Genomic and transcriptomic profiling expands precision cancer medicine: the WINTHER trial

The Landscape of Pediatric Precision Oncology: Program Design, Actionable Alterations, and Clinical Trial Development

Over the last years, various precision medicine programs have been developed for pediatric patients with high-risk, relapsed, or refractory malignancies, selecting patients for targeted treatment through comprehensive molecular profiling. In this review, we describe characteristics of these initiatives, demonstrating the feasibility and potential of molecular-driven precision medicine. Actionable events are identified in a significant subset of patients, although comparing results is complicated due to the lack of a standardized definition of actionable alterations and the different molecular profiling strategies used. The first biomarker-driven trials for childhood cancer have been initiated, but until now the effect of precision medicine on clinical outcome has only been reported for a small number of patients, demonstrating clinical benefit in some. Future perspectives include the incorporation of novel approaches such as liquid biopsies and immune monitoring as well as innovative collaborative trial design including combination strategies, and the development of agents specifically targeting aberrations in childhood malignancies.

Technological Advances in Tumor-On-Chip Technology: From Bench to Bedside

Simple Summary

Various 3D in vitro tumor models are rapidly advancing cancer research. Unlike animal models, they can be produced quickly and are amenable to high-throughput studies. Growing tumor spheroids in microfluidic tumor-on-chip platforms has particularly elevated the capabilities of such models. Tumor-on-chip devices can mimic multiple aspects of the dynamic in vivo tumor microenvironment in a precisely controlled manner. Moreover, new technologies for the on- and off-chip analysis of these tumor mimics are continuously emerging. There is thus an urgent need to review the latest developments in this rapidly progressing field. Here, we present an overview of the technological advances in tumor-on-chip technology by reviewing state-of-the-art tools for on-chip analysis. In particular, we evaluate the potential for tumor-on-chip technology to guide personalized cancer therapies. We strive to appeal to cancer researchers and biomedical engineers alike, informing on current progress, while provoking thought on the outstanding developments needed to achieve clinical-stage research.

Abstract

Tumor-on-chip technology has cemented its importance as an in vitro tumor model for cancer research. Its ability to recapitulate different elements of the in vivo tumor microenvironment makes it promising for translational medicine, with potential application in enabling personalized anti-cancer therapies. Here, we provide an overview of the current technological advances for tumor-on-chip generation. To further elevate the functionalities of the technology, these approaches need to be coupled with effective analysis tools. This aspect of tumor-on-chip technology is often neglected in the current literature. We address this shortcoming by reviewing state-of-the-art on-chip analysis tools for microfluidic tumor models. Lastly, we focus on the current progress in tumor-on-chip devices using patient-derived samples and evaluate their potential for clinical research and personalized medicine applications.

Molecularly profiled trials: toward a framework of actions for the "nil actionables"

The sequencing of tumour or blood samples is increasingly used to stratify patients into clinical trials of molecularly targeted agents, and this approach has frequently demonstrated clinical benefit for those who are deemed eligible. But what of those who have no clear and evident molecular driver? What of those deemed to have "nil actionable" mutations? How might we deliver better therapeutic opportunities for those left behind in the clamour toward stratified therapeutics? And what significant learnings lie hidden in the data we amass but do not interrogate and understand? This Perspective article suggests a holistic approach to the future treatment of such patients, and sets a framework through which significant additional patient benefit might be achieved. In order to deliver upon this framework, it encourages and invites the clinical community to engage more enthusiastically and share learnings with colleagues in the early drug discovery community, in order to deliver a step change in patient care.

Assigning evidence to actionability: An introduction to variant interpretation in precision cancer medicine

Modern concepts in precision cancer medicine are based on increasingly complex genomic analyses and require standardized criteria for the functional evaluation and reporting of detected genomic alterations in order to assess their clinical relevance. In this article, we propose and address the necessary steps in systematic variant evaluation consisting of bioinformatic analysis, functional annotation and clinical interpretation, focusing on the latter two aspects. We discuss the role and clinical application of current variant classification systems and point out their scope and limitations. Finally, we highlight the significance of the molecular tumor board as a platform for clinical decision-making based on genomic analyses.

Feasibility of next-generation sequencing in clinical practice: results of a pilot study in the Department of Precision Medicine at the University of Campania 'Luigi Vanvitelli'

Background

The emerging role of next-generation sequencing (NGS) targeted panels is revolutionising our approach to cancer patients, providing information on gene alterations helpful for diagnosis and clinical decision, in a short time and with acceptable costs.

Materials and methods

In this work, we evaluated the clinical application of FoundationOne CDx test, a hybrid capture-based NGS. This test identifies alterations in 324 genes, tumour mutational burden and genomic signatures as microsatellite instability. The decision to obtain the NGS assay for a particular patient was done according to investigator’s choice.

Results

Overall, 122 tumour specimens were analysed, of which 84 (68.85%) succeeded. The success rate was influenced by type of specimen formalin-fixed paraffin embedded (FFPE block vs FFPE slides), by origin of the sample (surgery vs biopsy) and by time of fixation (<5 years vs ≥5 years). The most frequent subgroups of effective reports derived from colorectal cancer (25 samples), non-small-cell lung cancer (16 samples), ovarian cancer (10 samples), biliary tract cancer (9 samples), breast cancer (7 samples), gastric cancer (7 samples). The most frequent alterations found in whole population referred to TP53 (45.9%), KRAS (19.6%) and APC (13.9%). Furthermore, we performed an analysis of patients in whom this comprehensive genomic profiling (CGP) had a relevance for the patient’s disease.

Conclusions

On our opinion, CGP could be proposed in clinical practice in order to select patients that could most benefit from the analysis proposed, like patients with good performance status without any available treatments or with unexpected resistance to a therapy.

Volumetric growth tracking of patient-derived cancer organoids using optical coherence tomography

Patient-derived cancer organoids (PCOs) are in vitro organotypic models that reflect in vivo drug response, thus PCOs are an accessible model for cancer drug screening in a clinically relevant timeframe. However, current methods to assess the response of PCOs are limited. Here, a custom swept-source optical coherence tomography (OCT) system was used to rapidly evaluate volumetric growth and drug response in PCOs. This system was optimized for an inverted imaging geometry to enable high-throughput imaging of PCOs. An automated image analysis framework was developed to perform 3D single-organoid tracking of PCOs across multiple time points over 48 hours. Metabolic inhibitors and cancer therapies decreased PCOs volumetric growth rate compared to control PCOs. Single-organoid tracking improved sensitivity to drug treatment compared to a pooled analysis of changes in organoid volume. OCT provided a more accurate assessment of organoid volume compared to a volume estimation method based on 2D projections. Single-organoid tracking with OCT also identified heterogeneity in drug response between solid and hollow PCOs. This work demonstrates that OCT and 3D single-organoid tracking are attractive tools to monitor volumetric growth and drug response in PCOs, providing rapid, non-destructive methods to quantify heterogeneity in PCOs.

A computational method for prioritizing targeted therapies in precision oncology: performance analysis in the SHIVA01 trial

Precision oncology is currently based on pairing molecularly targeted agents (MTA) to predefined single driver genes or biomarkers. Each tumor harbors a combination of a large number of potential genetic alterations of multiple driver genes in a complex system that limits the potential of this approach. We have developed an artificial intelligence (AI)-assisted computational method, the digital drug-assignment (DDA) system, to prioritize potential MTAs for each cancer patient based on the complex individual molecular profile of their tumor. We analyzed the clinical benefit of the DDA system on the molecular and clinical outcome data of patients treated in the SHIVA01 precision oncology clinical trial with MTAs matched to individual genetic alterations or biomarkers of their tumor. We found that the DDA score assigned to MTAs was significantly higher in patients experiencing disease control than in patients with progressive disease (1523 versus 580, P = 0.037). The median PFS was also significantly longer in patients receiving MTAs with high (1000+ <) than with low (<0) DDA scores (3.95 versus 1.95 months, P = 0.044). Our results indicate that AI-based systems, like DDA, are promising new tools for oncologists to improve the clinical benefit of precision oncology.

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.

Tumor Tissue- versus Plasma-based Genotyping for Selection of Matched Therapy and Impact on Clinical Outcomes in Patients with Metastatic Breast Cancer

PURPOSE

Actionable mutations can guide genotype-directed matched therapy. We evaluated the utility of tissue-based and plasma-based genotyping for the identification of actionable mutations and selection of matched therapy in patients with metastatic breast cancer (MBC).

EXPERIMENTAL DESIGN

Patients with MBC who underwent tissue genotyping (institutional platform, 91-gene assay) or plasma-based cell-free DNA (cfDNA, Guardant360, 73-gene assay) between January 2016 and December 2017 were included. A chart review of records to identify subtype, demographics, treatment, outcomes, and tissue genotyping or cfDNA results was performed. The incidence of actionable mutations and the selection of matched therapy in tissue genotyping or cfDNA cohorts was determined. The impact of matched therapy status on overall survival (OS) in tissue genotyping or cfDNA subgroups was determined with Cox regression analysis.

RESULTS

Of 252 patients who underwent cfDNA testing, 232 (92%) had detectable mutations, 196 (78%) had actionable mutations, and 86 (34%) received matched therapy. Of 118 patients who underwent tissue genotyping, 90 (76%) had detectable mutations, 59 (50%) had actionable mutations, and 13 (11%) received matched therapy. For cfDNA patients with actionable mutations, matched versus nonmatched therapy was associated with better OS [HR 0.41, 95% confidence interval (CI): 0.23-0.73, P = 0.002], and this remained significant in a multivariable analysis correcting for age, subtype, visceral metastases, and brain metastases (HR = 0.46, 95% CI: 0.26-0.83, P = 0.010).

CONCLUSIONS

Plasma-based genotyping identified high rates of actionable mutations, which was associated with significant application of matched therapy and better OS in patients with MBC.See related commentary by Rugo and Huppert, p. 3275.

Conserved pan-cancer microenvironment subtypes predict response to immunotherapy

The clinical use of molecular targeted therapy is rapidly evolving but has primarily focused on genomic alterations. Transcriptomic analysis offers an opportunity to dissect the complexity of tumors, including the tumor microenvironment (TME), a crucial mediator of cancer progression and therapeutic outcome. TME classification by transcriptomic analysis of >10,000 cancer patients identifies four distinct TME subtypes conserved across 20 different cancers. The TME subtypes correlate with patient response to immunotherapy in multiple cancers, with patients possessing immune-favorable TME subtypes benefiting the most from immunotherapy. Thus, the TME subtypes act as a generalized immunotherapy biomarker across many cancer types due to the inclusion of malignant and microenvironment components. A visual tool integrating transcriptomic and genomic data provides a global tumor portrait, describing the tumor framework, mutational load, immune composition, anti-tumor immunity, and immunosuppressive escape mechanisms. Integrative analyses plus visualization may aid in biomarker discovery and the personalization of therapeutic regimens.

EGFR and PI3K Pathway Activities Might Guide Drug Repurposing in HPV-Negative Head and Neck Cancers

While genetic alterations in Epidermal growth factor receptor (EGFR) and PI3K are common in head and neck squamous cell carcinomas (HNSCC), their impact on oncogenic signaling and cancer drug sensitivities remains elusive. To determine their consequences on the transcriptional network, pathway activities of EGFR, PI3K, and 12 additional oncogenic pathways were inferred in 498 HNSCC samples of The Cancer Genome Atlas using PROGENy. More than half of HPV-negative HNSCC showed a pathway activation in EGFR or PI3K. An amplification in EGFR and a mutation in PI3KCA resulted in a significantly higher activity of the respective pathway (p = 0.017 and p = 0.007). Interestingly, both pathway activations could only be explained by genetic alterations in less than 25% of cases indicating additional molecular events involved in the downstream signaling. Suitable in vitro pathway models could be identified in a published drug screen of 45 HPV-negative HNSCC cell lines. An active EGFR pathway was predictive for the response to the PI3K inhibitor buparlisib (p = 6.36E-03) and an inactive EGFR and PI3K pathway was associated with efficacy of the B-cell lymphoma (BCL) inhibitor navitoclax (p = 9.26E-03). In addition, an inactive PI3K pathway correlated with a response to multiple Histone deacetylase inhibitor (HDAC) inhibitors. These findings require validation in preclinical models and clinical studies.

Macropinocytosis requires Gal-3 in a subset of patient-derived glioblastoma stem cells

Recently, we involved the carbohydrate-binding protein Galectin-3 (Gal-3) as a druggable target for KRAS-mutant-addicted lung and pancreatic cancers. Here, using glioblastoma patient-derived stem cells (GSCs), we identify and characterize a subset of Gal-3high glioblastoma (GBM) tumors mainly within the mesenchymal subtype that are addicted to Gal-3-mediated macropinocytosis. Using both genetic and pharmacologic inhibition of Gal-3, we showed a significant decrease of GSC macropinocytosis activity, cell survival and invasion, in vitro and in vivo. Mechanistically, we demonstrate that Gal-3 binds to RAB10, a member of the RAS superfamily of small GTPases, and β1 integrin, which are both required for macropinocytosis activity and cell survival. Finally, by defining a Gal-3/macropinocytosis molecular signature, we could predict sensitivity to this dependency pathway and provide proof-of-principle for innovative therapeutic strategies to exploit this Achilles' heel for a significant and unique subset of GBM patients.

Comprehensive Genomic and Transcriptomic Analysis for Guiding Therapeutic Decisions in Patients with Rare Cancers

The clinical relevance of comprehensive molecular analysis in rare cancers is not established. We analyzed the molecular profiles and clinical outcomes of 1,310 patients (rare cancers, 75.5%) enrolled in a prospective observational study by the German Cancer Consortium that applies whole-genome/exome and RNA sequencing to inform the care of adults with incurable cancers. Based on 472 single and six composite biomarkers, a cross-institutional molecular tumor board provided evidence-based management recommendations, including diagnostic reevaluation, genetic counseling, and experimental treatment, in 88% of cases. Recommended therapies were administered in 362 of 1,138 patients (31.8%) and resulted in significantly improved overall response and disease control rates (23.9% and 55.3%) compared to previous therapies, translating into a progression-free survival ratio >1.3 in 35.7% of patients. These data demonstrate the benefit of molecular stratification in rare cancers and represent a resource that may promote clinical trial access and drug approvals in this underserved patient population.

Drug Development in Tissue-Agnostic Indications

A better understanding of cancer biology has led to the development of targeted therapies specifically designed to modulate an altered molecular pathway in the cancer cells or their microenvironment. Despite the identification of molecular targets across cancer types, most of targeted therapies were developed per cancer type. In this ancestral paradigm, randomization was the gold-standard approach for market access. Randomization of large patient populations was feasible for drugs developed in common cancer types but more challenging in rare cancer types. The traditional paradigm of drug development in oncology was further challenged by the ever-expanding molecular segmentation of cancer with ever-smaller subgroups of patients who might benefit from specific targeted therapies or immunotherapies and the identification of molecular alterations against which drugs may be effective across cancer types. In this novel drug development paradigm, novel ways of evaluating the efficacy of drugs are highly needed in these small patient populations. One approach is to use each patient as his/her own control by comparing the efficacy of a drug to the efficacy of prior treatments received. This approach allows to overcome patient heterogeneity, especially in a tissue-agnostic drug development paradigm.

Combining immunotherapy with an epidrug in squamous cell carcinomas of different locations: rationale and design of the PEVO basket trial

Squamous cell carcinomas (SCCs) are among the most frequent solid tumors in humans. SCCs, related or not to the human papillomavirus, share common molecular features. Immunotherapies, and specifically immune checkpoint inhibitors, have been shown to improve overall survival in multiple cancer types, including SCCs. However, only a minority of patients experience a durable response with immunotherapy. Epigenetic modulation plays a major role in escaping tumor immunosurveillance and confers resistance to immune checkpoint inhibitors. Preclinical evidence suggests that modulating the epigenome might improve the efficacy of immunotherapy. We herein review the preclinical and the clinical rationale for combining immunotherapy with an epidrug, and detail the design of PEVOsq, a basket clinical trial combining pembrolizumab with vorinostat, a histone deacetylase inhibitor, in patients with SCCs of different locations. Sequential blood and tumor sampling will be collected in order to identify predictive and pharmacodynamics biomarkers of efficacy of the combination. We also present how clinical and biological data will be managed with the aim to enable the development of a prospective integrative platform to allow secure and controlled access to the project data as well as further exploitations.

Genetically modified cell sheets in regenerative medicine and tissue engineering

Genetically modified cell sheet technology is emerging as a promising biomedical tool to deliver therapeutic genes for regenerative medicine and tissue engineering. Virus-based gene transfection and non-viral gene transfection have been used to fabricate genetically modified cell sheets. Preclinical and clinical studies have shown various beneficial effects of genetically modified cell sheets in the regeneration of bone, periodontal tissue, cartilage and nerves, as well as the amelioration of dental implant osseointegration, myocardial infarction, skeletal muscle ischemia and kidney injury. Furthermore, this technology provides a potential treatment option for various hereditary diseases. However, the method has several limitations, such as safety concerns and difficulties in controlling transgene expression. Therefore, recent studies explored efficient and safe gene transfection methods, prolonged and controllable transgene expression and their potential application in personalized and precision medicine. This review summarizes various types of genetically modified cell sheets, preparation procedures, therapeutic applications and possible improvements.

Individualized Molecular Profiling for Allocation to Clinical Trials Singapore Study-An Asian Tertiary Cancer Center Experience

PURPOSE

Precision oncology has transformed the management of advanced cancers through implementation of advanced molecular profiling technologies to identify increasingly defined subsets of patients and match them to appropriate therapy. We report outcomes of a prospective molecular profiling study in a high-volume Asian tertiary cancer center.

PATIENTS AND METHODS

Patients with advanced cancer were enrolled onto a prospective protocol for genomic profiling, the Individualized Molecular Profiling for Allocation to Clinical Trials Singapore study, at the National Cancer Center Singapore. Primary objective was to identify molecular biomarkers in patient's tumors for allocation to clinical trials. The study commenced in February 2012 and is ongoing, with the results of all patients who underwent multiplex next-generation sequencing (NGS) testing until December 2018 presented here. The results were discussed at a molecular tumor board where recommendations for allocation to biomarker-directed trials or targeted therapies were made.

RESULTS

One thousand fifteen patients were enrolled with a median age of 58 years (range 20-83 years). Most common tumor types were lung adenocarcinoma (26%), colorectal cancer (15%), and breast cancer (12%). A total of 1,064 NGS assays were performed, on fresh tumor tissue for 369 (35%) and archival tumor tissue for 687 (65%) assays. TP53 (39%) alterations were most common, followed by EGFR (21%), KRAS (14%), and PIK3CA (10%). Of 405 NGS assays with potentially actionable alterations, 111 (27%) were allocated to a clinical trial after molecular tumor board and 20 (4.9%) were enrolled on a molecularly matched clinical trial. Gene fusions were detected in 23 of 311 (7%) patients tested, including rare fusions in new tumor types and known fusions in rare tumors.

CONCLUSION

Individualized Molecular Profiling for Allocation to Clinical Trials Singapore demonstrates the feasibility of a prospective broad molecular profiling program in an Asian tertiary cancer center, with the ability to develop and adapt to a dynamic landscape of precision oncology.

Prospective high-throughput genome profiling of advanced cancers: results of the PERMED-01 clinical trial

BACKGROUND

The benefit of precision medicine based on relatively limited gene sets and often-archived samples remains unproven. PERMED-01 (NCT02342158) was a prospective monocentric clinical trial assessing, in adults with advanced solid cancer, the feasibility and impact of extensive molecular profiling applied to newly biopsied tumor sample and based on targeted NGS (t-NGS) of the largest gene panel to date and whole-genome array-comparative genomic hybridization (aCGH) with assessment of single-gene alterations and clinically relevant genomic scores.

METHODS

Eligible patients with refractory cancer had one tumor lesion accessible to biopsy. Extracted tumor DNA was profiled by t-NGS and aCGH. We assessed alterations of 802 "candidate cancer" genes and global genomic scores, such as homologous recombination deficiency (HRD) score and tumor mutational burden. The primary endpoint was the number of patients with actionable genetic alterations (AGAs). Secondary endpoints herein reported included a description of patients with AGA who received a "matched therapy" and their clinical outcome, and a comparison of AGA identification with t-NGS and aCGH versus whole-exome sequencing (WES).

RESULTS

Between November 2014 and September 2019, we enrolled 550 patients heavily pretreated. An exploitable complete molecular profile was obtained in 441/550 patients (80%). At least one AGA, defined in real time by our molecular tumor board, was found in 393/550 patients (71%, two-sided 90%CI 68-75%). Only 94/550 patients (17%, 95%CI 14-21) received an "AGA-matched therapy" on progression. The most frequent AGAs leading to "matched therapy" included PIK3CA mutations, KRAS mutations/amplifications, PTEN deletions/mutations, ERBB2 amplifications/mutations, and BRCA1/2 mutations. Such "matched therapy" improved by at least 1.3-fold the progression-free survival on matched therapy (PFS2) compared to PFS on prior therapy (PFS1) in 36% of cases, representing 6% of the enrolled patients. Within patients with AGA treated on progression, the use of "matched therapy" was the sole variable associated with an improved PFS2/PFS1 ratio. Objective responses were observed in 19% of patients treated with "matched therapy," and 6-month overall survival (OS) was 62% (95%CI 52-73). In a subset of 112 metastatic breast cancers, WES did not provide benefit in term of AGA identification when compared with t-NGS/aCGH.

CONCLUSIONS

Extensive molecular profiling of a newly biopsied tumor sample identified AGA in most of cases, leading to delivery of a "matched therapy" in 17% of screened patients, of which 36% derived clinical benefit. WES did not seem to improve these results.

TRIAL REGISTRATION

ID-RCB identifier: 2014-A00966-41; ClinicalTrials.gov identifier: NCT02342158 .

Clinical significance of comprehensive genomic profiling tests covered by public insurance in patients with advanced solid cancers in Hokkaido, Japan

BACKGROUND

Comprehensive cancer genomic profiling has been used recently for patients with advanced solid cancers. Two cancer genomic profiling tests for patients with no standard treatment are covered by Japanese public health insurance since June 2019.

METHODS

We prospectively analyzed data of 189 patients with solid cancers who underwent either of the two-cancer genomic profiling tests at Hokkaido University Hospital and its liaison hospitals and whose results were discussed in molecular tumor board at Hokkaido University Hospital between August 2019 and July 2020.

RESULTS

All 189 patients had appropriate results. Actionable gene alterations were identified in 93 patients (49%). Frequent mutations included PIK3CA (12%) mutation, BRCA1/2 alteration (7%), ERBB2 amplification (6%) and tumor mutation burden-High (4%). The median turnaround time from sample shipping to acquisition by the expert panel was 26 days. Although 115 patients (61%) were provided with information for genotype-matched therapies, only 21 (11%) received them. Notably, four of eight patients below the age of 20 years were provided information for genotype-matched therapies, and three received them. Their response rates and disease control rates were 29% and 67%, respectively. Most patients who did not undergo the genotype-matched therapies were provided information for only investigational drugs in phases I and II at distant clinical trial sites in central Japan. Twenty-six patients were informed of suspected germline findings, while 11 patients (42%) received genetic counseling.

CONCLUSIONS

The publicly reimbursed cancer genomic profilings may lead to the modest but favorable therapeutic efficacy of genotype-matched therapy for solid cancer patients with no standard therapy. However, poor access to genotype-matched therapy needs to be resolved.

Concomitant MEK and Cyclin Gene Alterations: Implications for Response to Targeted Therapeutics

PURPOSE

Cyclin and MAPK/MEK-related gene alterations are implicated in cell-cycle progression and cancer growth. Yet, monotherapy to target the cyclin (CDK4/6) or the MEK pathway has often yielded disappointing results. Because coalterations in cyclin and MEK pathway genes frequently cooccur, we hypothesized that resistance to CDK4/6 or MEK inhibitor monotherapy might be mediated via activation of oncogenic codrivers, and that combination therapy might be useful.

EXPERIMENTAL DESIGN

Herein, we describe 9 patients with advanced malignancies harboring concomitant CDKN2A and/or CDKN2B alterations (upregulate CDK4/6) along with KRAS or BRAF alterations (activate the MEK pathway) who were treated with palbociclib (CDK4/6 inhibitor) and trametinib (MEK inhibitor) combination-based regimens.

RESULTS

Two patients (with pancreatic cancer) achieved a partial remission (PR) and, overall, 5 patients (56%) had clinical benefit (stable disease ≥ 6 months/PR) with progression-free survival of approximately 7, 9, 9, 11, and 17.5+ months. Interestingly, 1 of these patients whose cancer (gastrointestinal stromal tumor) had progressed on MEK targeting regimen, did well for about 1 year after palbociclib was added.

CONCLUSIONS

These observations suggest that cotargeting cyclin and MEK signaling can be successful when tumors bear genomic coalterations that activate both of these pathways. Further prospective studies using this matching precision strategy to overcome resistance are warranted.See related commentary by Groisberg and Subbiah, p. 2672.

Digital Display Precision Predictor: the prototype of a global biomarker model to guide treatments with targeted therapy and predict progression-free survival

The expanding targeted therapy landscape requires combinatorial biomarkers for patient stratification and treatment selection. This requires simultaneous exploration of multiple genes of relevant networks to account for the complexity of mechanisms that govern drug sensitivity and predict clinical outcomes. We present the algorithm, Digital Display Precision Predictor (DDPP), aiming to identify transcriptomic predictors of treatment outcome. For example, 17 and 13 key genes were derived from the literature by their association with MTOR and angiogenesis pathways, respectively, and their expression in tumor versus normal tissues was associated with the progression-free survival (PFS) of patients treated with everolimus or axitinib (respectively) using DDPP. A specific eight-gene set best correlated with PFS in six patients treated with everolimus: AKT2, TSC1, FKB-12, TSC2, RPTOR, RHEB, PIK3CA, and PIK3CB (r = 0.99, p = 5.67E-05). A two-gene set best correlated with PFS in five patients treated with axitinib: KIT and KITLG (r = 0.99, p = 4.68E-04). Leave-one-out experiments demonstrated significant concordance between observed and DDPP-predicted PFS (r = 0.9, p = 0.015) for patients treated with everolimus. Notwithstanding the small cohort and pending further prospective validation, the prototype of DDPP offers the potential to transform patients' treatment selection with a tumor- and treatment-agnostic predictor of outcomes (duration of PFS).

Moving Molecular Profiling to Routine Clinical Practice: A Way Forward?

Molecular profiling of a patient's tumor to guide targeted treatment selection offers the potential to advance patient care by improving outcomes and minimizing toxicity (by avoiding ineffective treatments). However, current development of molecular profile (MP) panels is often based on applying institution-specific or subjective algorithms to nonrandomized patient cohorts. Consequently, obtaining reliable evidence that molecular profiling is offering clinical benefit and is ready for routine clinical practice is challenging. In particular, we discuss here the problems with interpreting for clinical utility nonrandomized studies that compare outcomes in patients treated based on their MP vs those treated with standard of care, studies that compare the progression-free survival (PFS) seen on a MP-directed treatment to the PFS seen for the same patient on a previous standard treatment (PFS ratio), and multibasket trials that evaluate the response rates of targeted therapies in specific molecularly defined subpopulations (regardless of histology). We also consider some limitations of randomized trial designs. A two-step strategy is proposed in which multiple mutation-agent pairs are tested for activity in one or more multibasket trials in the first step. The results of the first step are then used to identify promising mutation-agent pairs that are combined in a molecular panel that is then tested in the step-two strategy-design randomized clinical trial (the molecular panel-guided treatment for the selected mutations vs standard of care). This two-step strategy should allow rigorous evidence-driven identification of mutation-agent pairs that can be moved into routine clinical practice.

Current status of ctDNA in precision oncology for hepatocellular carcinoma

The conventional method used to obtain a tumor biopsy for hepatocellular carcinoma (HCC) is invasive and does not evaluate dynamic cancer progression or assess tumor heterogeneity. It is thus imperative to create a novel non-invasive diagnostic technique for improvement in cancer screening, diagnosis, treatment selection, response assessment, and predicting prognosis for HCC. Circulating tumor DNA (ctDNA) is a non-invasive liquid biopsy method that reveals cancer-specific genetic and epigenetic aberrations. Owing to the development of technology in next-generation sequencing and PCR-based assays, the detection and quantification of ctDNA have greatly improved. In this publication, we provide an overview of current technologies used to detect ctDNA, the ctDNA markers utilized, and recent advances regarding the multiple clinical applications in the field of precision medicine for HCC.

CATCH: A Prospective Precision Oncology Trial in Metastatic Breast Cancer

PURPOSE

CATCH (Comprehensive Assessment of clinical feaTures and biomarkers to identify patients with advanced or metastatic breast Cancer for marker driven trials in Humans) is a prospective precision oncology program that uses genomics and transcriptomics to guide therapeutic decisions in the clinical management of metastatic breast cancer. Herein, we report our single-center experience and results on the basis of the first 200 enrolled patients of an ongoing trial.

METHODS

From June 2017 to March 2019, 200 patients who had either primary metastatic or progressive disease, with any number of previous treatment lines and at least one metastatic site accessible to biopsy, were enrolled. DNA and RNA from tumor tissue and corresponding blood-derived nontumor DNA were profiled using whole-genome and transcriptome sequencing. Identified actionable alterations were brought into clinical context in a multidisciplinary molecular tumor board (MTB) with the aim of prioritizing personalized treatment recommendations.

RESULTS

Among the first 200 enrolled patients, 128 (64%) were discussed in the MTB, of which 64 (50%) were subsequently treated according to MTB recommendation. Of 53 evaluable patients, 21 (40%) achieved either stable disease (n = 13, 25%) or partial response (n = 8, 15%). Furthermore, 16 (30%) of those patients showed improvement in progression-free survival of at least 30% while on MTB-recommended treatment compared with the progression-free survival of the previous treatment line.

CONCLUSION

The initial phase of this study demonstrates that precision oncology on the basis of whole-genome and RNA sequencing is feasible when applied in the clinical management of patients with metastatic breast cancer and provides clinical benefit to a substantial proportion of patients.

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

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

Precision Oncology Beyond Genomics: The Future Is Here-It Is Just Not Evenly Distributed

Cancer is a multifactorial disease with increasing incidence. There are more than 100 different cancer types, defined by location, cell of origin, and genomic alterations that influence oncogenesis and therapeutic response. This heterogeneity between tumors of different patients and also the heterogeneity within the same patient's tumor pose an enormous challenge to cancer treatment. In this review, we explore tumor heterogeneity on the longitudinal and the latitudinal axis, reviewing current and future approaches to study this heterogeneity and their potential to support oncologists in tailoring a patient's treatment regimen. We highlight how the ideal of precision oncology is reaching far beyond the knowledge of genetic variants to inform clinical practice and discuss the technologies and strategies already available to improve our understanding and management of heterogeneity in cancer treatment. We will focus on integrating multi-omics technologies with suitable in vitro models and their proficiency in mimicking endogenous tumor heterogeneity.

Aust D, B. Baretton G. Routine Molecular Pathology Diagnostics in Precision Oncology

BACKGROUND

Technical advances in the field of molecular genetics permit precise genomic characterization of malignant tumors. This has not only improved our understanding of tumor biology but also paved the way for molecularly stratified treatment strategies in routine clinical practice.

METHODS

A selective search of PubMed to identify literature on molecular pathology methods, their indications, the challenges associated with molecular findings, and future developments.

RESULTS

Tumors can be characterized with the aid of immunohistochemistry, in-situ hybridization, and sequencing of DNA or RNA. The benefits of molecularly stratified tumor treatment have been demonstrated by randomized clinical trials on numerous tumor entities, e.g., non-small-cell lung cancer, colorectal cancer, and breast cancer. Therefore, initiation of specific treatment for these entities should be preceded by molecular pathology biomarker analyses, generally carried out on tumor tissue. Randomized controlled trials and non-controlled studies show that enhanced progression-free survival ensues if the pharmacological treatment is oriented on the findings of molecular pathology diagnostics. In next-generation sequencing, numerous relevant gene sequences or even whole genes can be sequenced in parallel, dispensing with complex staged diagnostics and reducing the use of biomaterials. These new methods also complement the currently relevant predictive biomarkers by permitting the investigation of genetic alterations presently of interest in the context of clinical studies. Prior to widespread routine clinical application, however, sequencing of large gene panels or whole genomes or exomes need to be even more stringently validated.

CONCLUSION

Quality-assured molecular pathology assays are universally available for the determination of currently relevant predictive biomarkers. However, the integration of extensive genomic analyses into routine molecular pathology diagnostics represents a future challenge in precision oncology.

Applications of single-cell and bulk RNA sequencing in onco-immunology

The rising interest for precise characterization of the tumour immune contexture has recently brought forward the high potential of RNA sequencing (RNA-seq) in identifying molecular mechanisms engaged in the response to immunotherapy. In this review, we provide an overview of the major principles of single-cell and conventional (bulk) RNA-seq applied to onco-immunology. We describe standard preprocessing and statistical analyses of data obtained from such techniques and highlight some computational challenges relative to the sequencing of individual cells. We notably provide examples of gene expression analyses such as differential expression analysis, dimensionality reduction, clustering and enrichment analysis. Additionally, we used public data sets to exemplify how deconvolution algorithms can identify and quantify multiple immune subpopulations from either bulk or single-cell RNA-seq. We give examples of machine and deep learning models used to predict patient outcomes and treatment effect from high-dimensional data. Finally, we balance the strengths and weaknesses of single-cell and bulk RNA-seq regarding their applications in the clinic.

Synthetic lethality-mediated precision oncology via the tumor transcriptome

Precision oncology has made significant advances, mainly by targeting actionable mutations in cancer driver genes. Aiming to expand treatment opportunities, recent studies have begun to explore the utility of tumor transcriptome to guide patient treatment. Here, we introduce SELECT (synthetic lethality and rescue-mediated precision oncology via the transcriptome), a precision oncology framework harnessing genetic interactions to predict patient response to cancer therapy from the tumor transcriptome. SELECT is tested on a broad collection of 35 published targeted and immunotherapy clinical trials from 10 different cancer types. It is predictive of patients' response in 80% of these clinical trials and in the recent multi-arm WINTHER trial. The predictive signatures and the code are made publicly available for academic use, laying a basis for future prospective clinical studies.

Elucidating transcriptomic profiles from single-cell RNA sequencing data using nature-inspired compressed sensing

Gene-expression profiling can define the cell state and gene-expression pattern of cells at the genetic level in a high-throughput manner. With the development of transcriptome techniques, processing high-dimensional genetic data has become a major challenge in expression profiling. Thanks to the recent widespread use of matrix decomposition methods in bioinformatics, a computational framework based on compressed sensing was adopted to reduce dimensionality. However, compressed sensing requires an optimization strategy to learn the modular dictionaries and activity levels from the low-dimensional random composite measurements to reconstruct the high-dimensional gene-expression data. Considering this, here we introduce and compare four compressed sensing frameworks coming from nature-inspired optimization algorithms (CSCS, ABCCS, BACS and FACS) to improve the quality of the decompression process. Several experiments establish that the three proposed methods outperform benchmark methods on nine different datasets, especially the FACS method. We illustrate therefore, the robustness and convergence of FACS in various aspects; notably, time complexity and parameter analyses highlight properties of our proposed FACS. Furthermore, differential gene-expression analysis, cell-type clustering, gene ontology enrichment and pathology analysis are conducted, which bring novel insights into cell-type identification and characterization mechanisms from different perspectives. All algorithms are written in Python and available at https://github.com/Philyzh8/Nature-inspired-CS.

Identifying potential germline variants from sequencing hematopoietic malignancies

Next-generation sequencing (NGS) of bone marrow and peripheral blood increasingly guides clinical care in hematological malignancies. NGS data may help to identify single nucleotide variants, insertions/deletions, copy number variations, and translocations at a single time point, and repeated NGS testing allows tracking of dynamic changes in variants during the course of a patient's disease. Tumor cells used for NGS may contain germline, somatic, and clonal hematopoietic DNA alterations, and distinguishing the etiology of a variant may be challenging. We describe an approach using patient history, individual variant characteristics, and sequential NGS assays to identify potential germline variants. Our current criteria for identifying an individual likely to have a deleterious germline variant include a strong family history or multiple cancers in a single patient, diagnosis of a hematopoietic malignancy at a younger age than seen in the general population, variant allele frequency > 0.3 of a deleterious allele in a known germline predisposition gene, and variant persistence identified on clinical NGS panels, despite a change in disease state. Sequential molecular testing of hematopoietic specimens may provide insight into disease pathology, impact patient and family members' care, and potentially identify new cancer-predisposing risk alleles. Ideally, individuals should give consent at the time of NGS testing to receive information about potential germline variants and to allow future contact as research advances.

The next horizon in precision oncology: Proteogenomics to inform cancer diagnosis and treatment

When it comes to precision oncology, proteogenomics may provide better prospects to the clinical characterization of tumors, help make a more accurate diagnosis of cancer, and improve treatment for patients with cancer. This perspective describes the significant contributions of The Cancer Genome Atlas and the Clinical Proteomic Tumor Analysis Consortium to precision oncology and makes the case that proteogenomics needs to be fully integrated into clinical trials and patient care in order for precision oncology to deliver the right cancer treatment to the right patient at the right dose and at the right time.

Building patient-specific models for receptor tyrosine kinase signaling networks

Cancer progresses due to changes in the dynamic interactions of multidimensional factors associated with gene mutations. Cancer research has actively adopted computational methods, including data-driven and mathematical model-driven approaches, to identify causative factors and regulatory rules that can explain the complexity and diversity of cancers. A data-driven, statistics-based approach revealed correlations between gene alterations and clinical outcomes in many types of cancers. A model-driven mathematical approach has elucidated the dynamic features of cancer networks and identified the mechanisms of drug efficacy and resistance. More recently, machine learning methods have emerged that can be used for mining omics data and classifying patient. However, as the strengths and weaknesses of each method becoming apparent, new analytical tools are emerging to combine and improve the methodologies and maximize their predictive power for classifying cancer subtypes and prognosis. Here, we introduce recent advances in cancer systems biology aimed at personalized medicine, with focus on the receptor tyrosine kinase signaling network.

BRAF V600E/V600K Mutations versus Nonstandard Alterations: Prognostic Implications and Therapeutic Outcomes

BRAF and MEK inhibitors are standard of care for BRAF V600E/K-mutated melanoma, but the benefit of BRAF and/or MEK inhibitors for nonstandard BRAF alterations for melanoma and other cancers is unclear. Patients with diverse malignancies whose cancers had undergone next-generation sequencing were screened for BRAF alterations. Demographics, treatment with BRAF and/or MEK inhibitors, clinical response, progression-free survival (PFS), and overall survival (OS) were determined from review of the electronic medical records for patients with standard BRAF V600E/K versus nonstandard BRAF alterations. A total of 213 patients with BRAF alterations (87 with nonstandard alterations) were identified; OS from diagnosis was significantly worse with nonstandard BRAF versus standard alterations, regardless of therapy [HR (95% confidence interval), 0.58 (0.38-0.88); P = 0.01]. Overall, 45 patients received BRAF/MEK-directed therapy (eight with nonstandard alterations); there were no significant differences in clinical benefit rate [stable disease ≥6 months/partial/complete response (74% vs. 63%; P = 0.39) or PFS (P = 0.24; BRAF V600E/K vs. others)]. In conclusion, patients with nonstandard versus standard BRAF alterations (BRAF V600E/K) have a worse prognosis with shorter survival from diagnosis. Even so, 63% of patients with nonstandard BRAF alterations achieved clinical benefit with BRAF/MEK inhibitors. Larger prospective studies are warranted to better understand the prognostic versus predictive implication of standard versus nonstandard BRAF alterations.

The Tumor Profiler Study: integrated, multi-omic, functional tumor profiling for clinical decision support

The application and integration of molecular profiling technologies create novel opportunities for personalized medicine. Here, we introduce the Tumor Profiler Study, an observational trial combining a prospective diagnostic approach to assess the relevance of in-depth tumor profiling to support clinical decision-making with an exploratory approach to improve the biological understanding of the disease.

Intrapatient comparisons of efficacy in a single-arm trial of entrectinib in tumour-agnostic indications

Background

Entrectinib is a tropomyosin receptor kinase inhibitor approved for the treatment of neurotrophic tyrosine receptor kinase (NTRK) fusion-positive solid tumours based on single-arm trials. Traditional randomised clinical trials in rare cancers are not feasible; we conducted an intrapatient analysis to evaluate the clinical benefit of entrectinib versus prior standard-of-care systemic therapies.

Methods

Patients with locally advanced/metastatic NTRK fusion-positive tumours enrolled in the global phase II, single-arm STARTRK-2 trial were grouped according to prior systemic therapy and response. The key analysis used growth modulation index [GMI; ratio of progression-free survival (PFS) on entrectinib to time to discontinuation (TTD) on the most recent prior therapy]; ratio ≥1.3 indicated clinically meaningful efficacy. Additional analyses investigated TTD and objective response rate (ORR) for entrectinib and prior therapies.

Results

Seventy-one patients were included; 51 received prior systemic therapy. In 38 patients who progressed on prior therapy, ORR was 60.5% (23/38) with entrectinib and 15.8% (6/38) with the most recent prior therapy. Median PFS [11.2 months; 95% confidence interval (CI) 6.7–not estimable] for entrectinib exceeded median TTD (2.9 months; 95% CI 2.0-4.9) for most recent prior therapy. From the intrapatient analysis of GMI, 65.8% had a ratio ≥1.3 and median GMI was 2.53. Consistent results were observed at more stringent GMI thresholds; 60.5% of patients had GMI ≥1.5 or ≥1.8 and 57.9% had GMI ≥2.0.

Conclusions

ORR was high and PFS was longer on entrectinib versus TTD on prior therapy. Furthermore, 65.8% of patients experienced clinically meaningful benefit based on GMI. This intrapatient analysis demonstrates comparative effectiveness of entrectinib in a rare, heterogeneous adult population.

•

Randomised trials are unfeasible for molecular targeted agents in rare indications because of low patient numbers.

•

Intrapatient comparison with prior therapies can be used to evaluate relative treatment efficacy in rare tumours.

•

Entrectinib is a potent tropomyosin receptor kinase (TRK) inhibitor with proven efficacy in neurotrophic tyrosine receptor kinase (NTRK) fusion-positive tumours from the global STARTRK-2 trial.

•

Median progression-free survival on entrectinib was longer than time to discontinuation on prior therapy (11.2 months versus 2.9 months).

•

About 61% of patients with prior therapy progression responded to entrectinib; 66% had growth modulation index ≥1.3 (clinically meaningful threshold).

Human blood serum can donor-specifically antagonize effects of EGFR-targeted drugs on squamous carcinoma cell growth

Many patients fail to respond to EGFR-targeted therapeutics, and personalized diagnostics is needed to identify putative responders. We investigated 1630 colorectal and lung squamous carcinomas and 1357 normal lung and colon samples and observed huge variation in EGFR pathway activation in both cancerous and healthy tissues, irrespectively on EGFR gene mutation status. We investigated whether human blood serum can affect squamous carcinoma cell growth and EGFR drug response. We demonstrate that human serum antagonizes the effects of EGFR-targeted drugs erlotinib and cetuximab on A431 squamous carcinoma cells by increasing IC50 by about 2- and 20-fold, respectively. The effects on clonogenicity varied significantly across the individual serum samples in every experiment, with up to 100% differences. EGF concentration could explain many effects of blood serum samples, and EGFR ligands-depleted serum showed lesser effect on drug sensitivity.

Assessment of Clinical Benefit of Integrative Genomic Profiling in Advanced Solid Tumors

Question

What is the clinical utility of genomic profiling for patients with advanced solid tumors?

Findings

In this cohort study of 1015 patients who underwent integrative genomic profiling, a high rate of pathogenic germline variants and a subset of patients who derive substantial clinical benefit from sequencing information were identified.

Meaning

These findings support (1) directed germline testing for inherited cancer predisposition in all patients with advanced cancer and (2) use of integrative genomic profiling as a component of standard of care for patients with cancer of unknown origin and other rare malignant neoplasms.

Importance

Use of next-generation sequencing (NGS) to identify clinically actionable genomic targets has been incorporated into routine clinical practice in the management of advanced solid tumors; however, the clinical utility of this testing remains uncertain.

Objective

To determine which patients derived the greatest degree of clinical benefit from NGS profiling.

Design, Setting, and Participants

Patients in this cohort study underwent fresh tumor biopsy and blood sample collection for genomic profiling of paired tumor and normal DNA (whole-exome or targeted-exome capture with analysis of 1700 genes) and tumor transcriptome (RNA) sequencing. Somatic and germline genomic alterations were annotated and classified according to degree of clinical actionability. Results were returned to treating oncologists. Data were collected from May 1, 2011, to February 28, 2018, and analyzed from May 1, 2011, to April 30, 2020.

Main Outcomes and Measures

Patients’ subsequent therapy and treatment response were extracted from the medical record to determine clinical benefit rate from NGS-directed therapy at 6 months and exceptional responses lasting 12 months or longer.

Results

During the study period, NGS was attempted on tumors from 1138 patients and was successful in 1015 (89.2%) (MET1000 cohort) (538 men [53.0%]; mean [SD] age, 57.7 [13.3] years). Potentially clinically actionable genomic alterations were discovered in 817 patients (80.5%). Of these, 132 patients (16.2%) received sequencing-directed therapy, and 49 had clinical benefit (37.1%). Exceptional responses were observed in 26 patients (19.7% of treated patients). Pathogenic germline variants (PGVs) were identified in 160 patients (15.8% of cohort), including 49 PGVs (4.8% of cohort) with therapeutic relevance. For 55 patients with carcinoma of unknown primary origin, NGS identified the primary site in 28 (50.9%), and sequencing-directed therapy in 13 patients resulted in clinical benefit in 7 instances (53.8%), including 5 exceptional responses.

Conclusions and Relevance

The high rate of therapeutically relevant PGVs identified across diverse cancer types supports a recommendation for directed germline testing in all patients with advanced cancer. The high frequency of therapeutically relevant somatic and germline findings in patients with carcinoma of unknown primary origin and other rare cancers supports the use of comprehensive NGS profiling as a component of standard of care for these disease entities.

Molecularly Targeted Clinical Trials

Glioblastoma remains incurable despite advances in surgery, radiation, and chemotherapy, underscoring the need for new therapies. The genetic heterogenicity, presence of redundant molecular pathways, and the blood-brain barrier have limited the applicability of molecularly targeted agents. The therapeutic benefit seen with a small subset of patients suggests, however, that patient selection is critical. Recent investigations show that molecularly targeted synthetic lethality is a promising complementary approach. The article provides an overview of the challenges of molecularly targeted therapy in adults with glioblastoma, including current trials and future therapeutic directions.

Patient Derived Xenografts for Genome-Driven Therapy of Osteosarcoma

Osteosarcoma (OS) is a rare malignant primary tumor of mesenchymal origin affecting bone. It is characterized by a complex genotype, mainly due to the high frequency of chromothripsis, which leads to multiple somatic copy number alterations and structural rearrangements. Any effort to design genome-driven therapies must therefore consider such high inter- and intra-tumor heterogeneity. Therefore, many laboratories and international networks are developing and sharing OS patient-derived xenografts (OS PDX) to broaden the availability of models that reproduce OS complex clinical heterogeneity. OS PDXs, and new cell lines derived from PDXs, faithfully preserve tumor heterogeneity, genetic, and epigenetic features and are thus valuable tools for predicting drug responses. Here, we review recent achievements concerning OS PDXs, summarizing the methods used to obtain ectopic and orthotopic xenografts and to fully characterize these models. The availability of OS PDXs across the many international PDX platforms and their possible use in PDX clinical trials are also described. We recommend the coupling of next-generation sequencing (NGS) data analysis with functional studies in OS PDXs, as well as the setup of OS PDX clinical trials and co-clinical trials, to enhance the predictive power of experimental evidence and to accelerate the clinical translation of effective genome-guided therapies for this aggressive disease.

KRAS-Mutated, Estrogen Receptor-Positive Low-Grade Serous Ovarian Cancer: Unraveling an Exceptional Response Mystery

We report on a woman with aggressive estrogen receptor‐positive, KRAS‐mutated ovarian cancer who achieved a remarkable response to combination therapy with the MEK inhibitor (trametinib) and the aromatase inhibitor (letrozole), even though the disease had failed to respond to a combination of a PI3K inhibitor and different MEK inhibitor, as well as to trametinib and the estrogen modulator, tamoxifen, and to letrozole by itself. The mechanism of action for exceptional response was elucidated by in vitro experiments that demonstrated that the fact that tamoxifen can have an agonistic effect in addition to antagonist activity, whereas letrozole results only in estrogen depletion was crucial to the response achieved when letrozole was combined with an MEK inhibitor. Our current observations indicate that subtle variations in mechanisms of action of outwardly similar regimens may have a major impact on outcome and that such translational knowledge is critical for optimizing a precision medicine strategy.

Key Points

This report describes the remarkable response of a patient with KRAS‐mutated, estrogen receptor‐positive low‐grade serous ovarian cancer treated with trametinib (MEK inhibitor) and letrozole (aromatase inhibitor), despite prior progression on similar agents including tamoxifen (estrogen modulator).

In vitro investigation revealed that tamoxifen can have agonistic in addition to antagonistic effects, which could be the reason for the patient not responding to the combination of trametinib and tamoxifen.

The current observations suggest that drugs with different mechanisms of action targeting the same receptor may have markedly different anticancer activity when used in combinations.

This article reports the case of a patient with aggressive estrogen receptor‐positive, KRAS‐mutated ovarian cancer who achieved a remarkable response to combination therapy with the MEK inhibitor trametinib and the aromatase inhibitor letrozole, despite earlier failures of treatment with other combination inhibitor treatment. This article focuses on the possibility that subtle variations in mechanisms of action of outwardly similar regimens may have major effects on patient outcomes.

Comprehensive genomic landscape and precision therapeutic approach in biliary tract cancers

Biliary tract cancers have dismal prognoses even when cytotoxic chemotherapy is administered. There is an unmet need to develop precision treatment approaches using comprehensive genomic profiling. A total of 121 patients with biliary tract cancers were analyzed for circulating-tumor DNA (ctDNA) and/or tissue-based tumor DNA (tissue-DNA) using clinical-grade next-generation sequencing: 71 patients (59%) had ctDNA; 90 (74%), tissue-DNA; and 40 (33%), both. Efficacy of targeted therapeutic approaches was assessed based upon ctDNA and tissue-DNA. At least one characterized alteration was detected in 76% of patients (54/71) for ctDNA [median, 2 (range, 0-9)] and 100% (90/90) for tissue-DNA [median, 4 (range, 1-9)]. Most common alterations occurred in TP53 (38%), KRAS (28%), and PIK3CA (14%) for ctDNA vs TP53 (44%), CDKN2A/B (33%) and KRAS (29%) for tissue-DNA. In 40 patients who had both ctDNA and tissue-DNA sequencing, overall concordance was higher between ctDNA and metastatic site tissue-DNA than between ctDNA and primary tumor DNA (78% vs 65% for TP53, 100% vs 74% for KRAS and 100% vs 87% for PIK3CA [But not statistical significance]). Among 80 patients who received systemic treatment, the molecularly matched therapeutic regimens based on genomic profiling showed a significantly longer progression-free survival (hazard ratio [95%confidence interval], 0.60 [0.37-0.99]. P = .047 [multivariate]) and higher disease control rate (61% vs 35%, P = .04) than unmatched regimens. Evaluation of ctDNA and tissue-DNA is feasible in biliary tract cancers.

At the dawn of the transcriptomic medicine

Progress in genomic analytical technologies has improved our possibilities to obtain information regarding DNA, RNA, and their dynamic changes that occur over time or in response to specific challenges. This information describes the blueprint for cells, tissues, and organisms and has fundamental importance for all living organisms. This review focuses on the technological challenges to analyze the transcriptome and what is the impact of transcriptomics on precision medicine. The transcriptome is a term that covers all RNA present in cells and a substantial part of it will never be translated into protein but is nevertheless functional in determining cell phenotype. Recent developments in transcriptomics have challenged the fundamentals of the central dogma of biology by providing evidence of pervasive transcription of the genome. Such massive transcriptional activity is challenging the definition of a gene and especially the term "pseudogene" that has now been demonstrated in many examples to be both transcribed and translated. We also review the common sources of biomaterials for transcriptomics and justify the suitability of whole blood RNA as the current optimal analyte for clinical transcriptomics. At the end of the review, a brief overview of the clinical implications of transcriptomics in clinical trial design and clinical diagnosis is given. Finally, we introduce the transcriptome as a target for modern drug development as a tool for extending our capacity for precision medicine in multiple diseases.

From Transcriptomics to Treatment in Inherited Optic Neuropathies

Inherited optic neuropathies, including Leber Hereditary Optic Neuropathy (LHON) and Dominant Optic Atrophy (DOA), are monogenetic diseases with a final common pathway of mitochondrial dysfunction leading to retinal ganglion cell (RGC) death and ultimately loss of vision. They are, therefore, excellent models with which to investigate this ubiquitous disease process-implicated in both common polygenetic ocular diseases (e.g., Glaucoma) and late-onset central nervous system neurodegenerative diseases (e.g., Parkinson disease). In recent years, cellular and animal models of LHON and DOA have matured in parallel with techniques (such as RNA-seq) to determine and analyze the transcriptomes of affected cells. This confluence leaves us at a particularly exciting time with the potential for the identification of novel pathogenic players and therapeutic targets. Here, we present a discussion of the importance of inherited optic neuropathies and how transcriptomic techniques can be exploited in the development of novel mutation-independent, neuroprotective therapies.

Artificial Intelligence for Histology-Based Detection of Microsatellite Instability and Prediction of Response to Immunotherapy in Colorectal Cancer

Microsatellite instability (MSI) is a molecular marker of deficient DNA mismatch repair (dMMR) that is found in approximately 15% of colorectal cancer (CRC) patients. Testing all CRC patients for MSI/dMMR is recommended as screening for Lynch Syndrome and, more recently, to determine eligibility for immune checkpoint inhibitors in advanced disease. However, universal testing for MSI/dMMR has not been uniformly implemented because of cost and resource limitations. Artificial intelligence has been used to predict MSI/dMMR directly from hematoxylin and eosin (H&E) stained tissue slides. We review the emerging data regarding the utility of machine learning for MSI classification, focusing on CRC. We also provide the clinician with an introduction to image analysis with machine learning and convolutional neural networks. Machine learning can predict MSI/dMMR with high accuracy in high quality, curated datasets. Accuracy can be significantly decreased when applied to cohorts with different ethnic and/or clinical characteristics, or different tissue preparation protocols. Research is ongoing to determine the optimal machine learning methods for predicting MSI, which will need to be compared to current clinical practices, including next-generation sequencing. Predicting response to immunotherapy remains an unmet need.

Molecular Profiling-Based Assignment of Cancer Therapy (NCI-MPACT): A Randomized Multicenter Phase II Trial

This trial assessed the utility of applying tumor DNA sequencing to treatment selection for patients with advanced, refractory cancer and somatic mutations in one of four signaling pathways by comparing the efficacy of four study regimens that were either matched to the patient's aberrant pathway (experimental arm) or not matched to that pathway (control arm).

MATERIALS AND METHODS

Adult patients with an actionable mutation of interest were randomly assigned 2:1 to receive either (1) a study regimen identified to target the aberrant pathway found in their tumor (veliparib with temozolomide or adavosertib with carboplatin [DNA repair pathway], everolimus [PI3K pathway], or trametinib [RAS/RAF/MEK pathway]), or (2) one of the same four regimens, but chosen from among those not targeting that pathway.

RESULTS

Among 49 patients treated in the experimental arm, the objective response rate was 2% (95% CI, 0% to 10.9%). One of 20 patients (5%) in the experimental trametinib cohort had a partial response. There were no responses in the other cohorts. Although patients and physicians were blinded to the sequencing and random assignment results, a higher pretreatment dropout rate was observed in the control arm (22%) compared with the experimental arm (6%; P = .038), suggesting that some patients may have had prior tumor mutation profiling performed that led to a lack of participation in the control arm.

CONCLUSION

Further investigation, better annotation of predictive biomarkers, and the development of more effective agents are necessary to inform treatment decisions in an era of precision cancer medicine. Increasing prevalence of tumor mutation profiling and preference for targeted therapy make it difficult to use a randomized phase II design to evaluate targeted therapy efficacy in an advanced disease setting.

Targeting G1/S phase cell-cycle genomic alterations and accompanying co-alterations with individualized CDK4/6 inhibitor-based regimens

BACKGROUNDAlthough CDK4/6 inhibitors are an established treatment for hormone receptor-positive, HER2-negative metastatic breast cancers, their benefit in other malignancies remains limited.METHODSWe investigated factors associated with clinical outcomes from CDK4/6 inhibitor-based therapy among patients with G1/S phase cell-cycle alterations (CDK4/6 amplifications, CCND1/2/3 amplifications, or CDKN2A/B alterations).RESULTSOverall, 2457 patients with diverse solid tumors that underwent clinical-grade, next-generation sequencing (182-465 genes) and therapy outcome of (non-breast cancer) patients treated with matched CDK4/6 inhibitors were analyzed. G1/S phase cell-cycle alterations occurred in 20.6% (507 of 2457) of patients; 99% of those patients (n = 501) harbored ≥1 characterized co-alteration (median, 4; range, 0-24). In 40 patients with G1/S phase cell-cycle alterations given CDK4/6 inhibitors as part of their regimen, significantly longer median progression-free survival (PFS) was observed when CDK4/6 inhibitor-based therapies matched a larger proportion of tumor alterations, often because CDK4/6 inhibitors were administered together with other drugs that were matched to genomic co-alterations, hence achieving a high matching score (high vs. low [≥50% vs. <50%] matching score, PFS, 6.2 vs. 2.0 months, P < 0.001 [n = 40] [multivariate]) and higher rate of stable disease ≥6 months or an objective response (57% vs. 21%, P = 0.048).CONCLUSIONIn summary, in cell-cycle-altered cancers, matched CDK4/6 inhibitors, as part of an individualized regimen targeting a majority of genomic alterations, was independently associated with longer PFS.TRIAL REGISTRATIONClinicalTrials.gov NCT02478931.FUNDINGJoan and Irwin Jacobs Fund, National Cancer Institute (P30 CA023100, R01 CA226803), and the FDA (R01 FD006334).