Assigning evidence to actionability: An introduction to variant interpretation in precision cancer medicine

Precision oncology - Guideline of the Austrian, German and Swiss Societies for hematology and medical oncology

Precision oncology is a multi-step process including patient selection, tumor profiling, molecular tumor board discussion and personalized cancer management. So far, it remains largely unstandardized. The implementation of precision oncology can be beneficial for patients but implementation differs widely between tumor types and local practices. A working group was established by the Austrian, German and Swiss societies for Hematology and Medical Oncology to establish an expert consensus on evidence-based standards and implementation of precision oncology. Herein, we present a summary of this guideline. The full documents are available at www.onkopedia-guidelines.info.

Molecular and functional profiling unravels targetable vulnerabilities in colorectal cancer

Colorectal cancer (CRC) patients with microsatellite-stable (MSS) tumors are mostly treated with chemotherapy. Clinical benefits of targeted therapies depend on mutational states and tumor location. Many tumors carry mutations in KRAS proto-oncogene, GTPase (KRAS) or B-Raf proto-oncogene, serine/threonine kinase (BRAF), rendering them more resistant to therapies. We performed whole-exome sequencing and RNA-Sequencing of 28 tumors of the Athens Comprehensive Cancer Center CRC cohort, and molecularly characterized CRC patients based on their microsatellite instability (MSI) status, single-nucleotide variations (SNVs)/copy number alterations (CNAs), and pathway/transcription factor activities at the individual patient level. Variants were classified using a computational score for integrative cancer variant annotation and prioritization. Complementing this with public multi-omics datasets, we identified activation of transforming growth factor beta (TGFβ) signaling to be more strongly activated in MSS patients, whereas Janus kinase (JAK)-signal transducer and activator of transcription (STAT) and mitogen-activated protein kinase (MAPK) molecular cascades were activated specifically in MSI tumors. We unraveled mechanisms consistently perturbed in the transcriptional and mutational circuits and identified Runt-related transcription factors (RUNX transcription factors) as putative biomarkers in CRC, given their role in the regulation of pathways involved in tumor progression and immune evasion. Assessing the immunogenicity of CRC tumors in the context of RAS/RAF mutations and MSI/MSS status revealed a critical impact that KRAS mutations have on immunogenicity, particularly in the MSS patient subgroup, with implications for diagnosis and treatment.

Unveiling the Digital Evolution of Molecular Tumor Boards

Molecular tumor boards (MTB) are interdisciplinary conferences involving various experts discussing patients with advanced tumors, to derive individualized treatment suggestions based on molecular variants. These discussions involve using heterogeneous internal data, such as patient clinical data, but also external resources such as knowledge databases for annotations and search for relevant clinical studies. This imposes a certain level of complexity that requires huge effort to homogenize the data and use it in a speedy manner to reach the needed treatment. For this purpose, most institutions involving an MTB are heading toward automation and digitalization of the process, hence reducing manual work requiring human intervention and subsequently time in deriving personalized treatment suggestions. The tools are also used to better visualize the patient's data, which allows a refined overview for the board members. In this paper, we present the results of our thorough literature research about MTBs, their process, the most common knowledge bases, and tools used to support this decision-making process.

Sex-specific survival gene mutations are discovered as clinical predictors of clear cell renal cell carcinoma

Although sex differences have been reported in patients with clear cell renal cell carcinoma (ccRCC), biological sex has not received clinical attention and genetic differences between sexes are poorly understood. This study aims to identify sex-specific gene mutations and explore their clinical significance in ccRCC. We used data from The Cancer Genome Atlas-Kidney Renal Clear Cell Carcinoma (TCGA-KIRC), The Renal Cell Cancer-European Union (RECA-EU) and Korean-KIRC. A total of 68 sex-related genes were selected from TCGA-KIRC through machine learning, and 23 sex-specific genes were identified through verification using the three databases. Survival differences according to sex were identified in nine genes (ACSS3, ALG13, ASXL3, BAP1, JADE3, KDM5C, KDM6A, NCOR1P1, and ZNF449). Female-specific survival differences were found in BAP1 in overall survival (OS) (TCGA-KIRC, p = 0.004; RECA-EU, p = 0.002; and Korean-KIRC, p = 0.003) and disease-free survival (DFS) (TCGA-KIRC, p = 0.001 and Korean-KIRC, p = 0.000004), and NCOR1P1 in DFS (TCGA-KIRC, p = 0.046 and RECA-EU, p = 0.00003). Male-specific survival differences were found in ASXL3 (OS, p = 0.017 in TCGA-KIRC; and OS, p = 0.005 in RECA-EU) and KDM5C (OS, p = 0.009 in RECA-EU; and DFS, p = 0.016 in Korean-KIRC). These results suggest that biological sex may be an important predictor and sex-specific tailored treatment may improve patient care in ccRCC.

Cosmic Whirl: Navigating the Comet Trail in DNA: H2AX Phosphorylation and the Enigma of Uncertain Significance Variants

Pathogenic variations in the BRCA2 gene have been detected with the development of next-generation sequencing (NGS)-based hereditary cancer panel testing technology. It also reveals an increasing number of variants of uncertain significance (VUSs). Well-established functional tests are crucial to accurately reclassifying VUSs for effective diagnosis and treatment. We retrospectively analyzed the multi-gene cancer panel results of 922 individuals and performed in silico analysis following ClinVar classification. Then, we selected five breast cancer-diagnosed patients' missense BRCA2 VUSs (T1011R, T1104P/M1168K, R2027K, G2044A, and D2819) for reclassification. The effects of VUSs on BRCA2 function were analyzed using comet and H2AX phosphorylation (γH2AX) assays before and after the treatment of peripheral blood mononuclear cells (PBMCs) of subjects with the double-strand break (DSB) agent doxorubicin (Dox). Before and after Dox-induction, the amount of DNA in the comet tails was similar in VUS carriers; however, notable variations in γH2AX were observed, and according to combined computational and functional analyses, we reclassified T1001R as VUS-intermediate, T1104P/M1168K and D2819V as VUS (+), and R2027K and G2044A as likely benign. These findings highlight the importance of the variability of VUSs in response to DNA damage before and after Dox-induction and suggest that further investigation is needed to understand the underlying mechanisms.

Integration of proteomics in the molecular tumor board

Cancer remains one of the most complex and challenging diseases in mankind. To address the need for a personalized treatment approach for particularly complex tumor cases, molecular tumor boards (MTBs) have been initiated. MTBs are interdisciplinary teams that perform in-depth molecular diagnostics to cooperatively and interdisciplinarily advise on the best therapeutic strategy. Current molecular diagnostics are routinely performed on the transcriptomic and genomic levels, aiming to identify tumor-driving mutations. However, these approaches can only partially capture the actual phenotype and the molecular key players of tumor growth and progression. Thus, direct investigation of the expressed proteins and activated signaling pathways provide valuable complementary information on the tumor-driving molecular characteristics of the tissue. Technological advancements in mass spectrometry-based proteomics enable the robust, rapid, and sensitive detection of thousands of proteins in minimal sample amounts, paving the way for clinical proteomics and the probing of oncogenic signaling activity. Therefore, proteomics is currently being integrated into molecular diagnostics within MTBs and holds promising potential in aiding tumor classification and identifying personalized treatment strategies. This review introduces MTBs and describes current clinical proteomics, its potential in precision oncology, and highlights the benefits of multi-omic data integration.

Molecular diagnostics tailoring personalized cancer therapy-an oncologist's view

Medical oncology is rapidly evolving with the implementation of personalized, targeted therapies. Advances in molecular diagnostics and the biologic understanding of cancer pathophysiology led to the identification of specific genetic alterations as drivers of cancer progression. Further, improvements in drug development enable the direct interference with these pathways, which allow tailoring personalized treatments based on a distinct molecular characterization of tumors. Thereby, we are currently experiencing a paradigm-shift in the treatment of cancers towards cancer-type agnostic, molecularly targeted, personalized therapies. However, this concept has several important hurdles and limitations to overcome to ultimately increase the proportion of patients benefitting from the precision oncology approach. These include the assessment of clinical relevancy of identified alterations, capturing and interpreting levels of heterogeneity based on intra-tumoral or time-dependent molecular evolution, and challenges in the practical implementation of precision oncology in routine clinical care. In the present review, we summarize the current state of cancer-agnostic precision oncology, discuss the concept of molecular tumor boards, and consider current limitations of personalized cancer therapy. Further, we provide an outlook towards potential future developments including the implementation of functionality assessments of identified genetic alterations and the broader use of liquid biopsies in order to obtain more comprehensive and longitudinal genetic information that might guide personalized cancer therapy in the future.

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.

Software-Tool Support for Collaborative, Virtual, Multi-Site Molecular Tumor Boards

The availability of high-throughput molecular diagnostics builds the foundation for Molecular Tumor Boards (MTBs). Although more fine-grained data is expected to support decision making of oncologists, assessment of data is complex and time-consuming slowing down the implementation of MTBs, e.g., due to retrieval of the latest medical publications, assessment of clinical evidence, or linkage to the latest clinical guidelines. We share our findings from analysis of existing tumor board processes and defininion of clinical processes for the adoption of MTBs. Building on our findings, we have developed a real-world software prototype together with oncologists and medical professionals, which supports the preparation and conduct of MTBs and enables collaboration between medical experts by sharing medical knowledge even across the hospital locations. We worked in interdisciplinary teams of clinicians, oncologists, medical experts, medical informaticians, and software engineers using design thinking methodology. With their input, we identified challenges and limitations of the current MTB approaches, derived clinical process models using Business Process and Modeling Notation (BMPN), and defined personas, functional and non-functional requirements for software tool support. Based on it, we developed software prototypes and evaluated them with clinical experts from major university hospitals across Germany. We extended the Kanban methodology enabling holistic tracking of patient cases from "backlog" to "follow-up" in our app. The feedback from interviewed medical professionals showed that our clinical process models and software prototype provide suitable process support for the preparation and conduction of molecular tumor boards. The combination of oncology knowledge across hospitals and the documentation of treatment decision can be used to form a unique medical knowledge base by oncologists for oncologists. Due to the high heterogeneity of tumor diseases and the spread of the latest medical knowledge, a cooperative decision-making process including insights from similar patient cases was considered as a very valuable feature. The ability to transform prepared case data into a screen presentation was recognized as an essential feature speeding up the preparation process. Oncologists require special software tool support to incorporate and assess molecular data for the decision-making process. In particular, the need for linkage to the latest medical knowledge, clinical evidence, and collaborative tools to discuss individual cases were named to be of importance. With the experiences from the COVID-19 pandemic, the acceptance of online tools and collaborative working is expected to grow. Our virtual multi-site approach proved to allow a collaborative decision-making process for the first time, which we consider to have a positive impact on the overall treatment quality.

A Review of Advanced Multifunctional Magnetic Nanostructures for Cancer Diagnosis and Therapy Integrated into an Artificial Intelligence Approach

The new era of nanomedicine offers significant opportunities for cancer diagnostics and treatment. Magnetic nanoplatforms could be highly effective tools for cancer diagnosis and treatment in the future. Due to their tunable morphologies and superior properties, multifunctional magnetic nanomaterials and their hybrid nanostructures can be designed as specific carriers of drugs, imaging agents, and magnetic theranostics. Multifunctional magnetic nanostructures are promising theranostic agents due to their ability to diagnose and combine therapies. This review provides a comprehensive overview of the development of advanced multifunctional magnetic nanostructures combining magnetic and optical properties, providing photoresponsive magnetic platforms for promising medical applications. Moreover, this review discusses various innovative developments using multifunctional magnetic nanostructures, including drug delivery, cancer treatment, tumor-specific ligands that deliver chemotherapeutics or hormonal agents, magnetic resonance imaging, and tissue engineering. Additionally, artificial intelligence (AI) can be used to optimize material properties in cancer diagnosis and treatment, based on predicted interactions with drugs, cell membranes, vasculature, biological fluid, and the immune system to enhance the effectiveness of therapeutic agents. Furthermore, this review provides an overview of AI approaches used to assess the practical utility of multifunctional magnetic nanostructures for cancer diagnosis and treatment. Finally, the review presents the current knowledge and perspectives on hybrid magnetic systems as cancer treatment tools with AI models.

Molecular characterization of an embryonal rhabdomyosarcoma occurring in a patient with Kabuki syndrome: report and literature review in the light of tumor predisposition syndromes

Kabuki syndrome is a well-recognized syndrome characterized by facial dysmorphism and developmental delay/intellectual disability and in the majority of patients a germline variant in KMT2D is found. As somatic KMT2D variants can be found in 5-10% of tumors a tumor predisposition in Kabuki syndrome is discussed. So far less than 20 patients with Kabuki syndrome and a concomitant malignancy have been published. Here we report on a female patient with Kabuki syndrome and a c.2558_2559delCT germline variant in KMT2D who developed an embryonal rhabdomyosarcoma (ERMS) at 10 years. On tumor tissue we performed DNA-methylation profiling and exome sequencing (ES). Copy number analyses revealed aneuploidies typical for ERMS including (partial) gains of chromosomes 2, 3, 7, 8, 12, 15, and 20 and 3 focal deletions of chromosome 11p. DNA methylation profiling mapped the case to ERMS by a DNA methylation-based sarcoma classifier. Sequencing suggested gain of the wild-type KMT2D allele in the trisomy 12. Including our patient literature review identified 18 patients with Kabuki syndrome and a malignancy. Overall, the landscape of malignancies in patients with Kabuki syndrome was reminiscent of that of the pediatric population in general. Histopathological and molecular data were only infrequently reported and no report included next generation sequencing and/or DNA-methylation profiling. Although we found no strong arguments pointing towards KS as a tumor predisposition syndrome, based on the small numbers any relation cannot be fully excluded. Further planned studies including profiling of additional tumors and long term follow-up of KS-patients into adulthood could provide further insights.

COGNITION: a prospective precision oncology trial for patients with early breast cancer at high risk following neoadjuvant chemotherapy

BACKGROUND

COGNITION (Comprehensive assessment of clinical features, genomics and further molecular markers to identify patients with early breast cancer for enrolment on marker driven trials) is a diagnostic registry trial that employs genomic and transcriptomic profiling to identify biomarkers in patients with early breast cancer with a high risk for relapse after standard neoadjuvant chemotherapy (NACT) to guide genomics-driven targeted post-neoadjuvant therapy.

PATIENTS AND METHODS

At National Center for Tumor Diseases Heidelberg patients were biopsied before starting NACT, and for patients with residual tumors after NACT additional biopsy material was collected. Whole-genome/exome and transcriptome sequencing were applied on tumor and corresponding blood samples.

RESULTS

In the pilot phase 255 patients were enrolled, among which 213 were assessable: thereof 48.8% were identified to be at a high risk for relapse following NACT; 86.4% of 81 patients discussed in the molecular tumor board were eligible for a targeted therapy within the interventional multiarm phase II trial COGNITION-GUIDE (Genomics-guided targeted post neoadjuvant therapy in patients with early breast cancer) starting enrolment in Q4/2022. An in-depth longitudinal analysis at baseline and in residual tumor tissue of 16 patients revealed some cases with clonal evolution but largely stable genetic alterations, suggesting restricted selective pressure of broad-acting cytotoxic neoadjuvant chemotherapies.

CONCLUSIONS

While most precision oncology initiatives focus on metastatic disease, the presented concept offers the opportunity to empower novel therapy options for patients with high-risk early breast cancer in the post-neoadjuvant setting within a biomarker-driven trial and provides the basis to test the value of precision oncology in a curative setting with the overarching goal to increase cure rates.

Data-driven support to decision-making in molecular tumour boards for lymphoma: A design science approach

Background

The increasing amount of molecular data and knowledge about genomic alterations from next-generation sequencing processes together allow for a greater understanding of individual patients, thereby advancing precision medicine. Molecular tumour boards feature multidisciplinary teams of clinical experts who meet to discuss complex individual cancer cases. Preparing the meetings is a manual and time-consuming process.

Purpose

To design a clinical decision support system to improve the multimodal data interpretation in molecular tumour board meetings for lymphoma patients at Karolinska University Hospital, Stockholm, Sweden. We investigated user needs and system requirements, explored the employment of artificial intelligence, and evaluated the proposed design with primary stakeholders.

Methods

Design science methodology was used to form and evaluate the proposed artefact. Requirements elicitation was done through a scoping review followed by five semi-structured interviews. We used UML Use Case diagrams to model user interaction and UML Activity diagrams to inform the proposed flow of control in the system. Additionally, we modelled the current and future workflow for MTB meetings and its proposed machine learning pipeline. Interactive sessions with end-users validated the initial requirements based on a fictive patient scenario which helped further refine the system.

Results

The analysis showed that an interactive secure Web-based information system supporting the preparation of the meeting, multidisciplinary discussions, and clinical decision-making could address the identified requirements. Integrating artificial intelligence via continual learning and multimodal data fusion were identified as crucial elements that could provide accurate diagnosis and treatment recommendations.

Impact

Our work is of methodological importance in that using artificial intelligence for molecular tumour boards is novel. We provide a consolidated proof-of-concept system that could support the end-to-end clinical decision-making process and positively and immediately impact patients.

Conclusion

Augmenting a digital decision support system for molecular tumour boards with retrospective patient material is promising. This generates realistic and constructive material for human learning, and also digital data for continual learning by data-driven artificial intelligence approaches. The latter makes the future system adaptable to human bias, improving adequacy and decision quality over time and over tasks, while building and maintaining a digital log.

The significance of the fusion partner gene genomic neighborhood analysis in translocation-defined tumors

INTRODUCTION

This study presents a novel molecular parameter potentially co-defining tumor biology-the total tumor suppressor gene (TSG) count at chromosomal loci harboring genes rearranged in fusion-defined tumors. It belongs to the family of molecular parameters created using a black-box approach.

METHOD

It is based on a public curated Texas TSG database. Its data are regrouped based on individual genes loci using another public database (Genecards). The total TSG count for NTRK (NTRK1; OMIM: 191315; NTRK2; OMIM: 600456; NTRK3; OMIM: 191316), NRG1 (OMIM: 142445), and RET (OMIM: 164761) rearranged tumors in patients treated with a theranostic approach is calculated using the results of recently published studies.

RESULTS

Altogether 138 loci containing at least three TSGs are identified. These include 21 "extremely hot" spots, with 10 to 28 TSGs mapping to a given locus. However, the study falls short of finding a correlation between tumor regression or patient survival and the TSG count owing to a low number of cases meeting the study criteria.

CONCLUSION

The total TSG count alone cannot predict the biology of translocation-defined tumors. The addition of other parameters, including microsatellite instability (MSI), tumor mutation burden (TMB), homologous recombination repair deficiency (HRD), and copy number heterogeneity (CNH), might be helpful. Thus a multi-modal data integration is advocated. We believe that large scale studies should evaluate the significance and value of the total TSG count.

The spectrum of sex differences in cancer

Sex differences in cellular and systems biology have been evolutionarily selected to optimize reproductive success in all species with little (sperm) and big (ova) gamete producers. They are evident from the time of fertilization and accrue throughout development through genetic, epigenetic, and circulating sex hormone-dependent mechanisms. Among other effects, they significantly impact on chromatin organization, metabolism, cell cycle regulation, immunity, longevity, and cancer risk and survival. Sex differences in cancer should be expected and accounted for in basic, translational, and clinical oncology research.