The Evolution of Oncology Companion Diagnostics from Signal Transduction to Immuno-Oncology

PTEN-mediated resistance in cancer: From foundation to future therapies

In cancer resistance, phosphatase and tensin homolog deleted (PTEN) has emerged as a prominent protagonist. PTEN exerts its influence by regulating crucial signaling pathways that govern cell proliferation, survival, and differentiation. This comprehensive review article investigates deeply into the complex realm of PTEN-mediated drug resistance mechanisms in cancers. Our journey begins by exploring PTEN's foundational role of PTEN, unveiling its significance as a molecular conductor that intricately coordinates vital cellular pathways. We thoroughly dissected the intricate milieu of PTEN alterations, including mutations, deletions, and epigenetic silencing, and elucidated their profound implications for fueling cancer growth and evading treatment. As we navigate the complex network of PTEN, we unravel the intricate interplay between PTEN and pivotal signaling pathways, such as PI3K/AKT, MAPK/ERK, and Wnt/β-catenin, further complicating the resistance landscape. This expedition, through these intricately intertwined signaling cascades, provides insight into the multifaceted mechanisms driving resistance, thereby revealing potential exploitable weaknesses. In our quest for therapeutic strategies, we need to explore innovative approaches to restore PTEN function, encompassing genetic therapies, pharmacological agents, and precision medicines tailored to PTEN status. The concept of combination therapy has emerged as a potent tool to overcome PTEN-associated resistance, offering promising synergistic interactions with standard treatments, targeted therapies, or immunotherapy. This review offers a comprehensive overview of PTEN-mediated drug resistance mechanisms in cancer and elucidates intricate interactions within this complex landscape. This underscores the central role of PTEN in drug resistance and provides valuable insights into promising strategies with the potential to reshape the future of cancer treatment.

Cellular and molecular aspects of drug resistance in cancers

OBJECTIVES

Cancer drug resistance is a multifaceted phenomenon. The present review article aims to comprehensively analyze the cellular and molecular aspects of drug resistance in cancer and the strategies employed to overcome it.

EVIDENCE ACQUISITION

A systematic search of relevant literature was conducted using electronic databases such as PubMed, Scopus, and Web of Science using appropriate key words. Original research articles and secondary literature were taken into consideration in reviewing the development in the field.

RESULTS AND CONCLUSIONS

Cancer drug resistance is a pervasive challenge that causes many treatments to fail therapeutically. Despite notable advances in cancer treatment, resistance to traditional chemotherapeutic agents and novel targeted medications remains a formidable hurdle in cancer therapy leading to cancer relapse and mortality. Indeed, a majority of patients with metastatic cancer experience are compromised on treatment efficacy because of drug resistance. The multifaceted nature of drug resistance encompasses various factors, such as tumor heterogeneity, growth kinetics, immune system, microenvironment, physical barriers, and the emergence of undruggable cancer drivers. Additionally, alterations in drug influx/efflux transporters, DNA repair mechanisms, and apoptotic pathways further contribute to resistance, which may manifest as either innate or acquired traits, occurring prior to or following therapeutic intervention. Several strategies such as combination therapy, targeted therapy, development of P-gp inhibitors, PROTACs and epigenetic modulators are developed to overcome cancer drug resistance. The management of drug resistance is compounded by the patient and tumor heterogeneity coupled with cancer's ability to evade treatment. Gaining further insight into the mechanisms underlying medication resistance is imperative for the development of effective therapeutic interventions and improved patient outcomes.

Emerging biomedical imaging-based companion diagnostics for precision medicine

The tumor heterogeneity, which leads to individual variations in tumor microenvironments, causes poor prognoses and limits therapeutic response. Emerging technology such as companion diagnostics (CDx) detects biomarkers and monitors therapeutic responses, allowing identification of patients who would benefit most from treatment. However, currently, most US Food and Drug Administration-approved CDx tests are designed to detect biomarkers in vitro and ex vivo, making it difficult to dynamically report variations of targets in vivo. Various medical imaging techniques offer dynamic measurement of tumor heterogeneity and treatment response, complementing CDx tests. Imaging-based companion diagnostics allow for patient stratification for targeted medicines and identification of patient populations benefiting from alternative therapeutic methods. This review summarizes recent developments in molecular imaging for predicting and assessing responses to cancer therapies, as well as the various biomarkers used in imaging-based CDx tests. We hope this review provides informative insights into imaging-based companion diagnostics and advances precision medicine.

High-Resolution Epitope Mapping and Affinity Binding Analysis Comparing a New Anti-Human LAG3 Rabbit Antibody Clone to the Commonly Used Mouse 17B4 Clone

Lymphocyte activation gene 3 (LAG3) is a T cell inhibitory receptor that promotes tumor cell immune escape and is a potential target for cancer diagnostic and immunotherapeutic applications. We used automated capillary electrophoresis (ACE), surface plasmon resonance (SPR), and immunohistochemistry (IHC) to compare the binding characteristics of a new anti-LAG3 rabbit antibody clone, SP464, with the thirty-year old and extensively used anti-LAG3 mouse 17B4 clone. The rabbit SP464 clone exhibited between 20× to 30× greater binding to LAG3 than did the mouse 17B4 clone. Using these tools, we precisely mapped the relative locations of the epitopes of these two antibodies. The SP464 and 17B4 minimal epitopes were localized to separate, but overlapping, sub-fragments within the amino-terminal fifteen acids of the original thirty-mer peptide immunogen used to generate both antibodies. Application of this approach for quantifying the effects of alanine substitutions along the minimal SP464 epitope identified two amino acids essential for binding and four amino acids that likely contribute towards binding. Together, ACE, SPR, and IHC constitute a powerful orthologous approach for comparing antibody-binding characteristics and for fine mapping of linear epitopes within short immunogens. Our results indicate that the rabbit clone SP464 may be useful for assessing LAG3 expression.

Targeted Immunoimaging of Tumor-Associated Macrophages in Orthotopic Glioblastoma by the NIR-IIb Nanoprobes

Developing dynamic and highly sensitive methods for imaging M2-type tumor-associated macrophages (TAMs) is vital for monitoring the tumor progression and assessing the therapeutic efficacy. Here, the fabrication and application of rationally designed Er-based rare-earth nanoprobes for the targeted imaging of M2-type TAMs in glioblastoma (GBM) through the second near-infrared (NIR-II) fluorescence beyond 1500 nm is reported. The NIR-IIb fluorescence of Er-based rare-earth nanoparticles can be remarkably enhanced by optimizing their core-shell structures and the shell thickness, which allows for in vivo imaging under excitation by a 980 nm laser with the lowest power density (40 mW cm^-2 ). These bright Er-based nanoparticles functionalized with M2pep polypeptide show notable targeting ability to M2-type macrophages, which has been well tested in both in vitro and in vivo experiments by their up-conversion (UC) fluorescence (540 nm) and down-shifting (DS) fluorescence (1525 nm), respectively. The targeting capability of these nanoprobes in vivo is also demonstrated by the overlap of immunofluorescence of M2-type TAMs and Arsenazo III staining of rare-earth ions in tumor tissue. It is envisioned that these nanoprobes can serve as a companion diagnostic tool to dynamically assess the progression and prognosis of GBM.

Making Biomarkers Relevant to Healthcare Innovation and Precision Medicine

Translational medicine, the exchange between laboratory (bench) and the clinic (bedside), is decidedly taking on a vital role. Many companies are now focusing on a translational medicinal approach as a therapeutic strategy in decision making upon realizing the expenses of drug attrition in late-stage advancement. In addition, the utility of biomarkers in clinical decision and therapy guidance seeks to improve the patient outcomes and decrease wasteful and harmful treatment. Efficient biomarkers are crucial for the advancement of diagnoses, better molecular targeted therapy, along with therapeutic advantages in a broad spectrum of various diseases. Despite recent advances in the discovery of biomarkers, the advancement route to a clinically validated biomarker remains intensely challenging, and many of the candidate biomarkers do not progress to clinical applications, thereby widening the innovation gap between research and application. The present article will focus on the clinical view of biomarkers in a reverse design, addressing how a biomarker program should appear if it is expected to create an impact on personalized medicine and patient care.

Enzyme-Engineered Conjugated Polymer Nanoplatform for Activatable Companion Diagnostics and Multistage Augmented Synergistic Therapy

Companion diagnostics (CDx) provides critical information for precision medicine. However, current CDx is mostly limited to in vitro tests, which cannot accurately evaluate the disease progression and treatment response in real time. To overcome this challenge, herein a glucose oxidase (GOx)-engineered conjugated polymer (polyaniline, PANI) nanoplatform (denoted as PANITG) is reported for activatable imaging-based CDx and multistage augmented photothermal/starvation synergistic therapy. PANITG comprises a pH-activatable conjugated polymer as a photothermal convertor and photoacoustic (PA) emitter, a GOx as a cancer starvation inducer as well as a H₂ O₂ and acid producer, and a H₂ O₂ -cleavable linker as a "switch" for GOx activity. The in vivo PA imaging and photothermal therapy abilities are activated by acidic tumor microenvironment and self-augmented by the reaction between GOx and glucose. Meanwhile, the photothermal effect will enhance the GOx activity in turn. Such multistage augmentation of the therapeutic effects will facilitate effective cancer management. In addition, the in vivo PA imaging with PANITG reveals the tumor pH level which is correlated to the efficiency of the photothermal therapy and to the catalytic activity of GOx at each stage, enabling real-time activatable CDx.

Photoacoustic imaging of elevated glutathione in models of lung cancer for companion diagnostic applications

Companion diagnostics (CDx) are powerful tests that can provide physicians with crucial biomarker information that can improve treatment outcomes by matching therapies to patients. Here, we report a photoacoustic imaging-based CDx (PACDx) for the selective detection of elevated glutathione (GSH) in a lung cancer model. GSH is abundant in most cells, so we adopted a physical organic chemistry approach to precisely tune the reactivity to distinguish between normal and pathological states. To evaluate the efficacy of PACDx in vivo, we designed a blind study where photoacoustic imaging was used to identify mice bearing lung xenografts. We also employed PACDx in orthotopic lung cancer and liver metastasis models to image GSH. In addition, we designed a matching prodrug, PARx, that uses the same SNAr chemistry to release a chemotherapeutic with an integrated PA readout. Studies demonstrate that PARx can inhibit tumour growth without off-target toxicity in a lung cancer xenograft model.

Benefits of functional assays in personalized cancer medicine: more than just a proof-of-concept

As complex and heterogeneous diseases, cancers require a more tailored therapeutic management than most pathologies. Recent advances in anticancer drug development, including the immuno-oncology revolution, have been too often plagued by unsatisfying patient response rates and survivals. In reaction to this, cancer care has fully transitioned to the “personalized medicine” concept. Numerous tools are now available tools to better adapt treatments to the profile of each patient. They encompass a large array of diagnostic assays, based on biomarkers relevant to targetable molecular pathways. As a subfamily of such so-called companion diagnostics, chemosensitivity and resistance assays represent an attractive, yet insufficiently understood, approach to individualize treatments. They rely on the assessment of a composite biomarker, the ex vivo functional response of cancer cells to drugs, to predict a patient's outcome. Systemic treatments, such as chemotherapies, as well as targeted treatments, whose efficacy cannot be fully predicted yet by other diagnostic tests, may be assessed through these means. The results can provide helpful information to assist clinicians in their decision-making process. We explore here the most advanced functional assays across oncology indications, with an emphasis on tests already displaying a convincing clinical demonstration. We then recapitulate the main technical obstacles faced by researchers and clinicians to produce more accurate, and thus more predictive, models and the recent advances that have been developed to circumvent them. Finally, we summarize the regulatory and quality frameworks surrounding functional assays to ensure their safe and performant clinical implementation. Functional assays are valuable in vitro diagnostic tools that already stand beyond the “proof-of-concept” stage. Clinical studies show they have a major role to play by themselves but also in conjunction with molecular diagnostics. They now need a final lift to fully integrate the common armament used against cancers, and thus make their way into the clinical routine.

Analytical Challenges in Development of Chemoresistance Predictors for Precision Oncology

Chemoresistance, i.e., tumor insensitivity to chemotherapy, shortens life expectancy of cancer patients. Despite the availability of new treatment options, initial systemic regimens for solid tumors are dominated by a set of standard chemotherapy drugs, and alternative therapies are used only when a patient has demonstrated chemoresistance clinically. Chemoresistance predictors use laboratory parameters measured on tissue samples to predict the patient's response to chemotherapy and help to avoid application of chemotherapy to chemoresistant patients. Despite thousands of publications on putative chemoresistance predictors, there are only about a dozen predictors that are sufficiently accurate for precision oncology. One of the major reasons for inaccuracy of predictors is inaccuracy of analytical methods utilized to measure their laboratory parameters: an inaccurate method leads to an inaccurate predictor. The goal of this study was to identify analytical challenges in chemoresistance-predictor development and suggest ways to overcome them. Here we describe principles of chemoresistance predictor development via correlating a clinical parameter, which manifests disease state, with a laboratory parameter. We further classify predictors based on the nature of laboratory parameters and analyze advantages and limitations of different predictors using the reliability of analytical methods utilized for measuring laboratory parameters as a criterion. Our eventual focus is on predictors with known mechanisms of reactions involved in drug resistance (drug extrusion, drug degradation, and DNA damage repair) and using rate constants of these reactions to establish accurate and robust laboratory parameters. Many aspects and conclusions of our analysis are applicable to all types of disease biomarkers built upon the correlation of clinical and laboratory parameters.

Immune disorder in endometrial cancer: Immunosuppressive microenvironment, mechanisms of immune evasion and immunotherapy

Immunotherapy is an emerging clinical approach that has gained traction over the past decade as a novel treatment option for lung cancer and melanoma. Notably, researchers have made marked improvements in the treatment of endometrial cancer (EC), and potential immune responses have been identified in patients with EC, thereby offering the possibility of exploring immunotherapy for EC. Nevertheless, various needs remain unmet, and immunotherapy applications in EC have yielded limited success, as only a minority of patients exhibited a clinical response. Therefore, further understanding of immune dysfunction associated with EC is still required. The present review describes recent findings regarding the immunosuppressive microenvironment of EC, with emphasis on immune evasion mechanisms and immunotherapy in EC.

PTEN as a Prognostic/Predictive Biomarker in Cancer: An Unfulfilled Promise?

Identifying putative biomarkers of clinical outcomes in cancer is crucial for successful enrichment, and for the selection of patients who are the most likely to benefit from a specific therapeutic approach. Indeed, current research in personalized cancer therapy focuses on the possibility of identifying biomarkers that predict prognosis, sensitivity or resistance to therapies. Phosphatase and tensin homolog deleted on chromosome 10 (PTEN) is a tumor suppressor gene that regulates several crucial cell functions such as proliferation, survival, genomic stability and cell motility through both enzymatic and non-enzymatic activities and phosphatidylinositol 3-kinase (PI3K)-dependent and -independent mechanisms. Despite its undisputed role as a tumor suppressor, assessment of PTEN status in sporadic human tumors has yet to provide clinically robust prognostic, predictive or therapeutic information. This is possibly due to the exceptionally complex regulation of PTEN function, which involves genetic, transcriptional, post-transcriptional and post-translational events. This review shows a brief summary of the regulation and function of PTEN and discusses its controversial aspects as a prognostic/predictive biomarker.

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.

Quantification of altered tissue turnover in a liquid biopsy: a proposed precision medicine tool to assess chronic inflammation and desmoplasia associated with a pro-cancerous niche and response to immuno-therapeutic anti-tumor modalities

Immuno-therapy has begun to revolutionize cancer treatment. However, despite the significant progress achieved in regard to the duration of clinical benefits, a substantial number of patients do not respond to these therapies. To improve the outcome of patients receiving immuno-therapy, there is a need for novel biomarkers that can predict and monitor treatment. Tumor microenvironment alterations, more specifically the state of chronic inflammation and desmoplasia (tumor fibrosis), are important factors to consider in this context. Here, we discuss the potential for quantification of altered tissue turnover in a liquid biopsy as a proposed precision medicine tool to assess chronic inflammation and desmoplasia in the immuno-oncology (IO) setting. We highlight the need for novel non-invasive biomarkers in IO and the importance of addressing tumor microenvironment alterations. We focus on desmoplasia and extracellular matrix (ECM) remodeling, and how the composition of the ECM defines T-cell permissiveness in the tumor microenvironment and opens up the possibility for associated liquid biopsy biomarkers. Moreover, we address the importance of the assessment of chronic inflammation, primarily macrophage activity, in a liquid biopsy.

The changing face of clinical trials in the personalized medicine and immuno-oncology era: report from the international congress on clinical trials in Oncology & Hemato-Oncology (ICTO 2017)

In the past decade, the oncology community has witnessed major advances in the understanding of cancer biology and major breakthroughs in several different therapeutic areas, from solid tumors to hematological malignancies; moreover, the advent of effective immunotherapy approaches, such as immune-checkpoint blockade, is revolutionizing treatment algorithms in almost all oncology disease areas. As knowledge evolves and new weapons emerge in the “war against cancer”, clinical and translational research need to adapt to a rapidly changing environment to effectively translate novel concepts into sustainable and accessible therapeutic options for cancer patients.

With this in mind, translational cancer researchers, oncology professionals, treatment experts, CRO and industry leaders, as well as patient representatives gathered in London, 16-17 March 2017, for The International Congress on Clinical Trials in Oncology and Hemato-Oncology (ICTO2017), to discuss the changing face of oncology clinical trials in the new era of personalized medicine and immuno-oncology. A wide range of topics, including clinical trial design in immuno-oncology, biomarker-oriented drug development paths, statistical design and endpoint selection, challenges in the design and conduct of personalized medicine clinical trials, risk-based monitoring, financing and reimbursement, as well as best operational practices, were discussed in an open, highly interactive format, favoring networking among all relevant stakeholders. The most relevant data, approaches and issues emerged and discussed during the conference are summarized in this report.

Translatability score revisited: differentiation for distinct disease areas

Background

Translational science supports successful transition of early biomedical research into human applications. In 2009 a translatability score to assess risk and identify strengths and weaknesses of a given project has been designed and successfully tested in case studies. The score elements, in particular the contributing weight factors, are heterogeneous for different disease areas; therefore, the score was individualized for six areas (cardiovascular, oncology, psychiatric, anti-viral, anti-bacterial/fungal and monogenetic diseases).

Results

FDA reviews and related literature were used for modifications of the score with emphasis on biomarkers, personalized medicine and animal models. 113 new medical entities approved by FDA from 2012 through 2016 were evaluated and metrics obtained for companion diagnostics and animal models as starting points for author-based individualization of the score. Most drugs approved in this period were related to oncology (46%), while the approvals were lowest for psychiatrics (4%). The evaluation of the FDA package inserts revealed that companion diagnostics play an important role in every field except psychiatrics. Further the analysis of the FDA reviews showed the weakness of animal models in psychiatrics and anti-virals, while useful animal models were present for all other fields. Consequently the scoring system was adapted to the different fields, resulting in increased weights for animal models, biomarker and personalized medicine in oncology. For psychiatrics the weights for animal models, biomarker and personalized medicine were decreased, while the weight for model compounds, clinical trials and surrogate or endpoint strategy were increased. For anti-viral drugs weights for in vitro data and personalized medicine were increased, while the weight for animal models was decreased. Further, for anti-bacterial/fungal drugs weights for animal models and personalized medicine were increased. Weights were increased for genetics and personalized medicine and decreased for model compounds for monogenetic orphans.

Conclusions

Adaptation of the score to different disease areas should help to support a structured and diverse approach to translation and encourage researchers in the private or public sectors to further customize the score.

Electronic supplementary material

The online version of this article (10.1186/s12967-017-1329-y) contains supplementary material, which is available to authorized users.

Molecular strategies in the management of bronchopulmonary and thymic neuroendocrine neoplasms

Thoracic NETs [bronchopulmonary NETs (BPNETs) and thymic NETs (TNET)] share a common anatomic primary location, likely a common cell of origin, the "Kulchitsky cell" and presumably, a common etiopathogenesis. Although they are similarly grouped into well-differentiated [typical carcinoids (TC) and atypical carcinoids (AC)] and poorly differentiated neoplasms and both express somatostatin receptors, they exhibit a wide variation in clinical behavior. TNETs are more aggressive, are frequently metastatic, and have a lower 5-year survival rate (~50% vs. ~80%) than BPNETs. They are typically symptomatic, most often secreting ACTH (40% of tumors) but both tumor groups share secretion of common biomarkers including chromogranin A and 5-HIAA. Consistently effective and accurate circulating biomarkers are, however, currently unavailable. Surgery is the primary therapeutic tool for both BPNET and TNETs but there remains little consensus about later interventions e.g., targeted therapy, or how these can be monitored. Genetic analyses have identified different topographies (e.g., significant alterations in chromatin and epigenetic remodeling in BPNETs versus frequent chromosomal abnormalities in TNETs) but there is an absence of clinically actionable mutations in both tumor groups. Liquid biopsies, tools that can measure neoplastic signatures in peripheral blood, can potentially be leveraged to detect disease early i.e., recurrence, predict tumors that may respond to specific therapies and serve as real-time monitors for treatment responses. Recent studies have identified that mRNA transcript analysis in blood effectively identifies both BPNET and TNETs. The clinical utility of this gene expression assay includes use as a diagnostic, confirmation of completeness of surgical resection and use as a molecular management tool to monitor efficacy of PRRT and other therapeutic strategies.

Systems analysis of apoptotic priming in ovarian cancer identifies vulnerabilities and predictors of drug response

The lack of effective chemotherapies for high-grade serous ovarian cancers (HGS-OvCa) has motivated a search for alternative treatment strategies. Here, we present an unbiased systems-approach to interrogate a panel of 14 well-annotated HGS-OvCa patient-derived xenografts for sensitivity to PI3K and PI3K/mTOR inhibitors and uncover cell death vulnerabilities. Proteomic analysis reveals that PI3K/mTOR inhibition in HGS-OvCa patient-derived xenografts induces both pro-apoptotic and anti-apoptotic signaling responses that limit cell killing, but also primes cells for inhibitors of anti-apoptotic proteins. In-depth quantitative analysis of BCL-2 family proteins and other apoptotic regulators, together with computational modeling and selective anti-apoptotic protein inhibitors, uncovers new mechanistic details about apoptotic regulators that are predictive of drug sensitivity (BIM, caspase-3, BCL-X_L) and resistance (MCL-1, XIAP). Our systems-approach presents a strategy for systematic analysis of the mechanisms that limit effective tumor cell killing and the identification of apoptotic vulnerabilities to overcome drug resistance in ovarian and other cancers.High-grade serous ovarian cancers (HGS-OvCa) frequently develop chemotherapy resistance. Here, the authors through a systematic analysis of proteomic and drug response data of 14 HGS-OvCa PDXs demonstrate that targeting apoptosis regulators can improve response of these tumors to inhibitors of the PI3K/mTOR pathway.

Systems analysis of apoptotic priming in ovarian cancer identifies vulnerabilities and predictors of drug response

The lack of effective chemotherapies for high-grade serous ovarian cancers (HGS-OvCa) has motivated a search for alternative treatment strategies. Here, we present an unbiased systems-approach to interrogate a panel of 14 well-annotated HGS-OvCa patient-derived xenografts for sensitivity to PI3K and PI3K/mTOR inhibitors and uncover cell death vulnerabilities. Proteomic analysis reveals that PI3K/mTOR inhibition in HGS-OvCa patient-derived xenografts induces both pro-apoptotic and anti-apoptotic signaling responses that limit cell killing, but also primes cells for inhibitors of anti-apoptotic proteins. In-depth quantitative analysis of BCL-2 family proteins and other apoptotic regulators, together with computational modeling and selective anti-apoptotic protein inhibitors, uncovers new mechanistic details about apoptotic regulators that are predictive of drug sensitivity (BIM, caspase-3, BCL-X_L) and resistance (MCL-1, XIAP). Our systems-approach presents a strategy for systematic analysis of the mechanisms that limit effective tumor cell killing and the identification of apoptotic vulnerabilities to overcome drug resistance in ovarian and other cancers.

High-grade serous ovarian cancers (HGS-OvCa) frequently develop chemotherapy resistance. Here, the authors through a systematic analysis of proteomic and drug response data of 14 HGS-OvCa PDXs demonstrate that targeting apoptosis regulators can improve response of these tumors to inhibitors of the PI3K/mTOR pathway.

Systems analysis of apoptotic priming in ovarian cancer identifies vulnerabilities and predictors of drug response

The lack of effective chemotherapies for high-grade serous ovarian cancers (HGS-OvCa) has motivated a search for alternative treatment strategies. Here, we present an unbiased systems-approach to interrogate a panel of 14 well-annotated HGS-OvCa patient-derived xenografts for sensitivity to PI3K and PI3K/mTOR inhibitors and uncover cell death vulnerabilities. Proteomic analysis reveals that PI3K/mTOR inhibition in HGS-OvCa patient-derived xenografts induces both pro-apoptotic and anti-apoptotic signaling responses that limit cell killing, but also primes cells for inhibitors of anti-apoptotic proteins. In-depth quantitative analysis of BCL-2 family proteins and other apoptotic regulators, together with computational modeling and selective anti-apoptotic protein inhibitors, uncovers new mechanistic details about apoptotic regulators that are predictive of drug sensitivity (BIM, caspase-3, BCL-X_L) and resistance (MCL-1, XIAP). Our systems-approach presents a strategy for systematic analysis of the mechanisms that limit effective tumor cell killing and the identification of apoptotic vulnerabilities to overcome drug resistance in ovarian and other cancers.High-grade serous ovarian cancers (HGS-OvCa) frequently develop chemotherapy resistance. Here, the authors through a systematic analysis of proteomic and drug response data of 14 HGS-OvCa PDXs demonstrate that targeting apoptosis regulators can improve response of these tumors to inhibitors of the PI3K/mTOR pathway.