Delivering precision oncology to patients with cancer

Pioneering the implementation of a precision oncology strategy in Portugal: the Precision Oncology Platform trial

BACKGROUND AND PURPOSE

The Precision Oncology Platform (POP) trial represents the effort of the Portuguese Oncology Institute of Porto (IPO Porto) for joining other leading European institutions in both 'Personalised Cancer Medicine for all EU citizens' (PCM4EU), and 'PRecisIon Cancer MEdicine RepurpOsing SystEm Using Pragmatic Clinical Trials' (PRIME-ROSE) consortia, enabling the development of the Portuguese version of the Drug Rediscovery Protocol (DRUP)-like Clinical Trial (DLCT), based on the experience of the DRUP trial developed in The Netherlands.

PATIENTS/MATERIAL AND METHODS

The POP trial is a phase II, pragmatic multicentric, non-randomised, open-label study, designed entirely like the other DLCTs. Its primary objective is to describe anti-tumour activity of targeted anticancer drugs in patients with advanced malignancies harbouring actionable molecular alterations. The primary endpoint is disease control rate (DCR). Secondary endpoints encompass treatment-related grade ≥3 adverse events, objective response rate (ORR), duration of response (DOR), progression-free survival (PFS), and overall survival (OS). Exploratory objectives will assess biomarkers, resource use and costs, and patient-reported outcome measures (PROMs).

INTERPRETATION

The POP trial will offer access to innovative treatments for patients without further therapeutic options and provide evidence on efficacy and safety of molecularly-guided treatments. Methodologically, it represents a pioneer approach in Portugal, including a pay-for-performance model embedded in the clinical trial. The POP trial represents a unique opportunity to integrate clinical research within cancer care, pursuing an evidence-based precision oncology strategy, and facilitating its rational and cost-effective implementation into the Portuguese healthcare system.

Pathological biopsy strategy by regulating intracellular ROS to precisely differentiate cancer cells from diseased tissues

We have developed an innovative pathological biopsy strategy by expanding the differences of ROS levels among cancer cells, inflammatory cells and normal cells using cross-linked lipoic acid vesicles loaded with vitamin C (VC@cLAVs), combined with chemiluminescence imaging technology. By analyzing the different trends of intracellular chemiluminescence intensity, the three types of cells were quickly and accurately differentiated from diseased tissues, thus holding clinical tumor diagnostic potential.

An All-Rounder for NIR-II Phototheranostics: Well-Tailored 1064 nm-Excitable Molecule for Photothermal Combating of Orthotopic Breast Cancer

The second near-infrared (NIR-II, 1000-1700 nm) light-activated organic photothermal agent that synchronously enables satisfying NIR-II fluorescence imaging is highly warranted yet rather challenging on the basis of the overwhelming nonradiative decay. Herein, such an agent, namely TPABT-TD, was tactfully designed and constructed via employing benzo[c]thiophene moiety as bulky electron donor/π-bridge and tailoring the peripheral molecular rotors. Benefitting from its high electron donor-acceptor strength and finely modulated intramolecular motion, TPABT-TD simultaneously exhibits ultralong absorption in NIR-II region, intense fluorescence emission in the NIR-IIa (1300-1500 nm) region as nanoaggregates, and high photothermal conversion upon 1064 nm laser irradiation. Those intrinsic advantages endow TPABT-TD nanoparticles with prominent fluorescence/photoacoustic/photothermal trimodal imaging-guided NIR-II photothermal therapy against orthotopic 4T1 breast tumor with negligible adverse effect.

CoHIT: a one-pot ultrasensitive ERA-CRISPR system for detecting multiple same-site indels

Genetic testing is crucial for precision cancer medicine. However, detecting multiple same-site insertions or deletions (indels) is challenging. Here, we introduce CoHIT (Cas12a-based One-for-all High-speed Isothermal Test), a one-pot CRISPR-based assay for indel detection. Leveraging an engineered AsCas12a protein variant with high mismatch tolerance and broad PAM scope, CoHIT can use a single crRNA to detect multiple NPM1 gene c.863_864 4-bp insertions in acute myeloid leukemia (AML). After optimizing multiple parameters, CoHIT achieves a detection limit of 0.01% and rapid results within 30 minutes, without wild-type cross-reactivity. It successfully identifies NPM1 mutations in 30 out of 108 AML patients and demonstrates potential in monitoring minimal residual disease (MRD) through continuous sample analysis from three patients. The CoHIT method is also competent for detecting indels of KIT, BRAF, and EGFR genes. Integration with lateral flow test strips and microfluidic chips highlights CoHIT's adaptability and multiplexing capability, promising significant advancements in clinical cancer diagnostics.

Spatial transcriptomics in cancer research and potential clinical impact: a narrative review

Spatial transcriptomics (ST) provides novel insights into the tumor microenvironment (TME). ST allows the quantification and illustration of gene expression profiles in the spatial context of tissues, including both the cancer cells and the microenvironment in which they are found. In cancer research, ST has already provided novel insights into cancer metastasis, prognosis, and immunotherapy responsiveness. The clinical precision oncology application of next-generation sequencing (NGS) and RNA profiling of tumors relies on bulk methods that lack spatial context. The ability to preserve spatial information is now possible, as it allows us to capture tumor heterogeneity and multifocality. In this narrative review, we summarize precision oncology, discuss tumor sequencing in the clinic, and review the available ST research methods, including seqFISH, MERFISH (Vizgen), CosMx SMI (NanoString), Xenium (10x), Visium (10x), Stereo-seq (STOmics), and GeoMx DSP (NanoString). We then review the current ST literature with a focus on solid tumors organized by tumor type. Finally, we conclude by addressing an important question: how will spatial transcriptomics ultimately help patients with cancer?

Clinical Utility of Tumor Next-Generation Sequencing Panel Testing to Inform Treatment Decisions for Patients With Advanced Solid Tumors in a Tertiary Care Center

PURPOSE

There is limited information about the clinical utility of targeted next-generation sequencing (NGS) panel testing to inform decision making for patients with advanced solid tumors. The Ontario-wide Cancer Targeted Nucleic Acid Evaluation (OCTANE) is a prospective study that enrolled more than 4,500 patients with solid tumor for NGS panel testing. We performed a retrospective survey of medical oncologists to evaluate the impact of NGS testing on treatment decisions.

METHODS

Patients and treating oncologists were identified at the Princess Margaret Cancer Center between 2016 and 2021. Tumor-only sequencing was performed using a gene panel of either 555 or 161 cancer genes. Oncologists were asked to review testing results and complete a survey indicating whether NGS testing affected treatment decisions. The primary outcome of this study was rate of treatment change on the basis of mutation results. Patient, test, and physician factors were evaluated for association with treatment changes using univariate analyses and a mixed-effects model.

RESULTS

Of the 582 surveys sent, 394 (67.7%) were completed. We found that 188 (47.7%) patients had testing results classified as actionable by the oncologist and 62 (15.7%) patients were matched to treatment, of whom 37 (60%) were enrolled in a clinical trial, 13 (21%) received an approved drug, four (6%) were prescribed off-label therapy, and eight (13%) avoided ineffective treatment. Patient, test, and physician characteristics were not significantly associated with treatment change. There was no difference in overall survival between patients who received matched treatment versus those who did not (P = .55, median survival not reached).

CONCLUSION

OCTANE testing led to a change in drug treatment in 15.7% of patients, supporting the clinical utility of NGS panel testing for patients with advanced solid tumors.

2023 Society for Academic Emergency Medicine Consensus Conference on Precision Emergency Medicine: Development of a policy-relevant, patient-centered research agenda

OBJECTIVES

Precision medicine is data-driven health care tailored to individual patients based on their unique attributes, including biologic profiles, disease expressions, local environments, and socioeconomic conditions. Emergency medicine (EM) has been peripheral to the precision medicine discourse, lacking both a unified definition of precision medicine and a clear research agenda. We convened a national consensus conference to build a shared mental model and develop a research agenda for precision EM.

METHODS

We held a conference to (1) define precision EM, (2) develop an evidence-based research agenda, and (3) identify educational gaps for current and future EM clinicians. Nine preconference workgroups (biomedical ethics, data science, health professions education, health care delivery and access, informatics, omics, population health, sex and gender, and technology and digital tools), comprising 84 individuals, garnered expert opinion, reviewed relevant literature, engaged with patients, and developed key research questions. During the conference, each workgroup shared how they defined precision EM within their domain, presented relevant conceptual frameworks, and engaged a broad set of stakeholders to refine precision EM research questions using a multistage consensus-building process.

RESULTS

A total of 217 individuals participated in this initiative, of whom 115 were conference-day attendees. Consensus-building activities yielded a definition of precision EM and key research questions that comprised a new 10-year precision EM research agenda. The consensus process revealed three themes: (1) preeminence of data, (2) interconnectedness of research questions across domains, and (3) promises and pitfalls of advances in health technology and data science/artificial intelligence. The Health Professions Education Workgroup identified educational gaps in precision EM and discussed a training roadmap for the specialty.

CONCLUSIONS

A research agenda for precision EM, developed with extensive stakeholder input, recognizes the potential and challenges of precision EM. Comprehensive clinician training in this field is essential to advance EM in this domain.

Machine learning and radiomics analysis by computed tomography in colorectal liver metastases patients for RAS mutational status prediction

PURPOSE

To assess the efficacy of machine learning and radiomics analysis by computed tomography (CT) in presurgical setting, to predict RAS mutational status in colorectal liver metastases.

METHODS

Patient selection in a retrospective study was carried out from January 2018 to May 2021 considering the following inclusion criteria: patients subjected to surgical resection for liver metastases; proven pathological liver metastases; patients subjected to enhanced CT examination in the presurgical setting with a good quality of images; and RAS assessment as standard reference. A total of 851 radiomics features were extracted using the PyRadiomics Python package from the Slicer 3D image computing platform after slice-by-slice segmentation on CT portal phase by two expert radiologists of each individual liver metastasis performed first independently by the individual reader and then in consensus. Balancing technique was performed, and inter- and intraclass correlation coefficients were calculated to assess the between-observer and within-observer reproducibility of features. Receiver operating characteristics (ROC) analysis with the calculation of area under the ROC curve (AUC), sensitivity (SENS), specificity (SPEC), positive predictive value (PPV), negative predictive value (NPV) and accuracy (ACC) were assessed for each parameter. Linear and non-logistic regression model (LRM and NLRM) and different machine learning-based classifiers were considered. Moreover, features selection was performed before and after a normalized procedure using two different methods (3-sigma and z-score).

RESULTS

Seventy-seven liver metastases in 28 patients with a mean age of 60 years (range 40-80 years) were analyzed. The best predictors, at univariate analysis for both normalized procedures, were original_shape_Maximum2DDiameter and wavelet_HLL_glcm_InverseVariance that reached an accuracy of 80%, an AUC ≥ 0.75, a sensitivity ≥ 80% and a specificity ≥ 70% (p value <  < 0.01). However, a multivariate analysis significantly increased the accuracy in RAS prediction when a linear regression model (LRM) was used. The best performance was obtained using a LRM combining linearly 12 robust features after a z-score normalization procedure: AUC of 0.953, accuracy 98%, sensitivity 96%, specificity of 100%, PPV 100% and NPV 96% (p value <  < 0.01). No statistically significant increase was obtained considering the tested machine learning both without normalization and with normalization methods.

CONCLUSIONS

Normalized approach in CT radiomics analysis allows to predict RAS mutational status in colorectal liver metastases patients.

Effect of Probiotic Supplements on the Oral Microbiota-A Narrative Review

Data from systematic reviews and meta-analyses show that probiotics positively impact clinical parameters of oral diseases such as gingivitis, dental caries, and periodontitis. However, the working mechanism of probiotics is not fully understood, but is hypothesized to be mediated by direct and indirect interactions with the oral microbiota and the human host. In the present narrative review, we focused on the microbiological effect of probiotic supplements based on data retrieved from randomized clinical trials (RCTs). In addition, we assessed to what extent contemporary molecular methods have been employed in clinical trials in the field of oral probiotics. Multiple RCTs have been performed studying the potential effect of probiotics on gingivitis, dental caries, and periodontitis, as evaluated by microbial endpoints. In general, results are conflicting, with some studies reporting a positive effect, whereas others are not able to record any effect. Major differences in terms of study designs and sample size, as well as delivery route, frequency, and duration of probiotic consumption, hamper comparison across studies. In addition, most RCTs have been performed with a limited sample size using relatively simple methods for microbial identification, such as culturing, qPCR, and DNA-DNA checkerboard, while high-throughput methods such as 16S sequencing have only been employed in a few studies. Currently, state-of-the-art molecular methods such as metagenomics, metatranscriptomics, and metaproteomics have not yet been used in RCTs in the field of probiotics. The present narrative review revealed that the effect of probiotic supplements on the oral microbiota remains largely uncovered. One important reason is that most RCTs are performed without studying the microbiological effect. To facilitate future systematic reviews and meta-analyses, an internationally agreed core outcome set for the reporting of microbial endpoints in clinical trials would be desirable. Such a standardized collection of outcomes would most likely improve the quality of probiotic research in the oral context.

Pragmatic nationwide master observational trial based on genomic alterations in advanced solid tumors: KOrean Precision Medicine Networking Group Study of MOlecular profiling guided therapy based on genomic alterations in advanced Solid tumors (KOSMOS)-II study protocol KCSG AL-22-09

BACKGROUND

Next-generation sequencing (NGS) has been introduced to many Korean institutions to support molecular diagnostics in cancer since 2017, when it became eligible for reimbursement by the National Health Insurance Service. However, the uptake of molecularly guided treatment (MGT) based on NGS results has been limited because of stringent regulations regarding prescriptions outside of approved indications, a lack of clinical trial opportunities, and limited access to molecular tumor boards (MTB) at most institutions. The KOSMOS-II study was designed to demonstrate the feasibility and effectiveness of MGT, informed by MTBs, using a nationwide precision medicine platform.

METHODS

The KOSMOS-II trial is a large-scale nationwide master observational study. It involves a framework for screening patients with metastatic solid tumors for actionable genetic alterations based on local NGS testing. It recommends MGT through a remote and centralized MTB meeting held biweekly. MGT can include one of the following options: Tier 1, the therapeutic use of investigational drugs targeting genetic alterations such as ALK, EGFR, ERBB2, BRAF, FH, ROS1, and RET, or those with high tumor mutational burden; Tier 2, comprising drugs with approved indications or those permitted for treatment outside of the indications approved by the Health Insurance Review and Assessment Service of Korea; Tier 3, involving clinical trials matching the genetic alterations recommended by the MTB. Given the anticipated proportion of patients receiving MGT in the range of 50% ± 3.25%, this study aims to enroll 1,000 patients. Patients must have progressed to one or more lines of therapy and undergone NGS before enrollment.

DISCUSSION

This pragmatic master protocol provides a mass-screening platform for rare genetic alterations and high-quality real-world data. Collateral clinical trials, translational studies, and clinico-genomic databases will contribute to generating evidence for drug repositioning and the development of new biomarkers.

TRIAL REGISTRATION

NCT05525858.

What Do German Molecular Tumor Boards Recommend in Patients with PIK3CA-Mutated Tumors? Launch and First Results from the German Transsectoral Molecular Tumor Board Exchange Platform Deutschland

INTRODUCTION

Comprehensive molecular tumor profiling is widely used in the management of patients with cancer. Molecular tumor boards devise treatment strategies based on testing results. In this setting, the Transsectoral Molecular Tumor Board exchange platform Deutschland (TEAM-D) aims to drive peer-to-peer exchange to connect experts in the field.

METHODS

During the first virtual TEAM-D meeting, participants from 16 German universities and 5 nonacademic institutions discussed five cases with PIK3CA hotspot mutations. Furthermore, an illustrative case vignette was presented.

RESULTS

Overall, German caregivers show restraint in administering off-label PIK3CA inhibitor and favor clinical trials in this setting.

CONCLUSION

In the setting of precision oncology, TEAM-D enables virtual case discussion across the different sectors of the German healthcare system. Based on the example of PIK3CA hotspot mutations, TEAM-D demonstrated the value of integrating knowledge from different healthcare professionals.

A Systematic Review of Value Criteria for Next-Generation Sequencing/Comprehensive Genomic Profiling to Inform Value Framework Development

OBJECTIVES

To comprehensively identify and map an exhaustive list of value criteria for the assessment of next-generation sequencing/comprehensive genomic profiling (NGS/CGP), to be used as an aid in decision making.

METHODS

We conducted a systematic review to identify existing value frameworks (VFs) applicable to any type of healthcare technology. VFs and criteria were mapped to a previously published Latin American (LA) VF to harmonize definitions and identify additional criteria and or subcriteria. Based on this analysis, we extracted a comprehensive, evidence-based list of criteria and subcriteria to be considered in the design of a NGS/CGP VF.

RESULTS

A total of 42 additional VFs were compared with the LA VF, 88% were developed in high-income countries, 30% targeted genomic testing, and 16% specifically targeted oncology. A total of 242 criteria and subcriteria were extracted; 227 (94%) were fully/partially included in the LA VF; and 15 (6%) were new. Clinical benefit and economic aspects were the most common criteria. VFs oriented to genomic testing showed significant overlap with other VFs. Considering all criteria and subcriteria, a total of 18 criteria and 36 individual subcriteria were identified.

CONCLUSIONS

Our study provides an evidence-based set of criteria and subcriteria for healthcare decision making useful for NGS/CGP as well as other health technologies. The resulting list can be beneficial to inform decision making and will serve as a foundation to co-create a multistakeholder NGS/CGP VF that is aligned with the needs and values of health systems and could help to improve patient access to high-value technologies.

Precision Medicine in Veterinary Science

Precision medicine focuses on the clinical management of the individual patient, not on population-based findings. Successes from human precision medicine inform veterinary oncology. Early evidence of success for canines shows how precision medicine can be integrated into practice. Decreasing genomic profiling costs will allow increased utilization and subsequent improvement of knowledge base from which to make better informed decisions. Utility of precision medicine in canine oncology will only increase for improved cancer characterization, enhanced therapy selection, and overall more successful management of canine cancer. As such, practitioners are called to interpret and leverage precision medicine reports for their patients.

NGS-Guided Precision Oncology in Breast Cancer and Gynecological Tumors-A Retrospective Molecular Tumor Board Analysis

Background: Precision oncology treatments are being applied more commonly in breast and gynecological oncology through the implementation of Molecular Tumor Boards (MTBs), but real-world clinical outcome data remain limited. Methods: A retrospective analysis was conducted in patients with breast cancer (BC) and gynecological malignancies referred to our center's MTB from 2018 to 2023. The analysis covered patient characteristics, next-generation sequencing (NGS) results, MTB recommendations, therapy received, and clinical outcomes. Results: Sixty-three patients (77.8%) had metastatic disease, and forty-four patients (54.3%) had previously undergone three or more lines of systemic treatment. Personalized treatment recommendations were provided to 50 patients (63.3%), while 29 (36.7%) had no actionable target. Ultimately, 23 patients (29.1%) underwent molecular-matched treatment (MMT). Commonly altered genes in patients with pan-gyn tumors (BC and gynecological malignancies) included TP53 (n = 42/81, 51.9%), PIK3CA (n = 18/81, 22.2%), BRCA1/2 (n = 10/81, 12.3%), and ARID1A (n = 9/81, 11.1%). Patients treated with MMT showed significantly prolonged progression-free survival (median PFS 5.5 vs. 3.5 months, p = 0.0014). Of all patients who underwent molecular profiling, 13.6% experienced a major clinical benefit (PFSr ≥ 1.3 and PR/SD ≥ 6 months) through precision oncology. Conclusions: NGS-guided precision oncology demonstrated improved clinical outcomes in a subgroup of patients with gynecological and breast cancers.

Precision medicine for prostate cancer: An international perspective

Greater personalization of cancer medicine continues to shape therapy development and patient selection accordingly. The treatment of prostate cancer has evolved considerably since the discovery of androgen deprivation therapy. The comprehensive profiling of the prostate cancer genome has mapped the targetable molecular landscape of the disease and identified opportunities for the implementation of novel and combination therapies. In this review, we provide an overview of the molecular biology of prostate cancer and tools developed to aid prognostication and prediction of therapy benefit. Modern treatment of advanced prostate cancer is reviewed as a paradigm of increasing precision-informed approach to patient care, and must be considered on a global scale with respect to the state of science and care delivery.

Supporting the decision to perform molecular profiling for cancer patients based on routinely collected data through the use of machine learning

BACKGROUND

Personalized medicine offers targeted therapy options for cancer treatment. However, the decision whether to include a patient into next-generation sequencing (NGS) testing is not standardized. This may result in some patients receiving unnecessary testing while others who could benefit from it are not tested. Typically, patients who have exhausted conventional treatment options are of interest for consideration in molecularly targeted therapy. To assist clinicians in decision-making, we developed a decision support tool using routine data from a precision oncology program.

METHODS

We trained a machine learning model on clinical data to determine whether molecular profiling should be performed for a patient. To validate the model, the model's predictions were compared with decisions made by a molecular tumor board (MTB) using multiple patient case vignettes with their characteristics.

RESULTS

The prediction model included 440 patients with molecular profiling and 13,587 patients without testing. High area under the curve (AUC) scores indicated the importance of engineered features in deciding on molecular profiling. Patient age, physical condition, tumor type, metastases, and previous therapies were the most important features. During the validation MTB experts made the same decision of recommending a patient for molecular profiling only in 10 out of 15 of their previous cases but there was agreement between the experts and the model in 9 out of 15 cases.

CONCLUSION

Based on a historical cohort, our predictive model has the potential to assist clinicians in deciding whether to perform molecular profiling.

Understanding the Landscape of Clinically Available Molecular Testing

Over the past three decades, the landscape of clinically available molecular tests has evolved due to advancements in basic science cancer research and the subsequent utilization of this knowledge to develop DNA, RNA, and protein-based molecular assays for oncology that can be employed for routine clinical use in diagnostics laboratories. Molecular testing of tumors is revealing gaps in previous histopathologic classification systems and opportunities for new, personalized treatment paradigms. Awareness of validated molecular assay options and their general advantages and limitations is crucial for oncology care providers to ensure the optimal test(s) are selected for each patient's circumstances.

Evolution of Precision Oncology, Personalized Medicine, and Molecular Tumor Boards

With multiple molecular targeted therapies available for patients with cancer that correspond to a specific genetic alteration, the selection of the best treatment is essential to ensure therapeutic efficacy. Molecular tumor boards (MTBs) play a key role in this process to deliver personalized medicine to patients with cancer in a multidisciplinary manner. Historically, personalized medicine has been offered to patients with advanced cancer, but the incorporation of molecular targeted therapies and immunotherapy into the perioperative setting requires clinicians to understand the role of the MTB. Evidence is accumulating to support feasibility and survival benefit in patients treated with matched therapy.

Expert-based collaborative analysis of the situation and prospects of biomarker test implementation in oncology in Spain

PURPOSE

Biomarkers as screening for precision medicine is a fundamental step. The purpose of this article is twofold. First, to highlight the existing barriers in the implementation of Precision Medicine in Spain, with a special emphasis on barriers in access to the determination of biomarkers. Second, to provide a Roadmap that can help implement Precision Medicine equitably at the national level and optimize the use of biomarkers.

METHODS

A systematic review of literature (SRL) and a focus group (FG) with multidisciplinary experts has been carried out in 2023. Participants were contacted individually, and discourse analysis was processed anonymously.

RESULTS

We carried out a quantitative (SRL) and a qualitative approach (FG). The discourse analysis and roadmap were sent individually to each expert for approval.

CONCLUSIONS

The potential of Precision Medicine has not been fulfilled in Spain. While several regional initiatives are in place, a national plan or strategy around Precision Medicine and use of biomarkers is lacking. In a general context of rapid progress at a global and European level, including the 2021 Europe's Beating Cancer Plan, it is time to define and implement a National Plan to make the promise come true. While some comparable countries within Europe - such as the UK or France - are mature enough to adopt such strategies, in Spain there is still a long way to go. We consider that the different strands of work outlined in the Roadmap can be used as basis for such purpose.

Myocardial DNA Damage Predicts Heart Failure Outcome in Various Underlying Diseases

BACKGROUND

Reliable predictors of treatment efficacy in heart failure have been long awaited. DNA damage has been implicated as a cause of heart failure.

OBJECTIVES

The purpose of this study was to investigate the association of DNA damage in myocardial tissue with treatment response and prognosis of heart failure.

METHODS

The authors performed immunostaining of DNA damage markers poly(ADP-ribose) (PAR) and γ-H2A.X in endomyocardial biopsy specimens from 175 patients with heart failure with reduced ejection fraction (HFrEF) of various underlying etiologies. They calculated the percentage of nuclei positive for each DNA damage marker (%PAR and %γ-H2A.X). The primary outcome was left ventricular reverse remodeling (LVRR) at 1 year, and the secondary outcome was a composite of cardiovascular death, heart transplantation, and ventricular assist device implantation.

RESULTS

Patients who did not achieve LVRR after the optimization of medical therapies presented with significantly higher %PAR and %γ-H2A.X. The ROC analysis demonstrated good performance of both %PAR and %γ-H2A.X for predicting LVRR (AUCs: 0.867 and 0.855, respectively). There was a negative correlation between the mean proportion of DNA damage marker-positive nuclei and the probability of LVRR across different underlying diseases. In addition, patients with higher %PAR or %γ-H2A.X had more long-term clinical events (PAR HR: 1.63 [95% CI: 1.31-2.01]; P < 0.001; γ-H2A.X HR: 1.48 [95% CI: 1.27-1.72]; P < 0.001).

CONCLUSIONS

DNA damage determines the consequences of human heart failure. Assessment of DNA damage is useful to predict treatment efficacy and prognosis of heart failure patients with various underlying etiologies.

Anti-Tumor Potential of Post-Translational Modifications of PD-1

Programmed cell death protein-1 (PD-1) is a vital immune checkpoint molecule. The location, stability, and protein-protein interaction of PD-1 are significantly influenced by post-translational modification (PTM) of proteins. The biological information of PD-1, including its gene and protein structures and the PD-1/PD-L1 signaling pathway, was briefly reviewed in this review. Additionally, recent research on PD-1 post-translational modification, including the study of ubiquitination, glycosylation, phosphorylation, and palmitoylation, was summarized, and research strategies for PD-1 PTM drugs were concluded. At present, only a part of PD-1/PD-L1 treated patients (35-45%) are benefited from immunotherapies, and novel strategies targeting PTM of PD-1/PD-L1 may be important for anti-PD-1/PD-L1 non-responders (poor responders).

New windows of surgical opportunity for gynecological cancers in the era of targeted therapies

Precision medicine through molecular profiling has taken a prominent role in the treatment of solid tumors and it is widely expected that this will continue to expand. With respect to gynecological cancers, a major change has particularly been observed in the treatment landscape of epithelial ovarian, endometrial, and cervical cancers. Regarding the former, maintenance therapy with either poly(ADP-ribose) polymerase inhibitors (PARPi) and/or bevacizumab has become an indispensable treatment option following the traditional combination of cytoreductive surgery and platinum-based chemotherapy. Considering endometrial cancer, the molecular classification system has now been incorporated into virtually every guideline available and molecular-directed treatment strategies are currently being researched, presumably leading to a further transformation of its treatment paradigm. After all, treatment with immune-checkpoint inhibitors that target the programmed cell death 1 (PD-1) receptor has already been shown to significantly improve disease outcomes in these patients, especially in those with mismatch repair deficient, microsatellite stability-high (MMRd-MSI-H) disease. Similarly, in recurrent/metastatic cervical cancer patients, these agents elicited improved survival rates when being added to platinum-based chemotherapy with or without bevacizumab. Interestingly, implications of these targeted therapies for surgical management have been touched on to a minor extent, but are at least as intriguing. This review therefore aims to address the wide-ranging opportunities the molecular tumor characteristics and their corresponding targeted therapies have to offer for the surgical management of epithelial ovarian, endometrial, and cervical cancers, both in the primary and recurrent setting.

Machine learning-based radiomics analysis in predicting RAS mutational status using magnetic resonance imaging

PURPOSE

To assess the efficacy of radiomics features, obtained by magnetic resonance imaging (MRI) with hepatospecific contrast agent, in pre-surgical setting, to predict RAS mutational status in liver metastases.

METHODS

Patients with MRI in pre-surgical setting were enrolled in a retrospective study. Manual segmentation was made by means 3D Slicer image computing, and 851 radiomics features were extracted as median values using the PyRadiomics Python package. The features were extracted considering the agreement with the Imaging Biomarker Standardization Initiative (IBSI). Balancing was performed through synthesis of samples for the underrepresented classes using the self-adaptive synthetic oversampling (SASYNO) approach. Inter- and intraclass correlation coefficients (ICC) were calculated to assess the between-observer and within-observer reproducibility of all radiomics characteristics. For continuous variables, nonparametric Wilcoxon-Mann-Whitney test was utilized. Benjamini and Hochberg's false discovery rate (FDR) adjustment for multiple testing was used. Receiver operating characteristics (ROC) analysis with the calculation of area under the ROC curve (AUC), sensitivity (SENS), specificity (SPEC), positive predictive value (PPV), negative predictive value (NPV) and accuracy (ACC) were assessed for each parameter. Linear and non-logistic regression model (LRM and NLRM) and different machine learning-based classifiers including decision tree (DT), k-nearest neighbor (KNN) and support vector machine (SVM) were considered. Moreover, features selection were performed before and after a normalized procedure using two different methods (3-sigma and z-score). McNemar test was used to assess differences statistically significant between dichotomic tables. All statistical procedures were done using MATLAB R2021b Statistics and Machine Toolbox (MathWorks, Natick, MA, USA).

RESULTS

Seven normalized radiomics features, extracted from arterial phase, 11 normalized radiomics features, from portal phase, 12 normalized radiomics features from hepatobiliary phase and 12 normalized features from T2-W SPACE sequence were robust predictors of RAS mutational status. The multivariate analysis increased significantly the accuracy in RAS prediction when a LRM was used, combining 12 robust normalized features extracted by VIBE hepatobiliary phase reaching an accuracy of 99%, a sensitivity 97%, a specificity of 100%, a PPV of 100% and a NPV of 98%. No statistically significant increase was obtained, considering the tested classifiers DT, KNN and SVM, both without normalization and with normalization methods.

CONCLUSIONS

Normalized approach in MRI radiomics analysis allows to predict RAS mutational status.

Moving toward precision medicine to predict drug sensitivity in patients with metastatic breast cancer

Tumor heterogeneity represents a major challenge in breast cancer, being associated with disease progression and treatment resistance. Precision medicine has been extensively applied to dissect tumor heterogeneity and, through a deeper molecular understanding of the disease, to personalize therapeutic strategies. In the last years, technological advances have widely improved the understanding of breast cancer biology and several trials have been developed to translate these new insights into clinical practice, with the ultimate aim of improving patients' outcomes. In the era of molecular oncology, genomics analyses and other methodologies are shaping a new treatment algorithm in breast cancer care. In this manuscript, we review the main steps of precision medicine to predict drug sensitivity in breast cancer from a translational point of view. Genomic developments and their clinical implications are discussed, along with technological advancements that could broaden precision medicine applications. Current achievements are put into perspective to provide an overview of the state-of-art of breast cancer precision oncology as well as to identify future research directions.

Fluorescence-guided assessment of bone and soft-tissue sarcomas for predicting the efficacy of telomerase-specific oncolytic adenovirus

Bone and soft-tissue sarcomas are rare malignancies with histological diversity and tumor heterogeneity, leading to the lack of a common molecular target. Telomerase is a key enzyme for keeping the telomere length and human telomerase reverse transcriptase (hTERT) expression is often activated in most human cancers, including bone and soft-tissue sarcomas. For targeting of telomerase-positive tumor cells, we developed OBP-301, a telomerase-specific replication-competent oncolytic adenovirus, in which the hTERT promoter regulates adenoviral E1 gene for tumor-specific viral replication. In this study, we present the diagnostic potential of green fluorescent protein (GFP)-expressing oncolytic adenovirus OBP-401 for assessing virotherapy sensitivity using bone and soft-tissue sarcomas. OBP-401-mediated GFP expression was significantly associated with the therapeutic efficacy of OBP-401 in human bone and soft-tissue sarcomas. In the tumor specimens from 68 patients, malignant and intermediate tumors demonstrated significantly higher expression levels of coxsackie and adenovirus receptor (CAR) and hTERT than benign tumors. OBP-401-mediated GFP expression was significantly increased in malignant and intermediate tumors with high expression levels of CAR and hTERT between 24 and 48 h after infection. Our results suggest that the OBP-401-based GFP expression system is a useful tool for predicting the therapeutic efficacy of oncolytic virotherapy on bone and soft-tissue sarcomas.

shinyDeepDR: A user-friendly R Shiny app for predicting anti-cancer drug response using deep learning

Advancing precision oncology requires accurate prediction of treatment response and accessible prediction models. To this end, we present shinyDeepDR, a user-friendly implementation of our innovative deep learning model, DeepDR, for predicting anti-cancer drug sensitivity. The web tool makes DeepDR more accessible to researchers without extensive programming experience. Using shinyDeepDR, users can upload mutation and/or gene expression data from a cancer sample (cell line or tumor) and perform two main functions: "Find Drug," which predicts the sample's response to 265 approved and investigational anti-cancer compounds, and "Find Sample," which searches for cell lines in the Cancer Cell Line Encyclopedia (CCLE) and tumors in The Cancer Genome Atlas (TCGA) with genomics profiles similar to those of the query sample to study potential effective treatments. shinyDeepDR provides an interactive interface to interpret prediction results and to investigate individual compounds. In conclusion, shinyDeepDR is an intuitive and free-to-use web tool for in silico anti-cancer drug screening.

"I just wanted more": Hereditary cancer syndromes patients' perspectives on the utility of circulating tumour DNA testing for cancer screening

Hereditary cancer syndromes (HCS) predispose individuals to a higher risk of developing multiple cancers. However, current screening strategies have limited ability to screen for all cancer risks. Circulating tumour DNA (ctDNA) detects DNA fragments shed by tumour cells in the bloodstream and can potentially detect cancers early. This study aimed to explore patients' perspectives on ctDNA's utility to help inform its clinical adoption and implementation. We conducted a qualitative interpretive description study using semi-structured phone interviews. Participants were purposively sampled adult HCS patients recruited from a Canadian HCS research consortium. Thirty HCS patients were interviewed (n = 19 women, age range 20s-70s, n = 25 were white). Participants were highly concerned about developing cancers, particularly those without reliable screening options for early detection. They "just wanted more" than their current screening strategies. Participants were enthusiastic about ctDNA's potential to be comprehensive (detect multiple cancers), predictive (detect cancers early) and tailored (lead to personalized clinical management). Participants also acknowledged ctDNA's potential limitations, including false positives/negatives risks and experiencing additional anxiety. However, they saw ctDNA's potential benefits outweighing its limitations. In conclusion, participants' belief in ctDNA's potential to improve their care overshadowed its limitations, indicating patients' support for using ctDNA in HCS care.

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.

Understanding communication between patients and healthcare professionals regarding comprehensive biomarker testing in precision oncology: A scoping review

BACKGROUND

Precision oncology, using comprehensive biomarker testing (cBT) to inform individual cancer diagnosis, prognosis and treatment, includes increasingly complex technology and clinical data sets. People impacted by cancer (patients and caregivers) and healthcare professionals (HCPs) face distinct challenges in navigating the cBT and personalized treatment landscape. This review summarizes evidence regarding cBT-related communication between people impacted by cancer and HCPs and identifies important avenues for future research in precision oncology.

METHODS

A scoping review was conducted using records published in PubMed during January 2017-August 2022, focusing on the breadth of topics on patient-HCP communication and knowledge resources used by HCPs as guidance in cBT-related communication. Data were extracted from records meeting inclusion criteria, and findings were summarized according to main topics.

RESULTS

The search identified 287 unique records and data were extracted from 42 records, including nine from expert input. Most records originated from the United States included patients with different types of cancer, and oncologists were the main HCPs. Patients' motivation for undergoing cBT and receiving results was generally high in different settings. However, patients' understanding of cBT-related concepts was limited, and their knowledge and information preferences changed based on cBT implications and significance to family members. HCPs were valued by patients as a trusted source of information. Limited evidence was available on HCPs' information-seeking behavior and factors influencing cBT-related knowledge and confidence, often self-reported as insufficient.

CONCLUSIONS

Patient education by knowledgeable and confident HCPs, information management and a caring patient-HCP relationship communicating continuity of care regardless of cBT results are crucial to empower patients and shared decision-making in precision oncology. More data on the process and structure of cBT-related communication, distinction between and characterization of different timepoints of patient-HCP interactions are needed.

Change of glucometabolic activity per PSMA expression predicts survival in mCRPC patients non-responding to PSMA radioligand therapy: introducing a novel dual imaging biomarker

Purpose

The value of [18F]fluorodeoxyglucose ([18F]FDG) PET/CT in monitoring prostate-specific membrane antigen (PSMA) targeted radioligand therapy (RLT) is still unclear. The aim of this study was to identify appropriate prognostic dynamic parameters derived from baseline and follow-up [18F]FDG and dual [18F]FDG/[68Ga]Ga-PSMA-11 PET/CT for monitoring early non-responding mCRPC patients undergoing PSMA-RLT.

Methods

Twenty-three mCRPC patients of a prospective registry (NCT04833517), who were treated with [177Lu]Lu-PSMA-617 RLT and classified as early non-responders were included in this study. All patients received dual PET/CT imaging with [18F]FDG and [68Ga]Ga-PSMA-11 at baseline and after median two cycles of RLT. We tested potential biomarkers representing the "change of glucometabolic activity (cGA)" and "change of glucometabolic activity in relation to PSMA expression (cGAP)" composed of established parameters on [18F]FDG PET/CT as SUVmax, cumulative SUV of five lesions (SUV5), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) and its corresponding parameters on [68Ga]Ga-PSMA-11 PET/CT, respectively, for association with overall survival (OS).

Results

Kaplan-Meier analyses showed no significant association with OS for each tested cGA (cGASUVmaxp = 0.904, cGASUV5, p = 0.747 cGAMTVp = 0.682 and cGATLGp = 0.700), likewise the dual imaging biomarkers cGAPSUVmax (p = 0.136), cGAPSUV5 (p = 0.097), and cGAPTV (p = 0.113) failed significance. In contrast, cGAPTL, which is based on TLG and total lesion PSMA (TLP) showed a significant association with OS (p = 0.004). Low cGAPTL (cut-off 0.7) was associated with significant longer survival (17.6 vs. 12.9 months).

Conclusion

The novel biomarker cGAPTL, which represents the temporal change of whole-body TLG normalized by TLP, predicts overall survival in the challenging cohort of patients non-responding to PSMA-RLT.

A multimodal graph neural network framework for cancer molecular subtype classification

BACKGROUND

The recent development of high-throughput sequencing has created a large collection of multi-omics data, which enables researchers to better investigate cancer molecular profiles and cancer taxonomy based on molecular subtypes. Integrating multi-omics data has been proven to be effective for building more precise classification models. Most current multi-omics integrative models use either an early fusion in the form of concatenation or late fusion with a separate feature extractor for each omic, which are mainly based on deep neural networks. Due to the nature of biological systems, graphs are a better structural representation of bio-medical data. Although few graph neural network (GNN) based multi-omics integrative methods have been proposed, they suffer from three common disadvantages. One is most of them use only one type of connection, either inter-omics or intra-omic connection; second, they only consider one kind of GNN layer, either graph convolution network (GCN) or graph attention network (GAT); and third, most of these methods have not been tested on a more complex classification task, such as cancer molecular subtypes.

RESULTS

In this study, we propose a novel end-to-end multi-omics GNN framework for accurate and robust cancer subtype classification. The proposed model utilizes multi-omics data in the form of heterogeneous multi-layer graphs, which combine both inter-omics and intra-omic connections from established biological knowledge. The proposed model incorporates learned graph features and global genome features for accurate classification. We tested the proposed model on the Cancer Genome Atlas (TCGA) Pan-cancer dataset and TCGA breast invasive carcinoma (BRCA) dataset for molecular subtype and cancer subtype classification, respectively. The proposed model shows superior performance compared to four current state-of-the-art baseline models in terms of accuracy, F1 score, precision, and recall. The comparative analysis of GAT-based models and GCN-based models reveals that GAT-based models are preferred for smaller graphs with less information and GCN-based models are preferred for larger graphs with extra information.

A systematic analysis of the landscape of synthetic lethality-driven precision oncology

BACKGROUND

Synthetic lethality (SL) denotes a genetic interaction between two genes whose co-inactivation is detrimental to cells. Because more than 25 years have passed since SL was proposed as a promising way to selectively target cancer vulnerabilities, it is timely to comprehensively assess its impact so far and discuss its future.

METHODS

We systematically analyzed the literature and clinical trial data from the PubMed and Trialtrove databases to portray the preclinical and clinical landscape of SL oncology.

FINDINGS

We identified 235 preclinically validated SL pairs and found 1,207 pertinent clinical trials, and the number keeps increasing over time. About one-third of these SL clinical trials go beyond the typically studied DNA damage response (DDR) pathway, testifying to the recently broadening scope of SL applications in clinical oncology. We find that SL oncology trials have a greater success rate than non-SL-based trials. However, about 75% of the preclinically validated SL interactions have not yet been tested in clinical trials.

CONCLUSIONS

Dissecting the recent efforts harnessing SL to identify predictive biomarkers, novel therapeutic targets, and effective combination therapy, our systematic analysis reinforces the hope that SL may serve as a key driver of precision oncology going forward.

FUNDING

Funded by the Samsung Research Funding & Incubation Center of Samsung Electronics, the Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Republic of Korea government (MSIT), the Kwanjeong Educational Foundation, the Intramural Research Program of the National Institutes of Health (NIH), National Cancer Institute (NCI), and Center for Cancer Research (CCR).

Implementing precision oncology in Latin America to improve patient outcomes: the status quo and a call to action for key stakeholders and decision-makers

Background

The advent of precision oncology (PO) has revolutionised diagnostic and follow up strategies and improved clinical outcomes for cancer patients. However, socio-economic inequalities in the level of implementation of PO in different countries is a prevailing issue. To improve this situation, the Latin America Patients Academy has gathered the recommendations of healthcare professionals and social civil members experienced in cancer management from Mexico, Guatemala, Costa Rica, Dominican Republic, Panama, Colombia, Chile, Ecuador, Peru and Argentina regarding the areas that need to be prioritised to improve the access to PO in Latin American (LATAM) countries.

Methods

This manuscript is the culmination of a series of educational campaigns and panel discussion aimed at improving the implementations of PO in LATAM that took place from June 2021 to January 2022.

The status of PO in Latin America

the level of PO implementation is generally low with some exceptions. The number of clinical trials and articles published with keywords related to PO from LATAM countries is drastically lower than in Europe and the United States. Despite sharing many complex challenges, progress is taking place in some countries in the region.

Focus areas defined by the expert panel

The expert panel determined the areas of PO that should be improved by LATAM countries to improve its implementation through cancer care plans, educational programs and collaborative strategies. These initiatives should increase awareness about PO in the region and eventually improve cancer control in the region.

Nanotechnology and Cancer Bioelectricity: Bridging the Gap Between Biology and Translational Medicine

Bioelectricity is the electrical activity that occurs within living cells and tissues. This activity is critical for regulating homeostatic cellular function and communication, and disruptions of the same can lead to a variety of conditions, including cancer. Cancer cells are known to exhibit abnormal electrical properties compared to their healthy counterparts, and this has driven researchers to investigate the potential of harnessing bioelectricity as a tool in cancer diagnosis, prognosis, and treatment. In parallel, bioelectricity represents one of the means to gain fundamental insights on how electrical signals and charges play a role in cancer insurgence, growth, and progression. This review provides a comprehensive analysis of the literature in this field, addressing the fundamentals of bioelectricity in single cancer cells, cancer cell cohorts, and cancerous tissues. The emerging role of bioelectricity in cancer proliferation and metastasis is introduced. Based on the acknowledgement that this biological information is still hard to access due to the existing gap between biological findings and translational medicine, the latest advancements in the field of nanotechnologies for cellular electrophysiology are examined, as well as the most recent developments in micro- and nano-devices for cancer diagnostics and therapy targeting bioelectricity.

A scoping review on 'Maharishi Amrit Kalash', an ayurveda formulation for cancer prevention and management

BACKGROUND

Cancer is one of the leading causes of morbidity and mortality. Current treatments include chemotherapy, radiotherapy, etc., are known to be associated with several side effects. Hence, complementary and alternative medicine is growing in acceptance around the world, particularly Ayurvedic formulations. MAK is one of the most scientifically acclaimed formulations with potential anti-neoplastic and chemoprotective properties.

OBJECTIVE

To study literature available on the anti-neoplastic and chemoprotective effects of MAK.

MATERIAL AND METHODS

A systematic literature review was conducted using multiple web-based sources: Google Scholar (185), PubMed (33), DHARA (49), AYUSH research portal (2), EBSCO (66), and CTRI (1) for all studies published before February 2021 using keywords: Maharishi Amrit Kalash, Amrit Kalash, Amrit, MAK-4, MAK-5, MAK-7, and others. A manual search was conducted on the reference list of all included articles to identify additional studies. Studies with cancer and/or chemotoxicity outcomes were selected manually. Evidence from both preclinical and clinical level studies have been included in the current review.

RESULTS

Out of total 79 studies on applications of MAK, 13 studies were found to state its anti-neoplastic and chemoprotective effects. The studies showed role of MAK in initiation of neoplastic transformation of cancer cells (1), carcinogenesis inhibition (4), metastases inhibition/reduction (1), cancer growth inhibition (4), induction of morphological and biochemical differentiation of cancer cells (3), and reduction in chemotoxicity (4). In studies with controlled clinical trial design (3), MAK use among patients with cancer showed a significant reduction in anorexia, vomiting, and other side effects associated with chemotherapy. A general improvement in quality-of-life scores (Karnofsky Performance Status) and well-being was also observed among patients using MAK.

CONCLUSION

Evidence from pre-clinical studies show promising results for use of MAK as an anti-cancer and a chemoprotective agent. More clinical studies are needed to assess the impact of MAK use for tumour regression among patients with cancer. Current scoping review provides sufficient evidence on MAK to be considered for further exploration for its anti-cancer/chemoprotective effects in bigger randomized clinical trials.

A Comprehensive Review of Small Interfering RNAs (siRNAs): Mechanism, Therapeutic Targets, and Delivery Strategies for Cancer Therapy

Small interfering RNA (siRNA) delivery by nanocarriers has been identified as a promising strategy in the study and treatment of cancer. Short nucleotide sequences are synthesized exogenously to create siRNA, which triggers RNA interference (RNAi) in cells and silences target gene expression in a sequence-specific way. As a nucleic acid-based medicine that has gained popularity recently, siRNA exhibits novel potential for the treatment of cancer. However, there are still many obstacles to overcome before clinical siRNA delivery devices can be developed. In this review, we discuss prospective targets for siRNA drug design, explain siRNA drug properties and benefits, and give an overview of the current clinical siRNA therapeutics for the treatment of cancer. Additionally, we introduce the siRNA chemical modifications and delivery systems that are clinically sophisticated and classify bioresponsive materials for siRNA release in a methodical manner. This review will serve as a reference for researchers in developing more precise and efficient targeted delivery systems, promoting ongoing advances in clinical applications.

Advancing maturity modeling for precision oncology

Introduction

This study aimed to map the maturity of precision oncology as an example of a Learning Health System by understanding the current state of practice, tools and informatics, and barriers and facilitators of maturity.

Methods

We conducted semi-structured interviews with 34 professionals (e.g., clinicians, pathologists, and program managers) involved in Molecular Tumor Boards (MTBs). Interviewees were recruited through outreach at 3 large academic medical centers (AMCs) (n = 16) and a Next Generation Sequencing (NGS) company (n = 18). Interviewees were asked about their roles and relationships with MTBs, processes and tools used, and institutional practices. The interviews were then coded and analyzed to understand the variation in maturity across the evolving field of precision oncology.

Results

The findings provide insight into the present level of maturity in the precision oncology field, including the state of tooling and informatics within the same domain, the effects of the critical environment on overall maturity, and prospective approaches to enhance maturity of the field. We found that maturity is relatively low, but continuing to evolve, across these dimensions due to the resource-intensive and complex sociotechnical infrastructure required to advance maturity of the field and to fully close learning loops.

Conclusion

Our findings advance the field by defining and contextualizing the current state of maturity and potential future strategies for advancing precision oncology, providing a framework to examine how learning health systems mature, and furthering the development of maturity models with new evidence.

"How is it going to help?": Exploring Black breast cancer patients' questions about biomarker testing to predict chemotherapy-induced peripheral neuropathy

Objective

Many Black breast cancer patients experience chemotherapy-induced peripheral neuropathy (CIPN). Our study assessed Black breast cancer patients' questions about a biomarker test that can predict likelihood of CIPN.

Methods

Nineteen Black women who were previous/current breast cancer patients participated in focus groups. Researchers briefly explained CIPN and the biomarker test, and then participants were asked what questions they would have about the test and its use in treatment decisions. These participant-voiced questions composed the data for this study and were analyzed using thematic analysis.

Results

Participants' questions centered on six themes: reasons for the test, effect on timeline of breast cancer treatment, testing procedure, limits of test (including accuracy), research done to develop this test (including research participants), and concerns about personal information connected to the test (including DNA).

Conclusion

This study provides an exploratory look at questions that Black breast cancer patients may have about toxicity biomarker testing use in breast cancer treatment decisions.

Innovation

These findings provide a starting point for developing patient-centered approaches for integrating this precision medicine tool into clinical care. The methodological choice to generate participants' questions (rather than answers to a question) led to robust, actionable data.

The New NCI Precision Medicine Trials

Basket, umbrella, and platform trial designs (master protocols) have emerged over the last decade to study precision medicine approaches in oncology. First-generation trials like NCI-MATCH (Molecular Analysis for Therapy Choice) have proven the principle that studying targeted therapies on a large scale is feasible both from the laboratory and clinical perspectives. However, single-agent targeted therapies have shown limited ability to control metastatic disease, despite careful matching of drug to target. As such, newer approaches employing combinations of targeted therapy, or targeted therapy with standard therapies, need to be considered. The NCI has recently embarked on three second-generation precision medicine trials to address this need: ComboMATCH, iMATCH, and myeloMATCH. The design of these trials and necessary infrastructure are discussed in the following perspective.

Principles of oncology taught in a one-week course

BACKGROUND

Growing challenges in oncology require evolving educational methods and content. International efforts to reform oncology education are underway. Hands-on, interdisciplinary, and compact course formats have shown great effectiveness in the education of medical students. Our aim was to establish a new interdisciplinary one-week course on the principles of oncology using state-of-the-art teaching methods.

METHODS

In an initial survey, medical students of LMU Munich were questioned about their current level of knowledge on the principles of oncology. In a second two-stage survey, the increase in knowledge resulting from our recently established interdisciplinary one-week course was determined.

RESULTS

The medical students' knowledge of clinically important oncological topics, such as the diagnostic workup and interdisciplinary treatment options, showed a need for improvement. Knowledge of the major oncological entities was also in an expandable state. By attending the one-week course on the principles of oncology, students improved their expertise in all areas of the clinical workup in oncology and had the opportunity to close previous knowledge gaps. In addition, students were able to gain more in-depth clinical knowledge on the most common oncological entities.

CONCLUSION

The interdisciplinary one-week course on the principles of oncology proved to be an effective teaching method to expand the knowledge of the future physicians to an appropriate level. With its innovative and interdisciplinary approach, the one-week course could be used as a showcase project for the ongoing development of medical education in Germany.

Molecular tumour boards - current and future considerations for precision oncology

Over the past 15 years, rapid progress has been made in developmental therapeutics, especially regarding the use of matched targeted therapies against specific oncogenic molecular alterations across cancer types. Molecular tumour boards (MTBs) are panels of expert physicians, scientists, health-care providers and patient advocates who review and interpret molecular-profiling results for individual patients with cancer and match each patient to available therapies, which can include investigational drugs. Interpretation of the molecular alterations found in each patient is a complicated task that requires an understanding of their contextual functional effects and their correlations with sensitivity or resistance to specific treatments. The criteria for determining the actionability of molecular alterations and selecting matched treatments are constantly evolving. Therefore, MTBs have an increasingly necessary role in optimizing the allocation of biomarker-directed therapies and the implementation of precision oncology. Ultimately, increased MTB availability, accessibility and performance are likely to improve patient care. The challenges faced by MTBs are increasing, owing to the plethora of identifiable molecular alterations and immune markers in tumours of individual patients and their evolving clinical significance as more and more data on patient outcomes and results from clinical trials become available. Beyond next-generation sequencing, broader biomarker analyses can provide useful information. However, greater funding, resources and expertise are needed to ensure the sustainability of MTBs and expand their outreach to underserved populations. Harmonization between practice and policy will be required to optimally implement precision oncology. Herein, we discuss the evolving role of MTBs and current and future considerations for their use in precision oncology.

Comprehensive genomic profiling for oncological advancements by precision medicine

Considerable advancements in next generation sequencing (NGS) techniques have sparked the use of comprehensive genomic profiling (CGP) as a guiding tool for precision-centered oncological treatments. The past two decades have seen the completion of the human genome project, and the consequential invention of NGS. High-throughput sequencing technologies support the discovery and commonplace use of individualized cancer treatments, specifically immune-centered checkpoint inhibitor therapies, and oncogene and tumor suppressor gene targeted therapies. Nevertheless, CGP is not commonly used in all clinical settings. This review investigates the clinically relevant applications of CGP. Studies published between the years 2000-2023 have shown substantial evidence of the benefits of integrating CGP into routine care practice, while also making important comparisons to current-standard oncological treatment strategies. Findings of a comprehensive genomic profile includes predictive, prognostic, and diagnostic biomarkers, together with somatic mutation identification which can indicate the efficacy of immunotherapies and molecularly guided therapies. This review highlights the importance of CGP in identifying driver mutations in tumors that subsequently can be effectively targeted with molecular therapeutics and lead to drug discovery, allowing for increased precision in treating tumors selectively based on their specific genetic mutations, thereby improving patient outcomes.

Identification of Immune Subtypes and Candidate mRNA Vaccine Antigens in Small Cell Lung Cancer

BACKGROUND

Immune checkpoint inhibitors (ICIs) have demonstrated promising outcomes in small cell lung cancer (SCLC), but not all patients benefit from it. Thus, developing precise treatments for SCLC is a particularly urgent need. In our study, we constructed a novel phenotype for SCLC based on immune signatures.

METHODS

We clustered patients with SCLC hierarchically in 3 publicly available datasets according to the immune signatures. ESTIMATE and CIBERSORT algorithm were used to evaluate the components of the tumor microenvironment. Moreover, we identified potential mRNA vaccine antigens for patients with SCLC, and qRT-PCR were performed to detect the gene expression.

RESULTS

We identified 2 SCLC subtypes and named Immunity High (Immunity_H) and Immunity Low (Immunity_L). Meanwhile, we obtained generally consistent results by analyzing different datasets, suggesting that this classification was reliable. Immunity_H contained the higher number of immune cells and a better prognosis compared to Immunity_L. Gene-set enrichment analysis revealed that several immune-related pathways such as cytokine-cytokine receptor interaction, programmed cell death-Ligand 1 expression and programmed cell death-1 checkpoint pathway in cancer were hyperactivated in the Immunity_H. However, most of the pathways enriched in the Immunity_L were not associated with immunity. Furthermore, we identified 5 potential mRNA vaccine antigens of SCLC (NEK2, NOL4, RALYL, SH3GL2, and ZIC2), and they were expressed higher in Immunity_L, it indicated that Immunity_L maybe more suitable for tumor vaccine development.

CONCLUSIONS

SCLC can be divided into Immunity_H and Immunity_L subtypes. Immunity_H may be more suitable for treatment with ICIs. NEK2, NOL4, RALYL, SH3GL2, and ZIC2 may be act as potential antigens for SCLC.

Precision oncology medicines and the need for real world evidence acceptance in health technology assessment: Importance of patient involvement in sustainable healthcare

Precision oncology has made remarkable strides in improving clinical outcomes, offering hope to patients with historically difficult-to-treat, as well as rare or neglected cancers. However, despite rapid advancement, precision oncology has reached a critical juncture, where patient access to these life-saving medicines may be hampered by strict requirements by Health Technology Assessment (HTA) bodies for randomised controlled trials (RCTs) for assessing new medicines against appropriate comparator. The very nature of precision oncology-matching a tumour's unique molecular alterations to targeted therapies predicted to elicit response-can make the use of RCTs very difficult, as only a very small number of patients might qualify for a given therapy within a traditional clinical trial setting. Real-world evidence (RWE) has been accepted for regulatory decision-making but has yet to reach widespread acceptance by HTA bodies. As the oncology treatment landscape has evolved towards favouring the concept of precision oncology, there is a growing need for flexibility in the way HTA bodies evaluate new medicines. We must acknowledge that current assessment methodologies can limit access to life-changing medicines for many patients who have no alternative options and that a growing number of precision oncology medicines with proven clinical benefits in rare tumours cannot be reasonably evaluated using traditional methodologies. The objectives of this paper are to advocate a change in mindset regarding best practices in drug assessment models and to propose alternative approaches when considering indications for which RWE is the most compelling data source available.

Implementing precision oncology for sarcoma patients: the CCCLMUmolecular tumor board experience

PURPOSE

Due to poor outcomes and limited treatment options, patients with advanced bone and soft tissue sarcomas (BS/STS) may undergo comprehensive molecular profiling of tumor samples to identify possible therapeutic targets. The aim of this study was to determine the impact of routine molecular profiling in the setting of a dedicated precision oncology program in patients with BS/STS in a German large-volume sarcoma center.

METHODS

92 BS/STS patients who received comprehensive genomic profiling (CGP) and were subsequently discussed in our molecular tumor board (MTB) between 2016 and 2022 were included. Patient records were retrospectively reviewed, and the clinical impact of NGS-related findings was analyzed.

RESULTS

89.1% of patients had received at least one treatment line before NGS testing. At least one molecular alteration was found in 71 patients (82.6%). The most common alterations were mutations in TP53 (23.3% of patients), followed by PIK3CA and MDM2 mutations (9.3% each). Druggable alterations were identified, and treatment recommended in 32 patients (37.2%). Of those patients with actionable alterations, ten patients (31.2%) received personalized treatment and six patients did benefit from molecular-based therapy in terms of a progression-free survival ratio (PFSr) > 1.3.

CONCLUSION

Our single-center experience shows an increasing uptake of next-generation sequencing (NGS) and highlights current challenges of implementing precision oncology in the management of patients with BS/STS. A relevant number of patients were diagnosed with clinically actionable alterations. Our results highlight the potential benefit of NGS in patients with rare cancers and currently limited therapeutic options.

Opportunities and challenges of 5G network technology toward precision medicine

Moving away from traditional "one-size-fits-all" treatment to precision-based medicine has tremendously improved disease prognosis, accuracy of diagnosis, disease progression prediction, and targeted-treatment. The current cutting-edge of 5G network technology is enabling a growing trend in precision medicine to extend its utility and value to the smart healthcare system. The 5G network technology will bring together big data, artificial intelligence, and machine learning to provide essential levels of connectivity to enable a new health ecosystem toward precision medicine. In the 5G-enabled health ecosystem, its applications involve predictive and preventative measurements which enable advances in patient personalization. This review aims to discuss the opportunities, challenges, and prospects posed to 5G network technology in moving forward to deliver personalized treatments and patient-centric care via a precision medicine approach.