Pilot Trial of Selecting Molecularly Guided Therapy for Patients with Non-V600 BRAF-Mutant Metastatic Melanoma: Experience of the SU2C/MRA Melanoma Dream Team

New clinical trial design in precision medicine: discovery, development and direction

In the era of precision medicine, it has been increasingly recognized that individuals with a certain disease are complex and different from each other. Due to the underestimation of the significant heterogeneity across participants in traditional "one-size-fits-all" trials, patient-centered trials that could provide optimal therapy customization to individuals with specific biomarkers were developed including the basket, umbrella, and platform trial designs under the master protocol framework. In recent years, the successive FDA approval of indications based on biomarker-guided master protocol designs has demonstrated that these new clinical trials are ushering in tremendous opportunities. Despite the rapid increase in the number of basket, umbrella, and platform trials, the current clinical and research understanding of these new trial designs, as compared with traditional trial designs, remains limited. The majority of the research focuses on methodologies, and there is a lack of in-depth insight concerning the underlying biological logic of these new clinical trial designs. Therefore, we provide this comprehensive review of the discovery and development of basket, umbrella, and platform trials and their underlying logic from the perspective of precision medicine. Meanwhile, we discuss future directions on the potential development of these new clinical design in view of the "Precision Pro", "Dynamic Precision", and "Intelligent Precision". This review would assist trial-related researchers to enhance the innovation and feasibility of clinical trial designs by expounding the underlying logic, which be essential to accelerate the progression of precision medicine.

Mechanisms of Melanoma Progression and Treatment Resistance: Role of Cancer Stem-like Cells

Melanoma is the third most common type of skin cancer, characterized by its heterogeneity and propensity to metastasize to distant organs. Melanoma is a heterogeneous tumor, composed of genetically divergent subpopulations, including a small fraction of melanoma-initiating cancer stem-like cells (CSCs) and many non-cancer stem cells (non-CSCs). CSCs are characterized by their unique surface proteins associated with aberrant signaling pathways with a causal or consequential relationship with tumor progression, drug resistance, and recurrence. Melanomas also harbor significant alterations in functional genes (BRAF, CDKN2A, NRAS, TP53, and NF1). Of these, the most common are the BRAF and NRAS oncogenes, with 50% of melanomas demonstrating the BRAF mutation (BRAFV600E). While the successful targeting of BRAFV600E does improve overall survival, the long-term efficacy of available therapeutic options is limited due to adverse side effects and reduced clinical efficacy. Additionally, drug resistance develops rapidly via mechanisms involving fast feedback re-activation of MAPK signaling pathways. This article updates information relevant to the mechanisms of melanoma progression and resistance and particularly the mechanistic role of CSCs in melanoma progression, drug resistance, and recurrence.

Next generation sequencing for personalized therapy: About a class III BRAF N581K mutation associated to NRAS Q61L mutation in malignant melanoma: Case report

In metastatic stage, therapeutic approach for malignant melanoma is particularly based on performance status, metastatic sites, and BRAF V600 status (BRAF V600E/V600K or V600R (class I BRAF mutations). In most cases, BRAF mutations and NRAS mutations are mutually exclusive to each other. However, some rare BRAF mutations class III are preferentially associated with a NRAS mutation, leading to the MAP Kinase pathway activation and subsequent cell proliferation. Melanomas with this double mutation are rare and difficult to treat because of the lack of codified therapeutic options. We report a patient with metastatic melanoma, harboring class III BRAF mutation (N581K) associated to NRAS mutation (Q61L) with treatment failure. He was treated in second line, after immunotherapy, by monotherapy of MEK inhibitor (MEKi), which underline the interest of NGS (Next Generation Sequencing) to early identify all mutations and enabling onco-dermatologist to discuss a treatment. Rare BRAF non V600 mutations represent 3 to 14% of melanoma mutants and the aim of this communication is to promote the next generation sequencing to extend the paradigm of individually therapeutic approach with target therapy into different spectrum of melanoma patients.

A transcriptomics approach to expand therapeutic options and optimize clinical trials in oncology

Background

The current model of clinical drug development in oncology displays major limitations due to a high attrition rate in patient enrollment in early phase trials and a high failure rate of drugs in phase III studies.

Objective

Integrating transcriptomics for selection of patients has the potential to achieve enhanced speed and efficacy of precision oncology trials for any targeted therapies or immunotherapies.

Methods

Relative gene expression level in the metastasis and normal organ-matched tissues from the WINTHER database was used to estimate in silico the potential clinical benefit of specific treatments in a variety of metastatic solid tumors.

Results

As example, high mRNA expression in tumor tissue compared to analogous normal tissue of c-MET and its ligand HGF correlated in silico with shorter overall survival (OS; p < 0.0001) and may constitute an independent prognostic marker for outcome of patients with metastatic solid tumors, suggesting a strategy to identify patients most likely to benefit from MET-targeted treatments. The prognostic value of gene expression of several immune therapy targets (PD-L1, CTLA4, TIM3, TIGIT, LAG3, TLR4) was investigated in non-small-cell lung cancers and colorectal cancers (CRCs) and may be useful to optimize the development of their inhibitors, and opening new avenues such as use of anti-TLR4 in treatment of patients with metastatic CRC.

Conclusion

This in silico approach is expected to dramatically decrease the attrition of patient enrollment and to simultaneously increase the speed and detection of early signs of efficacy. The model may significantly contribute to lower toxicities. Altogether, our model aims to overcome the limits of current approaches.

Dasatinib Resensitizes MAPK Inhibitor Efficacy in Standard-of-Care Relapsed Melanomas

Resistance to combination BRAF/MEK inhibitor (BRAFi/MEKi) therapy arises in nearly every patient with BRAFV600E/K melanoma, despite promising initial responses. Achieving cures in this expanding BRAFi/MEKi-resistant cohort represents one of the greatest challenges to the field; few experience additional durable benefit from immunotherapy and no alternative therapies exist. To better personalize therapy in cancer patients to address therapy relapse, umbrella trials have been initiated whereby genomic sequencing of a panel of potentially actionable targets guide therapy selection for patients; however, the superior efficacy of such approaches remains to be seen. We here test the robustness of the umbrella trial rationale by analyzing relationships between genomic status of a gene and the downstream consequences at the protein level of related pathway, which find poor relationships between mutations, copy number amplification, and protein level. To profile candidate therapeutic strategies that may offer clinical benefit in the context of acquired BRAFi/MEKi resistance, we established a repository of patient-derived xenograft models from heavily pretreated patients with resistance to BRAFi/MEKi and/or immunotherapy (R-PDX). With these R-PDXs, we executed in vivo compound repurposing screens using 11 FDA-approved agents from an NCI-portfolio with pan-RTK, non-RTK and/or PI3K-mTOR specificity. We identify dasatinib as capable of restoring BRAFi/MEKi antitumor efficacy in ~70% of R-PDX tested. A systems-biology analysis indicates elevated baseline protein expression of canonical drivers of therapy resistance (e.g., AXL, YAP, HSP70, phospho-AKT) as predictive of MAPKi/dasatinib sensitivity. We therefore propose that dasatinib-based MAPKi therapy may restore antitumor efficacy in patients that have relapsed to standard-of-care therapy by broadly targeting proteins critical in melanoma therapy escape. Further, we submit that this experimental PDX paradigm could potentially improve preclinical evaluation of therapeutic modalities and augment our ability to identify biomarker-defined patient subsets that may respond to a given clinical trial.

Identifying treatment options for BRAFV600 wild-type metastatic melanoma: A SU2C/MRA genomics-enabled clinical trial

Although combination BRAF and MEK inhibitors are highly effective for the 40-50% of cutaneous metastatic melanomas harboring BRAFV600 mutations, targeted agents have been ineffective for BRAFV600wild-type (wt) metastatic melanomas. The SU2C Genomics-Enabled Medicine for Melanoma Trial utilized a Simon two-stage optimal design to assess whether comprehensive genomic profiling improves selection of molecular-based therapies for BRAFV600wt metastatic melanoma patients who had progressed on standard-of-care therapy, which may include immunotherapy. Of the response-evaluable patients, binimetinib was selected for 20 patients randomized to the genomics-enabled arm, and nine were treated on the alternate treatment arm. Response rates for 27 patients treated with targeted recommendations included one (4%) partial response, 18 (67%) with stable disease, and eight (30%) with progressive disease. Post-trial genomic and protein pathway activation mapping identified additional drug classes that may be considered for future studies. Our results highlight the complexity and heterogeneity of metastatic melanomas, as well as how the lack of response in this trial may be associated with limitations including monotherapy drug selection and the dearth of available single and combination molecularly-driven therapies to treat BRAFV600wt metastatic melanomas.

Strategies for Testing Intervention Matching Schemes in Cancer

Personalized medicine, or the tailoring of health interventions to an individual's nuanced and often unique genetic, biochemical, physiological, behavioral, and/or exposure profile, is seen by many as a biological necessity given the great heterogeneity of pathogenic processes underlying most diseases. However, testing and ultimately proving the benefit of strategies or algorithms connecting the mechanisms of action of specific interventions to patient pathophysiological profiles (referred to here as "intervention matching schemes" (IMS)) is complex for many reasons. We argue that IMS are likely to be pervasive, if not ubiquitous, in future health care, but raise important questions about their broad deployment and the contexts within which their utility can be proven. For example, one could question the need to, the efficiency associated with, and the reliability of, strategies for comparing competing or perhaps complementary IMS. We briefly summarize some of the more salient issues surrounding the vetting of IMS in cancer contexts and argue that IMS are at the foundation of many modern clinical trials and intervention strategies, such as basket, umbrella, and adaptive trials. In addition, IMS are at the heart of proposed "rapid learning systems" in hospitals, and implicit in cell replacement strategies, such as cytotoxic T-cell therapies targeting patient-specific neo-antigen profiles. We also consider the need for sensitivity to issues surrounding the deployment of IMS and comment on directions for future research.

Genetic Profiling of Advanced Melanoma: Candidate Mutations for Predicting Sensitivity and Resistance to Targeted Therapy

BACKGROUND

Molecularly targeted therapy has revolutionized the treatment of advanced melanoma. However, despite its high efficiency, a majority of patients experience relapse within 1 year of treatment because of acquired resistance, and approximately 10-25% patients gain no benefit from these agents owing to intrinsic resistance. This is mainly caused by the genetic heterogeneity of melanoma cells.

OBJECTIVE

We aimed to validate the predictive significance of selected genes in advanced melanoma patients before treatment with BRAF/MEK inhibitors.

PATIENTS AND METHODS

Archival DNA derived from 37 formalin-fixed paraffin-embedded pre-treatment advanced melanoma samples of patients treated with targeted therapy was used for next-generation sequencing analysis using the Ion Torrent platform. The AmpliSeq Custom Panel comprised coding sequences or hot spots of 23 melanoma genes: ATM, BRAF, CDK4, CDKN2A, CTNNB1, EGFR, HOXD8, HRAS, IDH1, KIT, KRAS, MAP3K8, MAP2K1, MAP2K2, MITF, MYC, NF1, NRAS, PAX5, PIK3R1, PTEN, RAC1, and RB1. The sequences were evaluated for genomic alterations and further validated using Sanger sequencing.

RESULTS

Our analysis revealed non-BRAF genetic alterations in 28 out of 37 samples (75.7%). Genetic changes were identified in PTEN, CDK4, CDKN2A, CTNNB1, EGFR, HOXD8, HRAS, KIT, MAP2K1, MAP2K2, MITF, MYC, NF1, PAX5, RAC1, and RB1. Fifteen known pathogenic mutations (single nucleotide variants or indels) and 11 variants of unknown significance were detected. Statistical analysis revealed an association between the presence of pathogenic mutations and time to progression during treatment with combination therapy.

CONCLUSIONS

Pathogenic mutations identified by gene panel sequencing have potential predictive value for targeted therapy of melanoma and are worth further validation in a larger series of cases. The role of some known mutations (e.g. CDK4R24, PTEN c.801 + 1G > A, CTNNB1S45F) as well as variants of unknown significance identified in this study (e.g. MITFR316K, KITG498S) in the generation of resistance to BRAF/MEK inhibitors should be further investigated.

Systematic review of basket trials, umbrella trials, and platform trials: a landscape analysis of master protocols

BACKGROUND

Master protocols, classified as basket trials, umbrella trials, and platform trials, are novel designs that investigate multiple hypotheses through concurrent sub-studies (e.g., multiple treatments or populations or that allow adding/removing arms during the trial), offering enhanced efficiency and a more ethical approach to trial evaluation. Despite the many advantages of these designs, they are infrequently used.

METHODS

We conducted a landscape analysis of master protocols using a systematic literature search to determine what trials have been conducted and proposed for an overall goal of improving the literacy in this emerging concept. On July 8, 2019, English-language studies were identified from MEDLINE, EMBASE, and CENTRAL databases and hand searches of published reviews and registries.

RESULTS

We identified 83 master protocols (49 basket, 18 umbrella, and 16 platform trials). The number of master protocols has increased rapidly over the last five years. Most have been conducted in the US (n = 44/83) and investigated experimental drugs (n = 82/83) in the field of oncology (n = 76/83). The majority of basket trials were exploratory (i.e., phase I/II; n = 47/49) and not randomized (n = 44/49), and more than half (n = 28/48) investigated only a single intervention. The median sample size of basket trials was 205 participants (interquartile range, Q3-Q1 [IQR]: 500-90 = 410), and the median study duration was 22.3 (IQR: 74.1-42.9 = 31.1) months. Similar to basket trials, most umbrella trials were exploratory (n = 16/18), but the use of randomization was more common (n = 8/18). The median sample size of umbrella trials was 346 participants (IQR: 565-252 = 313), and the median study duration was 60.9 (IQR: 81.3-46.9 = 34.4) months. The median number of interventions investigated in umbrella trials was 5 (IQR: 6-4 = 2). The majority of platform trials were randomized (n = 15/16), and phase III investigation (n = 7/15; one did not report information on phase) was more common in platform trials with four of them using seamless II/III design. The median sample size was 892 (IQR: 1835-255 = 1580), and the median study duration was 58.9 (IQR: 101.3-36.9 = 64.4) months.

CONCLUSIONS

We anticipate that the number of master protocols will continue to increase at a rapid pace over the upcoming decades. More efforts to improve awareness and training are needed to apply these innovative trial design methods to fields outside of oncology.

Integrative omics analyses broaden treatment targets in human cancer

Background

Although large-scale, next-generation sequencing (NGS) studies of cancers hold promise for enabling precision oncology, challenges remain in integrating NGS with clinically validated biomarkers.

Methods

To overcome such challenges, we utilized the Database of Evidence for Precision Oncology (DEPO) to link druggability to genomic, transcriptomic, and proteomic biomarkers. Using a pan-cancer cohort of 6570 tumors, we identified tumors with potentially druggable biomarkers consisting of drug-associated mutations, mRNA expression outliers, and protein/phosphoprotein expression outliers identified by DEPO.

Results

Within the pan-cancer cohort of 6570 tumors, we found that 3% are druggable based on FDA-approved drug-mutation interactions in specific cancer types. However, mRNA/phosphoprotein/protein expression outliers and drug repurposing across cancer types suggest potential druggability in up to 16% of tumors. The percentage of potential drug-associated tumors can increase to 48% if we consider preclinical evidence. Further, our analyses showed co-occurring potentially druggable multi-omics alterations in 32% of tumors, indicating a role for individualized combinational therapy, with evidence supporting mTOR/PI3K/ESR1 co-inhibition and BRAF/AKT co-inhibition in 1.6 and 0.8% of tumors, respectively. We experimentally validated a subset of putative druggable mutations in BRAF identified by a protein structure-based computational tool. Finally, analysis of a large-scale drug screening dataset lent further evidence supporting repurposing of drugs across cancer types and the use of expression outliers for inferring druggability.

Conclusions

Our results suggest that an integrated analysis platform can nominate multi-omics alterations as biomarkers of druggability and aid ongoing efforts to bring precision oncology to patients.

Electronic supplementary material

The online version of this article (10.1186/s13073-018-0564-z) contains supplementary material, which is available to authorized users.

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

With the increasing availability of genomics, routine analysis of advanced cancers is now feasible. Treatment selection is frequently guided by the molecular characteristics of a patient's tumor, and an increasing number of trials are genomically selected. Furthermore, multiple studies have demonstrated the benefit of therapies that are chosen based upon the molecular profile of a tumor. However, the rapid evolution of genomic testing platforms and emergence of new technologies make interpreting molecular testing reports more challenging. More sophisticated precision oncology decision support services are essential. This review outlines existing tools available for health care providers and precision oncology teams and highlights strategies for optimizing decision support. Specific attention is given to the assays currently available for molecular testing, as well as considerations for interpreting alteration information. This article also discusses strategies for identifying and matching patients to clinical trials, current challenges, and proposals for future development of precision oncology decision support. Clin Cancer Res; 24(12); 2719-31. ©2018 AACR.

Molecular Tumor Boards: current practice and future needs

Background

Due to rapid technical advances, steeply declining sequencing costs, and the ever-increasing number of targeted therapies, it can be expected that extensive tumor sequencing such as whole-exome and whole-genome sequencing will soon be applied in standard care. Clinicians will thus be confronted with increasingly complex genetic information and multiple test-platforms to choose from. General medical training, meanwhile, can hardly keep up with the pace of innovation. Consequently, there is a rapidly growing gap between clinical knowledge and genetic potential in cancer care. Multidisciplinary Molecular Tumor Boards (MTBs) have been suggested as a means to address this disparity, but shared experiences are scarce in literature and no quality requirements or guidelines have been published to date.

Methods

Based on literature review, a survey among hospitals in The Netherlands, and our own experience with the establishment of a nationally operating MTB, this article evaluates current knowledge and unmet needs and lays out a strategy for successful MTB implementation.

Results

Having access to an MTB can improve and increase the application of genetics-guided cancer care. In our survey, however, <50% of hospitals and only 5% of nonacademic hospitals had access to an MTB. In addition, current MTBs vary widely in terms of composition, tasks, tools, and workflow. This may not only lead to variation in quality of care but also hinders data sharing and thus creation of an effective learning community.

Conclusions

This article acknowledges a leading role for MTBs to govern (extensive) tumor sequencing into daily practice and proposes three basic necessities for successful MTB implementation: (i) global harmonization in cancer sequencing practices and procedures, (ii) minimal member and operational requirements, and (iii) an appropriate unsolicited findings policy. Meeting these prerequisites would not only optimize MTB functioning but also improve general interpretation and application of genomics-guided cancer care.

Analysis of variability in high throughput screening data: applications to melanoma cell lines and drug responses

High-throughput screening (HTS) strategies and protocols have undergone significant development in the last decade. It is now possible to screen hundreds of thousands of compounds, each exploring multiple biological phenotypes and parameters, against various cell lines or model systems in a single setting. However, given the vast amount of data such studies generate, the fact that they use multiple reagents, and are often technician-intensive, questions have been raised about the variability, reliability and reproducibility of HTS results. Assessments of the impact of the multiple factors in HTS studies could arguably lead to more compelling insights into the robustness of the results of a particular screen, as well as the overall quality of the study. We leveraged classical, yet highly flexible, analysis of variance (ANOVA)-based linear models to explore how different factors contribute to the variation observed in a screening study of four different melanoma cell lines and 120 drugs over nine dosages studied in two independent academic laboratories. We find that factors such as plate effects, appropriate dosing ranges, and to a lesser extent, the laboratory performing the screen, are significant predictors of variation in drug responses across the cell lines. Further, we show that when sources of variation are quantified and controlled for, they contextualize claims of inconsistencies and reveal the overall quality of the HTS studies performed at each participating laboratory. In the context of the broader screening study, we show that our analysis can also elucidate the robust effects of drugs, even those within specific cell lines.

Precision oncology in the age of integrative genomics

Precision oncology applies genomic and other molecular analyses of tumor biopsies to improve the diagnosis and treatment of cancers. In addition to identifying therapeutic options, precision oncology tracks the response of a tumor to an intervention at the molecular level and detects drug resistance and the mechanisms by which it occurs. Integrative genomics can include sequencing specific panels of genes, exomes, or the entire triad of the patient's germline, tumor exome, and tumor transcriptome. Although the capabilities of sequencing technologies continue to improve, widespread adoption of genomics-driven precision oncology in the clinic has been held back by logistical, regulatory, financial, and ethical considerations. Nevertheless, integrative clinical sequencing programs applied at the point of care have the potential to improve the clinical management of cancer patients.

Prospective Feasibility Trial for Genomics-Informed Treatment in Recurrent and Progressive Glioblastoma

Purpose: Glioblastoma is an aggressive and molecularly heterogeneous cancer with few effective treatment options. We hypothesized that next-generation sequencing can be used to guide treatment recommendations within a clinically acceptable time frame following surgery for patients with recurrent glioblastoma.Experimental Design: We conducted a prospective genomics-informed feasibility trial in adults with recurrent and progressive glioblastoma. Following surgical resection, genome-wide tumor/normal exome sequencing and tumor RNA sequencing were performed to identify molecular targets for potential matched therapy. A multidisciplinary molecular tumor board issued treatment recommendations based on the genomic results, blood-brain barrier penetration of the indicated therapies, drug-drug interactions, and drug safety profiles. Feasibility of generating genomics-informed treatment recommendations within 35 days of surgery was assessed.Results: Of the 20 patients enrolled in the study, 16 patients had sufficient tumor tissue for analysis. Exome sequencing was completed for all patients, and RNA sequencing was completed for 14 patients. Treatment recommendations were provided within the study's feasibility time frame for 15 of 16 (94%) patients. Seven patients received treatment based on the tumor board recommendations. Two patients reached 12-month progression-free survival, both adhering to treatments based on the molecular profiling results. One patient remained on treatment and progression free 21 months after surgery, 3 times longer than the patient's previous time to progression. Analysis of matched nonenhancing tissue from 12 patients revealed overlapping as well as novel putatively actionable genomic alterations.Conclusions: Use of genome-wide molecular profiling is feasible and can be informative for guiding real-time, central nervous system-penetrant, genomics-informed treatment recommendations for patients with recurrent glioblastoma. Clin Cancer Res; 24(2); 295-305. ©2017 AACRSee related commentary by Wick and Kessler, p. 256.

Twenty-First Century Precision Medicine in Oncology: Genomic Profiling in Patients With Cancer

The advent of next-generation sequencing has accelerated the implementation of genomic profiling in the care and management of patients with cancer. Initial efforts have focused on target identification in patients with advanced cancer. Prognostication, resistance detection, disease monitoring, and early detection efforts are also underway. This review highlights some of the challenges in this evolving space. This includes choosing between gene-panel and comprehensive approaches, DNA and transcriptome data integration, reduction of false-positive variants, addressing tumor heterogeneity, establishment of workflows to address unsolicited findings, and data sharing and privacy concerns.

A prospective pilot study of genome-wide exome and transcriptome profiling in patients with small cell lung cancer progressing after first-line therapy

Background

Small cell lung cancer (SCLC) that has progressed after first-line therapy is an aggressive disease with few effective therapeutic strategies. In this prospective study, we employed next-generation sequencing (NGS) to identify therapeutically actionable alterations to guide treatment for advanced SCLC patients.

Methods

Twelve patients with SCLC were enrolled after failing platinum-based chemotherapy. Following informed consent, genome-wide exome and RNA-sequencing was performed in a CLIA-certified, CAP-accredited environment. Actionable targets were identified and therapeutic recommendations made from a pharmacopeia of FDA-approved drugs. Clinical response to genomically-guided treatment was evaluated by Response Evaluation Criteria in Solid Tumors (RECIST) 1.1.

Results

The study completed its accrual goal of 12 evaluable patients. The minimum tumor content for successful NGS was 20%, with a median turnaround time from sample collection to genomics-based treatment recommendation of 27 days. At least two clinically actionable targets were identified in each patient, and six patients (50%) received treatment identified by NGS. Two had partial responses by RECIST 1.1 on a clinical trial involving a PD-1 inhibitor + irinotecan (indicated by MLH1 alteration). The remaining patients had clinical deterioration before NGS recommended therapy could be initiated.

Conclusions

Comprehensive genomic profiling using NGS identified clinically-actionable alterations in SCLC patients who progressed on initial therapy. Recommended PD-1 therapy generated partial responses in two patients. Earlier access to NGS guided therapy, along with improved understanding of those SCLC patients likely to respond to immune-based therapies, should help to extend survival in these cases with poor outcomes.

Capturing tumor heterogeneity and clonal evolution in solid cancers using circulating tumor DNA analysis

Circulating tumor DNA analysis has emerged as a potential noninvasive alternative to tissue biopsies for tumor genotyping in patients with metastatic cancer. This is particularly attractive in cases where tissue biopsies are contraindicated or repeat genotyping after progression on treatment is required. However, tissue and plasma analysis results are not always concordant and clinical interpretation of discordant results is not completely understood. Discordant results could arise due to analytical limits of assays used for tumor and plasma DNA analysis or due to low overall contribution of tumor-specific DNA in plasma. Once these factors are ruled out, tissue-plasma concordance and quantitative levels of somatic mutations in plasma can capture tumor heterogeneity. During longitudinal follow-up of patients, this feature can be leveraged to track subclonal evolution and to guide combination or sequential adaptive treatment. Here, we summarize recent results evaluating the opportunities and limitations of circulating tumor DNA analysis in the context of tumor heterogeneity and subclonal evolution in patients with advanced cancers.