on ctDNA analysis was investigated. Sensitivity of ctDNA analysis was influenced by an interplay between increased plasma volume (p < 0.001) and short transit time (p = 0.018). Multistep, high-speed centrifugation both increased plasma generation (p < 0.001) and reduced genomic DNA (gDNA) contamination. Longer transit time increased the risk of hemolysis (p < 0.001) and low temperatures were shown to have a negative effect. Metastatic sites were found to be strongly associated with ctDNA detection (p < 0.001), as well as allele frequency (p = 0.034). Activating mutations were detected in a higher concentration and allele frequency compared to the T790M mutation (p = 0.003, and p = 0.002, respectively). Optimization of (pre-) analytical variables is key to successful ctDNA analysis. Sufficient plasma volumes without hemolysis or gDNA contamination can be achieved by using multistep, high-speed centrifugation, coupled with short transit time and temperature regulation. Metastatic site location influenced ctDNA detection. Finally, ctDNA levels might have further value in detecting resistance mechanisms.

On December 2019, an outbreak of atypical pneumonia, known as COVID-19, was identified in Wuhan, China. This disease, characterized by the rapid human-to-human transmission of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread rapidly in more than 200 countries. Northern Italy's regions have been hit hard in terms of deaths. Here, we report the experience of the Pathology Department of the Fondazione IRCCS Istituto Nazionale Tumori (INT) in Milan, the first Italian public cancer center, in the period of the lockdown that took place in Lombardy from March to May 2020.

In most diagnostic laboratories, targeted next-generation sequencing (NGS) is currently the default assay for the detection of somatic variants in solid as well as haematological tumours. Independent of the method, the final outcome is a list of variants that differ from the human genome reference sequence of which some may relate to the establishment of the tumour in the patient. A critical point towards a uniform patient management is the assignment of the biological contribution of each variant to the malignancy and its subsequent clinical impact in a specific malignancy. These so-called biological and clinical classifications of somatic variants are currently not standardized and are vastly dependent on the subjective analysis of each laboratory. This subjectivity can thus result in a different classification and subsequent clinical interpretation of the same variant. Therefore, the ComPerMed panel of Belgian experts in cancer diagnostics set up a working group with the goal to harmonize the biological classification and clinical interpretation of somatic variants detected by NGS. This effort resulted in the establishment of a uniform, two-level classification workflow system that should enable high consistency in diagnosis, prognosis, treatment and follow-up of cancer patients. Variants are first classified into a tumour-independent biological five class system and subsequently in a four tier ACMG clinical classification. Here, we describe the ComPerMed workflow in detail including examples for each step of the pipeline. Moreover, this workflow can be implemented in variant classification software tools enabling automatic reporting of NGS data, independent of panel, method or analysis software.

Glioblastomas (GBMs) are high-grade malignancies with a poor prognosis. The current standard of care for GBM is maximal surgical resection followed by radiotherapy and chemotherapy. Despite all these treatments, the overall survival is still limited, with a median of 15 months. For patients harboring inoperable GBM, due to the anatomical location of the tumor or poor general condition of the patient, the life expectancy is even worse. The challenge of managing GBM is therefore to improve the local control especially for non-surgical patients. Interstitial photodynamic therapy (iPDT) is a minimally invasive treatment relying on the interaction of light, a photosensitizer and oxygen. In the case of brain tumors, iPDT consists of introducing one or several optical fibers in the tumor area, without large craniotomy, to illuminate the photosensitized tumor cells. It induces necrosis and/or apoptosis of the tumor cells, and it can destruct the tumor vasculature and produces an acute inflammatory response that attracts leukocytes. Interstitial PDT has already been applied in the treatment of brain tumors with very promising results. However, no standardized procedure has emerged from previous studies. Herein, we propose a standardized and reproducible workflow for the clinical application of iPDT to GBM. This workflow, which involves intraoperative imaging, a dedicated treatment planning system (TPS) and robotic assistance for the implantation of stereotactic optical fibers, represents a key step in the deployment of iPDT for the treatment of GBM. This end-to-end procedure has been validated on a phantom in real operating room conditions. The thorough description of a fully integrated iPDT workflow is an essential step forward to a clinical trial to evaluate iPDT in the treatment of GBM.

Tools for microRNA (miR) sequencing data analyses are broadly used in biomedical research. However, the complexity of computational approaches still remains a challenge for biologists with scarce experience in data analytics and bioinformatics. Here, we present miRGalaxy, a Galaxy-based framework for comprehensive analysis of miRs and their sequence variants-miR isoforms (isomiRs). Though isomiRs are commonly reported in deep-sequencing experiments, their detailed structure complexity and specific differential expression (DE) remain not fully examined by the majority of the available analysis tools. miRGalaxy encompasses biologist-user-friendly tools and workflows dedicated to the analysis of the isomiR-ome and its complex behavior in various biological samples. miRGalaxy is developed as a modular, accessible, redistributable, shareable, and user-friendly framework for scientists working with small RNA (sRNA)-seq data. Due to its modular workflow, advanced users can customize the steps and tools for their needs. In addition, the framework provides an analysis report where the significant output results are summarized in charts and visualizations. miRGalaxy can be accessed via preconfigured Docker image flavor and a Toolshed installation if the user already has a running Galaxy instance. Over the last decade, studies on the expression of miRs and isomiRs in normal and deregulated tissues have led to the discovery of their potential as diagnostic biomarkers. The detection of miRs in biofluids further expanded the exploration of the miR repertoire as a source of liquid biopsy biomarkers. Here we show the miRGalaxy framework application for in-depth analysis of the sRNA-seq data from two different biofluids, milk and plasma, to identify, annotate, and discover specific differentially expressed miRs and isomiRs.

Tobacco is the primary etiologic agent in worsened lung squamous cell carcinoma (LUSC) outcomes. Meanwhile, it has been shown that etiologic agents alter enhancer RNAs (eRNAs) expression. Therefore, we aimed to identify the effects of tobacco and electronic cigarette (e-cigarette) use on eRNA expression in relation to LUSC outcomes. We extracted eRNA counts from RNA-sequencing data of tumor/adjacent normal tissue and before/after e-cigarette tissue from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO), respectively. Tobacco-mediated LUSC eRNAs were correlated to patient survival, clinical variables, and immune-associated elements. eRNA expression was also correlated to mutation rates through the Repeated Evaluation of Variables Conditional Entropy and Redundance (REVEALER) algorithm and methylated sites through methylationArrayAnalysis. Differential expression analysis was then completed for the e-cigarette data to compare with key tobacco-mediated eRNAs. We identified 684 downregulated eRNAs and 819 upregulated eRNAs associated with tobacco-mediated LUSC, specifically, with the cancer pathological stage. We also observed a decrease in immune cell abundance in tobacco-mediated LUSC. Yet, we found an increased association of eRNA expression with immune cell abundance in tobacco-mediated LUSC. We identified 16 key eRNAs with significant correlations to 8 clinical variables, implicating these eRNAs in LUSC malignancy. Furthermore, we observed that these 16 eRNAs were highly associated with chromosomal alterations and reduced CpG site methylation. Finally, we observed large eRNA expression upregulation with e-cigarette use, which corresponded to the upregulation of the 16 key eRNAs. Our findings provide a novel mechanism by which tobacco and e-cigarette smoke influences eRNA interactions to promote LUSC pathogenesis and provide insight regarding disease progression at a molecular level.

Our aim was to determine the prevalence, prognostic and predictive role of germline pathogenic/likely pathogenic variants (P/LPVs) in cancer predisposing genes in patients with pancreatic ductal adenocarcinoma (PDAC). Germline testing of 62 cancer susceptibility genes was performed on unselected patients diagnosed from 02/2003 to 01/2020 with PDAC, treated at Hellenic Cooperative Oncology Group (HeCOG)-affiliated Centers. The main endpoints were prevalence of P/LPVs and overall survival (OS). P/LPVs in PDAC-associated and homologous recombination repair (HRR) genes were identified in 22 (4.0%) and 42 (7.7%) of 549 patients, respectively. P/LPVs were identified in 16 genes, including ATM (11, 2.0%) and BRCA2 (6, 1.1%), while 19 patients (3.5%) were heterozygotes for MUTYH P/LPVs and 9 (1.6%) carried the low-risk allele, CHEK2 p.(Ile157Thr). Patients carrying P/LPVs had improved OS compared to non-carriers (22.6 vs. 13.9 months, p = 0.006). In multivariate analysis, there was a trend for improved OS in P/LPV carriers (p = 0.063). The interaction term between platinum exposure and mutational status of HRR genes was not significant (p-value = 0.35). A significant proportion of patients with PDAC carries clinically relevant germline P/LPVs, irrespectively of age, family history or disease stage. The predictive role of these P/LPVs has yet to be defined. ClinicalTrials.gov Identifier: NCT03982446.

While the clinical importance of CD8+ and CD3+ cells in colorectal cancer (CRC) is well established, the impact of other immune cell subsets is less well described. We sought to provide a detailed overview of the immune landscape of CRC in the largest study to date in terms of patient numbers and in situ analyzed immune cell types. Tissue microarrays from 536 patients were stained using multiplexed immunofluorescence panels, and fifteen immune cell subclasses, representing adaptive and innate immunity, were analyzed. Overall, therapy-naïve CRC patients clustered into an 'inflamed' and a 'desert' group. Most T cell subsets and M2 macrophages were enriched in the right colon (p-values 0.046-0.004), while pDC cells were in the rectum (p = 0.008). Elderly patients had higher infiltration of M2 macrophages (p = 0.024). CD8+ cells were linked to improved survival in colon cancer stages I-III (q = 0.014), while CD4+ cells had the strongest impact on overall survival in metastatic CRC (q = 0.031). Finally, we demonstrated repopulation of the immune infiltrate in rectal tumors post radiation, following an initial radiation-induced depletion. This study provides a detailed analysis of the in situ immune landscape of CRC paving the way for better diagnostics and providing hints to better target the immune microenvironment.

Circulating tumor cells (CTCs) serve as crucial metastatic precursor cells, but their study in animal models has been hindered by their low numbers. To address this challenge, we present DanioCTC, an innovative xenograft workflow that overcomes the scarcity of patient-derived CTCs in animal models. By combining diagnostic leukapheresis (DLA), the Parsortix microfluidic system, flow cytometry, and the CellCelector setup, DanioCTC effectively enriches and isolates CTCs from metastatic breast cancer (MBC) patients for injection into zebrafish embryos. Validation experiments confirmed that MDA-MB-231 cells, transplanted following the standard protocol, localized frequently in the head and blood-forming regions of the zebrafish host. Notably, when MDA-MB-231 cells spiked (i.e., supplemented) into DLA aliquots were processed using DanioCTC, the cell dissemination patterns remained consistent. Successful xenografting of CTCs from a MBC patient revealed their primary localization in the head and trunk regions of zebrafish embryos. DanioCTC represents a major step forward in the endeavors to study the dissemination of individual and rare patient-derived CTCs, thereby enhancing our understanding of metastatic breast cancer biology and facilitating the development of targeted interventions in MBC. Summary statement: DanioCTC is a novel workflow to inject patient-derived CTCs into zebrafish, enabling studies of the capacity of these rare tumor cells to induce metastases.

Almost 25% of lung cancers (LCs) occur in never-smokers. LC inflammatory profile, based on plasma C-reactive protein levels (CRP), predicts mortality, independently by smoking-status. We hypothesized that: CRP could be associated with tumor immune contexture (TIC) in never-smokers and both these two parameters may improve their prognosis. Sixty-eight never-smokers LC patients with high or low CRP were selected. The programmed cell death protein 1 (PD-1) and its ligand (PD-L1), the human leukocyte antigens (HLA-DR and HLA-I), CD8, CD4, CD3, CD33, CD163, and CD68 were evaluated by immunohistochemistry on surgical samples given TIC evaluation. The classification model based on TIC scores was generated by Classification and Regression Tree analysis. Tumor mutational burden was evaluated by targeted next-generation sequencing. Exclusively high CRP (H-CRP) subset showed PD-L1 expression in 35% of LC as well as lower HLA-I and HLA-DR in their stromal cells. CD3, CD4, CD8, HLA-I, HLA-DR tumor cells staining were associated with a "low inflammatory profile" subset. CRP and LC immune profiles drive clinical outcome: 5-year survival 88% against 8% was associated with low and high-risk profiles (p < 0.0001). Clinical outcome prediction in never-smoker LC patients may be improved by both CRP and tumor immune contexture evaluation.

Analysis of circulating tumor cells (CTCs) from blood samples provides a non-invasive approach for early cancer detection. However, the rarity of CTCs makes it challenging to establish assays with the required sensitivity and specificity. We combine a highly sensitive CTC capture assay exploiting the cancer cell binding recombinant malaria VAR2CSA protein (rVAR2) with the detection of colon-related mRNA transcripts (USH1C and CKMT1A). Cancer cell transcripts are detected by RT-qPCR using proprietary Target Enrichment Long-probe Quantitative Amplified Signal (TELQAS) technology. We validate each step of the workflow using colorectal cancer (CRC) cell lines spiked into blood and compare this with antibody-based cell detection. USH1C and CKMT1A are expressed in healthy colon tissue and CRC cell lines, while only low-level expression can be detected in healthy white blood cells (WBCs). The qPCR reaction shows a near-perfect amplification efficiency for all primer targets with minimal interference of WBC cDNA. Spike-in of 10 cancer cells in 3 mL blood can be detected and statistically separated from control blood using the RT-qPCR assay after rVAR2 capture (p < 0.01 for both primer targets, Mann-Whitney test). Our results provide a validated workflow for highly sensitive detection of magnetically enriched cancer cells.

Circulating tumor cells (CTCs) are promising tools for risk prediction and the monitoring of response to therapy in cancer patients. Within the EU/IMI CANCER-ID consortium, we validated CTC enrichment systems for future inclusion into clinical trials. Due to the known heterogeneity of markers expressed on CTCs, we tested the Parsortix® system (ANGLE plc) which enables label-independent CTC enrichment from whole blood based on increased size and deformability of these tumor cells compared to leukocytes. We performed extensive comparisons both with spiked-in blood models (i.e., MDA-MB-468 tumor cell line cells spiked at very low concentration into blood from healthy donors) and validated the protocol on actual clinical samples from breast, lung, and gastrointestinal cancer patients to define optimal conditions for CTC enrichment. Multiple parameters including cassette gap, separation pressure, and cell fixatives were compared in parallel. Also, the compatibility of blood collection tubes with whole genome amplification of isolated tumor cells was demonstrated and we furthermore established a workflow for semi-automated CTC detection using a quantitative cell imager. The established workflow will contribute to supporting the use of size-based CTC enrichment platforms in clinical trials testing the clinical validity and utility of CTCs for personalized medicine.

Subungual melanoma (SUM) is a rare type of malignant melanoma that arises beneath the nails. SUM is categorized as a type of acral melanoma (AM), which occurs on the hands and feet. SUM is an aggressive type of cutaneous melanoma that is most common among Asian patients. Recent studies reveal that SUM and AM might have different molecular characteristics. Treatment of melanoma relies on analysis of both clinical and molecular data. Therefore, the clinical and molecular characteristics of SUM need to be established, especially during metastasis. To define the mutation profiles of SUM and compare them with those of AM, we performed next-generation sequencing of primary and metastatic tumors of SUM and AM patients. Subungual location was a better independent prognostic factor than acral location for better overall survival (p = 0.001). Patients with SUM most commonly had the triple wild-type (75%) driven by GNAQ (58%) and KIT (25%) mutations, whereas patients with AM had BRAF (28.6%) and RAF (14.3%) molecular types of mutations. Single-nucleotide variations (SNVs) were more common in SUM than in AM, whereas copy number alterations (CNAs) were more common metastatic lesions of AM. Metastatic tumors in patients with SUM and AM showed increases in CNAs (43% and 80%, respectively), but not in SNVs. The number of CNAs increased during metastasis. When compared with AM, SUM has distinct clinical and molecular characteristics.

An emerging theory about racial differences in cancer risk and outcomes is that psychological and social stressors influence cellular stress responses; however, limited empirical data are available on racial differences in cellular stress responses among men who are at risk for adverse prostate cancer outcomes. In this study, we undertook a systems approach to examine molecular profiles and cellular stress responses in an important segment of African American (AA) and European American (EA) men: men undergoing prostate biopsy. We assessed the prostate transcriptome with a single biopsy core via high throughput RNA sequencing (RNA-Seq). Transcriptomic analyses uncovered impacted biological pathways including PI3K-Akt signaling pathway, Neuroactive ligand-receptor interaction pathway, and ECM-receptor interaction. Additionally, 187 genes mapping to the Gene Ontology (GO) terms RNA binding, structural constituent of ribosome, SRP-dependent co-translational protein targeting to membrane and the biological pathways, translation, L13a-mediated translational silencing of Ceruloplasmin expression were differentially expressed (DE) between EA and AA. This signature allowed separation of AA and EA patients, and AA patients with the most severe clinical characteristics. AA patients with elevated expression levels of this genomic signature presented with higher Gleason scores, a greater number of positive core biopsies, elevated dehydroepiandrosterone sulfate levels and serum vitamin D deficiency. Protein-protein interaction (PPI) network analysis revealed a high degree of connectivity between these 187 proteins.

Adult T-cell leukemia/lymphoma (ATL) is an intractable disease affecting nearly 4% of Human T-cell Leukemia Virus Type 1 (HTLV-1) carriers. Acute ATL has a unique interaction with bone characterized by aggressive bone invasion, osteolytic metastasis, and hypercalcemia. We hypothesized that dual tumor and bone-targeted therapies would decrease tumor burden in bone, the incidence of metastasis, and ATL-associated osteolysis. Our goal was to evaluate dual targeting of both ATL bone tumors and the bone microenvironment using an anti-tumor HDACi (AR-42) and an osteoclast inhibitor (zoledronic acid, Zol), alone and in combination. Our results showed that AR-42, Zol, and AR-42/Zol significantly decreased the viability of multiple ATL cancer cell lines in vitro. Zol and AR-42/Zol decreased tumor growth in vivo. Zol ± AR-42 significantly decreased ATL-associated bone resorption and promoted new bone formation. AR-42-treated ATL cells had increased mRNA levels of PTHrP, ENPP2 (autotaxin) and MIP-1α, and TAX viral gene expression. AR-42 alone had no significant effect on tumor growth or osteolysis in mice. These findings indicate that Zol adjuvant therapy has the potential to reduce growth of ATL in bone and its associated osteolysis.