Targeted therapy in cancer Tsimberidou, Apostolia-Maria
Cancer Chemotherapy and Pharmacology,
12/2015, Letnik:
76, Številka:
6
Journal Article, Book Review
Recenzirano
Odprti dostop
Purpose
To describe the emergence of targeted therapies that have led to significant breakthroughs in cancer therapy and completed or ongoing clinical trials of novel agents for the treatment of ...patients with advanced cancer.
Methods
The literature was systematically reviewed, based on clinical experience and the use of technologies that improved our understanding of carcinogenesis.
Results
Genomics and model systems have enabled the validation of novel therapeutic strategies. Tumor molecular profiling has enabled the reclassification of cancer and elucidated some mechanisms of disease progression or resistance to treatment, the heterogeneity between primary and metastatic tumors, and the dynamic changes of tumor molecular profiling over time. Despite the notable technologic advances, there is a gap between the plethora of preclinical data and the lack of effective therapies, which is attributed to suboptimal drug development for “driver” alterations of human cancer, the high cost of clinical trials and available drugs, and limited access of patients to clinical trials. Bioinformatic analyses of complex data to characterize tumor biology, function, and the dynamic tumor changes in time and space may improve cancer diagnosis. The application of discoveries in cancer biology in clinic holds the promise to improve the clinical outcomes in a large scale of patients with cancer. Increased harmonization between discoveries, policies, and practices will expedite the development of anticancer drugs and will accelerate the implementation of precision medicine.
Conclusions
Combinations of targeted, immunomodulating, antiangiogenic, or chemotherapeutic agents are in clinical development. Innovative adaptive study design is used to expedite effective drug development.
•Genomic studies have revealed that tumors are significantly heterogeneous and complex and therefore optimized therapy does not often result from classical clinical research and practice ...models.•Complete tumor and cell-free DNA profiling, exome sequencing, transcriptomics, proteomics, and exploration of the immune machinery hold the promise of complete characterization of drivers of carcinogenesis.•Precision oncology focuses on gene-directed, histology-agnostic treatments, which are individualized for each patient on the basis of biomarker analysis, and immunotherapy, including adoptive cell therapy.•Innovative trial designs, including “N of 1” models, will enable optimization of treatment for individual patients and to expedite drug discovery and approval.
In recent years, biotechnological breakthroughs have led to identification of complex and unique biologic features associated with carcinogenesis. Tumor and cell-free DNA profiling, immune markers, and proteomic and RNA analyses are used to identify these characteristics for optimization of anticancer therapy in individual patients. Consequently, clinical trials have evolved, shifting from tumor type-centered to gene-directed, histology-agnostic, with innovative adaptive design tailored to biomarker profiling with the goal to improve treatment outcomes. A plethora of precision medicine trials have been conducted. The majority of these trials demonstrated that matched therapy is associated with superior outcomes compared to non-matched therapy across tumor types and in specific cancers. To improve the implementation of precision medicine, this approach should be used early in the course of the disease, and patients should have complete tumor profiling and access to effective matched therapy. To overcome the complexity of tumor biology, clinical trials with combinations of gene-targeted therapy with immune-targeted approaches (e.g., checkpoint blockade, personalized vaccines and/or chimeric antigen receptor T-cells), hormonal therapy, chemotherapy and/or novel agents should be considered. These studies should target dynamic changes in tumor biologic abnormalities, eliminating minimal residual disease, and eradicating significant subclones that confer resistance to treatment. Mining and expansion of real-world data, facilitated by the use of advanced computer data processing capabilities, may contribute to validation of information to predict new applications for medicines. In this review, we summarize the clinical trials and discuss challenges and opportunities to accelerate the implementation of precision oncology.
Recent rapid biotechnological breakthroughs have led to the identification of complex and unique molecular features that drive malignancies. Precision medicine has exploited next-generation ...sequencing and matched targeted therapy/immunotherapy deployment to successfully transform the outlook for several fatal cancers. Tumor and liquid biopsy genomic profiling and transcriptomic, immunomic, and proteomic interrogation can now all be leveraged to optimize therapy. Multiple new trial designs, including basket and umbrella trials, master platform trials, and N-of-1 patient-centric studies, are beginning to supplant standard phase I, II, and III protocols, allowing for accelerated drug evaluation and approval and molecular-based individualized treatment. Furthermore, real-world data, as well as exploitation of digital apps and structured observational registries, and the utilization of machine learning and/or artificial intelligence, may further accelerate knowledge acquisition. Overall, clinical trials have evolved, shifting from tumor type-centered to gene-directed and histology-agnostic trials, with innovative adaptive designs and personalized combination treatment strategies tailored to individual biomarker profiles. Some, but not all, novel trials now demonstrate that matched therapy correlates with superior outcomes compared to non-matched therapy across tumor types and in specific cancers. To further improve the precision medicine paradigm, the strategy of matching drugs to patients based on molecular features should be implemented earlier in the disease course, and cancers should have comprehensive multi-omic (genomics, transcriptomics, proteomics, immunomic) tumor profiling. To overcome cancer complexity, moving from drug-centric to patient-centric individualized combination therapy is critical. This review focuses on the design, advantages, limitations, and challenges of a spectrum of clinical trial designs in the era of precision oncology. Keywords: Clinical trials, Precision oncology, Personalized medicine, Real-world data
Transcriptomics, which encompasses assessments of alternative splicing and alternative polyadenylation, identification of fusion transcripts, explorations of noncoding RNAs, transcript annotation, ...and discovery of novel transcripts, is a valuable tool for understanding cancer mechanisms and identifying biomarkers. Recent advances in high-throughput technologies have enabled large-scale gene expression profiling. Importantly, RNA expression profiling of tumor tissue has been successfully used to determine clinically actionable molecular alterations. The WINTHER precision medicine clinical trial was the first prospective trial in diverse solid malignancies that assessed both genomics and transcriptomics to match treatments to specific molecular alterations. The use of transcriptome analysis in WINTHER and other trials increased the number of targetable -omic changes compared to genomic profiling alone. Other applications of transcriptomics involve the evaluation of tumor and circulating noncoding RNAs as predictive and prognostic biomarkers, the improvement of risk stratification by the use of prognostic and predictive multigene assays, the identification of fusion transcripts that drive tumors, and an improved understanding of the impact of DNA changes as some genomic alterations are silenced at the RNA level. Finally, RNA sequencing and gene expression analysis have been incorporated into clinical trials to identify markers predicting response to immunotherapy. Many issues regarding the complexity of the analysis, its reproducibility and variability, and the interpretation of the results still need to be addressed. The integration of transcriptomics with genomics, proteomics, epigenetics, and tumor immune profiling will improve biomarker discovery and our understanding of disease mechanisms and, thereby, accelerate the implementation of precision oncology.
The development of checkpoint blockade immunotherapy has transformed the medical oncology armamentarium. But despite its favorable impact on clinical outcomes, immunotherapy benefits only a subset of ...patients, and a substantial proportion of these individuals eventually manifest resistance. Serious immune-related adverse events and hyperprogression have also been reported. It is therefore essential to understand the molecular mechanisms and identify the drivers of therapeutic response and resistance. In this review, we provide an overview of the current and emerging clinically relevant genomic biomarkers implicated in checkpoint blockade outcome. US Food and Drug Administration-approved molecular biomarkers of immunotherapy response include mismatch repair deficiency and/or microsatelliteinstability and tumor mutational burden of at least 10 mutations/megabase. Investigational genomic-associated biomarkers for immunotherapy response include alterations of the following genes/associated pathways: chromatin remodeling (ARID1A, PBRM1, SMARCA4, SMARCB1, BAP1), major histocompatibility complex, specific (eg, ultraviolet, APOBEC) mutational signatures, T-cell receptor repertoire, PDL1, POLE/POLD1, and neo-antigens produced by the mutanome, those potentially associated with resistance include β2-microglobulin, EGFR, Keap1, JAK1/JAK2/interferon-gamma signaling, MDM2, PTEN, STK11, and Wnt/Beta-catenin pathway alterations. Prospective clinical trials are needed to assess the role of a composite of these biomarkers to optimize the implementation of precision immunotherapy in patient care.
Little prospective data are available on clinical outcomes and immune correlates from combination radiation and immunotherapy. We conducted a phase I trial (NCT02239900) testing stereotactic ablative ...radiotherapy (SABR) with ipilimumab.
SABR was given either concurrently (1 day after the first dose) or sequentially (1 week after the second dose) with ipilimumab (3 mg/kg every 3 weeks for 4 doses) to five treatment groups: concurrent 50 Gy (in 4 fractions) to liver; sequential 50 Gy (in 4 fractions) to liver; concurrent 50 Gy (in 4 fractions) to lung; sequential 50 Gy (in 4 fractions) to lung; and sequential 60 Gy (in 10 fractions) to lung or liver. MTD was determined with a 3 + 3 dose de-escalation design. Immune marker expression was assessed by flow cytometry.
Among 35 patients who initiated ipilimumab, 2 experienced dose-limiting toxicity and 12 (34%) grade 3 toxicity. Response outside the radiation field was assessable in 31 patients. Three patients (10%) exhibited partial response and 7 (23%) experienced clinical benefit (defined as partial response or stable disease lasting ≥6 months). Clinical benefit was associated with increases in peripheral CD8
T cells, CD8
/CD4
T-cell ratio, and proportion of CD8
T cells expressing 4-1BB and PD1. Liver (vs. lung) irradiation produced greater T-cell activation, reflected as increases in the proportions of peripheral T cells expressing ICOS, GITR, and 4-1BB.
Combining SABR and ipilimumab was safe with signs of efficacy, peripheral T-cell markers may predict clinical benefit, and systemic immune activation was greater after liver irradiation.
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...many patients had hormone receptor abnormalities; response to hormone monotherapy in pretreated patients with advanced disease is unlikely.3 Fourth, some matches were incorrect: imatinib, an ...ineffective RET inhibitor (IC50 37 μmol/L) was matched to RET alterations.4 Fifth, precision medicine is defined by the presence of biological data showing that a targeted drug affects a molecular alteration and needs to be taken in the context of clinical experience--an unmet criterion for many matches in SHIVA.
Widespread clinical laboratory implementation of next-generation sequencing-based cancer testing has highlighted the importance and potential benefits of standardizing the interpretation and ...reporting of molecular results among laboratories. A multidisciplinary working group tasked to assess the current status of next-generation sequencing-based cancer testing and establish standardized consensus classification, annotation, interpretation, and reporting conventions for somatic sequence variants was convened by the Association for Molecular Pathology with liaison representation from the American College of Medical Genetics and Genomics, American Society of Clinical Oncology, and College of American Pathologists. On the basis of the results of professional surveys, literature review, and the Working Group's subject matter expert consensus, a four-tiered system to categorize somatic sequence variations based on their clinical significances is proposed: tier I, variants with strong clinical significance; tier II, variants with potential clinical significance; tier III, variants of unknown clinical significance; and tier IV, variants deemed benign or likely benign. Cancer genomics is a rapidly evolving field; therefore, the clinical significance of any variant in therapy, diagnosis, or prognosis should be reevaluated on an ongoing basis. Reporting of genomic variants should follow standard nomenclature, with testing method and limitations clearly described. Clinical recommendations should be concise and correlate with histological and clinical findings.
Many immuno-oncology (IO) trials are conducted without biomarker selection. We performed a meta-analysis of phase I/II clinical trials evaluating immune checkpoint inhibitors (ICIs) to determine the ...association between biomarkers and clinical outcomes, if any.
A PubMed search for phase I/II clinical trials with drugs approved by the Food and Drug Administration (labelled, off-label, combined with investigational ICIs or other treatment modalities) from 2018 to 2020 was performed. The objective response rate (ORR), progression-free survival (PFS) and overall survival (OS) were compared between biomarker-positive and biomarker-negative groups, using studies that explored the correlation of biomarkers with outcomes.
Overall, 174 clinical studies that included 19,178 patients were identified, and 132 studies investigated>30 correlative biomarkers that included PD-L1 expression (≥1%, 111 studies), tumour mutational burden (20 studies) and microsatellite instability/mismatch repair deficiency (10 studies). Overall, 123, 46 and 30 cohorts (drugs, tumour types or biomarkers) with 11,692, 3065, and 2256 patient outcomes for ORR, PFS and OS, respectively, were analysed in correlation with biomarkers. Meta-analyses demonstrated that ICIs in patients with biomarker-positive tumours were associated with higher ORR (odds ratio 2.15 95% CI, 1.79–2.58, p < 0.0001); and longer PFS (hazard ratio HR 0.55 95% CI, 0.45–0.67, p < 0.0001), and OS (HR 0.65 95% CI, 0.53–0.80, p < 0.0001) compared with those with biomarker-negative tumours. Significance for ORR and PFS was retained in multivariate analysis (p < 0.001) (OS, not included owing to the small number of trials reporting OS).
Our data suggest that IO biomarkers should be used in patient selection for ICIs. Prospective studies are warranted.
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•Many phase I-II immuno-oncology trials are conducted without biomarker selection•The association of biomarkers with outcomes with ICI use was evaluated in a meta-analysis•Overall, 174 studies with 19,178 patients evaluating> 30 biomarkers were included•Biomarker positivity was correlated with higher rates of response, PFS and OS•Immunotherapy biomarkers should be used in patient selection for ICI therapy
We initiated a personalized medicine program in the context of early clinical trials, using targeted agents matched with tumor molecular aberrations. Herein, we report our observations.
Patients with ...advanced cancer were treated in the Clinical Center for Targeted Therapy. Molecular analysis was conducted in the MD Anderson Clinical Laboratory Improvement Amendments (CLIA)-certified laboratory. Patients whose tumors had an aberration were treated with matched targeted therapy, when available. Treatment assignment was not randomized. The clinical outcomes of patients with molecular aberrations treated with matched targeted therapy were compared with those of consecutive patients who were not treated with matched targeted therapy.
Of 1,144 patients analyzed, 460 (40.2%) had 1 or more aberration. In patients with 1 molecular aberration, matched therapy (n = 175) compared with treatment without matching (n = 116) was associated with a higher overall response rate (27% vs. 5%; P < 0.0001), longer time-to-treatment failure (TTF; median, 5.2 vs. 2.2 months; P < 0.0001), and longer survival (median, 13.4 vs. 9.0 months; P = 0.017). Matched targeted therapy was associated with longer TTF compared with their prior systemic therapy in patients with 1 mutation (5.2 vs. 3.1 months, respectively; P < 0.0001). In multivariate analysis in patients with 1 molecular aberration, matched therapy was an independent factor predicting response (P = 0.001) and TTF (P = 0.0001).
Keeping in mind that the study was not randomized and patients had diverse tumor types and a median of 5 prior therapies, our results suggest that identifying specific molecular abnormalities and choosing therapy based on these abnormalities is relevant in phase I clinical trials.
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