Evidence-Based Network Approach to Recommending Targeted Cancer Therapies

Molecular-Guided Off-Label Targeted Therapy in a Large-Scale Precision Oncology Program

PURPOSE

Increasing utilization of comprehensive genomic profiling (CGP) and a growing number of targeted agents (TAs) have led to substantial improvements in outcomes among patients with cancer with actionable mutations. We sought to evaluate real-world experience with off-label TAs among Veterans who underwent CGP.

METHODS

The National Precision Oncology Program database and VA Corporate Data Warehouse were queried to identify patients who underwent CGP between February 2019 and December 2021 and were prescribed 1 of 73 TAs for malignancy. OncoKB annotations were used to select patients who received off-label TAs based upon CGP results. Chart abstraction was performed to review response, toxicities, and time to progression.

RESULTS

Of 18,686 patients who underwent CGP, 2,107 (11%) were prescribed a TA and 169 (0.9%) were prescribed a total of 183 regimens containing off-label TAs for variants in 31 genes. Median age was 68 years and 83% had prior systemic therapy, with 28% receiving three or more lines. Frequency of off-label TA prescriptions was highest for patients undergoing CGP for thyroid (8.6%) and breast (7.6%) cancers. Most patients harbored alterations in BRCA1/BRCA2/ATM (22.5%), ERBB2 (19.5%), and BRAF (19.5%). Among the 160 regimens prescribed > 4 weeks, 43 (27%) led to response. Median progression-free survival and overall survival were 5.3 (4.2-6.5) and 9.7 (7.5-11.9) months, respectively. Patients with OncoKB level 2/3A/3B annotations had longer median progression-free survival (5.8 [4.5-7] months v 3.7 [1.6-7.7] months; hazard ratio, 0.45; 95% CI, 0.24 to 0.82; P = .01) compared with those receiving level 4 treatments.

CONCLUSION

Although administration of off-label TAs is infrequent after CGP, more than one quarter of treatment regimens led to response. TAs associated with level 4 annotations lead to worse outcomes than TAs bearing higher levels of evidence.

2b or Not 2b: How Opposing FGF Receptor Splice Variants Are Blocking Progress in Precision Oncology

More than ten thousand peer-reviewed studies have assessed the role of fibroblast growth factors (FGFs) and their receptors (FGFRs) in cancer, but few patients have yet benefited from drugs targeting this molecular family. Strategizing how best to use FGFR-targeted drugs is complicated by multiple variables, including RNA splicing events that alter the affinity of ligands for FGFRs and hence change the outcomes of stromal-epithelial interactions. The effects of splicing are most relevant to FGFR2; expression of the FGFR2b splice isoform can restore apoptotic sensitivity to cancer cells, whereas switching to FGFR2c may drive tumor progression by triggering epithelial-mesenchymal transition. The differentiating and regulatory actions of wild-type FGFR2b contrast with the proliferative actions of FGFR1 and FGFR3, and may be converted to mitogenicity either by splice switching or by silencing of tumor suppressor genes such as CDH1 or PTEN. Exclusive use of small-molecule pan-FGFR inhibitors may thus cause nonselective blockade of FGFR2 isoforms with opposing actions, undermining the rationale of FGFR2 drug targeting. This splice-dependent ability of FGFR2 to switch between tumor-suppressing and -driving functions highlights an unmet oncologic need for isoform-specific drug targeting, e.g., by antibody inhibition of ligand-FGFR2c binding, as well as for more nuanced molecular pathology prediction of FGFR2 actions in different stromal-tumor contexts.

Rationality of Time-Dependent Antimicrobial Use in Intensive Care Units in China: A Nationwide Cross-Sectional Survey

Background: Extended/continuous infusion and therapeutic drug monitoring (TDM) of time-dependent antimicrobials are recommended for optimizing drug exposure for patients in intensive care units (ICUs), although practical application of these measures remains uncertain. We surveyed current practices in infusion and monitoring of commonly prescribed time-dependent antimicrobials in ICUs across China.

Methods: From December 2019 to January 2020, we sent online questionnaires about various aspects of infusion and monitoring of time-dependent antimicrobials to intensivists across China. Responses from clinicians were matched with their professional titles using the Sankey diagram. Univariate and multivariate logistic regression analyses were performed to find factors associated with TDM.

Results: A total of 3,687 ICU specialists from 31 provincial administrative regions of China responded to our questionnaires. Antibiotic stewardship (ABS) teams were available in hospitals as reported by 3,243 (88.0%) intensivists, including 1,308 (35.5%) who were ABS team members. Although most intensivists (3,490, 94.7%) were acquainted with the concept of prolonged/continuous infusion, nearly half of them (1,634, 44.3%) commonly administered β-lactam antibiotics intermittently. Nearly two-thirds of the respondents reported that their hospitals could not perform TDM. Our multivariable logistic regression analysis revealed that at the hospital level, knowledge of drug sample timing and attitude toward monitoring treatment effects, and drug trough or peak concentration influenced the decision to conduct TDM.

Conclusions: We found great variability in prescribing practices, from drug administration to TDM, for several time-dependent antibiotics commonly used for patients with severe infections. Further studies are necessary to effectively evaluate strategies to promote consistent prescribing behavior.

OncoMX: A Knowledgebase for Exploring Cancer Biomarkers in the Context of Related Cancer and Healthy Data

PURPOSE

The purpose of OncoMX¹ knowledgebase development was to integrate cancer biomarker and relevant data types into a meta-portal, enabling the research of cancer biomarkers side by side with other pertinent multidimensional data types.

METHODS

Cancer mutation, cancer differential expression, cancer expression specificity, healthy gene expression from human and mouse, literature mining for cancer mutation and cancer expression, and biomarker data were integrated, unified by relevant biomedical ontologies, and subjected to rule-based automated quality control before ingestion into the database.

RESULTS

OncoMX provides integrated data encompassing more than 1,000 unique biomarker entries (939 from the Early Detection Research Network [EDRN] and 96 from the US Food and Drug Administration) mapped to 20,576 genes that have either mutation or differential expression in cancer. Sentences reporting mutation or differential expression in cancer were extracted from more than 40,000 publications, and healthy gene expression data with samples mapped to organs are available for both human genes and their mouse orthologs.

CONCLUSION

OncoMX has prioritized user feedback as a means of guiding development priorities. By mapping to and integrating data from several cancer genomics resources, it is hoped that OncoMX will foster a dynamic engagement between bioinformaticians and cancer biomarker researchers. This engagement should culminate in a community resource that substantially improves the ability and efficiency of exploring cancer biomarker data and related multidimensional data.

The Community Oncology and Academic Medical Center Alliance in the Age of Precision Medicine: Cancer Genetics and Genomics Considerations

Recent public policy, governmental regulatory and economic trends have motivated the establishment and deepening of community health and academic medical center alliances. Accordingly, community oncology practices now deliver a significant portion of their oncology care in association with academic cancer centers. In the age of precision medicine, this alliance has acquired critical importance; novel advances in nucleic acid sequencing, the generation and analysis of immense data sets, the changing clinical landscape of hereditary cancer predisposition and ongoing discovery of novel, targeted therapies challenge community-based oncologists to deliver molecularly-informed health care. The active engagement of community oncology practices with academic partners helps with meeting these challenges; community/academic alliances result in improved cancer patient care and provider efficacy. Here, we review the community oncology and academic medical center alliance. We examine how practitioners may leverage academic center precision medicine-based cancer genetics and genomics programs to advance their patients' needs. We highlight a number of project initiatives at the City of Hope Comprehensive Cancer Center that seek to optimize community oncology and academic cancer center precision medicine interactions.

Collaborative, Multidisciplinary Evaluation of Cancer Variants Through Virtual Molecular Tumor Boards Informs Local Clinical Practices

PURPOSE

The cancer research community is constantly evolving to better understand tumor biology, disease etiology, risk stratification, and pathways to novel treatments. Yet the clinical cancer genomics field has been hindered by redundant efforts to meaningfully collect and interpret disparate data types from multiple high-throughput modalities and integrate into clinical care processes. Bespoke data models, knowledgebases, and one-off customized resources for data analysis often lack adequate governance and quality control needed for these resources to be clinical grade. Many informatics efforts focused on genomic interpretation resources for neoplasms are underway to support data collection, deposition, curation, harmonization, integration, and analytics to support case review and treatment planning.

METHODS

In this review, we evaluate and summarize the landscape of available tools, resources, and evidence used in the evaluation of somatic and germline tumor variants within the context of molecular tumor boards.

RESULTS

Molecular tumor boards (MTBs) are collaborative efforts of multidisciplinary cancer experts equipped with genomic interpretation resources to aid in the delivery of accurate and timely clinical interpretations of complex genomic results for each patient, within an institution or hospital network. Virtual MTBs (VMTBs) provide an online forum for collaborative governance, provenance, and information sharing between experts outside a given hospital network with the potential to enhance MTB discussions. Knowledge sharing in VMTBs and communication with guideline-developing organizations can lead to progress evidenced by data harmonization across resources, crowd-sourced and expert-curated genomic assertions, and a more informed and explainable usage of artificial intelligence.

CONCLUSION

Advances in cancer genomics interpretation aid in better patient and disease classification, more streamlined identification of relevant literature, and a more thorough review of available treatments and predicted patient outcomes.