Personalized Clinical Decision Making Through Implementation of a Molecular Tumor Board: A German Single-Center Experience

[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.

[Personalized medicine in oncology]

Due to the considerable technological progress in molecular and genetic diagnostics as well as increasing insights into the molecular pathogenesis of diseases, there has been a fundamental paradigm shift in the past two decades from a "one-size-fits-all approach" to personalized, molecularly informed treatment strategies. Personalized medicine or precision medicine focuses on the genetic, physiological, molecular, and biochemical differences between individuals and considers their effects on the development, prevention, and treatment of diseases. As a pioneer of personalized medicine, the field of oncology is particularly noteworthy, where personalized diagnostics and treatment have led to lasting change in the treatment of cancer patients in recent years. In this article, the significant change towards personalized treatment concepts, especially in the field of personalized oncology, will be discussed and examined in more detail.

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.

Extending cBioPortal for Therapy Recommendation Documentation in Molecular Tumor Boards: Development and Usability Study

BACKGROUND

In molecular tumor boards (MTBs), patients with rare or advanced cancers are discussed by a multidisciplinary team of health care professionals. Software support for MTBs is lacking; in particular, tools for preparing and documenting MTB therapy recommendations need to be developed.

OBJECTIVE

We aimed to implement an extension to cBioPortal to provide a tool for the documentation of therapy recommendations from MTB sessions in a secure and standardized manner. The developed extension should be embedded in the patient view of cBioPortal to enable easy documentation during MTB sessions. The resulting architecture for storing therapy recommendations should be integrable into various hospital information systems.

METHODS

On the basis of a requirements analysis and technology analysis for authentication techniques, a prototype was developed and iteratively refined through a user-centered development process. In conclusion, the tool was evaluated via a usability evaluation, including interviews, structured questionnaires, and the System Usability Scale.

RESULTS

The patient view of cBioPortal was extended with a new tab that enables users to document MTB sessions and therapy recommendations. The role-based access control was expanded to allow for a finer distinction among the rights to view, edit, and delete data. The usability evaluation showed overall good usability and a System Usability Scale score of 83.57.

CONCLUSIONS

This study demonstrates how cBioPortal can be extended to not only visualize MTB patient data but also be used as a documentation platform for therapy recommendations.

Using proteomics for stratification and risk prediction in patients with solid tumors

Proteomics, the study of proteins and their functions, has greatly evolved due to advances in analytical chemistry and computational biology. Unlike genomics or transcriptomics, proteomics captures the dynamic and diverse nature of proteins, which play crucial roles in cellular processes. This is exemplified in cancer, where genomic and transcriptomic information often falls short in reflecting actual protein expression and interactions. Liquid chromatography-mass spectrometry (LC-MS) is pivotal in proteomic data generation, enabling high-throughput analysis of protein samples. The MS-based workflow involves protein digestion, chromatographic separation, ionization, and fragmentation, leading to peptide identification and quantification. Computational biostatistics, particularly using tools in R (R Foundation for Statistical Computing, Vienna, Austria; www.R-project.org ), aid in data analysis, revealing protein expression patterns and correlations with clinical variables. Proteomic studies can be explorative, aiming to characterize entire proteomes, or targeted, focusing on specific proteins of interest. The integration of proteomics with genomics addresses database limitations and enhances peptide identification. Case studies in intrahepatic cholangiocarcinoma, glioblastoma multiforme, and pancreatic ductal adenocarcinoma highlight proteomics' clinical applications, from subtyping cancers to identifying diagnostic markers. Moreover, proteomic data augment molecular tumor boards by providing deeper insights into pathway activities and genomic mutations, supporting personalized treatment decisions. Overall, proteomics contributes significantly to advancing our understanding of cellular biology and improving clinical care.

Molecularly Stratified Treatment Options in Primary Refractory DLBCL/HGBL with MYC and BCL2 or BCL6 Rearrangements (HGBL, NOS with MYC/BCL6)

BACKGROUND

There is growing evidence supporting multidisciplinary molecular tumor boards (MTB) in solid tumors whereas hematologic malignancies remain underrepresented in this regard.

OBJECTIVE

The present study aimed to assess the clinical relevance of MTBs in primary refractory diffuse large B-cell lymphomas/high-grade B-cell lymphomas with MYC and BCL2 rearrangements (prDLBCL/HGBL-MYC/BCL2) (n = 13) and HGBL, not otherwise specified (NOS), with MYC and BCL6 rearrangements (prHGBL, NOS-MYC/BCL6) (n = 6) based on our previously published whole-exome sequencing (WES) cohort.

PATIENTS AND METHODS

For genomic analysis, the institutional MTB WES pipeline (University Cancer Center Schleswig-Holstein: UCCSH), certified for routine clinical diagnostics, was employed and supplemented by a comprehensive immunohistochemical work-up. Consecutive database research and annotation according to established evidence levels for molecularly stratified therapies was performed (NCT-DKTK/ESCAT).

RESULTS

Molecularly tailored treatment options with NCT-DKTK evidence level of at least m2A were identified in each case. We classified mutations in accordance with biomarker/treatment baskets and detected a heterogeneous spectrum of targetable alterations affecting immune evasion (IE; n = 30), B-cell targets (BCT; n = 26), DNA damage repair (DDR; n = 20), tyrosine kinases (TK; n = 13), cell cycle (CC; n = 7), PI3K-MTOR-AKT pathway (PAM; n = 2), RAF-MEK-ERK cascade (RME; n = 1), and others (OTH; n = 11).

CONCLUSION

Our virtual MTB approach identified potential molecularly targeted treatment options alongside targetable genomic signatures for both prDLBCL/HGBL-MYC/BCL2 and prHGBL, NOS-MYC/BCL6. These results underline the potential of MTB consultations in difficult-to-treat lymphomas early in the treatment sequence.

Off-label use of immune checkpoint inhibitors for the treatment of solid tumors: analysis of a nationwide patient sample

PURPOSE

Immune checkpoint inhibitors (ICIs) have become an indispensable part of clinical practice; however, off-label use of these agents is unknown. We aimed to define the patterns of off-label use of ICIs in a nationwide sample of patients.

METHODS

The online database (Reçetem) was retrospectively searched for off-label use cases related to ICIs approved during a 6-month period. Adult patients with metastatic solid tumors were included. Ethics approval was obtained. Reasons for off-label use were recorded in eight categories and cases were assessed for adherence to current guidelines. Statistical analysis was performed with GNU PSPP version 1.5.3.

RESULTS

Five hundred seventy-seven reasons for use were recorded for 538 cases related to 527 patients (67.5% male). Non-small-cell lung cancer (NSCLC) (35.9%) was the most common cancer type. Nivolumab (49%), pembrolizumab (25.5%), and atezolizumab (25%) were commonly used. The top reason for off-label use was lack of approval for the cancer type (37.1%), followed by use beyond the approved treatment line (21%). Nivolumab was more frequently used than atezolizumab and/or pembrolizumab in patients with malignant melanoma, kidney cancer, head and neck cancer, and hepatocellular carcinoma (Chi-square goodness-of-fit test, p < 0.001). The guideline adherence rate was 60.5%.

CONCLUSION

Off-label use of ICIs was primarily related to (NSCLC), and most patients were treatment-naïve in contrast to the acceptance that off-label use results from exhausted treatment options. Lack of approval is a significant reason for the off-label use of ICIs.

Primary refractory plasmablastic lymphoma: A precision oncology approach

Introduction

Hematologic malignancies are currently underrepresented in multidisciplinary molecular-tumor-boards (MTB). This study assesses the potential of precision-oncology in primary-refractory plasmablastic-lymphoma (prPBL), a highly lethal blood cancer.

Methods

We evaluated clinicopathological and molecular-genetic data of 14 clinically annotated prPBL-patients from initial diagnosis. For this proof-of-concept study, we employed our certified institutional MTB-pipeline (University-Cancer-Center-Schleswig-Holstein, UCCSH) to annotate a comprehensive dataset within the scope of a virtual MTB-setting, ultimately recommending molecularly stratified therapies. Evidence-levels for MTB-recommendations were defined in accordance with the NCT/DKTK and ESCAT criteria.

Results

Median age in the cohort was 76.5 years (range 56-91), 78.6% of patients were male, 50% were HIV-positive and clinical outcome was dismal. Comprehensive genomic/transcriptomic analysis revealed potential recommendations of a molecularly stratified treatment option with evidence-levels according to NCT/DKTK of at least m2B/ESCAT of at least IIIA were detected for all 14 prPBL-cases. In addition, immunohistochemical-assessment (CD19/CD30/CD38/CD79B) revealed targeted treatment-recommendations in all 14 cases. Genetic alterations were classified by treatment-baskets proposed by Horak et al. Hereby, we identified tyrosine-kinases (TK; n=4), PI3K-MTOR-AKT-pathway (PAM; n=3), cell-cycle-alterations (CC; n=2), RAF-MEK-ERK-cascade (RME; n=2), immune-evasion (IE; n=2), B-cell-targets (BCT; n=25) and others (OTH; n=4) for targeted treatment-recommendations. The minimum requirement for consideration of a drug within the scope of the study was FDA-fast-track development.

Discussion

The presented proof-of-concept study demonstrates the clinical potential of precision-oncology, even in prPBL-patients. Due to the aggressive course of the disease, there is an urgent medical-need for personalized treatment approaches, and this population should be considered for MTB inclusion at the earliest time.

Big data in basic and translational cancer research

Historically, the primary focus of cancer research has been molecular and clinical studies of a few essential pathways and genes. Recent years have seen the rapid accumulation of large-scale cancer omics data catalysed by breakthroughs in high-throughput technologies. This fast data growth has given rise to an evolving concept of 'big data' in cancer, whose analysis demands large computational resources and can potentially bring novel insights into essential questions. Indeed, the combination of big data, bioinformatics and artificial intelligence has led to notable advances in our basic understanding of cancer biology and to translational advancements. Further advances will require a concerted effort among data scientists, clinicians, biologists and policymakers. Here, we review the current state of the art and future challenges for harnessing big data to advance cancer research and treatment.

Clinical associations and genetic interactions of oncogenic BRAF alleles

BRAF is a serine/threonine-specific protein kinase that regulates the MAPK/ERK signaling pathway, and mutations in the BRAF gene are considered oncogenic drivers in diverse types of cancer. Based on the signaling mechanism, oncogenic BRAF mutations can be assigned to three different classes: class 1 mutations constitutively activate the kinase domain and lead to RAS-independent signaling, class 2 mutations induce artificial dimerization of BRAF and RAS-independent signaling and class 3 mutations display reduced or abolished kinase function and require upstream signals. Despite the importance of BRAF mutations in cancer, the clinical associations, genetic interactions and therapeutic implications of non-V600 BRAF mutations have not been explored comprehensively yet. In this study, the author analyzed publically available data from the AACR Project GENIE to further understand clinical associations and genetic interactions of oncogenic BRAF mutations. The analyses identified 93 recurrent BRAF mutations, out of which 50 could be assigned to a functional class based on literature review. The author could show that the frequency of BRAF mutations varies across cancer types and subtypes, and that the BRAF mutation classes are unequally distributed across cancer types and subtypes. Using permutation testing-based co-occurrence analyses, the author defined the genetic interactions of BRAF mutations in multiple cancer types and revealed unexplored genetic interactions that might define clinically relevant subgroups. With non-small cell lung cancer as example, the author further showed that the genetic interactions are BRAF mutation class-specific. The presented analyses explore the properties of oncogenic BRAF mutations and will help to further delineate the complex role of BRAF in cancer.

Combined Focused Next-Generation Sequencing Assays to Guide Precision Oncology in Solid Tumors: A Retrospective Analysis from an Institutional Molecular Tumor Board

BACKGROUND

Increasing knowledge of cancer biology and an expanding spectrum of molecularly targeted therapies provide the basis for precision oncology. Despite extensive gene diagnostics, previous reports indicate that less than 10% of patients benefit from this concept.

METHODS

We retrospectively analyzed all patients referred to our center's Molecular Tumor Board (MTB) from 2018 to 2021. Molecular testing by next-generation sequencing (NGS) included a 67-gene panel for the detection of short-sequence variants and copy-number alterations, a 53- or 137-gene fusion panel and an ultra-low-coverage whole-genome sequencing for the detection of additional copy-number alterations outside the panel's target regions. Immunohistochemistry for microsatellite instability and PD-L1 expression complemented NGS.

RESULTS

A total of 109 patients were referred to the MTB. In all, 78 patients received therapeutic proposals (70 based on NGS) and 33 were treated accordingly. Evaluable patients treated with MTB-recommended therapy (n = 30) had significantly longer progression-free survival than patients treated with other therapies (n = 17) (4.3 vs. 1.9 months, p = 0.0094). Seven patients treated with off-label regimens experienced major clinical benefits.

CONCLUSION

The combined focused sequencing assays detected targetable alterations in the majority of patients. Patient benefits appeared to lie in the same range as with large-scale sequencing approaches.

Challenges and Obstacles in Applying Therapeutical Indications Formulated in Molecular Tumor Boards

Considering the rapid improvement of cancer drugs' efficacy and the discovery of new molecular targets, the formulation of therapeutical indications based on the multidisciplinary approach of MTB is becoming increasingly important for attributing the correct salience to the targets identified in a single patient. Nevertheless, one of the biggest stumbling blocks faced by MTBs is not the bare indication, but its implementation in the clinical practice. Indeed, administering the drug suggested by MTB deals with some relevant difficulties: the economical affordability and geographical accessibility represent some of the major limits in the patient's view, while bureaucracy and regulatory procedures are often a disincentive for the physicians. In this review, we explore the current literature reporting MTB experiences and precision medicine clinical trials, focusing on the challenges that authors face in applying their therapeutical indications. Furthermore, we analyze and discuss some of the solutions devised to overcome these difficulties to support the MTBs in finding the most suitable solution for their specific situation. In conclusion, we strongly encourage regulatory agencies and pharmaceutical companies to develop effective strategies with medical centers implementing MTBs to facilitate access to innovative drugs and thereby allow broader therapeutical opportunities to patients.

Clinical Impact of High Throughput Sequencing on Liquid Biopsy in Advanced Solid Cancer

Background: Cancer therapies targeting actionable molecular alterations (AMA) have developed, but the clinical routine impact of high-throughput molecular profiling remains unclear. We present a monocentric experience of molecular profiling based on liquid biopsy in patients with cancer. Methods: Patients included had solid cancer and underwent cfDNA genomic profiling with FoudationOne Liquid CDx (F1LCDx) test, analyzing 324 genes. Primary endpoint was to describe patients with an AMA for whom clinical decisions were impacted by F1LCDx test results. Results: 191 patients were included, mostly with lung cancer (46%). An AMA was found in 52%. The most common molecular alterations were: TP53 (52%), KRAS (14%) and DNMT3 (11%). The most common AMA were: CHEK2 (10%), PIK3CA (9%), ATM (7%). There was no difference in progression-free survival (2.66 months vs. 3.81 months, p = 0.17), overall survival (5.3 months vs. 7.1 months, p = 0.64), or PFS2/PFS1 ratio ≥ 1.3 (20% vs. 24%, p = 0.72) between patients receiving a molecularly matched therapy (MMT) or a non-MMT, respectively. Patients with a MMT had an overall response rate of 19% and a disease control of 32%. Conclusions: Routine cfDNA molecular profiling is feasible and can lead to the access of targeted therapies. However, no notable benefit in patient’s outcomes was shown in this unselected pan-cancer study.

Mutational Landscape and Actionable Target Rates on Advanced Stage Refractory Cancer Patients: A Multicenter Chilean Experience

Major advances in sequencing technologies and targeted therapies have accelerated the incorporation of oncology into the era of precision medicine and “biomarker-driven” treatments. However, the impact of this approach on the everyday clinic has yet to be determined. Most precision oncology reports are based on developed countries and usually involve metastatic, hard-to-treat or incurable cancer patients. Moreover, in many cases race and ethnicity in these studies is commonly unreported and real-world evidence in this topic is scarce. Herein, we report data from a total of 202 Chilean advanced stage refractory cancer patients. Retrospectively, we collected patient data from NGS tests and IHC in order to determine the proportion of patients that would benefit from targeted treatments. Overall >20 tumor types were included in our cohort and 37% of patients (n = 74) displayed potentially actionable alterations, including on-label, off-label and immune checkpoint inhibitor recommendations. Our findings were in-line with previous reports such as the cancer genome atlas (TCGA). To our knowledge, this is the first report of its kind in Latin America delivering real-world evidence to estimate the percentage of refractory tumor patients that might benefit from precision oncology. Although this approach is still in its infancy in Chile, we strongly encourage the implementation of mutational tumor boards in our country in order to provide more therapeutic options for advanced stage refractory patients.

Combination of Lenvatinib and Pembrolizumab Is an Effective Treatment Option for Anaplastic and Poorly Differentiated Thyroid Carcinoma

Background: Anaplastic thyroid carcinoma (ATC) and metastatic poorly differentiated thyroid carcinomas (PDTCs) are rare aggressive malignancies with poor overall survival (OS) despite extensive multimodal therapy. These tumors are highly proliferative, with frequently increased tumor mutational burden (TMB) compared with differentiated thyroid carcinomas, and elevated programmed death ligand 1 (PD-L1) levels. These tumor properties implicate responsiveness to antiangiogenic and antiproliferative multikinase inhibitors such as lenvatinib, and immune checkpoint inhibitors such as pembrolizumab. Patients and Methods: In a retrospective study, we analyzed six patients with metastatic ATC and two patients with PDTC, who received a combination therapy of lenvatinib and pembrolizumab. Lenvatinib was started at 14-24 mg daily and combined with pembrolizumab at a fixed dose of 200 mg every three weeks. Maximum treatment duration with this combination was 40 months, and 3 of 6 ATC patients are still on therapy. Patient tumors were characterized by whole-exome sequencing and PD-L1 expression levels (tumor proportion score [TPS] 1-90%). Results: Best overall response (BOR) within ATCs was 66% complete remissions (4/6 CR), 16% stable disease (1/6 SD), and 16% progressive disease (1/6 PD). BOR within PDTCs was partial remission (PR 2/2). The median progression-free survival was 17.75 months for all patients, and 16.5 months for ATCs, with treatment durations ranging from 1 to 40 months (1, 4, 11, 15, 19, 25, 27, and 40 months). Grade III/IV toxicities developed in 4 of 8 patients, requiring dose reduction/discontinuation of lenvatinib. The median OS was 18.5 months, with three ATC patients being still alive without relapse (40, 27, and 19 months) despite metastatic disease at the time of treatment initiation (UICC and stage IVC). All patients with long-term (>2 years) or complete responses (CRs) had either increased TMB or a PD-L1 TPS >50%. Conclusions: Our results implicate that the combination of lenvatinib and pembrolizumab might be safe and effective in patients with ATC/PDTC and can result in complete and long-term remissions. The combination treatment is now being systematically examined in a phase II clinical trial (Anaplastic Thyroid Carcinoma Lenvatinib Pembrolizumab [ATLEP]) in ATC/PDTC patients.

Implementation of Precision Oncology for Patients with Metastatic Breast Cancer in an Interdisciplinary MTB Setting

The advent of molecular diagnostics and the rising number of targeted therapies have facilitated development of precision oncology for cancer patients. In order to demonstrate its impact for patients with metastatic breast cancer (mBC), we initiated a Molecular Tumor Board (MTB) to provide treatment recommendations for mBC patients who had disease progression under standard treatment. NGS (next generation sequencing) was carried out using the Oncomine multi-gene panel testing system (Ion Torrent). The MTB reviewed molecular diagnostics' results, relevant tumor characteristics, patient's course of disease and made personalized treatment and/or diagnostic recommendations for each patient. From May 2017 to December 2019, 100 mBC patients were discussed by the local MTB. A total 72% of the mBC tumors had at least one molecular alteration (median 2 per case, range: 1 to 6). The most frequent genetic changes were found in the following genes: PIK3CA (19%) and TP53 (17%). The MTB rated 53% of these alterations as actionable and treatment recommendations were made accordingly for 49 (49%) patients. Sixteen patients (16%) underwent the suggested therapy. Nine out of sixteen patients (56%; 9% of all) experienced a clinical benefit with a progression-free survival ratio ≥ 1.3. Personalized targeted therapy recommendations resulting from MTB case discussions could provide substantial benefits for patients with mBC and should be implemented for all suitable patients.

Transitioning the Molecular Tumor Board from Proof of Concept to Clinical Routine: A German Single-Center Analysis

Molecular precision oncology faces two major challenges: first, to identify relevant and actionable molecular variants in a rapidly changing field and second, to provide access to a broad patient population. Here, we report a four-year experience of the Molecular Tumor Board (MTB) of the Comprehensive Cancer Center Freiburg (Germany) including workflows and process optimizations. This retrospective single-center study includes data on 488 patients enrolled in the MTB from February 2015 through December 2018. Recommendations include individual molecular diagnostics, molecular stratified therapies, assessment of treatment adherence and patient outcomes including overall survival. The majority of MTB patients presented with stage IV oncologic malignancies (90.6%) and underwent an average of 2.1 previous lines of therapy. Individual diagnostic recommendations were given to 487 patients (99.8%). A treatment recommendation was given in 264 of all cases (54.1%) which included a molecularly matched treatment in 212 patients (43.4%). The 264 treatment recommendations were implemented in 76 patients (28.8%). Stable disease was observed in 19 patients (25.0%), 17 had partial response (22.4%) and five showed a complete remission (6.6%). An objective response was achieved in 28.9% of cases with implemented recommendations and for 4.5% of the total population (22 of 488 patients). By optimizing the MTB workflow, case-discussions per session increased significantly while treatment adherence and outcome remained stable over time. Our data demonstrate the feasibility and effectiveness of molecular-guided personalized therapy for cancer patients in a clinical routine setting showing a low but robust and durable disease control rate over time.

Clinical Utility of Next-Generation Sequencing-Based Panel Testing under the Universal Health-Care System in Japan: A Retrospective Analysis at a Single University Hospital

Next-generation sequencing (NGS) assay is part of routine care in Japan owing to its reimbursement by Japan's universal health-care system; however, reimbursement is limited to patients who finished standard treatment. We retrospectively investigated 221 patients who underwent Foundation One CDX (F1CDx) at our hospital. Every F1CDx result was assessed at the molecular tumor board (MTB) for treatment recommendation. Based on patients' preferences, presumed germline findings were also assessed at the MTB and disclosed at the clinic. In total, 204 patients underwent F1CDx and 195 patients completed the analysis; however, 13.8% of them could not receive the report due to disease progression. Among 168 patients who received the results, 41.6% had at least one actionable alteration, and 3.6% received genomically matched treatment. Presumed germline findings were nominated in 24 patients, and 16.7% of them contacted a geneticist counselor. The NGS assay should be performed earlier in the clinical course to maximize the clinical benefit. Broader reimbursement for the NGS assay would enhance the delivery of precision oncology to patients. Access to clinical trials affects the number of patients who benefit from NGS. Additionally, the disclosure of presumed germline findings is feasible in clinical practice.

NGS-guided precision oncology in metastatic breast and gynecological cancer: first experiences at the CCC Munich LMU

Purpose

Comprehensive genomic profiling identifying actionable molecular alterations aims to enable personalized treatment for cancer patients. The purpose of this analysis was to retrospectively assess the impact of personalized recommendations made by a multidisciplinary tumor board (MTB) on the outcome of patients with breast or gynecological cancers, who had progressed under standard treatment. Here, first experiences of our Comprehensive Cancer Center Molecular Tumor Board are reported.

Methods

All patients were part of a prospective local registry. 95 patients diagnosed with metastatic breast cancer or gynecological malignancies underwent extended molecular profiling. From May 2017 through March 2019, the MTB reviewed all clinical cases considering tumor profile and evaluated molecular alterations regarding further diagnostic and therapeutic recommendations.

Results

95 patients with metastatic breast or gynecological cancers were discussed in the MTB (68% breast cancer, 20% ovarian cancer, 5% cervical cancer, 3% endometrial cancer and 4% others). Genes with highest mutation rate were PIK3CA and ERBB2. Overall, 34 patients (36%) received a biomarker-based targeted therapy recommendation. Therapeutic recommendations were implemented in nine cases; four patients experienced clinical benefit with a partial response or disease stabilization lasting over 4 months.

Conclusion

In the setting of a multidisciplinary molecular tumor board, a small but clinically meaningful group of breast and gynecological cancer patients benefits from comprehensive genomic profiling. Broad and successful implementation of precision medicine is complicated by patient referral at late stage disease and limited access to targeted agents and early clinical trials.

Trial registration number

284-10 (03.05.2018).

Next-Generation Sequencing of Advanced GI Tumors Reveals Individual Treatment Options

PURPOSE

Precision oncology connects highly complex diagnostic procedures with patient histories to identify individualized treatment options in interdisciplinary molecular tumor boards (MTBs). Detailed data on MTB-guided treatments and outcome with a focus on advanced GI cancers have not been reported yet.

PATIENTS AND METHODS

Next-generation sequencing of tumor and normal tissue pairs was performed between April 2016 and February 2018. After identification of relevant molecular alterations, available clinical studies or in-label, off-label, or matched experimental treatment options were recommended. Follow-up data and a response assessment that was based on radiologic imaging were recorded.

RESULTS

Ninety-six patients were presented to the MTB of Tuebingen University Hospital. Sixteen (17%) showed "pathogenic" or "likely pathogenic" germline variants. Recommendations on the basis of molecular alterations or tumor mutational burden were given for 41 patients (43%). Twenty-five received the suggested drug, and 20 were evaluable for best response assessment. Three patients (15%) reached a partial response (PR), and 6 (30%), stable disease (SD), whereas 11 (55%) had tumor progression (progressive disease). Median progression-free survival (PFS) for all treated and evaluable patients was 2.8 months (range, 1.0-9.0 months), and median overall survival (OS) of all treated patients was 5.2 months (range, 0.1 months to not reached). Patients with SD for ≥ 3 months or PR compared with progressive disease showed both a statistically significant longer median PFS (7.8 months [95% CI, 4.2 to 11.4 months] v 2.2 months [95% CI, 1.5 to 2.8 months], P < .0001) and median OS (18.0 months [95% CI, 10.4 to 25.6 months] v 3.8 months [95% CI, 2.3 to 5.4 months], P < .0001).

CONCLUSION

Next-generation sequencing diagnostics of advanced GI cancers identified a substantial number of pathogenic or likely pathogenic germline variants and unique individual treatment options. Patients with PR or SD in the course of MTB-recommended treatments seemed to benefit with respect to PFS and OS.

Requirements Analysis and Specification for a Molecular Tumor Board Platform Based on cBioPortal

Clinicians in molecular tumor boards (MTB) are confronted with a growing amount of genetic high-throughput sequencing data. Today, at German university hospitals, these data are usually handled in complex spreadsheets from which clinicians have to obtain the necessary information. The aim of this work was to gather a comprehensive list of requirements to be met by cBioPortal to support processes in MTBs according to clinical needs. Therefore, oncology experts at nine German university hospitals were surveyed in two rounds of interviews. To generate an interview guideline a scoping review was conducted. For visual support in the second round, screenshot mockups illustrating the requirements from the first round were created. Requirements that cBioPortal already meets were skipped during the second round. In the end, 24 requirements with sometimes several conceivable options were identified and 54 screenshot mockups were created. Some of the identified requirements have already been suggested to the community by other users or are currently being implemented in cBioPortal. This shows, that the results are in line with the needs expressed by various disciplines. According to our findings, cBioPortal has the potential to significantly improve the processes and analyses of an MTB after the implementation of the identified requirements.

Targeted Therapy in Advanced Melanoma With Rare BRAF Mutations

PURPOSE

BRAF/MEK inhibition is a standard of care for patients with BRAF V600E/K-mutated metastatic melanoma. For patients with less frequent BRAF mutations, however, efficacy data are limited.

METHODS

In the current study, 103 patients with metastatic melanoma with rare, activating non-V600E/K BRAF mutations that were treated with either a BRAF inhibitor (BRAFi), MEK inhibitor (MEKi), or the combination were included. BRAF mutation, patient and disease characteristics, response, and survival data were analyzed.

RESULTS

Fifty-eight patient tumors (56%) harbored a non-E/K V600 mutation, 38 (37%) a non-V600 mutation, and seven had both V600E and a rare BRAF mutation (7%). The most frequent mutations were V600R (43%; 44 of 103), L597P/Q/R/S (15%; 15 of 103), and K601E (11%; 11 of 103). Most patients had stage IV disease and 42% had elevated lactate dehydrogenase at BRAFi/MEKi initiation. Most patients received combined BRAFi/MEKi (58%) or BRAFi monotherapy (37%). Of the 58 patients with V600 mutations, overall response rate to BRAFi monotherapy and combination BRAFi/MEKi was 27% (six of 22) and 56% (20 of 36), respectively, whereas median progression-free survival (PFS) was 3.7 months and 8.0 months, respectively (P = .002). Of the 38 patients with non-V600 mutations, overall response rate was 0% (zero of 15) to BRAFi, 40% (two of five) to MEKi, and 28% (five of 18) to combination treatment, with a median PFS of 1.8 months versus 3.7 months versus 3.3 months, respectively. Multivariable analyses revealed superior survival (PFS and overall survival) with combination over monotherapy in rare V600 and non-V600 mutated melanoma.

CONCLUSION

Patients with rare BRAF mutations can respond to targeted therapy, however, efficacy seems to be lower compared with V600E mutated melanoma. Combination BRAFi/MEKi seems to be the best regimen for both V600 and non-V600 mutations. Yet interpretation should be done with care because of the heterogeneity of patients with small sample sizes for some of the reported mutations.

Genomic expertise in action: molecular tumour boards and decision-making in precision oncology

The recent development of cancer precision medicine is associated with the emergence of 'molecular tumour boards' (MTBs). Attended by a heterogenous set of practitioners, MTBs link genomic platforms to clinical practices by establishing 'actionable' connections between drugs and molecular alterations. Their activities rely on a number of evidential resources - for example databases, clinical trial results, basic knowledge about mutations and pathways - that need to be associated with the clinical trajectory of individual patients. Experts from various domains are required to master and align diverse kinds of information. However, rather than examining MTBs as an institution interfacing different kinds of expertise embedded in individual experts, we argue that expertise is the emergent outcome of MTBs, which can be conceptualised as networks or 'agencements' of humans and devices. Based on the ethnographic analysis of the activities of four clinical trial MTBs (three in France and an international one) and of two French routine-care MTBs, the paper analyses how MTBs produce therapeutic decisions, centring on the new kind of expertise they engender. The development and activities of MTBs signal a profound transformation of the evidentiary basis and processes upon which biomedical expertise and decision-making in oncology are predicated and, in particular, the emergence of a clinic of variants.

A Simulation Study Comparing Different Statistical Approaches for the Identification of Predictive Biomarkers

Identification of relevant biomarkers that are associated with a treatment effect is one requirement for adequate treatment stratification and consequently to improve health care by administering the best available treatment to an individual patient. Various statistical approaches were proposed that allow assessing the interaction between a continuous covariate and treatment. Nevertheless, categorization of a continuous covariate, e.g., by splitting the data at the observed median value, appears to be very prevalent in practice. In this article, we present a simulation study considering data as observed in a randomized clinical trial with a time-to-event outcome performed to compare properties of such approaches, namely, Cox regression with linear interaction, Multivariable Fractional Polynomials for Interaction (MFPI), Local Partial-Likelihood Bootstrap (LPLB), and the Subpopulation Treatment Effect Pattern Plot (STEPP) method, and of strategies based on categorization of continuous covariates (splitting the covariate at the median, splitting at quartiles, and using an "optimal" split by maximizing a corresponding test statistic). In different scenarios with no interactions, linear interactions or nonlinear interactions, type I error probability and the power for detection of a true covariate-treatment interaction were estimated. The Cox regression approach was more efficient than the other methods for scenarios with monotonous interactions, especially when the number of observed events was small to moderate. When patterns of the biomarker-treatment interaction effect were more complex, MFPI and LPLB performed well compared to the other approaches. Categorization of data generally led to a loss of power, but for very complex patterns, splitting the data into multiple categories might help to explore the nature of the interaction effect. Consequently, we recommend application of statistical methods developed for assessment of interactions between continuous biomarkers and treatment instead of arbitrary or data-driven categorization of continuous covariates.