Influence of companion diagnostics on efficacy and safety of targeted anti-cancer drugs: systematic review and meta-analyses

Novel genomic prognostic biomarkers for dogs with cancer

BACKGROUND

Growing evidence from dogs and humans supports the abundance of mutation-based biomarkers in tumors of dogs. Increasing the use of clinical genomic diagnostic testing now provides another powerful data source for biomarker discovery.

HYPOTHESIS

Analyzed clinical outcomes in dogs with cancer profiled using SearchLight DNA, a cancer gene panel for dogs, to identify mutations with prognostic value.

ANIMALS

A total of 127 cases of cancer in dogs were analyzed using SearchLight DNA and for which clinical outcome information was available.

METHODS

Clinical data points were collected by medical record review. Variables including mutated genes, mutations, signalment, and treatment were fitted using Cox proportional hazard models to identify factors associated with progression-free survival (PFS). The log-rank test was used to compare PFS between patients receiving and not receiving targeted treatment before first progression.

RESULTS

Combined genomic and outcomes analysis identified 336 unique mutations in 89 genes across 26 cancer types. Mutations in 6 genes (CCND1, CCND3, SMARCB1, FANCG, CDKN2A/B, and MSH6) were significantly associated with shorter PFS. Dogs that received targeted treatment before first progression (n = 45) experienced significantly longer PFS compared with those that did not (n = 82, P = .01). This significance held true for 29 dogs that received genomically informed targeted treatment compared with those that did not (P = .05).

CONCLUSION AND CLINICAL IMPORTANCE

We identified novel mutations with prognostic value and demonstrate the benefit of targeted treatment across multiple cancer types. These results provide clinical evidence of the potential for genomics and precision medicine in dogs with cancer.

Association between control group therapy and magnitude of clinical benefit of cancer drugs

Little is known about the impact of control group therapy on clinical benefit scales such as American Society of Clinical Oncology Value Framework (ASCO-VF), European Society for Medical Oncology Magnitude Clinical Benefit Scale (ESMO-MCBS), National Comprehensive Cancer Network (NCCN) Evidence Blocks and ASCO Cancer Research Committee (ASCO-CRC). We searched Drugs@FDA to identify cancer drugs approved between January 2012 and December 2021 based on randomized trials (RCTs). Definition of substantial clinical benefit was based on recommendations for each scale. Associations between characteristics of control group therapy and clinical benefit were explored using logistic regression. RCTs with a control group of active treatment plus placebo were associated with significantly lower odds of substantial benefit with ESMO-MCBS (OR 0.27, P = 0.003) and ASCO-VF (OR 0.30, P = 0.008) but not with NCCN Evidence Blocks or ASCO-CRC. This effect was attenuated and lost statistical significance without adjustment for quality of life (QoL) and/or toxicity (ESMO-MCBS OR 0.50, P = 0.17; ASCO-VF OR 0.49, P = 0.11). Clinical benefit scales can be sensitive to control group therapy. RCTs with substantial overlap between experimental and control therapy showed lower magnitude of clinical benefit using ESMO-MCBS and ASCO-VF scales; possibly due to differences in the weighting of QoL and toxicity between different frameworks.

Changes in Companion Diagnostic Labelling: Implementation of FDA's April 2020 Guidance for Industry for In Vitro CDx Labeling for Specific Oncology Therapeutic Groups

Advanced understanding of the molecular pathways of oncologic diseases has shifted therapeutic treatment development to focus on mechanism of actions targeting specific genomic alterations. These precision medicines are indicated for patient subsets defined by these specific mutations as determined by diagnostic devices approved by the Food and Drug Administration (FDA). The Intended Use section within the companion diagnostic (CDx) labeling has historically specified the therapeutic products for which they have been clinically validated. In April 2020, the FDA reiterated their position that therapeutic class labeling may be used, if appropriate, instead of named products. Labels for FDA approved in vitro CDxs were reviewed to evaluate the implementation of therapeutic class labeling. A total of 47 devices have been approved as of 2 January 2022, of which 3 labels were found to contain therapeutic class labeling: two devices targeting EGFR mutations for the treatment of non-small cell lung cancer (NSCLC), and one targeting BRAF V600E and BRAF/MEK inhibitor combinations for melanoma. Two devices received therapeutic class labeling upon initial approval, while the third implemented the language though a label revision. A total of 25 different indications were identified across the 47 CDx devices, of which 9 (34.6%) were associated with more than 1 CDx device. Implementation of therapeutic class labeling has been slow following the release of the FDA’s April 2020 guidance; however, the potential to incorporate such language into existing and newly approved CDx labels exists. Precedence and manufacturer experience are expected to drive an increase in therapeutic class labeling.

A Systematic Review of Companion Diagnostic Tests by Immunohistochemistry for the Screening of Alectinib-Treated Patients in ALK-Positive Non-Small Cell Lung Cancer

Companion diagnostic tests and targeted therapy changed the management of non-small cell lung cancer by diagnosing genetic modifications and enabling individualized treatment. The purpose of this systematic review is to assess the clinical applicability of companion diagnostic tests (IHC method) by comparing the effects of alectinib and crizotinib in patients with ALK-positive NSCLC. We searched for literature up to March 2022 in PubMed, Web of Science, Cochrane, and Google Scholar. The inclusion criteria were randomized controlled trials comparing the effectiveness of alectinib and crizotinib using an IHC-based companion diagnostic test. The primary outcome was progression-free survival (PFS). The secondary outcomes were objective response rate (ORR), duration of response (DOR), and overall survival (OS). PFS was longer in alectinib (68.4 [61.0, 75.9]) than crizotinib (48.7 [40.4, 56.9]). This indicated that alectinib had a superior efficacy to that of crizotinib (HR range 0.15–0.47). In all secondary outcomes, alectinib was better than crizotinib. Particularly for the ORR, the odds ratio (OR) confirmed that alectinib had a lower risk rate (OR: 2.21, [1.46–3.36], p = 0.0002, I² = 39%). Therefore, the companion diagnostic test (immunohistochemistry) is an effective test to determine whether to administer alectinib to ALK-positive NSCLC patients.

How clinically useful is comprehensive genomic profiling for patients with non-small cell lung cancer? A systematic review

Given the lack of a gold standard, the clinical usefulness of Comprehensive Genomic Profiling (CGP) has not been established. This systematic review aimed to evaluate evidence about the clinical benefit of CGP for patients with Non-small cell lung carcinoma (NSCLC). All controlled studies that evaluated the ability of CGP to detect actionable targets (ATs) reported increases in the number of samples with ATs. The frequency of ATs detected in uncontrolled case series ranged from 0.7 % for RET mutations to 45 % for EGFR mutations. The studies that evaluated therapies targeted to EGFR, ALK, ROS-1, MET, and RET mutations documented significant improvement in clinical outcomes. This review suggests that CGP tests may be clinically helpful for treating patients with NSCLC. Although current evidence is associated with a high risk of bias, the significant impact of NSCLC on individuals and society may justify the routine use of CGP testing for this disease.

Antibody therapies for multiple myeloma

Introduction: Multiple myeloma (MM) is characterized by the uncontrollable proliferation of plasma cells and the excessive production of a specific type of immunoglobulin. Immune system is deregulated in MM and, thus, immunotherapy is a promising therapeutic strategy.Areas covered: The first approach is to use monoclonal antibodies that recognize specific antigens on the surface of myeloma cells, such as CD38 and B-cell maturation antigen. Upon binding to their target, monoclonal antibodies activate the immune cells to destroy the malignant cell. Anti-CD38 molecules as part of highly effective combination regimens have been approved in both newly diagnosed and relapsed/refractory patients and have significantly changed the myeloma treatment landscape in the recent years. Another strategy is to use antibodies that bind both to a molecule on the surface of the myeloma cell and another molecule on the surface of a T-cell (bispecific antibodies). Consecutively, the T-cell comes close to and recognizes the myeloma cell. These have shown promising results in heavily pre-treated patients.Expert opinion: Antibody therapy has significantly enhanced the armamentarium against MM. Further research should focus on tailoring the combination regimens based on disease and patient characteristics in order to optimize the efficacy and safety.

Precision Medicine in Lymphoma by Innovative Instrumental Platforms

In recent years, many efforts have been addressed to the growing field of precision medicine in order to offer individual treatments to every patient on the basis of his/her genetic background. Formerly adopted to achieve new disease classifications as it is still done, innovative platforms, such as microarrays, genome-wide association studies (GWAS), and next generation sequencing (NGS), have made the progress in pharmacogenetics faster and cheaper than previously expected. Several studies in lymphoma patients have demonstrated that these platforms can be used to identify biomarkers predictive of drug efficacy and tolerability, discovering new possible druggable proteins. Indeed, GWAS and NGS allow the investigation of the human genome, finding interesting associations with putative or unexpected targets, which in turns may represent new therapeutic possibilities. Importantly, some objective difficulties have initially hampered the translation of findings in clinical routines, such as the poor quantity/quality of genetic material or the paucity of targets that could be investigated at the same time. At present, some of these technical issues have been partially solved. Furthermore, these analyses are growing in parallel with the development of bioinformatics and its capabilities to manage and analyze big data. Because of pharmacogenetic markers may become important during drug development, regulatory authorities (i.e., EMA, FDA) are preparing ad hoc guidelines and recommendations to include the evaluation of genetic markers in clinical trials. Concerns and difficulties for the adoption of genetic testing in routine are still present, as well as affordability, reliability and the poor confidence of some patients for these tests. However, genetic testing based on predictive markers may offers many advantages to caregivers and patients and their introduction in clinical routine is justified.

Targeted Therapies in Non-small-Cell Lung Cancer

The treatment landscape for non-small-cell lung cancer (NSCLC) has dramatically shifted over the past two decades. Targeted or precision medicine has primarily been responsible for this shift. Older paradigms of treating metastatic NSCLC with cytotoxic chemotherapy, while still important, have given way to evaluating tumor tissues for specific driver mutations that can be treated with targeted agents. Patients treated with targeted agents frequently have improved progression-free survival and overall survival compared to patients without a targetable driver mutation, highlighting the clinical benefit of precision medicine. In this chapter, we explore the historic landmark trials, the current state of the field, and potential future targets under investigation, in this exciting, rapidly evolving discipline of precision medicine in lung cancer.

The lonely driver or the orchestra of mutations? How next generation sequencing datasets contradict the concept of single driver checkpoint mutations in solid tumours - NSCLC as a scholarly example

Driver mutations are considered to be responsible for the majority of cancers and several of those mutations provide targets in order to set up personalized therapies. So far the generally accepted opinion had been that driver mutations occur as stand-alone factors, but novel sequencing technologies induced an essential rethink. Next generation sequencing approaches have shown that double, triple or multiple concurrent mutations could occur within the same tumour and may by interaction influence sensitivity to anticancer drugs and therapy success. This review focusses on this novel concept and discusses the challenges for molecular pathology and laboratory diagnostics while providing putative solutions to overcome the present pitfalls, thereby taking NSCLC as an example.

Safety differentiation: emerging competitive edge in drug development

With increasing expectations to provide evidence of drug efficacy, safety, and cost-effectiveness, best-in-class drugs are a major value driver for the pharmaceutical industry. Superior safety is a key differentiation criterion that could be achieved through better risk:benefit profiles, safety margins, fewer contraindications, and improved patient compliance. To accomplish this, comparative safety assessments using innovative and adaptive nonclinical and clinical outcome-based approaches should be undertaken, and continuous strategic adjustments must be made as the risk:benefit profiles evolve. Key success criteria include scientific expertise and integration between all disciplines during the full extent of the drug development process.

Clinical Development and Initial Approval of Novel Immune Checkpoint Inhibitors in Oncology: Insights From a Global Regulatory Perspective

Immune checkpoint inhibitors (ICI) have demonstrated meaningful patterns of clinical efficacy across various cancers. During their development, novel regulatory strategies and clinical design approaches were explored. This metrics-based narrative review examines submission strategies and clinical evidence expectations of the US, European, and Japanese drug agencies, as well as their impact on approval and overall development times. Also discussed is the role of emerging clinical science and biomarker evaluation to get the first six ICI initially approved.

miR-9-5p in Nephrectomy Specimens is a Potential Predictor of Primary Resistance to First-Line Treatment with Tyrosine Kinase Inhibitors in Patients with Metastatic Renal Cell Carcinoma

Approximately 20–30% of patients with metastatic renal cell carcinoma (mRCC) in first-line treatment with tyrosine kinase inhibitors (TKIs) do not respond due to primary resistance to this drug. At present, suitable robust biomarkers for prediction of a response are not available. Therefore, the aim of this study was to evaluate a panel of microRNAs (miRNAs) in nephrectomy specimens for use as predictive biomarkers for TKI resistance. Archived formalin-fixed, paraffin embedded nephrectomy samples from 60 mRCC patients treated with first-line TKIs (sunitinib, n = 51; pazopanib, n = 6; sorafenib, n = 3) were categorized into responders and non-responders. Using the standard Response Evaluation Criteria in Solid Tumors, patients with progressive disease within 3 months after the start of treatment with TKI were considered as non-responders and those patients with stable disease and complete or partial response under the TKI treatment for at least 6 months as responders. Based on a miRNA microarray expression profile in the two stratified groups of patients, seven differentially expressed miRNAs were validated using droplet digital reverse-transcription quantitative real-time polymerase chain reaction (RT-qPCR) assays in the two groups. Receiver operating characteristic curve analysis and binary logistic regression of response prediction were performed. MiR-9-5p and miR-489-3p were able to discriminate between the two groups. MiR-9-5p, as the most significant miRNA, improved the correct prediction of primary resistance against TKIs in comparison to that of conventional clinicopathological variables. The results of the decision curve analyses, Kaplan-Meier analyses and Cox regression analyses confirmed the potential of miR-9-5p in the prediction of response to TKIs and the prediction of progression-free survival after the initiation of TKI treatment.

86/90Y-Based Theranostics Targeting Angiogenesis in a Murine Breast Cancer Model

Angiogenesis is widely recognized as one of the hallmarks of cancer. Therefore, imaging and therapeutic agents targeted to angiogenic vessels may be widely applicable in many types of cancer. To this end, the theranostic isotope pair, 86Y and 90Y, were used to create a pair of agents for targeted imaging and therapy of neovasculature in murine breast cancer models using a chimeric anti-CD105 antibody, TRC105. Serial positron emission tomography imaging with 86Y-DTPA-TRC105 demonstrated high uptake in 4T1 tumors, peaking at 9.6 ± 0.3%ID/g, verified through ex vivo studies. Additionally, promising results were obtained in therapeutic studies with 90Y-DTPA-TRC105, wherein significantly ( p < 0.05) decreased tumor volumes were observed for the targeted treatment group over all control groups near the end of the study. Dosimetric extrapolation and tissue histological analysis corroborated trends found in vivo. Overall, this study demonstrated the potential of the pair 86/90Y for theranostics, enabling personalized treatments for cancer.

Big Potential from Small Agents: Nanoparticles for Imaging-Based Companion Diagnostics

The importance of medical imaging in the diagnosis and monitoring of cancer cannot be overstated. As personalized cancer treatments are gaining popularity, a need for more advanced imaging techniques has grown significantly. Nanoparticles are uniquely suited to fill this void, not only as imaging contrast agents but also as companion diagnostics. This review provides an overview of many ways nanoparticle imaging agents have contributed to cancer imaging, both preclinically and in the clinic, as well as charting future directions in companion diagnostics. We conclude that, while nanoparticle-based imaging agents are not without considerable scientific and developmental challenges, they enable enhanced imaging in nearly every modality, hold potential as in vivo companion diagnostics, and offer precise cancer treatment and maximize intervention efficacy.

Value-based genomics

Advancements in next-generation sequencing have greatly enhanced the development of biomarker-driven cancer therapies. The affordability and availability of next-generation sequencers have allowed for the commercialization of next-generation sequencing platforms that have found widespread use for clinical-decision making and research purposes. Despite the greater availability of tumor molecular profiling by next-generation sequencing at our doorsteps, the achievement of value-based care, or improving patient outcomes while reducing overall costs or risks, in the era of precision oncology remains a looming challenge. In this review, we highlight available data through a pre-established and conceptualized framework for evaluating value-based medicine to assess the cost (efficiency), clinical benefit (effectiveness), and toxicity (safety) of genomic profiling in cancer care. We also provide perspectives on future directions of next-generation sequencing from targeted panels to whole-exome or whole-genome sequencing and describe potential strategies needed to attain value-based genomics.

PD-L1 immunohistochemistry for non-small cell lung carcinoma: which strategy should be adopted?

INTRODUCTION

PD-L1 detection with immunohistochemistry (IHC) is the only predictive biomarker available to date for PD-L1/PD1 immunotherapy in thoracic oncology. While many studies have been published on this biomarker, they raise a number of questions concerning mainly, (i) the type of antibody for use and its condition of utilization, (ii) the threshold to be used, (iii) the message and information to communicate to the thoracic oncologist and, (iv) the adoption of this methodology as part of the daily practices of a pathology laboratory. Areas covered: This review provides an update on the use of the different PD-L1 antibodies for IHC in the context of metastatic non-small cell lung cancer (NSCLC) and discusses their use as companion or complementary diagnostic tests. The limits of PD-L1 IHC as a predictive test, the precautions to be adopted as well as some perspectives will then be considered. Expert commentary: IHC for PD-L1 can be considered as a theranostic test, which implies providing an extremely reliable result that avoids any false positive and negative results. PD-L1 IHC requires considerable expertise and specific training of pathologists. PD-L1 IHC can be a companion or complementary diagnostic test depending on the clone employed, the molecular therapy prescribed and the indication of use.

Personalized Computational Models as Biomarkers

Biomarkers are cornerstones of clinical medicine, and personalized medicine, in particular, is highly dependent on reliable and highly accurate biomarkers for individualized diagnosis and treatment choice. Modern omics technologies, such as genome sequencing, allow molecular profiling of individual patients with unprecedented resolution, but biomarkers based on these technologies often lack the dynamic element to follow the progression of a disease or response to therapy. Here, we discuss computational models as a new conceptual approach to biomarker discovery and design. Being able to integrate a large amount of information, including dynamic information, computational models can simulate disease evolution and response to therapy with high sensitivity and specificity. By populating these models with personal data, they can be highly individualized and will provide a powerful new tool in the armory of personalized medicine.

A phase I study of the SRC kinase inhibitor dasatinib with trastuzumab and paclitaxel as first line therapy for patients with HER2-overexpressing advanced breast cancer. GEICAM/2010-04 study

The anti-HER2 antibody trastuzumab have shown clinical activity in combination with chemotherapy in different breast cancer settings. However, most of patients treated with this antibody progress after a period of treatment. Activation of the kinase SRC has been linked with resistance to trastuzumab in several preclinical studies. We designed a phase I clinical study to explore the activity of weekly trastuzumab (2 mg/kg) plus paclitaxel (80 mg/m²) in combination with the anti-SRC kinase inhibitor Dasatinib in the first line treatment of HER2 metastatic breast cancer. The primary objective was to determine the maximum tolerated dose (MTD) and recommended phase II dose (RP2D); secondary objectives included efficacy, objective response rate (ORR), pharmacokinetics and pharmacodynamics. A “3+3” design guided dose escalation with two oral dose levels of dasatinib: 100mg (DL1) and 140 mg (DL2). 10 patients were included in the phase I part. Dasatinib 100 mg q.d. was established as the recommended RP2D. The median number of administered cycles was 12 (range, 1 to 18). Grade 3 treatment-related AEs at DL1 were diarrhea (n = 2), hyponatremia (n = 1), fatigue (n = 1), and AST/ALT elevation (n = 1). A significant reduction in p-SRC expression on epidermal keratinocytes on sequential skin biopsies was observed. In conclusion, we describe the feasibility of the combination of dasatinib, trastuzumab and paclitaxel, and its effect on proteins involved in trastuzumab resistance. The phase II part of this study is currently evaluating efficacy.