Comprehensive genomic and epigenomic analysis in cancer of unknown primary guides molecularly-informed therapies despite heterogeneity

MUC16/CA125 in cancer: new advances

MUC16/CA125 is a common diagnostic marker for many types of cancer. However, due to the widespread expression of MUC16 in cancer, its specificity and sensitivity as a target are poor, which severely limits its clinical application. In recent years, various studies have shown that the clinical application potential of MUC16/CA125 has been greatly improved. The update of detection technology improves the accuracy and range of detection, and improves the early diagnosis rate of cancer. Targeting MUC16/CA125 is an important strategy for tumor therapy. Targeting residual amino acids, n-glycoylation structures or other targets on the surface of MUC16 cells can greatly improve the accuracy of detection and therapy. The new drug delivery method broke through the original technical shackles, targeted MUC16 positive cells more specifically and improved the drug efficacy. In this paper, the technological advances in detecting and identifying MUC16 targets and the great progress in cancer screening and treatment based on MUC16 as a target are described in detail, revealing the great potential of MUC16 as a target in cancer screening and treatment, and illustrating the potential clinical application value of MUC16.

Factors for a broad technology assessment of comprehensive genomic profiling in advanced cancer, a systematic review

Comprehensive Genomic Profiling (CGP) allows for the identification of many targets. Reimbursement decision-making is, however, challenging because besides the health benefits of on-label treatments and costs, other factors related to diagnostic and treatment pathways may also play a role. The aim of this study was to identify which other factors are relevant for the technology assessment of CGP and to summarize the available evidence for these factors. After a scoping search and two expert sessions, five factors were identified: feasibility, test journey, wider implications of diagnostic results, organisation of laboratories, and "scientific spillover". Subsequently, a systematic search identified 83 studies collecting mainly evidence for the factors "test journey" and "wider implications of diagnostic results". Its nature was, however, of limited value for decision-making. We recommend the use of comparative strategies, uniformity in outcome definitions, and the inclusion of a comprehensive set of factors in future evidence generation.

Exploring the molecular landscape of cancer of unknown primary: A comparative analysis with other metastatic cancers

Cancer of unknown primary (CUP) tumors are biologically very heterogeneous, which complicates stratification of patients for treatment. Consequently, these patients face limited treatment options and a poor prognosis. With this study, we aim to expand on the current knowledge of CUP biology by analyzing two cohorts: a well-characterized cohort of 44 CUP patients, and 213 metastatic patients with known primary. These cohorts were treated at the same institution and characterized by identical molecular assessments. Through comparative analysis of genomic and transcriptomic data, we found that CUP tumors were characterized by high expression of immune-related genes and pathways compared to other metastatic tumors. Moreover, CUP tumors uniformly demonstrated high levels of tumor-infiltrating leukocytes and circulating T cells, indicating a strong immune response. Finally, the genetic landscape of CUP tumors resembled that of other metastatic cancers and demonstrated mutations in established cancer genes. In conclusion, CUP tumors possess a distinct immunophenotype that distinguishes them from other metastatic cancers. These results may suggest an immune response in CUP that facilitates metastatic tumor growth while limiting growth of the primary tumor.

A machine learning-based method for feature reduction of methylation data for the classification of cancer tissue origin

BACKGROUND

Genome DNA methylation profiling is a promising yet costly method for cancer classification, involving substantial data. We developed an ensemble learning model to identify cancer types using methylation profiles from a limited number of CpG sites.

METHODS

Analyzing methylation data from 890 samples across 10 cancer types from the TCGA database, we utilized ANOVA and Gain Ratio to select the most significant CpG sites, then employed Gradient Boosting to reduce these to just 100 sites.

RESULTS

This approach maintained high accuracy across multiple machine learning models, with classification accuracy rates between 87.7% and 93.5% for methods including Extreme Gradient Boosting, CatBoost, and Random Forest. This method effectively minimizes the number of features needed without losing performance, helping to classify primary organs and uncover subgroups within specific cancers like breast and lung.

CONCLUSIONS

Using a gradient boosting feature selector shows potential for streamlining methylation-based cancer classification.

The WERA cancer center matrix: Strategic management of patient access to precision oncology in a large and mostly rural area of Germany

PURPOSE

Providing patient access to precision oncology (PO) is a major challenge of clinical oncologists. Here, we provide an easily transferable model from strategic management science to assess the outreach of a cancer center.

METHODS

As members of the German WERA alliance, the cancer centers in Würzburg, Erlangen, Regensburg and Augsburg merged care data regarding their geographical impact. Specifically, we examined the provenance of patients from WERA´s molecular tumor boards (MTBs) between 2020 and 2022 (n = 2243). As second dimension, we added the provenance of patients receiving general cancer care by WERA. Clustering our catchment area along these two dimensions set up a four-quadrant matrix consisting of postal code areas with referrals towards WERA. These areas were re-identified on a map of the Federal State of Bavaria.

RESULTS

The WERA matrix overlooked an active screening area of 821 postal code areas - representing about 50 % of Bavaria´s spatial expansion and more than six million inhabitants. The WERA matrix identified regions successfully connected to our outreach structures in terms of subsidiarity - with general cancer care mainly performed locally but PO performed in collaboration with WERA. We also detected postal code areas with a potential PO backlog - characterized by high levels of cancer care performed by WERA and low levels or no MTB representation.

CONCLUSIONS

The WERA matrix provided a transparent portfolio of postal code areas, which helped assessing the geographical impact of our PO program. We believe that its intuitive principle can easily be transferred to other cancer centers.

Metastatic renal cell carcinoma with occult primary: a multicenter prospective cohort

Metastatic carcinoma of presumed renal origin (rCUP) has recently emerged as a new entity within the heterogeneous entity of Cancers of Unknown Primary (CUP) but their biological features and optimal therapeutic management remain unknown. We report the molecular characteristics and clinical outcome of a series of 25 rCUP prospectively identified within the French National Multidisciplinary Tumor Board for CUP. This cohort strongly suggests that rCUP share similarities with common RCC subtypes and benefit from renal-tailored systemic treatment. This study highlights the importance of integrating clinical and molecular data for optimal diagnosis and management of CUP.

Recommendations for the use of next-generation sequencing (NGS) for patients with advanced cancer in 2024: a report from the ESMO Precision Medicine Working Group

BACKGROUND

Advancements in the field of precision medicine have prompted the European Society for Medical Oncology (ESMO) Precision Medicine Working Group to update the recommendations for the use of tumour next-generation sequencing (NGS) for patients with advanced cancers in routine practice.

METHODS

The group discussed the clinical impact of tumour NGS in guiding treatment decision using the ESMO Scale for Clinical Actionability of molecular Targets (ESCAT) considering cost-effectiveness and accessibility.

RESULTS

As for 2020 recommendations, ESMO recommends running tumour NGS in advanced non-squamous non-small-cell lung cancer, prostate cancer, colorectal cancer, cholangiocarcinoma, and ovarian cancer. Moreover, it is recommended to carry out tumour NGS in clinical research centres and under specific circumstances discussed with patients. In this updated report, the consensus within the group has led to an expansion of the recommendations to encompass patients with advanced breast cancer and rare tumours such as gastrointestinal stromal tumours, sarcoma, thyroid cancer, and cancer of unknown primary. Finally, ESMO recommends carrying out tumour NGS to detect tumour-agnostic alterations in patients with metastatic cancers where access to matched therapies is available.

CONCLUSION

Tumour NGS is increasingly expanding its scope and application within oncology with the aim of enhancing the efficacy of precision medicine for patients with cancer.

PD-L1 expression and microsatellite instability (MSI) in cancer of unknown primary site

BACKGROUND

Cancer of unknown primary site (CUP) is a heterogeneous group of tumors for which the origin remains unknown. Clinical outcomes might be influenced by regulatory processes in its microenvironment. Microsatellite instability (MSI) is a predictive biomarker for cancer immunotherapy and its status, as well as co-occurrence with PD-L1 expression, is poorly evaluated. We aim to evaluate the expression of PD-L1 and the status of MSI in CUP and their possible associations with clinical-pathological features.

METHODS

The combined positive score (CPS) PD-L1 expression was evaluated by immunohistochemistry. MSI status was assessed using a hexa-plex marker panel by polymerase chain reaction followed by fragment analysis.

RESULTS

Among the 166 cases, MSI analysis was conclusive in 120, with two cases being MSI positive (1.6%). PD-L1 expression was positive in 18.3% of 109 feasible cases. PD-L1 expression was significantly associated with non-visceral metastasis and a dominance of nodal metastasis. The median overall survival (mOS) was 3.7 (95% CI 1.6-5.8) months and patients who expressed PD-L1 achieved a better mOS compared to those who did not express PD-L1 (18.7 versus 3.0 months, p-value: < .001). ECOG-PS equal to or more than two and PD-L1 expression were independent prognostic factors in multivariate analysis (2.37 and 0.42, respectively).

CONCLUSION

PD-L1 is expressed in a subset (1/5) of patients with CUP and associated with improved overall survival, while MSI is a rare event. There is a need to explore better the tumor microenvironment as well as the role of immunotherapy to change such a bad clinical outcome.

[The collaborative project "Personalized medicine for oncology" (PM4Onco) as part of the Medical Informatics Initiative (MII)]

The collaborative project Personalized Medicine for Oncology (PM4Onco) was launched in 2023 as part of the National Decade against Cancer (NKD) and is executed within the Medical Informatics Initiative (MII). Its aim is to establish a sustainable infrastructure for the integration and use of data from clinical and biomedical research and therefore combines the experience and preliminary work of all four consortia of the MII and the leading oncology centers in Germany. The data provided by PM4Onco will be prepared in a suitable form to support decision making in molecular tumor boards. This concept and infrastructure will be extended to 23 participating partner sites and thus improve access to targeted therapies based on clinical information and analysis of molecular genetic alterations in tumors at different stages of the disease. This will help to improve the treatment and prognosis of tumor diseases.Clinical cancer registries are involved in the project to improve data quality through standardized documentation routines. Clinical experts advise on the expansion of the core datasets for personalized medicine (PM). Information on quality of life and treatment outcomes reported by patients in questionnaires, which is rarely collected outside of clinical trials, will make a significant contribution. Patient representatives are involved from the onset to ensure that the important perspective of patients is taken into account in the decision-making process. PM4Onco thus creates an alliance between the MII, oncological centers of excellence, clinical cancer registries, young scientists, patients, and citizens to strengthen and advance PM in cancer therapy.

MUC16: clinical targets with great potential

Mucin 16 (MUC16) is a membrane-bound mucin that is abnormally expressed or mutated in a variety of diseases, especially tumors, while being expressed in normal body epithelium. MUC16 and its extracellular components are often important cancer-related biomarkers. Abnormal expression of MUC16 promotes tumor progression through mesenchymal protein, PI3K/AKT pathway, JAK2/STAT3 pathway, ERK/FBW7/c-Myc, and other mechanisms, and plays an important role in the occurrence and development of tumors. In addition, MUC16 also helps tumor immune escape by inhibiting T cells and NK cells. Many drugs and trials targeting MUC16 have been developed, and MUC16 may be a new direction for future treatments. In this paper, the mechanism of action of MUC16 in the development of cancer, especially in the immune escape of tumor, is introduced in detail, indicating the potential of MUC16 in clinical treatment.

A cfDNA methylation-based tissue-of-origin classifier for cancers of unknown primary

Cancers of Unknown Primary (CUP) remains a diagnostic and therapeutic challenge due to biological heterogeneity and poor responses to standard chemotherapy. Predicting tissue-of-origin (TOO) molecularly could help refine this diagnosis, with tissue acquisition barriers mitigated via liquid biopsies. However, TOO liquid biopsies are unexplored in CUP cohorts. Here we describe CUPiD, a machine learning classifier for accurate TOO predictions across 29 tumour classes using circulating cell-free DNA (cfDNA) methylation patterns. We tested CUPiD on 143 cfDNA samples from patients with 13 cancer types alongside 27 non-cancer controls, with overall sensitivity of 84.6% and TOO accuracy of 96.8%. In an additional cohort of 41 patients with CUP CUPiD predictions were made in 32/41 (78.0%) cases, with 88.5% of the predictions clinically consistent with a subsequent or suspected primary tumour diagnosis, when available (23/26 patients). Combining CUPiD with cfDNA mutation data demonstrated potential diagnosis re-classification and/or treatment change in this hard-to-treat cancer group.

Head and neck cancer of unknown primary: unveiling primary tumor sites through machine learning on DNA methylation profiles

BACKGROUND

The unknown tissue of origin in head and neck cancer of unknown primary (hnCUP) leads to invasive diagnostic procedures and unspecific and potentially inefficient treatment options for patients. The most common histologic subtype, squamous cell carcinoma, can stem from various tumor primary sites, including the oral cavity, oropharynx, larynx, head and neck skin, lungs, and esophagus. DNA methylation profiles are highly tissue-specific and have been successfully used to classify tissue origin. We therefore developed a support vector machine (SVM) classifier trained with publicly available DNA methylation profiles of commonly cervically metastasizing squamous cell carcinomas (n = 1103) in order to identify the primary tissue of origin of our own cohort of squamous cell hnCUP patient's samples (n = 28). Methylation analysis was performed with Infinium MethylationEPIC v1.0 BeadChip by Illumina.

RESULTS

The SVM algorithm achieved the highest overall accuracy of tested classifiers, with 87%. Squamous cell hnCUP samples on DNA methylation level resembled squamous cell carcinomas commonly metastasizing into cervical lymph nodes. The most frequently predicted cancer localization was the oral cavity in 11 cases (39%), followed by the oropharynx and larynx (both 7, 25%), skin (2, 7%), and esophagus (1, 4%). These frequencies concord with the expected distribution of lymph node metastases in epidemiological studies.

CONCLUSIONS

On DNA methylation level, hnCUP is comparable to primary tumor tissue cancer types that commonly metastasize to cervical lymph nodes. Our SVM-based classifier can accurately predict these cancers' tissues of origin and could significantly reduce the invasiveness of hnCUP diagnostics and enable a more precise therapy after clinical validation.

Retrospective analysis of clinical characteristics and outcomes of patients with carcinoma of unknown primary from three tertiary centers in Australia

BACKGROUND

Carcinoma of unknown primary (CUP) remains an important tumor entity and a disproportionate cause of cancer mortality. Little is known about the contemporary clinical characteristics, treatment patterns, and outcomes of CUP patients based on updated international classification guidelines. We evaluated a contemporary CUP cohort to provide insight into current clinical practice and the impact of tissue of origin assignment, site-specific and empirical therapy in a real-world setting.

METHODS

We conducted a retrospective cohort study of CUP patients, as defined by the updated European Society of Medical Oncology (ESMO) 2023 guidelines, across three tertiary referral centers in Australia between 2015 and 2022. We analyzed clinical characteristics, treatment patterns, and survival outcomes using the Kaplan-Meier method and Cox regression proportional hazard model between favorable and unfavorable risk groups.

RESULTS

We identified a total of 123 CUP patients (n = 86 unfavorable, n = 37 favorable risk as per the 2023 ESMO guidelines). Sixty-four patients (52%) were assigned a tissue of origin by the treating clinician. Median progression free survival (PFS) was 6.8 (95% confidence interval (CI) 5.1-12.1) months and overall survival (OS) 10.2 (95% CI 6.0-18.5) months. Unfavorable risk (hazard ratio [HR] 2.9, p = 0.006), poor performance status (HR 2.8, p < 0.001), and non-squamous histology (HR 2.5, p < 0.05) were associated with poor survival outcome. A total of 70 patients (57%) proceeded to systemic therapy. In patients with non-squamous histology and unfavorable risk, site-specific therapy compared to empirical chemotherapy did not improve outcome (median OS 8.2 vs. 11.8 months, p = 0.7).

CONCLUSIONS

In this real-world cohort, CUP presentations were heterogenous. Overall survival and rates of systemic treatment were poor. Poor performance status and unfavorable risk were associated with worse survival. For most patients, site-specific therapy did not improve survival outcome. Improved and timely access to diagnostic tests and therapeutics for this group of patients is urgently required.

Advances in Cancer Research: Current and Future Diagnostic and Therapeutic Strategies

Cancers of unknown primary (CUP) exhibit significant cellular heterogeneity and malignancy, which poses significant challenges for diagnosis and treatment. Recent years have seen deeper insights into the imaging, pathology, and genetic characteristics of CUP, driven by interdisciplinary collaboration and the evolution of diagnostic and therapeutic strategies. However, due to their insidious onset, lack of evidence-based medicine, and limited clinical understanding, diagnosing and treating CUP remain a significant challenge. To inspire more creative and fantastic research, herein, we report and highlight recent advances in the diagnosis and therapeutic strategies of CUP. Specifically, we discuss advanced diagnostic technologies, including 12-deoxy-2-[fluorine-18]fluoro-D-glucose integrated with computed tomography (18F-FDG PET/CT) or 68Ga-FAPI (fibroblast activation protein inhibitor) PET/CT, liquid biopsy, molecular diagnostics, self-assembling nanotechnology, and artificial intelligence (AI). In particular, the discussion will extend to the effective treatment techniques currently available, such as targeted therapies, immunotherapies, and bio-nanotechnology-based therapeutics. Finally, a novel perspective on the challenges and directions for future CUP diagnostic and therapeutic strategies is discussed.

Decoding the DNA methylome of central nervous system tumors: An emerging modality for integrated diagnosis

The definitive diagnosis and classification of individual cancers are crucial for patient care and cancer research. To achieve a robust diagnosis of central nervous system (CNS) tumors, a genotype-phenotype integrated diagnostic approach was introduced in recent versions of the World Health Organization classification, followed by the incorporation of a genome-wide DNA methylome-based classification. Microarray-based platforms are widely used to obtain DNA methylome data, and the German Cancer Research Center (Deutsches Krebsforschungszentrum [DKFZ]) has a webtool for a DNA methylation-based classifier (DKFZ classifier). Integration of DNA methylome will further enhance the precision of CNS tumor classification, especially in diagnostically challenging cases. However, in the clinical application of DNA methylome-based classification, challenges related to data interpretation persist, in addition to technical caveats, regulations, and limited accessibility. Dimensionality reduction (DMR) can complement integrated diagnosis by visualizing a profile and comparing it with other known samples. Therefore, DNA methylome-based classification is a highly useful research tool for auxiliary analysis in challenging diagnostic and rare disease cases, and for establishing novel tumor concepts. Decoding the DNA methylome, especially by DMR in addition to DKFZ classifier, emphasizes the capability of grasping the fundamental biological principles that provide new perspectives on CNS tumors.

Single Nucleus RNA Sequencing of Remnant Kidney Biopsies and Urine Cell RNA Sequencing Reveal Cell Specific Markers of Covid-19 Acute Kidney Injury

Acute kidney injury (AKI) in COVID-19 patients is associated with high mortality and morbidity. Critically ill COVID-19 patients are at twice the risk of in-hospital mortality compared to non-COVID AKI patients. We know little about the cell-specific mechanism in the kidney that contributes to worse clinical outcomes in these patients. New generation single cell technologies have the potential to provide insights into physiological states and molecular mechanisms in COVID-AKI. One of the key limitations is that these patients are severely ill posing significant risks in procuring additional biopsy tissue. We recently generated single nucleus RNA-sequencing data using COVID-AKI patient biopsy tissue as part of the human kidney atlas. Here we describe this approach in detail and report deeper comparative analysis of snRNAseq of 4 COVID-AKI, 4 reference, and 6 non-COVID-AKI biopsies. We also generated and analyzed urine transcriptomics data to find overlapping COVID-AKI-enriched genes and their corresponding cell types in the kidney from snRNA-seq data. We identified all major and minor cell types and states by using by using less than a few cubic millimeters of leftover tissue after pathological workup in our approach. Differential expression analysis of COVID-AKI biopsies showed pathways enriched in viral response, WNT signaling, kidney development, and cytokines in several nephron epithelial cells. COVID-AKI profiles showed a much higher proportion of altered TAL cells than non-COVID AKI and the reference samples. In addition to kidney injury and fibrosis markers indicating robust remodeling we found that, 17 genes overlap between urine cell COVID-AKI transcriptome and the snRNA-seq data from COVID-AKI biopsies. A key feature was that several of the distal nephron and collecting system cell types express these markers. Some of these markers have been previously observed in COVID-19 studies suggesting a common mechanism of injury and potentially the kidney as one of the sources of soluble factors with a potential role in disease progression.

Translational Statement

The manuscript describes innovation, application and discovery that impact clinical care in kidney disease. First, the approach to maximize use of remnant frozen clinical biopsies to inform on clinically relevant molecular features can augment existing pathological workflow for any frozen tissue without much change in the protocol. Second, this approach is transformational in medical crises such as pandemics where mechanistic insights are needed to evaluate organ injury, targets for drug therapy and diagnostic and prognostic markers. Third, the cell type specific and soluble markers identified and validated can be used for diagnoses or prognoses in AKI due to different etiologies and in multiorgan injury.

Modified study designs to expand treatment options in personalised oncology: a multistakeholder view

Personalised oncology, whereby patients are given therapies based on their molecular tumour profile, is rapidly becoming an essential part of optimal clinical care, at least partly facilitated by recent advances in next-generation sequencing-based technology using liquid- and tissue-based biopsies. Consequently, clinical trials have shifted in approach, from traditional studies evaluating cytotoxic chemotherapy in largely histology-based populations to modified, biomarker-driven studies (e.g. basket, umbrella, platform) of molecularly guided therapies and cancer immunotherapies in selected patient subsets. Such modified study designs may assess, within the same trial structure, multiple cancer types and treatments, and should incorporate a multistakeholder perspective. This is key to generating complementary, fit-for-purpose and timely evidence for molecularly guided therapies that can be used as proof-of-concept to inform further study designs, lead to approval by regulatory authorities and be used as confirmation of clinical benefit for health technology assessment bodies. In general, the future of cancer clinical trials requires a framework for the application of innovative technologies and dynamic design methodologies, in order to efficiently transform scientific discoveries into clinical utility. Next-generation, modified studies that involve the joint efforts of all key stakeholders will offer individualised strategies that ultimately contribute to globalised knowledge and collective learning. In this review, we outline the background and purpose of such modified study designs and detail key aspects from a multistakeholder perspective. We also provide methodological considerations for designing the studies and highlight how insights from already-ongoing studies may address current challenges and opportunities in the era of personalised oncology.

NCT/DKFZ MASTER handbook of interpreting whole-genome, transcriptome, and methylome data for precision oncology

Analysis of selected cancer genes has become an important tool in precision oncology but cannot fully capture the molecular features and, most importantly, vulnerabilities of individual tumors. Observational and interventional studies have shown that decision-making based on comprehensive molecular characterization adds significant clinical value. However, the complexity and heterogeneity of the resulting data are major challenges for disciplines involved in interpretation and recommendations for individualized care, and limited information exists on how to approach multilayered tumor profiles in clinical routine. We report our experience with the practical use of data from whole-genome or exome and RNA sequencing and DNA methylation profiling within the MASTER (Molecularly Aided Stratification for Tumor Eradication Research) program of the National Center for Tumor Diseases (NCT) Heidelberg and Dresden and the German Cancer Research Center (DKFZ). We cover all relevant steps of an end-to-end precision oncology workflow, from sample collection, molecular analysis, and variant prioritization to assigning treatment recommendations and discussion in the molecular tumor board. To provide insight into our approach to multidimensional tumor profiles and guidance on interpreting their biological impact and diagnostic and therapeutic implications, we present case studies from the NCT/DKFZ molecular tumor board that illustrate our daily practice. This manual is intended to be useful for physicians, biologists, and bioinformaticians involved in the clinical interpretation of genome-wide molecular information.

Signaling-induced systematic repression of miRNAs uncovers cancer vulnerabilities and targeted therapy sensitivity

Targeted therapies are effective in treating cancer, but success depends on identifying cancer vulnerabilities. In our study, we utilize small RNA sequencing to examine the impact of pathway activation on microRNA (miRNA) expression patterns. Interestingly, we discover that miRNAs capable of inhibiting key members of activated pathways are frequently diminished. Building on this observation, we develop an approach that integrates a low-miRNA-expression signature to identify druggable target genes in cancer. We train and validate our approach in colorectal cancer cells and extend it to diverse cancer models using patient-derived in vitro and in vivo systems. Finally, we demonstrate its additional value to support genomic and transcriptomic-based drug prediction strategies in a pan-cancer patient cohort from the National Center for Tumor Diseases (NCT)/German Cancer Consortium (DKTK) Molecularly Aided Stratification for Tumor Eradication (MASTER) precision oncology trial. In conclusion, our strategy can predict cancer vulnerabilities with high sensitivity and accuracy and might be suitable for future therapy recommendations in a variety of cancer subtypes.

Feasibility and value of genomic profiling in cancer of unknown primary: real-world evidence from prospective profiling study

Real-world evidence regarding the value of integrating genomic profiling (GP) in managing cancer of unknown primary (CUP) is limited. We assessed this clinical utility using a prospective trial of 158 patients with CUP (October 2016-September 2019) who underwent GP using next-generation sequencing designed to identify genomic alterations (GAs). Only 61 (38.6%) patients had sufficient tissue for successful profiling. GAs were seen in 55 (90.2%) patients of which GAs with US Food and Drug Administration-approved genomically matched therapy were seen in 25 (40.9%) patients. A change in therapy was recommended and implemented (primary endpoint of the study) in 16 (10.1%) and 4 (2.5%) patients of the entire study cohort, respectively. The most common reason for inability to implement the profiling-guided therapy was worsening of performance status (56.3%). Integrating GP in management of CUP is feasible but challenging because of paucity of tissue and aggressive natural history of the disease and requires innovative precision strategies.

Current practice of genomic profiling of patients with advanced solid tumours in Italy: the Italian Register of Actionable Mutations (RATIONAL) study

BACKGROUND

The Italian Register of Actionable Mutations (RATIONAL) is a multicentric, observational study collecting next-generation sequencing (NGS)-based tumour profiling data of patients with advanced solid tumours.

METHODS

The study enrols patients who had available an NGS-based tumour profiling (Pathway-A) or undergo comprehensive genomic profiling (CGP) with FoundationOne CDx assays within the trial (Pathway-B). The primary endpoint was the rate of actionable mutations identified.

RESULTS

Sequencing data were available for 738 patients in Pathway-A (218) and -B (520). In Pathway-A, 154/218 (70.6%) tests were performed using NGS panels ≤52 genes, and genomic alterations (GAs) were found in 164/218 (75.2%) patients. In Pathway-B, CGP revealed GAs in 512/520 (98.5%) patients. Levels I/II/III actionable GAs according to the European Society of Medical Oncology Scale for Clinical Actionability of molecular Targets (ESCAT) were identified in 254/554 (45.8%) patients with non-small-cell lung cancer, cholangiocarcinoma, colorectal, gastric, pancreatic and breast cancer. The rate of patients with level I GAs was similar in Pathways A and B (69 versus 102). CGP in Pathway-B revealed a higher number of patients with level II/III GAs (99 versus 20) and potentially germline pathogenic/likely pathogenic variants (58 versus 15) as compared with standard testing in Pathway-A. In patients with cancer of unknown primary, CGP detected OncoKB levels 3B/4 GAs in 31/58 (53.4%) cases. Overall, 67/573 (11.7%) of patients received targeted therapy based on genomic testing.

CONCLUSION

The Italian Register of Actionable Mutations represents the first overview of genomic profiling in Italian current clinical practice and highlights the utility of CGP for identifying therapeutic targets in selected cancer patients.

Spatial transcriptomics reveal topological immune landscapes of Asian head and neck angiosarcoma

Angiosarcomas are rare malignant tumors of the endothelium, arising commonly from the head and neck region (AS-HN) and recently associated with ultraviolet (UV) exposure and human herpesvirus-7 infection. We examined 81 cases of angiosarcomas, including 47 cases of AS-HN, integrating information from whole genome sequencing, gene expression profiling and spatial transcriptomics (10X Visium). In the AS-HN cohort, we observed recurrent somatic mutations in CSMD3 (18%), LRP1B (18%), MUC16 (18%), POT1 (16%) and TP53 (16%). UV-positive AS-HN harbored significantly higher tumor mutation burden than UV-negative cases (p = 0.0294). NanoString profiling identified three clusters with distinct tumor inflammation signature scores (p < 0.001). Spatial transcriptomics revealed topological profiles of the tumor microenvironment, identifying dominant but tumor-excluded inflammatory signals in immune-hot cases and immune foci even in otherwise immune-cold cases. In conclusion, spatial transcriptomics reveal the tumor immune landscape of angiosarcoma, and in combination with multi-omic information, may improve implementation of treatment strategies.

Benchmarking of Nanopore R10.4 and R9.4.1 flow cells in single-cell whole-genome amplification and whole-genome shotgun sequencing

Third-generation sequencing can be used in human cancer genomics and epigenomic research. Oxford Nanopore Technologies (ONT) recently released R10.4 flow cell, which claimed an improved read accuracy compared to R9.4.1 flow cell. To evaluate the benefits and defects of R10.4 flow cell for cancer cell profiling on MinION devices, we used the human non-small-cell lung-carcinoma cell line HCC78 to construct libraries for both single-cell whole-genome amplification (scWGA) and whole-genome shotgun sequencing. The R10.4 and R9.4.1 reads were benchmarked in terms of read accuracy, variant detection, modification calling, genome recovery rate and compared with the next generation sequencing (NGS) reads. The results highlighted that the R10.4 outperforms R9.4.1 reads, achieving a higher modal read accuracy of over 99.1%, superior variation detection, lower false-discovery rate (FDR) in methylation calling, and comparable genome recovery rate. To achieve high yields scWGA sequencing in the ONT platform as NGS, we recommended multiple displacement amplification with a modified T7 endonuclease Ⅰ cutting procedure as a promising method. In addition, we provided a possible solution to filter the likely false positive sites among the whole genome region with R10.4 by using scWGA sequencing result as a negative control. Our study is the first benchmark of whole genome single-cell sequencing using ONT R10.4 and R9.4.1 MinION flow cells by clarifying the capacity of genomic and epigenomic profiling within a single flow cell. A promising method for scWGA sequencing together with the methylation calling results can benefit researchers who work on cancer cell genomic and epigenomic profiling using third-generation sequencing.

Germline findings in patients with advanced malignancies screened with paired blood-tumour testing for personalised treatment approaches

BACKGROUND

Sequencing of tumour tissue with comprehensive gene panels is increasingly used to guide treatment in precision oncology. Analysis of tumour-normal pairs allows in contrast to tumour-only assessment direct discrimination between somatic and germline alterations, which might have important implications not only for the patients but also their families.

METHODS

We performed tumour normal sequencing with a large gene panel in 1048 patients with advanced cancer to support treatment decision. Sequencing results were correlated with clinical and family data.

RESULTS

We identified 156 likely pathogenic or pathogenic (LP/P) germline variants in cancer predisposition genes (CPGs) in 144 cases (13.7%). Of all patients, 8.8% had a LP/P variant in autosomal-dominant cancer predisposition genes (AD-CPGs), most of them being genes with high or moderate penetrance (ATM, BRCA2, CHEK2 and BRCA1). In 48 cases, the P/LP variant matched the expected tumour spectrum. A second variant in tumour tissue was found in 31 patients with AD-CPG variants. Low frequency mutations in either TP53, ATM or DNMT3A in the normal sample indicated clonal haematopoiesis in five cases.

CONCLUSIONS

Tumour-normal testing for personalised treatment identifies germline LP/P variants in a relevant proportion of patients with cancer. The majority of them would not have been referred to genetic counselling based on family history. Indirect functional readouts of tumour-normal sequencing can provide novel links between CPGs and unexpected cancers. The interpretation of increasingly complex datasets in precision oncology is challenging and concepts of interdisciplinary personalised cancer prevention are needed to support patients and their families.

Complete genomic characterization in patients with cancer of unknown primary origin in routine diagnostics

BACKGROUND

In ∼3%-5% of patients with metastatic disease, tumor origin remains unknown despite modern imaging techniques and extensive pathology work-up. With long diagnostic delays and limited and ineffective therapy options, the clinical outcome of patients with cancer of unknown primary (CUP) remains poor. Large-scale genome sequencing studies have revealed that tumor types can be predicted based on distinct patterns of somatic variants and other genomic characteristics. Moreover, actionable genomic events are present in almost half of CUP patients. This study investigated the clinical value of whole genome sequencing (WGS) in terms of primary tumor identification and detection of actionable events, in the routine diagnostic work-up of CUP patients.

PATIENTS AND METHODS

A WGS-based tumor type 'cancer of unknown primary prediction algorithm' (CUPPA) was developed based on previously described principles and validated on a large pan-cancer WGS database of metastatic cancer patients (>4000 samples) and 254 independent patients, respectively. We assessed the clinical value of this prediction algorithm as part of routine WGS-based diagnostic work-up for 72 CUP patients.

RESULTS

CUPPA correctly predicted the primary tumor type in 78% of samples in the independent validation cohort (194/254 patients). High-confidence predictions (>95% precision) were obtained for 162/254 patients (64%). When integrated in the diagnostic work-up of CUP patients, CUPPA could identify a primary tumor type for 49/72 patients (68%). Most common diagnoses included non-small-cell lung (n = 7), gastroesophageal (n = 4), pancreatic (n = 4), and colorectal cancer (n = 3). Actionable events with matched therapy options in clinical trials were identified in 47% of patients.

CONCLUSIONS

Genome-based tumor type prediction can predict cancer diagnoses with high accuracy when integrated in the routine diagnostic work-up of patients with metastatic cancer. With identification of the primary tumor type in the majority of patients and detection of actionable events, WGS is a valuable diagnostic tool for patients with CUP.

Implementation of Whole-Genome and Transcriptome Sequencing Into Clinical Cancer Care

PURPOSE

The combination of whole-genome and transcriptome sequencing (WGTS) is expected to transform diagnosis and treatment for patients with cancer. WGTS is a comprehensive precision diagnostic test that is starting to replace the standard of care for oncology molecular testing in health care systems around the world; however, the implementation and widescale adoption of this best-in-class testing is lacking.

METHODS

Here, we address the barriers in integrating WGTS for cancer diagnostics and treatment selection and answer questions regarding utility in different cancer types, cost-effectiveness and affordability, and other practical considerations for WGTS implementation.

RESULTS

We review the current studies implementing WGTS in health care systems and provide a synopsis of the clinical evidence and insights into practical considerations for WGTS implementation. We reflect on regulatory, costs, reimbursement, and incidental findings aspects of this test.

CONCLUSION

WGTS is an appropriate comprehensive clinical test for many tumor types and can replace multiple, cascade testing approaches currently performed. Decreasing sequencing cost, increasing number of clinically relevant aberrations and discovery of more complex biomarkers of treatment response, should pave the way for health care systems and laboratories in implementing WGTS into clinical practice, to transform diagnosis and treatment for patients with cancer.