Optimizing cancer immunotherapy: Is it time for personalized predictive biomarkers?

Microbiome miracles and their pioneering advances and future frontiers in cardiovascular disease

Cardiovascular diseases (CVDs) represent a significant global health challenge, underscoring the need for innovative approaches to prevention and treatment. Recent years have seen a surge in interest in unraveling the complex relationship between the gut microbiome and cardiovascular health. This article delves into current research on the composition, diversity, and impact of the gut microbiome on CVD development. Recent advancements have elucidated the profound influence of the gut microbiome on disease progression, particularly through key mediators like Trimethylamine-N-oxide (TMAO) and other microbial metabolites. Understanding these mechanisms reveals promising therapeutic targets, including interventions aimed at modulating the gut microbiome's interaction with the immune system and its contribution to endothelial dysfunction. Harnessing this understanding, personalized medicine strategies tailored to individuals' gut microbiome profiles offer innovative avenues for reducing cardiovascular risk. As research in this field continues to evolve, there is vast potential for transformative advancements in cardiovascular medicine, paving the way for precision prevention and treatment strategies to address this global health challenge.

Editorial: Immunotherapy in renal cell carcinoma

This collection contains 10 reports published In Frontiers in Oncology between August 2020 and March 2022 broadly focused on the immunobiology of renal cell carcinoma (RCC), the impact of immunotherapy in the setting of RCC, and the identification of biomarkers that are prognostic of RCC patient outcomes and response to immunotherapy.

Personalized Immuno-Oncology

Cancer immunotherapy, which aims to control the immune system to eradicate cancer cells and prevent their spread, needs to be personalized because anticancer immune responses can be inhibited in several ways that vary from patient to patient. Cancer immunotherapy includes pharmaceuticals such as immune checkpoint inhibitors and monoclonal antibodies (MAbs) as well as cell therapy, immunogene therapy, and vaccines. Combination of programmed cell death protein 1 (PD-1)/programmed cell death protein ligand 1 (PD-L1) drugs with other immunotherapy drugs, for example, antibody-drug conjugates, as well as combination of PD-1/PD-L1 drugs with other therapies, for example, chemotherapy and radiation therapy, are being explored. Biomarkers are important for predicting the response to immunotherapy. Molecular diagnostics and sequencing are important technologies for guiding treatment in immuno-oncology. Genomic profiling of tumor mutational burden may enhance the predictive utility of PD-L1 expression and facilitate personalized combination immunotherapy. Optimization of personalized immuno-oncology requires integration of several technologies and selection of those best suited for an individual patient. Advances in immuno-oncology are also attributed to technologies for targeted delivery of anticancer therapeutics such as antigen-capturing nanoparticles for precision targeting and selective delivery. A breakthrough in cell therapy of cancer is a chimeric antigen receptors-T cell, which combines the antigen-binding site of a MAb with the signal activating machinery of a T cell, freeing antigen recognition from major histocompatibility complex restriction. Gene-editing tools such as clustered regularly interspaced short palindromic repeats have a promising application for removing alloreactivity and decreasing immunogenicity of third-party T cells. In conclusion, personalized immuno-oncology is one of the most promising approaches to management of cancer.

Response of human melanoma cell lines to interferon-beta gene transfer mediated by a modified adenoviral vector

Since melanomas often retain wild type p53, we developed an adenoviral vector, AdRGD-PG, which provides robust transduction and transgene expression in response to p53. Previously, this vector was used for interferon-β gene transfer in mouse models of melanoma, resulting in control of tumor progression, but limited cell killing. Here, the AdRGD-PG-hIFNβ vector encoding the human interferon-β cDNA (hIFNβ) was used to transduce human melanoma cell lines SK-MEL-05 and SK-MEL-147 (both wild type p53). In vitro, cell death was induced in more than 80% of the cells and correlated with elevated annexinV staining and caspase 3/7 activity. Treatment with hIFNβ promoted cell killing in neighboring, non-transduced cells, thus revealing a bystander effect. In situ gene therapy resulted in complete inhibition of tumor progression for SK-MEL-147 when using nude mice with no evidence of hepatotoxicity. However, the response in Nod-Scid mice was less robust. For SK-MEL-05, tumor inhibition was similar in nude and Nod-Scid mice and was less efficient than seen for SK-MEL-147, indicating both cell type and host specific responses. The AdRGD-PG-hIFNβ vector provides extensive killing of human melanoma cells in vitro and a potent anti-tumor effect in vivo. This study provides a critical advance in the development of our melanoma gene therapy approach.

Data-driven microbiota biomarker discovery for personalized drug therapy of cardiovascular disease

Cardiovascular disease (CVD) is the most wide-spread disorder all over the world. The personalized and precision diagnosis, treatment and prevention of CVD is still a challenge. With the developing of metagenome sequencing technologies and the paradigm shifting to data-driven discovery in life science, the computer aided microbiota biomarker discovery for CVD is becoming reality. We here summarize the data resources, knowledgebases and computational models available for CVD microbiota biomarker discovery, and review the present status of the findings about the microbiota patterns associated with the therapeutic effects on CVD. The future challenges and opportunities of the translational informatics on the personalized drug usages in CVD diagnosis, prognosis and treatment are also discussed.

Endocrine adverse events related with immune checkpoint inhibitors: an update for clinicians

Designated as scientific breakthrough of current decade, immune checkpoint inhibitors attenuate the cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) and the programmed cell death 1 (PD-1)/ligand 1 (PD-L1) pathways, depriving cancer cells of a key strategy of evasion from immunosurveillance. The reinvigoration of immune response translates into clinical success, inevitably entwined with a novel constellation of immune-related adverse events. The present review dissects the endocrine immune-related adverse events, emphasizing their unique profile featured by unpredictable onset, irreversibility, nonspecific symptoms, wide clinical spectrum and sophisticated diagnostic work-up. Guidelines advocate individualized decision-making process guided by clinicians' judgement. Future perspective should be governed by five principles - prevention, anticipation, detection, treatment, monitoring - aiming to gain the optimal profit diminishing immunotoxicity.

Immunoscore: a novel prognostic tool. Association with clinical outcome, response to treatment and survival in several malignancies

The predictive accuracy of the traditional staging system for cancer, the American Joint Committee on Cancer/Union Internationale Centre le Cancer (AJCC/UICC) classification of malignant tumors, is based on disease progression as a tumor cell-autonomous process, regardless the effects of the host immune response. The natural history of a tumor includes different phases of growth, migration and invasion. During these phases, tumor cells interact with their microenvironment and are influenced by signals from stromal, endothelial, inflammatory and immune cells. Indeed, tumors are often infiltrated by defensive cells such as lymphocytes, macrophages or mast cells and it has been shown extensively that lymphocytes may control cancer outcome, as evidenced in several human malignancies. Increasing evidence suggests that cancer progression is strongly influenced by host immune response, which is represented by immune cell infiltrates. The T-lymphocyte-based immunoscore (IS) has proved to be a prognostic factor in human malignancies such as colon, pancreas and lung cancer, hepatocellular carcinoma, melanoma and even brain metastases. Although the IS was initially established to evaluate the prognosis of stage I/II/III colon cancer patients, its association with clinical outcomes and survival has been shown in other malignancies. The aim of this review is to analyze the association of IS with prognosis, survival and response to therapy in different tumor types.

Mass Spectrometry-Based Multivariate Proteomic Tests for Prediction of Outcomes on Immune Checkpoint Blockade Therapy: The Modern Analytical Approach

The remarkable success of immune checkpoint inhibitors (ICIs) has given hope of cure for some patients with advanced cancer; however, the fraction of responding patients is 15-35%, depending on tumor type, and the proportion of durable responses is even smaller. Identification of biomarkers with strong predictive potential remains a priority. Until now most of the efforts were focused on biomarkers associated with the assumed mechanism of action of ICIs, such as levels of expression of programmed death-ligand 1 (PD-L1) and mutation load in tumor tissue, as a proxy of immunogenicity; however, their performance is unsatisfactory. Several assays designed to capture the complexity of the disease by measuring the immune response in tumor microenvironment show promise but still need validation in independent studies. The circulating proteome contains an additional layer of information characterizing tumor-host interactions that can be integrated into multivariate tests using modern machine learning techniques. Here we describe several validated serum-based proteomic tests and their utility in the context of ICIs. We discuss test performances, demonstrate their independence from currently used biomarkers, and discuss various aspects of associated biological mechanisms. We propose that serum-based multivariate proteomic tests add a missing piece to the puzzle of predicting benefit from ICIs.

Midkine (MDK) growth factor: a key player in cancer progression and a promising therapeutic target

Midkine is a heparin-binding growth factor, originally reported as the product of a retinoic acid-responsive gene during embryogenesis, but currently viewed as a multifaceted factor contributing to both normal tissue homeostasis and disease development. Midkine is abnormally expressed at high levels in various human malignancies and acts as a mediator for the acquisition of critical hallmarks of cancer, including cell growth, survival, metastasis, migration, and angiogenesis. Several studies have investigated the role of midkine as a cancer biomarker for the detection, prognosis, and management of cancer, as well as for monitoring the response to cancer treatment. Moreover, several efforts are also being made to elucidate its underlying mechanisms in therapeutic resistance and immunomodulation within the tumor microenvironment. We hereby summarize the current knowledge on midkine expression and function in cancer development and progression, and highlight its promising potential as a cancer biomarker and as a future therapeutic target in personalized cancer medicine.

Digging deeper into volatile organic compounds associated with cancer

Volatile organic compounds (VOCs), produced and emitted through the metabolism of cancer cells or the body's immune system, are considered novel cancer biomarkers for diagnostic purposes. Of late, a large number of work has been done to find a relationship between VOCs' signature of body and cancer. Cancer-related VOCs can be used to detect several types of cancers at the earlier stages which in turn provide a significantly higher chance of survival. Here we aim to provide an updated picture of cancer-related VOCs based on recent findings in this field focusing on cancer odor database.

Circulating biomarkers predictive of tumor response to cancer immunotherapy

Introduction: The advent of checkpoint blockade immunotherapy has revolutionized cancer treatment, but clinical response to immunotherapies is highly heterogeneous among individual patients and between cancer types. This represents a challenge to oncologists when choosing specific immunotherapies for personalized medicine. Thus, biomarkers that can predict tumor responsiveness to immunotherapies before and during treatment are invaluable. Areas covered: We review the latest advances in 'liquid biopsy' biomarkers for noninvasive prediction and in-treatment monitoring of tumor response to immunotherapy, focusing primarily on melanoma and non-small cell lung cancer. We concentrate on high-quality studies published within the last five years on checkpoint blockade immunotherapies, and highlight significant breakthroughs, identify key areas for improvement, and provide recommendations for how these diagnostic tools can be translated into clinical practice. Expert opinion: The first biomarkers proposed to predict tumor response to immunotherapy were based on PD1/PDL1 expression, but their predictive value is limited to specific cancers or patient populations. Recent advances in single-cell molecular profiling of circulating tumor cells and host cells using next-generation sequencing has dramatically expanded the pool of potentially useful predictive biomarkers. As immunotherapy moves toward personalized medicine, a composite panel of both genomic and proteomic biomarkers will have enormous utility in therapeutic decision-making.

Biomarkers for Predicting Response to Immunotherapy with Immune Checkpoint Inhibitors in Cancer Patients

BACKGROUND

Immunotherapy, especially the use of immune checkpoint inhibitors, has revolutionized the management of several different cancer types in recent years. However, for most types of cancer, only a minority of patients experience a durable response. Furthermore, administration of immunotherapy can result in serious adverse reactions. Thus, for the most efficient and effective use of immunotherapy, accurate predictive biomarkers that have undergone analytical and clinical validation are necessary.

CONTENT

Among the most widely investigated predictive biomarkers for immunotherapy are programmed death-ligand 1 (PD-L1), microsatellite instability/defective mismatch repair (MSI/dMMR), and tumor mutational burden (TMB). MSI/dMMR is approved for clinical use irrespective of the tumor type, whereas PD-L1 is approved only for use in certain cancer types (e.g., for predicting response to first-line pembrolizumab monotherapy in non-small cell lung cancer). Although not yet approved for clinical use, TMB has been shown to predict response to several different forms of immunotherapy and across multiple cancer types. Less widely investigated predictive biomarkers for immunotherapy include tumor-infiltrating CD8⁺ lymphocytes and specific gene signatures. Despite being widely investigated, assays for MSI/dMMR, PD-L1, and TMB lack standardization and are still evolving. An urgent focus of future research should be the optimization and standardization of method for determining these biomarkers.

SUMMARY

Biomarkers for predicting response to immunotherapy are paving the way for personalized treatment for patients with diverse cancer types. However, standardization of the available biomarker assays is an urgent requirement.