Precision Oncology Decision Support: Current Approaches and Strategies for the Future

Cancer management in terms of precision oncology

Cancer processes have been studied for over a century, but clinical care still relies on morphological and histological approaches. Modern diagnostic and therapy options include molecular characterisation of abnormal genes, cell surface indicators, hormonal/endocrine mediators, and signaling pathways. Targeted medicines, synthetic lethal targeting, and immune checkpoint inhibitors have spurred hope for molecular targets in cancer management. Precision medicine programs aim to transform population-based research into biomarker-driven clinical trials, but disparities in access to genetic profiling and inexpensive precision oncology drugs must be addressed to ensure cost-effective therapies are available to all patients.

Development of an Electronic Health Record-Based Clinical Decision Support Tool for Patients With Lynch Syndrome

PURPOSE

To develop an electronic health record (EHR)-based clinical decision support (CDS) tool to promote guideline-recommended cancer risk management among patients with Lynch syndrome (LS), an inherited cancer syndrome that confers an increased risk of colorectal and other cancer types.

MATERIALS AND METHODS

We conducted a cross-sectional study to determine the baseline prevalence and predictors of guideline-recommended colonic surveillance and annual genetics program visits among patients with LS. Multivariable log-binomial regressions estimated prevalence ratios (PRs) of cancer risk management adherence by baseline sociodemographic and clinical characteristics. These analyses provided rationale for the development of an EHR-based CDS tool to support patients and clinicians with LS-related endoscopic surveillance and annual genetics program visits. The CDS leverages an EHR platform linking discrete genetic data to LS Genomic Indicators, in turn driving downstream clinician- and patient-facing CDS.

RESULTS

Among 323 patients with LS, cross-sectional adherence to colonic surveillance and annual genetics program visits was 69.3% and 55.4%, respectively. Patients with recent electronic patient portal use were more likely to be adherent to colonic surveillance (PR, 1.67; 95% CI, 1.11 to 2.52). Patients more recently diagnosed with LS were more likely to be adherent to annual genetics program visits (PR, 0.58; 95% CI, 0.44 to 0.76 for 2-4 years; PR, 0.62; 95% CI, 0.51 to 0.75 for ≥4 compared with <2 years). Our EHR-based CDS tool is now active for 421 patients with LS throughout our health system.

CONCLUSION

We have successfully developed an EHR-based CDS tool to promote guideline-recommended cancer risk management among patients with LS.

Actionability classification of variants of unknown significance correlates with functional effect

Genomically-informed therapy requires consideration of the functional impact of genomic alterations on protein expression and/or function. However, a substantial number of variants are of unknown significance (VUS). The MD Anderson Precision Oncology Decision Support (PODS) team developed an actionability classification scheme that categorizes VUS as either "Unknown" or "Potentially" actionable based on their location within functional domains and/or proximity to known oncogenic variants. We then compared PODS VUS actionability classification with results from a functional genomics platform consisting of mutant generation and cell viability assays. 106 (24%) of 438 VUS in 20 actionable genes were classified as oncogenic in functional assays. Variants categorized by PODS as Potentially actionable (N = 204) were more likely to be oncogenic than those categorized as Unknown (N = 230) (37% vs 13%, p = 4.08e-09). Our results demonstrate that rule-based actionability classification of VUS can identify patients more likely to have actionable variants for consideration with genomically-matched therapy.

Camonsertib in DNA damage response-deficient advanced solid tumors: phase 1 trial results

Predictive biomarkers of response are essential to effectively guide targeted cancer treatment. Ataxia telangiectasia and Rad3-related kinase inhibitors (ATRi) have been shown to be synthetic lethal with loss of function (LOF) of ataxia telangiectasia-mutated (ATM) kinase, and preclinical studies have identified ATRi-sensitizing alterations in other DNA damage response (DDR) genes. Here we report the results from module 1 of an ongoing phase 1 trial of the ATRi camonsertib (RP-3500) in 120 patients with advanced solid tumors harboring LOF alterations in DDR genes, predicted by chemogenomic CRISPR screens to sensitize tumors to ATRi. Primary objectives were to determine safety and propose a recommended phase 2 dose (RP2D). Secondary objectives were to assess preliminary anti-tumor activity, to characterize camonsertib pharmacokinetics and relationship with pharmacodynamic biomarkers and to evaluate methods for detecting ATRi-sensitizing biomarkers. Camonsertib was well tolerated; anemia was the most common drug-related toxicity (32% grade 3). Preliminary RP2D was 160 mg weekly on days 1-3. Overall clinical response, clinical benefit and molecular response rates across tumor and molecular subtypes in patients who received biologically effective doses of camonsertib (>100 mg d-1) were 13% (13/99), 43% (43/99) and 43% (27/63), respectively. Clinical benefit was highest in ovarian cancer, in tumors with biallelic LOF alterations and in patients with molecular responses. ClinicalTrials.gov registration: NCT04497116 .

Role of the Molecular Tumor Board for the Personalized Treatment of Patients with Metastatic Breast Cancer: A Focus on the State of the Art in Italy

Molecular tumor boards (MTBs) are multidisciplinary groups that combine molecular and clinical data from cancer patients in order to formulate treatment recommendations for precision medicine. To date, there is insufficient data to support the use of singleplex or next-generation sequencing (NGS) technologies to select first-line therapy for patients with metastatic breast cancer (MBC), but considering the high number of level II alterations, according to the ESMO scale for clinical actionability of molecular targets (ESCAT), it is suggested to include patients in molecular screening programs in order to be able to offer targeted therapies for specific genomic alterations. This article aims at reviewing the most recent literature related to the most used methodologies/approaches for molecular diagnostics and variants’ classification, summarizing the internationally published molecular screening studies in support of MTB activity and, in the end, discussing MTBs’ current position and role in Italy, the number of which is increasing, also thanks to the thrust of institutions.

Personalized Precision Medicine for Health Care Professionals: Development of a Competency Framework

BACKGROUND

Personalized precision medicine represents a paradigm shift and a new reality for the health care system in Spain, with training being fundamental for its full implementation and application in clinical practice. In this sense, health care professionals face educational challenges related to the acquisition of competencies to perform their professional practice optimally and efficiently in this new environment. The definition of competencies for health care professionals provides a clear guide on the level of knowledge, skills, and attitudes required to adequately carry out their professional practice. In this context, this acquisition of competencies by health care professionals can be defined as a dynamic and longitudinal process by which they use knowledge, skills, attitudes, and good judgment associated with their profession to develop it effectively in all situations corresponding to their field of practice.

OBJECTIVE

This report aims to define a proposal of essential knowledge domains and common competencies for all health care professionals, which are necessary to optimally develop their professional practice within the field of personalized precision medicine as a fundamental part of the medicine of the future.

METHODS

Based on a benchmark analysis and the input and expertise provided by a multidisciplinary group of experts through interviews and workshops, a new competency framework that would guarantee the optimal performance of health care professionals was defined. As a basis for the development of this report, the most relevant national and international competency frameworks and training programs were analyzed to identify aspects that are having an impact on the application of personalized precision medicine and will be considered when developing professional competencies in the future.

RESULTS

This report defines a framework made up of 58 competencies structured into 5 essential domains: determinants of health, biomedical informatics, practical applications, participatory health, and bioethics, along with a cross-cutting domain that impacts the overall performance of the competencies linked to each of the above domains. Likewise, 6 professional profiles to which this proposal of a competency framework is addressed were identified according to the area where they carry out their professional activity: health care, laboratory, digital health, community health, research, and management and planning. In addition, a classification is proposed by progressive levels of training that would be advisable to acquire for each competency according to the professional profile.

CONCLUSIONS

This competency framework characterizes the knowledge, skills, and attitudes required by health care professionals for the practice of personalized precision medicine. Additionally, a classification by progressive levels of training is proposed for the 6 professional profiles identified according to their professional roles.

Patient attrition in Molecular Tumour Boards: a systematic review

BACKGROUND

Molecular Tumour Boards (MTBs) were created with the purpose of supporting clinical decision-making within precision medicine. Though in use globally, reporting on these meetings often focuses on the small percentages of patients that receive treatment via this process and are less likely to report on, and assess, patients who do not receive treatment.

METHODS

A literature review was performed to understand patient attrition within MTBs and barriers to patients receiving treatment. A total of 51 papers were reviewed spanning a 6-year period from 11 different countries.

RESULTS

In total, 20% of patients received treatment through the MTB process. Of those that did not receive treatment, the main reasons were no mutations identified (27%), no actionable mutations (22%) and clinical deterioration (15%). However, data were often incomplete due to inconsistent reporting of MTBs with only 55% reporting on patients having no mutations, 55% reporting on the presence of actionable mutations with no treatment options and 59% reporting on clinical deterioration.

DISCUSSION

As patient attrition in MTBs is an issue which is very rarely alluded to in reporting, more transparent reporting is needed to understand barriers to treatment and integration of new technologies is required to process increasing omic and treatment data.

Targeting molecular alterations in non-small-cell lung cancer: what's next?

In recent years, major advances have been achieved in our understanding of non-small-cell lung cancer (NSCLC) with oncogenic driver alterations and in the specific treatment of these with tyrosine kinase inhibitors. Currently, state-of-the-art management of patients with NSCLC (particularly adenocarcinoma or non-adenocarcinoma but with mild tobacco exposure) consists of the determination of EGFR, ALK, ROS1 and BRAF status, as they have US FDA and EMA approved targeted therapies. The increase in molecular knowledge of NSCLC and the development of drugs against other targets has settled new therapeutic indications. In this review we have incorporated the development around MET, KRAS and NTRK in the diagnosis of NSCLC given the therapeutic potential that they represent, as well as the drugs approved for these indications.

Precision combination therapies based on recurrent oncogenic co-alterations

Cancer cells depend on multiple driver alterations whose oncogenic effects can be suppressed by drug combinations. Here, we provide a comprehensive resource of precision combination therapies tailored to oncogenic co-alterations that are recurrent across patient cohorts. To generate the resource, we developed Recurrent Features Leveraged for Combination Therapy (REFLECT), which integrates machine learning and cancer informatics algorithms. Using multi-omic data, the method maps recurrent co-alteration signatures in patient cohorts to combination therapies. We validated the REFLECT pipeline using data from patient-derived xenografts, in vitro drug screens, and a combination therapy clinical trial. These validations demonstrate that REFLECT-selected combination therapies have significantly improved efficacy, synergy, and survival outcomes. In patient cohorts with immunotherapy response markers, DNA repair aberrations, and HER2 activation, we have identified therapeutically actionable and recurrent co-alteration signatures. REFLECT provides a resource and framework to design combination therapies tailored to tumor cohorts in data-driven clinical trials and pre-clinical studies.

Developing a Data Quality Standard Primer for Cardiovascular Risk Assessment from Electronic Health Record Data Using the DataGauge Process

The learning health systems aim to support the needs of patients with chronic diseases, which require methods that account for electronic health recorded (EHR) data limitations. EHR data is often used to calculate cardiovascular risk scores. However, it is unclear whether EHR data presents high enough quality to provide accurate estimates. Still, there is currently no open standard available to assess data quality for such applications. We applied the DataGauge process to develop a data quality standard based on expert clinical, analytical and informatics knowledge by conducting four interviews and one focus group that produced 61 individual data quality requirements. These requirements covered all standard data quality dimensions and uncovered 705 quality issues in EHR data for 456 patients. These requirements will be expanded and further validated in future work. Our work initiates the development of open and explicit data quality standards for specific secondary uses of clinical data.

Use of Circulating Tumour DNA (ctDNA) for Measurement of Therapy Predictive Biomarkers in Patients with Cancer

Biomarkers that predict likely response or resistance to specific therapies are critical in personalising treatment for cancer patients. Such biomarkers are now available for an increasing number of anti-cancer therapies, especially targeted therapy and immunotherapy. The gold-standard method for determining predictive biomarkers requires tumour tissue. Obtaining tissue, however, is not always possible and even if possible, the amount or quality of tissue obtained may be inadequate for biomarker analysis. Tumour DNA, however, can be released into the bloodstream, giving rise to what is referred to as circulating tumour DNA (ctDNA). In contrast to tissue, blood can be obtained from effectively all patients in a minimally invasive and safe manner. Other advantages of blood over tissue for biomarker testing include a shorter turn-around time and an ability to perform serial measurements. Furthermore, blood should provide a more complete profile of mutations present in heterogeneous tumours than a single-needle tissue biopsy. A limitation of blood vis-à-vis tissue, however, is lower sensitivity and, thus, the possibility of missing an actionable mutation. Despite this limitation, blood-based predictive biomarkers, such as mutant EGFR for predicting response to EGFR tyrosine kinase inhibitors in advanced non-small-cell lung cancer and mutant PIK3CA for predicting response to alpelisib in combination with fulvestrant in advanced breast cancer, may be used when tissue is unavailable. Although tissue remains the gold standard for detecting predictive biomarkers, it is likely that several further blood-based assays will soon be validated and used when tissue is unavailable or unsuitable for analysis.

First Nationwide Molecular Screening Program in Spain for Patients With Advanced Breast Cancer: Results From the AGATA SOLTI-1301 Study

Background

The SOLTI-1301 AGATA study aimed to assess the feasibility of a multi-institutional molecular screening program to better characterize the genomic landscape of advanced breast cancer (ABC) and to facilitate patient access to matched-targeted therapies in Spain.

Methods

DNA sequencing of 74 cancer-related genes was performed using FFPE tumor samples in three different laboratories with three different gene panels. A multidisciplinary advisory board prospectively recommended potential targeted treatments. The primary objective was to determine the success of matching somatic DNA alteration to an experimental drug/drug class.

Results

Between September 2014 and July 2017, 305 patients with ABC from 10 institutions were enrolled. Tumor sequencing was successful in 260 (85.3%) patients. Median age was 54 (29-80); most tumors were hormone receptor-positive/HER2-negative (74%), followed by triple-negative (14.5%) and HER2-positive (11.5%). Ninety-seven (37%) tumor samples analyzed proceeded from metastatic sites. Somatic mutations were identified in 163 (62.7%) patients, mostly in PIK3CA (34%), TP53 (22%), AKT1 (5%), ESR1 (3%), and ERBB2 (3%) genes. Significant enrichment of AKT1 mutation was observed in metastatic versus primary samples (9% vs. 2%; p=0.01). Genome-driven cancer therapy was recommended in 45% (n=116) of successfully screened patients, 11% (n=13) of whom finally received it. Among these patients, 46.2% had a PFS of ≥6 months on matched therapy.

Conclusions

AGATA is the first nationwide molecular screening program carried out in Spain and we proved that implementing molecular data in the management of ABC is feasible. Although these results are promising, only 11% of the patients with genome-driven cancer therapy received it.

Clinician perspectives on communication and implementation challenges in precision oncology

Aim: To describe patient communication challenges encountered by oncology clinicians, which represent a fundamental barrier to implementing precision oncology. Materials & methods: We conducted three focus groups including breast, melanoma and thoracic oncology clinicians regarding their precision oncology communication experiences. Transcripts were reviewed and coded using inductive thematic text analysis. Results: We identified four themes: varied definitions of precision oncology exist, clinicians and patients face unique challenges to precision oncology implementation, patient communication challenges engendered or heightened by precision oncology implementation and clinician communication solutions and training needs. Conclusion: This study elucidated clinicians' perspectives on implementing precision oncology and related communication challenges. Understanding these challenges and developing strategies to help clinicians navigate these discussions are critical for ensuring that patients reap the full benefits of precision oncology.

Shifting Gears in Precision Oncology-Challenges and Opportunities of Integrative Data Analysis

For decades, research relating to modification of host immunity towards antitumor response activation has been ongoing, with the breakthrough discovery of immune-checkpoint blockers. Several biomarkers with potential predictive value have been reported in recent studies for these novel therapies. However, with the plethora of therapeutic options existing for a given cancer entity, modern oncology is now being confronted with multifactorial interpretation to devise “the best therapy” for the individual patient. Into the bargain come the multiverse guidelines for established and emerging diagnostic biomarkers, as well as the complex interplay between cancer cells and tumor microenvironment, provoking immense challenges in the therapy decision-making process. Through this review, we present various molecular diagnostic modalities and techniques, such as genomics, immunohistochemistry and quantitative image analysis, which have the potential of becoming powerful tools in the development of an optimal treatment regime when analogized with patient characteristics. We will summarize the underlying complexities of these methods and shed light upon the necessary considerations and requirements for data integration. It is our hope to provide compelling evidence to emphasize on the need for inclusion of integrative data analysis in modern cancer therapy, and thereupon paving a path towards precision medicine and better patient outcomes.

Revisiting social MPE: an integration of molecular pathological epidemiology and social science in the new era of precision medicine

INTRODUCTION

Molecular pathological epidemiology (MPE) is an integrative transdisciplinary area examining the relationships between various exposures and pathogenic signatures of diseases. In line with the accelerating advancements in MPE, social science and its health-related interdisciplinary areas have also developed rapidly. Accumulating evidence indicates the pathological role of social-demographic factors. We therefore initially proposed social MPE in 2015, which aims to elucidate etiological roles of social-demographic factors and address health inequalities globally. With the ubiquity of molecular diagnosis, there are ample opportunities for researchers to utilize and develop the social MPE framework.

AREAS COVERED

Molecular subtypes of breast cancer have been investigated rigorously for understanding its etiologies rooted from social factors. Emerging evidence indicates pathogenic heterogeneity of neurological disorders such as Alzheimer's disease. Presenting specific patterns of social-demographic factors across different molecular subtypes should be promising for advancing the screening, prevention, and treatment strategies of those heterogeneous diseases. This article rigorously reviewed literatures investigating differences of race/ethnicity and socioeconomic status across molecular subtypes of breast cancer and Alzheimer's disease to date.

EXPERT OPINION

With advancements of the multi-omics technologies, we foresee a blooming of social MPE studies, which can address health disparities, advance personalized molecular medicine, and enhance public health.

Precision oncology: a clinical and patient perspective

Molecular characterization of tumors has shifted cancer treatment strategies away from nonspecific cytotoxic treatment of histology-specific tumors toward targeting of actionable mutations that can be found across multiple cancer types. The development of high-throughput technologies such as next-generation sequencing, combined with decision support applications and availability of patient databases, has provided tools that optimize disease management. Precision oncology has proven success in improving outcomes and quality of life, as well as identifying and overcoming mechanisms of drug resistance and relapse. Addressing challenges that impede its use will improve matching of therapies to patients. Here we review the current status of precision oncology medicine, emphasizing its impact on patients - what they understand about precision oncology medicine and their hopes for the future.

Criteria-based curation of a therapy-focused compendium to support treatment recommendations in precision oncology

While several resources exist that interpret therapeutic significance of genomic alterations in cancer, many regional real-world issues limit access to drugs. There is a need for a pragmatic, evidence-based, context-adapted tool to guide clinical management based on molecular biomarkers. To this end, we have structured a compendium of approved and experimental therapies with associated biomarkers following a survey of drug regulatory databases, existing knowledge bases, and published literature. Each biomarker-disease-therapy triplet was categorised using a tiering system reflective of key therapeutic considerations: approved and reimbursed therapies with respect to a jurisdiction (Tier 1), evidence of efficacy or approval in another jurisdiction (Tier 2), evidence of antitumour activity (Tier 3), and plausible biological rationale (Tier 4). Two resistance categories were defined: lack of efficacy (Tier R1) or antitumor activity (Tier R2). Based on this framework, we curated a digital resource focused on drugs relevant in the Australian healthcare system (TOPOGRAPH: Therapy Oriented Precision Oncology Guidelines for Recommending Anticancer Pharmaceuticals). As of November 2020, TOPOGRAPH comprised 2810 biomarker-disease-therapy triplets in 989 expert-appraised entries, including 373 therapies, 199 biomarkers, and 106 cancer types. In the 345 therapies catalogued, 84 (24%) and 65 (19%) were designated Tiers 1 and 2, respectively, while 271 (79%) therapies were supported by preclinical studies, early clinical trials, retrospective studies, or case series (Tiers 3 and 4). A companion algorithm was also developed to support rational, context-appropriate treatment selection informed by molecular biomarkers. This framework can be readily adapted to build similar resources in other jurisdictions to support therapeutic decision-making.

Genomic, Transcriptomic, and Proteomic Profiling of Metastatic Breast Cancer

PURPOSE

Metastatic breast cancer (MBC) is not curable and there is a growing interest in personalized therapy options. Here we report molecular profiling of MBC focusing on molecular evolution in actionable alterations.

EXPERIMENTAL DESIGN

Sixty-two patients with MBC were included. An analysis of DNA, RNA, and functional proteomics was done, and matched primary and metastatic tumors were compared when feasible.

RESULTS

Targeted exome sequencing of 41 tumors identified common alterations in TP53 (21; 51%) and PIK3CA (20; 49%), as well as alterations in several emerging biomarkers such as NF1 mutations/deletions (6; 15%), PTEN mutations (4; 10%), and ARID1A mutations/deletions (6; 15%). Among 27 hormone receptor-positive patients, we identified MDM2 amplifications (3; 11%), FGFR1 amplifications (5; 19%), ATM mutations (2; 7%), and ESR1 mutations (4; 15%). In 10 patients with matched primary and metastatic tumors that underwent targeted exome sequencing, discordances in actionable alterations were common, including NF1 loss in 3 patients, loss of PIK3CA mutation in 1 patient, and acquired ESR1 mutations in 3 patients. RNA sequencing in matched samples confirmed loss of NF1 expression with genomic NF1 loss. Among 33 patients with matched primary and metastatic samples that underwent RNA profiling, 14 actionable genes were differentially expressed, including antibody-drug conjugate targets LIV-1 and B7-H3.

CONCLUSIONS

Molecular profiling in MBC reveals multiple common as well as less frequent but potentially actionable alterations. Genomic and transcriptional profiling demonstrates intertumoral heterogeneity and potential evolution of actionable targets with tumor progression. Further work is needed to optimize testing and integrated analysis for treatment selection.

Understanding Contemporary Molecular Biomarker Testing Rates and Trends for Metastatic NSCLC Among Community Oncologists

INTRODUCTION

Although guidelines recommend testing for actionable biomarkers for patients with advanced or metastatic non-small cell lung cancer (NSCLC), testing rates have varied. This study aimed to assess molecular testing patterns in a large network of US community-based oncology practices.

METHODS

This retrospective observational study examined adult patients with newly diagnosed stage IV NSCLC with ≥ 2 visits in The US Oncology Network from July 1, 2016 to September 30, 2019. Testing patterns were examined using electronic health record structured fields and chart review. Structured data were analyzed for the overall study population (cohort A), and structured and unstructured data were analyzed for a select cohort of 300 patients (cohort B).

RESULTS

In cohort A (n = 3337), programmed death ligand 1 (37%) was the most frequently tested biomarker documented in structured data, followed by epidermal growth factor receptor (36%), anaplastic lymphoma kinase (35%), ROS1 (20%), and BRAF (16%). According to unstructured data in cohort B (n = 300), epidermal growth factor receptor (80%) was the most frequently tested biomarker, followed by anaplastic lymphoma kinase (79%), programmed death ligand 1 (72%), ROS1 (71%), and BRAF (56%). The proportion of tests ordered prior to first-line (1L) treatment increased from 2016 to 2018 for all biomarkers, as did the proportion of test results available prior to 1L treatment. However, some of the test results became available after 1L or later lines of treatment were in progress.

CONCLUSION

Our study found increased testing rates over time and decreases in testing turnaround times. However, rates of testing for all biomarkers still need to improve, as does completion of testing prior to initiation of therapy.

Barriers to Prescribing Targeted Therapies for Patients With NSCLC With Highly Actionable Gene Variants in the Veterans Affairs National Precision Oncology Program

PURPOSE

Next-generation sequencing (NGS) gene panels are frequently completed for patients with advanced non-small-cell lung cancer (NSCLC). Patients with highly actionable gene variants have improved outcomes and reduced toxicities with the use of corresponding targeted agents. We sought to identify barriers to targeted agent use within the Veterans Health Affairs' National Precision Oncology Program (NPOP).

METHODS

A retrospective evaluation of patients with NSCLC who underwent NGS multigene panels through NPOP between July 2015 and February 2019 was conducted. Patients who were assigned level 1 or 2A evidence for oncogenic gene variants by an artificial intelligence offering (IBM Watson for Genomics [WfG]) and NPOP staff were selected. Antineoplastic drug prescriptions and provider notes were reviewed. Reasons for withholding targeted treatments were categorized.

RESULTS

Of 1,749 patients with NSCLC who successfully underwent NGS gene panel testing, 112 (6.4%) patients were assigned level 1 and/or 2A evidence for available targeted treatments by WfG and NPOP staff. All highly actionable gene variants were within ALK, BRAF, EGFR, ERBB2, MET, RET, and ROS1. Of these, 36 (32.1%) patients were not prescribed targeted agents. The three most common reasons were (1) patient did not carry a diagnosis of metastatic disease (33.3%), (2) treating provider did not comment on the NGS results (25.0%), and (3) provider felt that patient could not tolerate therapy (19.4%). No patients were denied access to level 1 or 2A targeted drugs because of rejection of a nonformulary drug request.

CONCLUSION

A substantial minority of patients with NSCLC bearing highly actionable gene variants are not prescribed targeted agents. Further provider- and pathologist-directed educational efforts and implementation of health informatics systems to provide real-time decision support for test ordering and interpretation are needed.

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.

Comprehensive molecular profiling of Taiwanese breast cancers revealed potential therapeutic targets: prevalence of actionable mutations among 380 targeted sequencing analyses

BACKGROUND

Breast cancer is one of the leading causes of cancer-related deaths in women, and there is a demand in developing an Asian-based genetic profiling database for breast cancer in improving the treatment response. This study aimed to determine molecular alternations and identify potential therapeutic targets by analyzing the genetic profiling from a cohort of Taiwanese breast cancers using a commercialized next-generation sequencing (NGS) targeted panel.

METHODS

The study population comprised a broad spectrum of breast cancer patients in Taiwan, including Group 1: planned to receive first-line surgery and followed by adjuvant therapy, or early relapse within three years, Group 2: planned to receive first-line neoadjuvant therapy and followed by surgery, and Group 3: de novo stage IV, or stage IV with recurrence beyond three years. Molecular profiles were determined using Thermo Fisher™ Oncomine™ Comprehensive Assay version 3 (TMO comprehensive assay) from Formalin-Fixed Paraffin-Embedded (FFPE) tissues. Level of actionability was evaluated with the ESMO Scale of clinical actionability of molecular targets (ESCAT).

RESULTS

A total of 380 TMO comprehensive assays were conducted on 372 patients, and we presented targeted sequencing analyses of Tier I: alteration-drug match associated with improved outcome in clinical trials including ERBB2 amplification, BRCA1/2 germline mutation, PIK3CA mutation, and NTRK translocation, and Tier II: antitumor activity associated with the matched alteration-drug but lack of prospective outcome data including PTEN loss, ESR1 mutation, AKT1 mutation, and ERBB2 mutation, and Tier III: matched drug-alteration that led to clinical benefit in another tumor type including MDM2 amplification, and ERBB3 mutation. Among them, 249 (66%) showed at least one actionable alternation based on the ESCAT criteria. The most frequent impacted genes (all variants combined within each sample) were PIK3CA (38%), followed by ERBB2 (23%), ESR1 (10%), AKT1 (6%), and BRCA2 (5%), and the remaining rare variants (less than 5% of assayed cohort) were BRCA1 (3%), MDM2 (2.2%), and ERBB3 (1.1%).

CONCLUSION

Targeted sequencing of actionable genes is believed to provide clinical applicability and substantial benefits for Taiwanese breast cancer patients. A valid scale of clinical actionability should be adopted for precision medicine practice under multidisciplinary molecular tumor board.

Democratizing genomics: Leveraging software to make genetics an integral part of routine care

Genetic testing can provide definitive molecular diagnoses and guide clinical management decisions from preconception through adulthood. Innovative solutions for scaling clinical genomics services are necessary if they are to transition from a niche specialty to a routine part of patient care. The expertise of specialists, like genetic counselors and medical geneticists, has traditionally been relied upon to facilitate testing and follow-up, and while ideal, this approach is limited in its ability to integrate genetics into primary care. As individuals, payors, and providers increasingly realize the value of genetics in mainstream medicine, several implementation challenges need to be overcome. These include electronic health record integration, patient and provider education, tools to stay abreast of guidelines, and simplification of the test ordering process. Currently, no single platform offers a holistic view of genetic testing that streamlines the entire process across specialties that begins with identifying at-risk patients in mainstream care settings, providing pretest education, facilitating consent and test ordering, and following up as a "genetic companion" for ongoing management. We describe our vision for using software that includes clinical-grade chatbots and decision support tools, with direct access to genetic counselors and pharmacists within a modular, integrated, end-to-end testing journey.

First-in-Human Trial of the Oral Ataxia Telangiectasia and RAD3-Related (ATR) Inhibitor BAY 1895344 in Patients with Advanced Solid Tumors

Targeting the ataxia telangiectasia and RAD3-related (ATR) enzyme represents a promising anticancer strategy for tumors with DNA damage response (DDR) defects and replication stress, including inactivation of ataxia telangiectasia mutated (ATM) signaling. We report the dose-escalation portion of the phase I first-in-human trial of oral ATR inhibitor BAY 1895344 intermittently dosed 5 to 80 mg twice daily in 21 patients with advanced solid tumors. The MTD was 40 mg twice daily 3 days on/4 days off. Most common adverse events were manageable and reversible hematologic toxicities. Partial responses were achieved in 4 patients and stable disease in 8 patients. Median duration of response was 315.5 days. Responders had ATM protein loss and/or deleterious ATM mutations and received doses ≥40 mg twice daily. Overall, BAY 1895344 is well tolerated, with antitumor activity against cancers with certain DDR defects, including ATM loss. An expansion phase continues in patients with DDR deficiency. SIGNIFICANCE: Oral BAY 1895344 was tolerable, with antitumor activity in heavily pretreated patients with various advanced solid tumors, particularly those with ATM deleterious mutations and/or loss of ATM protein; pharmacodynamic results supported a mechanism of action of increased DNA damage. Further study is warranted in this patient population.See related commentary by Italiano, p. 14.This article is highlighted in the In This Issue feature, p. 1.

Integrating proteomics into precision oncology

DNA sequencing and RNA sequencing are increasingly applied in precision oncology, where molecular tumor boards evaluate the actionability of genetic events in individual tumors to guide targeted treatment. To work toward an additional level of patient characterization, we assessed the abundance and activity of 27 proteins in 134 patients whose tumors had previously undergone whole-exome and RNA sequencing within the Molecularly Aided Stratification for Tumor Eradication Research (MASTER) program of National Center for Tumor Diseases, Heidelberg. Proteomic and phosphoproteomic targets were selected to reflect the most relevant therapeutic baskets in MASTER. Among six different therapeutic baskets, the proteomic data supported treatment recommendations that were based on DNA and RNA analyses in 10% to 57% and frequently suggested alternative treatment options. In several cases, protein activities explained the patients' clinical course and provided potential explanations for treatment failure. Our study indicates that the integrative analysis of DNA, RNA and protein data may refine therapeutic stratification of individual patients and, thus, holds potential to increase the success rate of precision cancer therapy. Prospective validation studies are needed to advance the integration of proteomic analysis into precision oncology.

Medical oncologists' perspectives of the Veterans Affairs National Precision Oncology Program

BACKGROUND

To support the rising need for testing and to standardize tumor DNA sequencing practices within the U.S. Department of Veterans Affairs (VA)'s Veterans Health Administration (VHA), the National Precision Oncology Program (NPOP) was launched in 2016. We sought to assess oncologists' practices, concerns, and perceptions regarding Next-Generation Sequencing (NGS) and the NPOP.

MATERIALS AND METHODS

Using a purposive total sampling approach, oncologists who had previously ordered NGS for at least one tumor sample through the NPOP were invited to participate in semi-structured interviews. Questions assessed the following: expectations for the NPOP, procedural requirements, applicability of testing results, and the summative utility of the NPOP. Interviews were assessed using an open coding approach. Thematic analysis was conducted to evaluate the completed codebook. Themes were defined deductively by reviewing the direct responses to interview questions as well as inductively by identifying emerging patterns of data.

RESULTS

Of the 105 medical oncologists who were invited to participate, 20 (19%) were interviewed from 19 different VA medical centers in 14 states. Five recurrent themes were observed: (1) Educational Efforts Regarding Tumor DNA Sequencing Should be Undertaken, (2) Pathology Departments Share a Critical Role in Facilitating Test Completion, (3) Tumor DNA Sequencing via NGS Serves as the Most Comprehensive Testing Modality within Precision Oncology, (4) The Availability of the NPOP Has Expanded Options for Select Patients, and (5) The Completion of Tumor DNA Sequencing through the NPOP Could Help Improve Research Efforts within VHA Oncology Practices.

CONCLUSION

Medical oncologists believe that the availability of tumor DNA sequencing through the NPOP could potentially lead to an improvement in outcomes for veterans with metastatic solid tumors. Efforts should be directed toward improving oncologists' understanding of sequencing, strengthening collaborative relationships between oncologists and pathologists, and assessing the role of comprehensive NGS panels within the battery of precision tests.

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.

Workflow Differences Affect Data Accuracy in Oncologic EHRs: A First Step Toward Detangling the Diagnosis Data Babel

PURPOSE

Diagnosis (DX) information is key to clinical data reuse, yet accessible structured DX data often lack accuracy. Previous research hints at workflow differences in cancer DX entry, but their link to clinical data quality is unclear. We hypothesized that there is a statistically significant relationship between workflow-describing variables and DX data quality.

METHODS

We extracted DX data from encounter and order tables within our electronic health records (EHRs) for a cohort of patients with confirmed brain neoplasms. We built and optimized logistic regressions to predict the odds of fully accurate (ie, correct neoplasm type and anatomic site), inaccurate, and suboptimal (ie, vague) DX entry across clinical workflows. We selected our variables based on correlation strength of each outcome variable.

RESULTS

Both workflow and personnel variables were predictive of DX data quality. For example, a DX entered in departments other than oncology had up to 2.89 times higher odds of being accurate (P < .0001) compared with an oncology department; an outpatient care location had up to 98% fewer odds of being inaccurate (P < .0001), but had 458 times higher odds of being suboptimal (P < .0001) compared with main campus, including the cancer center; and a DX recoded by a physician assistant had 85% fewer odds of being suboptimal (P = .005) compared with those entered by physicians.

CONCLUSION

These results suggest that differences across clinical workflows and the clinical personnel producing EHR data affect clinical data quality. They also suggest that the need for specific structured DX data recording varies across clinical workflows and may be dependent on clinical information needs. Clinicians and researchers reusing oncologic data should consider such heterogeneity when conducting secondary analyses of EHR data.

How Machine Learning Will Transform Biomedicine

This Perspective explores the application of machine learning toward improved diagnosis and treatment. We outline a vision for how machine learning can transform three broad areas of biomedicine: clinical diagnostics, precision treatments, and health monitoring, where the goal is to maintain health through a range of diseases and the normal aging process. For each area, early instances of successful machine learning applications are discussed, as well as opportunities and challenges for machine learning. When these challenges are met, machine learning promises a future of rigorous, outcomes-based medicine with detection, diagnosis, and treatment strategies that are continuously adapted to individual and environmental differences.

Molecular profiling for precision cancer therapies

The number of druggable tumor-specific molecular aberrations has grown substantially in the past decade, with a significant survival benefit obtained from biomarker matching therapies in several cancer types. Molecular pathology has therefore become fundamental not only to inform on tumor diagnosis and prognosis but also to drive therapeutic decisions in daily practice. The introduction of next-generation sequencing technologies and the rising number of large-scale tumor molecular profiling programs across institutions worldwide have revolutionized the field of precision oncology. As comprehensive genomic analyses become increasingly available in both clinical and research settings, healthcare professionals are faced with the complex tasks of result interpretation and translation. This review summarizes the current and upcoming approaches to implement precision cancer medicine, highlighting the challenges and potential solutions to facilitate the interpretation and to maximize the clinical utility of molecular profiling results. We describe novel molecular characterization strategies beyond tumor DNA sequencing, such as transcriptomics, immunophenotyping, epigenetic profiling, and single-cell analyses. We also review current and potential applications of liquid biopsies to evaluate blood-based biomarkers, such as circulating tumor cells and circulating nucleic acids. Last, lessons learned from the existing limitations of genotype-derived therapies provide insights into ways to expand precision medicine beyond genomics.

Targeting ERBB2 (HER2) Amplification Identified by Next-Generation Sequencing in Patients With Advanced or Metastatic Solid Tumors Beyond Conventional Indications

PURPOSE

Human epidermal growth factor receptor 2 (HER2) is an effective therapeutic target in breast and gastric and gastroesophageal junction cancers. However, less is known about the prevalence of ERBB2 (HER2) amplification and the efficacy of HER2-targeted treatment in other tumors.

PATIENTS AND METHODS

We assessed HER2 amplification status among 5,002 patients with advanced disease (excluding breast cancer) who underwent next-generation sequencing. We evaluated the clinical benefit of HER2-targeted therapy by measuring the time-dependent overall survival (OS) from the genomic testing results, progression-free survival (PFS), and PFS during HER2-targeted therapy (PFS2) compared with PFS during prior therapy (PFS1).

RESULTS

Overall, 122 patients (2.4%) had HER2 amplification, including patients with endometrial (5.3%), bladder (5.2%), biliary or gallbladder (4.9%), salivary (4.7%), and colorectal cancer (3.6%). Forty patients (38%) with nongastric, nongastroesophageal junction, or nonesophageal cancers received at least one line of HER2-targeted therapy. Patients receiving HER2-targeted therapy had a median OS of 18.6 months, compared with 10.9 months for patients who did not receive HER2-targeted therapy (P = .070). On multivariable analysis, HER2-targeted therapy was significantly associated with increased OS (hazard ratio, 0.5; 95% CI, 0.27 to 0.93; P = .029), regardless of sex, age, or number of prior lines of treatment. The PFS2-to-PFS1 ratio was 1.3 or greater in 21 (57%) of 37 patients who received HER2-targeted therapy not in the first line of systemic treatment, and the median PFS2 and PFS1 times were 24 and 13 weeks, respectively (P < .001).

CONCLUSION

HER2 amplifications using next-generation sequencing can be identified in a variety of tumor types. HER2-targeted therapy may confer clinical benefit in tumor types other than those for which HER2 inhibitors are approved.

Clinical decision support for therapeutic decision-making in cancer: A systematic review

Cancer management, including supportive care, is complex and requires availability and synthesis of published and patient-specific data to make appropriate therapeutic decisions. Clinical decision support (CDS) may be an effective implementation strategy to support complex decision making although it is unclear whether it improves process outcomes, patient outcomes or both in cancer settings. We therefore conducted a systematic review to identify CDS that have been used to support therapeutic decision making in clinical cancer settings. Outcomes of interest included the effect of CDS on the process, such as clinician's decision making and effect on patient outcomes. Ten studies met inclusion criteria, with variability in the study design, setting, and intervention. Of the nine studies that measured process outcomes, five demonstrated significant improvement; and of the six that measured patient outcomes, four demonstrated significant improvement. All included studies utilized CDS that were informed by clinical practice guidelines. In conclusion, CDS to guide cancer therapeutic decision making is an understudied but promising area. Further research is needed.

Identification of Actionable Genomic Alterations Using Circulating Cell-Free DNA

PURPOSE

Cell-free DNA (cfDNA) next-generation sequencing is a noninvasive approach for genomic testing. We report the frequency of identifying alterations and their clinical actionability in patients with advanced/metastatic cancer.

PATIENTS AND METHODS

Prospectively consented patients had cfDNA testing performed. Alterations were assessed for therapeutic implications.

RESULTS

We enrolled 575 patients with 37 tumor types. Of these patients, 438 (76.2%) had at least one alteration detected, and 205 (35.7%) had one or more alterations of high potential for clinical action. In diseases with 10 or more patients enrolled, 50% or more had at least one alteration deemed of high potential for clinical action. Trials were identified in 80% of patients (286 of 357) with any alteration and in 92% of patients (188 of 205) with one or more alterations of high potential for clinical action of whom 57.6% (118 of 205) had 6 or more months of follow-up available. Of these patients, 10% (12 of 118) had received genomically matched therapy through enrollment in clinical trials (n = 8), off-label drug use (n = 3), or standard of care (n = 1). Although 88.6% of all patients had a performance status of 0 or 1 upon enrollment, the primary reason for not acting on alterations was poor performance status at next treatment change (28.1%; 27 of 96).

CONCLUSION

cfDNA testing represents a readily accessible method for genomic testing and allows for detection of genomic alterations in most patients with advanced disease. Utility may be higher in patients interested in investigational therapeutics with adequate performance status. Additional study is needed to determine whether utility is enhanced by testing earlier in the treatment course.

Cancer Panel Assay for Precision Oncology Clinic: Results from a 1-Year Study

Next-generation sequencing (NGS)-based cancer panel tests are actively being applied in the clinic for precision oncology. Given the importance of NGS panel tests in the palliative clinical setting, it is critical to understand success rates, factors responsible for test failures, and the incidence of clinically meaningful genetic alterations. We performed NGS cancer panel test with tumors from the stomach (n = 234), colorectum (n = 196), and rare tumors (n = 105) from 535 recurrent or metastatic cancer patients for 1 year. Sequencing was successful in 483 (95.3%) archival tumor samples to find single nucleotide variant (SNV), copy number alteration (CNA), and fusion. NGS testing was unsuccessful in 52 (9.7%) specimens due to inadequate tissue (n = 28), low tumor volume (n = 19), and poor quality of nucleic acid (n = 5). According to the Tier system, variants were classified as Tier IA, 0.8%; IIC, 10.3%; IID, 2.0%; III, 66.7% for gastric: Tier IA, 3.6%; IIC, 11.6% for colorectal: Tier IA, 1.6%; IIC, 13.5%; IID, 0.5%; III, 70.8% for melanoma, and Tier IA, 9.1%; IIC, 1.8%; IID, 1.0%; III, 66.4% for GIST. In total, 30.8% of 483 sequenced cases harbored clinically meaningful variants. In Tier IA, KRAS and ERBB2 were the most commonly altered genes. Interestingly, we identified CD274 (PD-L1) amplification, PTPN11 (SHP2) SNV, TPM3-NTRK1 fusion, and FGFR3-TACC3 fusion as a rare (<2%) alteration having therapeutic targets. In conclusion, although small biopsy samples constitute half of cases, informative NGS results were successfully reported in >90% of archival tissue samples, and 30.8% of them harbored clinically meaningful variants.

Individualization of Treatment Improves the Survival of Children With High-Risk Solid Tumors: Comparative Patient Series Analysis in a Real-Life Scenario

Introduction: The individualization of treatment is attractive, especially in children with high-risk cancer. In such a rare and very heterogeneous group of diseases, large population-based clinical randomized trials are not feasible without international collaboration. We therefore propose comparative patient series analysis in a real-life scenario.

Methods: Open cohort observational study, comparative analysis. Seventy patients with high-risk solid tumors diagnosed between 2003 and 2015 and in whom the treatment was individualized either empirically or based on biomarkers were analyzed. The heterogeneity of the cohort and repeated measurements were advantageously utilized to increase effective sample size using appropriate statistical tools.

Results: We demonstrated a beneficial effect of empirically given low-dose metronomic chemotherapy (HR 0.46 for relapses, p = 0.017) as well as various repurposed or targeted agents (HR 0.15 for deaths, p = 0.004) in a real-life scenario. However, targeted agents given on the basis of limited biological information were not beneficial.

Conclusions: Comparative patient series analysis provides institutional-level evidence for treatment individualization in high-risk pediatric malignancies. Our findings emphasize the need for a comprehensive, multi omics assessment of the tumor and the host as well whenever molecularly driven targeted therapies are being considered. Low-dose metronomic chemotherapy or local control of the disease may be a more rational option in situations where targeted treatment cannot be justified by robust evidence and comprehensive biological information. “Targeted drugs” may be given empirically with a realistic benefit expectation when based on robust rationale.

Dedifferentiated Endometrial Carcinoma Could be A Target for Immune Checkpoint Inhibitors (Anti PD-1/PD-L1 Antibodies)

Dedifferentiated endometrial carcinoma (DDEC) is defined as an undifferentiated carcinoma admixed with differentiated endometrioid carcinoma (Grade 1 or 2). It has poor prognosis compared with Grade 3 endometrioid adenocarcinoma and is often associated with the loss of mismatch repair (MMR) proteins, which is seen in microsatellite instability (MSI)-type endometrial cancer. Recent studies have shown that the effectiveness of immune checkpoint inhibitor therapy is related to MMR deficiency; therefore, we analyzed the immunophenotype (MMR deficient and expression of PD-L1) of 17 DDEC cases. In the undifferentiated component, nine cases (53%) were deficient in MMR proteins and nine cases (53%) expressed PD-L1. PD-L1 expression was significantly associated with MMR deficiency (p = 0.026). In addition, the presence of tumor-infiltrating lymphocytes (CD8+) was significantly associated with MMR deficiency (p = 0.026). In contrast, none of the cases showed PD-L1 expression in the well-differentiated component. Our results show that DDEC could be a target for immune checkpoint inhibitors (anti PD-L1/PD-1 antibodies), especially in the undifferentiated component. As a treatment strategy for DDEC, conventional paclitaxel plus carboplatin and cisplatin plus doxorubicin therapies are effective for those with the well-differentiated component. However, by using immune checkpoint inhibitors in combination with other conventional treatments, it may be possible to control the undifferentiated component and improve prognosis.

Integration of microbiology, molecular pathology, and epidemiology: a new paradigm to explore the pathogenesis of microbiome-driven neoplasms

Molecular pathological epidemiology (MPE) is an integrative transdisciplinary field that addresses heterogeneous effects of exogenous and endogenous factors (collectively termed 'exposures'), including microorganisms, on disease occurrence and consequences, utilising molecular pathological signatures of the disease. In parallel with the paradigm of precision medicine, findings from MPE research can provide aetiological insights into tailored strategies of disease prevention and treatment. Due to the availability of molecular pathological tests on tumours, the MPE approach has been utilised predominantly in research on cancers including breast, lung, prostate, and colorectal carcinomas. Mounting evidence indicates that the microbiome (inclusive of viruses, bacteria, fungi, and parasites) plays an important role in a variety of human diseases including neoplasms. An alteration of the microbiome may be not only a cause of neoplasia but also an informative biomarker that indicates or mediates the association of an epidemiological exposure with health conditions and outcomes. To adequately educate and train investigators in this emerging area, we herein propose the integration of microbiology into the MPE model (termed 'microbiology-MPE'), which could improve our understanding of the complex interactions of environment, tumour cells, the immune system, and microbes in the tumour microenvironment during the carcinogenic process. Using this approach, we can examine how lifestyle factors, dietary patterns, medications, environmental exposures, and germline genetics influence cancer development and progression through impacting the microbial communities in the human body. Further integration of other disciplines (e.g. pharmacology, immunology, nutrition) into microbiology-MPE would expand this developing research frontier. With the advent of high-throughput next-generation sequencing technologies, researchers now have increasing access to large-scale metagenomics as well as other omics data (e.g. genomics, epigenomics, proteomics, and metabolomics) in population-based research. The integrative field of microbiology-MPE will open new opportunities for personalised medicine and public health. Copyright © 2019 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Review: Precision medicine and driver mutations: Computational methods, functional assays and conformational principles for interpreting cancer drivers

At the root of the so-called precision medicine or precision oncology, which is our focus here, is the hypothesis that cancer treatment would be considerably better if therapies were guided by a tumor’s genomic alterations. This hypothesis has sparked major initiatives focusing on whole-genome and/or exome sequencing, creation of large databases, and developing tools for their statistical analyses—all aspiring to identify actionable alterations, and thus molecular targets, in a patient. At the center of the massive amount of collected sequence data is their interpretations that largely rest on statistical analysis and phenotypic observations. Statistics is vital, because it guides identification of cancer-driving alterations. However, statistics of mutations do not identify a change in protein conformation; therefore, it may not define sufficiently accurate actionable mutations, neglecting those that are rare. Among the many thematic overviews of precision oncology, this review innovates by further comprehensively including precision pharmacology, and within this framework, articulating its protein structural landscape and consequences to cellular signaling pathways. It provides the underlying physicochemical basis, thereby also opening the door to a broader community.

Human Microbiota and Personalized Cancer Treatments: Role of Commensal Microbes in Treatment Outcomes for Cancer Patients

The human gut microbiota consists of about 3.8 × 10¹³ microorganisms that play an essential role in health, metabolism, and immunomodulation. These gut microbes alter therapeutic response and toxicity to cancer therapies including cytotoxic chemotherapy, radiation therapy, kinase inhibitors, and immunotherapy agents. The gut microbiota generates short-chain fatty acids that are significant regulators of histone post-translational modifications that fundamentally regulate gene expression, linking the microbiota to cellular metabolism and transcriptional regulation. The short-chain fatty acids not only act locally but can be taken up in the blood stream to inhibit the activity of histone deacetylases, regulate gene expression in distant organs as well as the effector function of CD8+ T cells. Cancer and the treatments for it negatively impact the microbiome often resulting in dysbiosis. This can diminish a patient's response to treatment as well as increase systemic toxicities from these therapies. In addition to the gut microbiota, microbes have been detected in tumors that can modulate chemotherapeutic drug response and can result in immune suppression. The gut microbiota and tumor-associated bacteria may be a significant contributor to the interindividual differences and heterogeneous responses to cancer therapies and drug tolerability and strategies that support and/or manipulate the microbiota to improve therapeutic outcome is an emerging area for personalized cancer treatment.

Precision Oncology in Solid Tumors: A Longitudinal Tertiary Care Center Experience

Purpose

Precision oncology is widely discussed, but cohort studies are limited. We previously reported our prospective experience of precision oncology in solid tumors, and here we report our longitudinal experience, focusing on therapeutic impact.

Patients and Methods

We conducted a retrospective review of 600 consecutive patients seen at Cleveland Clinic from 2013 to 2016 for treatment of incurable solid tumor malignancies for whom tumor genomic profiling was ordered using FoundationOne (Cambridge, MA). Results were discussed at our multidisciplinary genomics tumor board. Data analyzed included subsequent therapy and overall survival (OS).

Results

Median age was 59 years (range, 18 to 94 years), 308 (51.3%) were female, and 533 (88.8%) were white. Targeted therapy was recommended in 310 patients (51.7%). After results, 313 patients (52.2%) started any subsequent therapy; of these, 95 (30%; 15.8% overall) received genomics-driven therapy (G), and 218 (70%) received non–genomics-driven treatment (NG). For the G versus NG group, the on-label, off-label, and clinical trial therapy breakdowns were 23% versus 88%, 47% versus 3%, and 30% versus 9%, respectively. Median OS for patients receiving no therapy after tumor genomic profiling was 5.5 months; for the G and NG groups, it was 18 ( P < .001) and 14.4 ( P < .001) months, respectively ( P = NS for G v NG). The use of G increased from 10% in the first 250-patient cohort (reported earlier) to 20% in the subsequent 350-patient cohort.

Conclusion

Tumor genomic profiling influenced treatment in 15.8% of patients. More patients received treatment via clinical trials in the G cohort, and although not statistically significant, there was a trend toward increased OS in the G ( v NG) group. These data can further guide real-world applications of precision oncology.