Review of precision cancer medicine: Evolution of the treatment paradigm

Active compounds and potential targets of Shuganning injection in the treatment of hepatocellular carcinoma by network pharmacology and in vitro validation

Shuganning injection (SGNI), a TCM (traditional Chinese medicine) injection with good hepatoprotective effects, exerted therapeutic effects on hepatocellular carcinoma (HCC). However, the active compounds and effects of SGNI on HCC remain unclear. The objective of this study was to investigate the active compounds and potential targets of SGNI in the treatment of HCC, and explore the molecular mechanisms of main compounds. Network pharmacology was applied to predict the active compounds and targets of SGNI on cancer. The interactions between active compounds and target proteins were validated by drug affinity responsive target stability (DARTS), cellular thermal shift assay (CETSA), and pull-down assay. The in vitro test of the effects and mechanism of vanillin and baicalein was elucidated by MTT, western blot, immunofluorescence, and apoptosis analysis. According to compound characteristics, targets, etc., two typical active ingredients (vanillin and baicalein) were selected as representatives to explore the effects on HCC. Vanillin (an important food additive) bound to NF-κB1 and baicalein (a bioactive flavonoid) bound to FLT3 (FMS-like tyrosine kinase 3) were confirmed in this study. Vanillin and baicalein both inhibited cell viability and promoted apoptosis of Hep3B and Huh7 cells. In addition, both vanillin and baicalein could enhance the activation of the p38/MAPK (mitogen-activated protein kinase) signaling pathway, which may partially explain the anti-apoptosis effects of the two compounds. In conclusion, two active compounds of SGNI, vanillin and baicalein, promoted apoptosis of HCC cells via binding with NF-κB1 or FLT3, and regulating the p38/MAPK pathway. Baicalein and vanillin may be good candidates for HCC treatment on drug development.

Precision medicine in gastroenteropancreatic neuroendocrine neoplasms: Where are we in 2023?

Precision medicine describes a target-related approach to tailoring diagnosis and treatment of the individual patient. While this personalized approach is revoluzionizing many areas of oncology, it is quite late in the field of gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs), in which there are few molecular alterations to be therapeutically targeted. We critically reviewed the current evidence about precision medicine in GEP NENs, focusing on potential clinically relevant actionable targets for GEP NENs, such as the mTOR pathway, MGMT, hypoxia markers, RET, DLL-3, and some general agnostic targets. We analysed the main investigational approaches with solid and liquid biopsies. Furthermore, we reviewed a model of precision medicine more specific for NENs that is the theragnostic use of radionuclides. Overall, currently no true predictive factors for therapy have been validated so far in GEP NENs, and the personalized approach is based more on clinical thinking within a NEN-dedicated multidisciplinary team. However, there is a robust background to suppose that precision medicine, with the theragnostic model will yield new insights in this context soon.

The challenges of access to innovative medicines with limited evidence in the European Union

The European Medicines Agency (EMA) fosters access to innovative medicines through accelerated procedures and flexibility in the authorization requirements for diseases with unmet medical needs, such as many rare diseases as well as oncological diseases. However, the resulting increase of medicines being marketed with conditional authorizations and in exceptional circumstances has lead to higher clinical uncertainty about their efficacy and safety than when the standard authorizations are applied. This uncertainty has significant implications for clinical practice and the negotiation of pricing and reimbursement, particularly as high prices are based on assumptions of high value, supported by regulatory prioritization. The burden of clinical development is often shifted towards public healthcare systems, resulting in increased spending budgets and opportunity costs. Effective management of uncertainty, through appropriate testing and evaluation, and fair reflection of costs and risks in prices, is crucial. However, it is important not to sacrifice essential elements of evidence-based healthcare for the sake of access to new treatments. Balancing sensitive and rational access to new treatments, ensuring their safety, efficacy, and affordability to healthcare systems requires thoughtful decision-making. Ultimately, a responsible approach to timely access to innovative medicines that balances the needs of patients with healthcare systems' concerns is necessary. This approach emphasizes the importance of evidence-based decision-making and fair pricing and reimbursement.

Learning chemical sensitivity reveals mechanisms of cellular response

Chemical probes interrogate disease mechanisms at the molecular level by linking genetic changes to observable traits. However, comprehensive chemical screens in diverse biological models are impractical. To address this challenge, we developed ChemProbe, a model that predicts cellular sensitivity to hundreds of molecular probes and drugs by learning to combine transcriptomes and chemical structures. Using ChemProbe, we inferred the chemical sensitivity of cancer cell lines and tumor samples and analyzed how the model makes predictions. We retrospectively evaluated drug response predictions for precision breast cancer treatment and prospectively validated chemical sensitivity predictions in new cellular models, including a genetically modified cell line. Our model interpretation analysis identified transcriptome features reflecting compound targets and protein network modules, identifying genes that drive ferroptosis. ChemProbe is an interpretable in silico screening tool that allows researchers to measure cellular response to diverse compounds, facilitating research into molecular mechanisms of chemical sensitivity.

L858R emerges as a potential biomarker predicting response of lung cancer models to anti-EGFR antibodies: Comparison of osimertinib vs. cetuximab

EGFR-specific tyrosine kinase inhibitors (TKIs), especially osimertinib, have changed lung cancer therapy, but secondary mutations confer drug resistance. Because other EGFR mutations promote dimerization-independent active conformations but L858R strictly depends on receptor dimerization, we herein evaluate the therapeutic potential of dimerization-inhibitory monoclonal antibodies (mAbs), including cetuximab. This mAb reduces viability of cells expressing L858R-EGFR and blocks the FOXM1-aurora survival pathway, but other mutants show no responses. Unlike TKI-treated patient-derived xenografts, which relapse post osimertinib treatment, cetuximab completely prevents relapses of L858R+ tumors. We report that osimertinib's inferiority associates with induction of mutagenic reactive oxygen species, whereas cetuximab's superiority is due to downregulation of adaptive survival pathways (e.g., HER2) and avoidance of mutation-prone mechanisms that engage AXL, RAD18, and the proliferating cell nuclear antigen. These results identify L858R as a predictive biomarker, which may pave the way for relapse-free mAb monotherapy relevant to a large fraction of patients with lung cancer.

Crosstalk of Mast Cells and Natural Killer Cells with Neurons in Chemotherapy-Induced Peripheral Neuropathy

Chemotherapy-induced peripheral neuropathy (CIPN) is a major comorbidity of cancer. Multiple clinical interventions have been studied to effectively treat CIPN, but the results have been disappointing, with no or little efficacy. Hence, understanding the pathophysiology of CIPN is critical to improving the quality of life and clinical outcomes of cancer patients. Although various mechanisms of CIPN have been described in neuropathic anti-cancer agents, the neuroinflammatory process involving cytotoxic/proinflammatory immune cells remains underexamined. While mast cells (MCs) and natural killer (NK) cells are the key innate immune compartments implicated in the pathogenesis of peripheral neuropathy, their role in CIPN has remained under-appreciated. Moreover, the biology of proinflammatory cytokines associated with MCs and NK cells in CIPN is particularly under-evaluated. In this review, we will focus on the interactions between MCs, NK cells, and neuronal structure and their communications via proinflammatory cytokines, including TNFα, IL-1β, and IL-6, in peripheral neuropathy in association with tumor immunology. This review will help lay the foundation to investigate MCs, NK cells, and cytokines to advance future therapeutic strategies for CIPN.

A Photosensitizer-Loaded Polydopamine Nanomedicine Agent for Synergistic Photodynamic and Photothermal Therapy

Photodynamic therapy (PDT) and photothermal therapy (PTT) have emerged as promising non-invasive approaches to cancer treatment. However, the development of multifunctional nanomedicines is necessary to enhance these approaches' effectiveness and safety. In this study, we investigated a polydopamine-based nanoparticle (PDA-ZnPc+ Nps) loaded with the efficient photosensitizer ZnPc(4TAP)12+ (ZnPc+) through in vitro and in vivo experiments to achieve synergistic PDT and PTT. Our results demonstrated that PDA-ZnPc+ Nps exhibited remarkable efficacy due to its ability to generate reactive oxygen species (ROS), induce photothermal effects, and promote apoptosis in cancer cells. Moreover, in both MCF-7 cells and MCF-7 tumor-bearing mice, the combined PDT/PTT treatment with PDA-ZnPc+ Nps led to synergistic effects. Subcellular localization analysis revealed a high accumulation of ZnPc+ in the cytoplasm of cancer cells, resulting in cellular disruption and vacuolation following synergistic PDT/PTT. Furthermore, PDA-ZnPc+ Nps exhibited significant antitumor effects without causing evident systemic damage in vivo, enabling the use of lower doses of photosensitizer and ensuring safer treatment. Our study not only highlights the potential of PDA-ZnPc+ Nps as a dual-functional anticancer agent combining PDA and PTT but also offers a strategy for mitigating the side effects associated with clinical photosensitizers, particularly dark toxicity.

Gynecologic and Breast Cancers: What's New in Chemoresistance and Chemosensitivity Tests?

Gynecological and breast cancers affect women's health worldwide. Although chemotherapy is one of the principal treatments for cancer, it also has limitations owing to toxicity and tumor resistance to the drugs used. Thus, individualized treatment based on personal tumor characteristics is essential for improving therapeutic outcomes and patient survival. Chemoresistance and chemosensitivity tests can be useful for predicting tumor response and guiding chemotherapy choices. This methodology has already been applied to breast, ovarian, cervical, and endometrial cancers, identifying successfully which drugs cause resistance and sensitivity responses for each individual person, influencing their progression-free survival and overall response. In addition, more recent techniques, such as organoids and patient-derived xenografts, can also recapitulate patients' tumor characteristics and contribute to chemo response evaluation. Therefore, this review compiles information on chemoresistance and chemosensitivity tests performed in gynecologic and breast cancers and their main results for women's health improvement.

Orchestrating smart therapeutics to achieve optimal treatment in small cell lung cancer: recent progress and future directions

Small cell lung cancer (SCLC) is a recalcitrant malignancy with elusive mechanism of pathogenesis and dismal prognosis. Over the past decades, platinum-based chemotherapy has been the backbone treatment for SCLC. However, subsequent chemoresistance after initial effectiveness urges researchers to explore novel therapeutic targets of SCLC. Recent years have witnessed significant improvements in targeted therapy in SCLC. New molecular candidates such as Ataxia telangiectasia and RAD3-related protein (ATR), WEE1, checkpoint kinase 1 (CHK1) and poly-ADP-ribose polymerase (PARP) have shown promising therapeutic utility in SCLC. While immune checkpoint inhibitor (ICI) has emerged as an indispensable treatment modality for SCLC, approaches to boost efficacy and reduce toxicity as well as selection of reliable biomarkers for ICI in SCLC have remained elusive and warrants our further investigation. Given the increasing importance of precision medicine in SCLC, optimal subtyping of SCLC using multi-omics have gradually applied into clinical practice, which may identify more drug targets and better tailor treatment strategies to each individual patient. The present review summarizes recent progress and future directions in SCLC. In addition to the emerging new therapeutics, we also focus on the establishment of predictive model for early detection of SCLC. More importantly, we also propose a multi-dimensional model in the prognosis of SCLC to ultimately attain the goal of accurate treatment of SCLC.

A Multipronged Unbiased Strategy Guides the Development of an Anti-EGFR/EPHA2-Bispecific Antibody for Combination Cancer Therapy

PURPOSE

Accumulating analyses of pro-oncogenic molecular mechanisms triggered a rapid development of targeted cancer therapies. Although many of these treatments produce impressive initial responses, eventual resistance onset is practically unavoidable. One of the main approaches for preventing this refractory condition relies on the implementation of combination therapies. This includes dual-specificity reagents that affect both of their targets with a high level of selectivity. Unfortunately, selection of target combinations for these treatments is often confounded by limitations in our understanding of tumor biology. Here, we describe and validate a multipronged unbiased strategy for predicting optimal co-targets for bispecific therapeutics.

EXPERIMENTAL DESIGN

Our strategy integrates ex vivo genome-wide loss-of-function screening, BioID interactome profiling, and gene expression analysis of patient data to identify the best fit co-targets. Final validation of selected target combinations is done in tumorsphere cultures and xenograft models.

RESULTS

Integration of our experimental approaches unambiguously pointed toward EGFR and EPHA2 tyrosine kinase receptors as molecules of choice for co-targeting in multiple tumor types. Following this lead, we generated a human bispecific anti-EGFR/EPHA2 antibody that, as predicted, very effectively suppresses tumor growth compared with its prototype anti-EGFR therapeutic antibody, cetuximab.

CONCLUSIONS

Our work not only presents a new bispecific antibody with a high potential for being developed into clinically relevant biologics, but more importantly, successfully validates a novel unbiased strategy for selecting biologically optimal target combinations. This is of a significant translational relevance, as such multifaceted unbiased approaches are likely to augment the development of effective combination therapies for cancer treatment. See related commentary by Kumar, p. 2570.

Spatial metabolomics in head and neck tumors: a review

The joint analysis of single-cell transcriptomics, proteomics, lipidomics, metabolomics and spatial metabolomics is continually transforming our understanding of the mechanisms of metabolic reprogramming in tumor cells. Since head and neck tumor is the sixth most common tumor in the world, the study of the metabolic mechanism of its occurrence, development and prognosis is still undeveloped. In the past decade, this field has witnessed tremendous technological revolutions and considerable development that enables major breakthroughs to be made in the study of human tumor metabolism. In this review, a comprehensive comparison of traditional metabolomics and spatial metabolomics has been concluded, and the recent progress and challenges of the application of spatial metabolomics combined multi-omics in the research of metabolic reprogramming in tumors are reviewed. Furthermore, we also highlight the advances of spatial metabolomics in the study of metabolic mechanisms of head and neck tumors, and provide an outlook of its application prospects.

An interpretable deep learning framework for genome-informed precision oncology

Cancers result from aberrations in cellular signaling systems, typically resulting from driver somatic genome alterations (SGAs) in individual tumors. Precision oncology requires understanding the cellular state and selecting medications that induce vulnerability in cancer cells under such conditions. To this end, we developed a computational framework consisting of two components: 1) A representation-learning component, which learns a representation of the cellular signaling systems when perturbed by SGAs, using a biologically-motivated and interpretable deep learning model. 2) A drug-response-prediction component, which predicts the response to drugs by leveraging the information of the cellular state of the cancer cells derived by the first component. Our cell-state-oriented framework significantly enhances the accuracy of genome-informed prediction of drug responses in comparison to models that directly use SGAs as inputs. Importantly, our framework enables the prediction of response to chemotherapy agents based on SGAs, thus expanding genome-informed precision oncology beyond molecularly targeted drugs.

Central Sensitization in Cancer Survivors and Its Clinical Implications: State of the Art

Although the prevalence of cancer pain is 47% after treatment, cancer pain is often underestimated, and many patients are undertreated. The complexity of cancer pain contributes to the lack of its management. Recently, as the mechanism of cancer pain, it has become clear that central sensitization (CS) influences chronic pain conditions and the transition from acute to chronic pain. In this state-of-the-art review, we summarized the association of CS or central sensitivity syndrome with pain and the treatment for pain targeting CS in cancer survivors. The management of patients with CS should not only focus on tissue damage in either the affected body regions or within the central nervous system; rather, it should aim to target the underlying factors that sustain the CS process. Pain neuroscience education (PNE) is gaining popularity for managing chronic musculoskeletal pain and could be effective for pain and CS in breast cancer survivors. However, there is a study that did not demonstrate significant improvements after PNE, so further research is needed. Precision medicine involves the classification of patients into subgroups based on a multifaceted evaluation of disease and the implementation of treatment tailored to the characteristics of each patient, which may play a central role in the treatment of CS.

Oncogenic Proteomics Approaches for Translational Research and HIV-Associated Malignancy Mechanisms

Recent advances in the field of proteomics have allowed extensive insights into the molecular regulations of the cell proteome. Specifically, this allows researchers to dissect a multitude of signaling arrays while targeting for the discovery of novel protein signatures. These approaches based on data mining are becoming increasingly powerful for identifying both potential disease mechanisms as well as indicators for disease progression and overall survival predictive and prognostic molecular markers for cancer. Furthermore, mass spectrometry (MS) integrations satisfy the ongoing demand for in-depth biomarker validation. For the purpose of this review, we will highlight the current developments based on MS sensitivity, to place quantitative proteomics into clinical settings and provide a perspective to integrate proteomics data for future applications in cancer precision medicine. We will also discuss malignancies associated with oncogenic viruses such as Acquire Immunodeficiency Syndrome (AIDS) and suggest novel mechanisms behind this phenomenon. Human Immunodeficiency Virus type-1 (HIV-1) proteins are known to be oncogenic per se, to induce oxidative and endoplasmic reticulum stresses, and to be released from the infected or expressing cells. HIV-1 proteins can act alone or in collaboration with other known oncoproteins, which cause the bulk of malignancies in people living with HIV-1 on ART.

How will the identification and therapeutic intervention of genetic targets in oncology evolve for future therapy?

INTRODUCTION

Mapping of the human genome, together with the broad understanding of new biomolecular pathways involved in cancer development, represents a huge dividing line for advances in cancer treatment. This special article aims to express the next evolution of cancer therapy, while also considering the challenges and uncertainties facing future directions.

AREA COVERED

The recent achievements of medical science in the oncology field concern both new diagnostic techniques, such as liquid biopsy, and therapeutic strategies with innovative anticancer drugs. Although several molecular characteristics of tumors are linked to the tissue of origin, some mutations are shared by multiple tumor histologies, thus paving the way for what is called 'precision oncology.' The article highlights the importance of identifying new mutations and biomolecular pathways that can be pursued with new anticancer drugs.

EXPERT OPINION

Oncology and medical science have made great progress in understanding new molecular targets; being able to early identify tumor markers that are not confined to a single organ through minimally invasive diagnostic techniques allows us to design new effective therapeutic strategies. Multidisciplinary teams now aim to evaluate the most appropriate and personalized diagnostic/therapeutic approach for the individual patient.

MIRACUM-Pipe: An Adaptable Pipeline for Next-Generation Sequencing Analysis, Reporting, and Visualization for Clinical Decision Making

(1) Background: Next-generation sequencing (NGS) of patients with advanced tumors is becoming an established method in Molecular Tumor Boards. However, somatic variant detection, interpretation, and report generation, require in-depth knowledge of both bioinformatics and oncology. (2) Methods: MIRACUM-Pipe combines many individual tools into a seamless workflow for comprehensive analyses and annotation of NGS data including quality control, alignment, variant calling, copy number variation estimation, evaluation of complex biomarkers, and RNA fusion detection. (3) Results: MIRACUM-Pipe offers an easy-to-use, one-prompt standardized solution to analyze NGS data, including quality control, variant calling, copy number estimation, annotation, visualization, and report generation. (4) Conclusions: MIRACUM-Pipe, a versatile pipeline for NGS, can be customized according to bioinformatics and clinical needs and to support clinical decision-making with visual processing and interactive reporting.

Monoclonal Antibodies for the Treatment of Graves Orbitopathy: Precision Medicine?

PURPOSE

To summarize the development, nomenclature, and rationale of the reported use of monoclonal antibodies (Mabs) in Graves Orbitopathy (GO) and to undertake a systematic review of the management of GO with Mabs.

METHODS

The Pubmed and Embase databases and the Federal Brazilian searching site (Periódicos-CAPES) were screened. The authors searched all the keywords "monoclonal antibodies," "adalimumab," "belimumab," "infliximab," "rituximab," "teprotumumab," and "tocilizumab" combined with the terms "Graves Orbitopathy," "Graves eye disease" and "thyroid eye disease." All the articles published in English, French, and Spanish from 2000 to May 2022 were screened. Only publications with quantitative data on the activity of orbitopathy, proptosis, or both were included.

RESULTS

Seventy-six articles of the 954 screened records met the inclusion criteria. Seven Mabs were described for treating GO. The three most reported Mabs were Rituximab, Tocilizumab, and Teprotumumab. Only eight randomized clinical trials compared the effect of these three Mabs and Belimumab with the effect of steroids or placebos. Adalimumab, Infliximab, and K1-70 only appeared in a few case series and case reports. Frequent mild-to-moderate and few major side effects occurred with the three most used Mabs. Relapse rates ranged from 7.4% for Tocilizumab to at least 29.4% for Teprotumumab. No randomized clinical trials compared Mabs head-to-head.

CONCLUSION

Considering the lack of head-to-head comparisons between Mabs, the relapse rate, the possibility of severe collateral effects, and the cost of Mabs, it is not clear which Mab is the safest and most useful to treat GO.

The significance of tissue-agnostic biomarkers in solid tumors: the more the merrier?

INTRODUCTION

To date, several emerging biomarkers have gained considerable interest in the field of predictive molecular oncology. The advent of precision medicine has led to the development of innovative drugs targeting rare molecular pathways independently from histology, defined as tissue-agnostic drugs.

AREAS COVERED

Although there is a lot of promise for this new tissue-agnostic model in the oncological scenario, crucial issues from both the diagnostic and therapeutic standpoint are emerging. This review aims to critically examine the role of tissue-agnostic biomarkers in different solid tumors, focusing on the prevalence and methods of detection of agnostic biomarkers together with drug approvals to guide clinicians in this evolving landscape.

EXPERT OPINION

To strengthen the framework for tissue-agnostic approvals, the dialogue between regulatory, industrial, and academic parties should be intensified. Critical questions include the development of an efficient network system that can overcome the heterogeneity of patients' inclusion criteria along with the increasingly difficult interpretation of next-generation sequencing (NGS) profiling technologies. Cost-effectiveness and risk-benefit studies are needed in the national context considering the modalities of access to diagnostic tests and reimbursement of treatments.

The Clinical Significance of Genetic Variation in Ovarian Cancer

Genetic variation is a well-known contributor to the onset and progression of cancer. The goal of this study is to provide a comprehensive examination of the nucleotide and chromosomal variation associated with the onset and progression of serous ovarian cancer. Using a variety of computational and statistical methods, we examine the exome sequence profiles of genetic variants present in the primary tumors of 432 ovarian cancer patient samples to compute: (1) the tumor mutational burden for all genes and (2) the chromosomal copy number alterations associated with the onset/progression of ovarian cancer. Tumor mutational burden is reduced in the late vs. early stages, with the highest levels being associated with loss-of-function mutations in DNA-repair genes. Nucleotide variation and copy number alterations associated with known cancer driver genes are selectively favored over ovarian cancer development. The results indicate that genetic variation is a significant contributor to the onset and progression of ovarian cancer. The measurement of the relative levels of genetic variation associated with individual ovarian cancer patient tumors may be a clinically valuable predictor of potential tumor aggressiveness and resistance to chemotherapy. Tumors found to be associated with high levels of genetic variation may help in the clinical identification of high-risk ovarian cancer patients who could benefit from more frequent monitoring.

Single-Cell Analysis in the Omics Era: Technologies and Applications in Cancer

Cancer molecular profiling obtained with conventional bulk sequencing describes average alterations obtained from the entire cellular population analyzed. In the era of precision medicine, this approach is unable to track tumor heterogeneity and cannot be exploited to unravel the biological processes behind clonal evolution. In the last few years, functional single-cell omics has improved our understanding of cancer heterogeneity. This approach requires isolation and identification of single cells starting from an entire population. A cell suspension obtained by tumor tissue dissociation or hematological material can be manipulated using different techniques to separate individual cells, employed for single-cell downstream analysis. Single-cell data can then be used to analyze cell-cell diversity, thus mapping evolving cancer biological processes. Despite its unquestionable advantages, single-cell analysis produces massive amounts of data with several potential biases, stemming from cell manipulation and pre-amplification steps. To overcome these limitations, several bioinformatic approaches have been developed and explored. In this work, we provide an overview of this entire process while discussing the most recent advances in the field of functional omics at single-cell resolution.

A Deadly Liaison between Oxidative Injury and p53 Drives Methyl-Gallate-Induced Autophagy and Apoptosis in HCT116 Colon Cancer Cells

Methyl gallate (MG), which is a gallotannin widely found in plants, is a polyphenol used in traditional Chinese phytotherapy to alleviate several cancer symptoms. Our studies provided evidence that MG is capable of reducing the viability of HCT116 colon cancer cells, while it was found to be ineffective on differentiated Caco-2 cells, which is a model of polarized colon cells. In the first phase of treatment, MG promoted both early ROS generation and endoplasmic reticulum (ER) stress, sustained by elevated PERK, Grp78 and CHOP expression levels, as well as an upregulation in intracellular calcium content. Such events were accompanied by an autophagic process (16-24 h), where prolonging the time (48 h) of MG exposure led to cellular homeostasis collapse and apoptotic cell death with DNA fragmentation and p53 and γH2Ax activation. Our data demonstrated that a crucial role in the MG-induced mechanism is played by p53. Its level, which increased precociously (4 h) in MG-treated cells, was tightly intertwined with oxidative injury. Indeed, the addition of N-acetylcysteine (NAC), which is a ROS scavenger, counteracted the p53 increase, as well as the MG effect on cell viability. Moreover, MG promoted p53 accumulation into the nucleus and its inhibition by pifithrin-α (PFT-α), which is a negative modulator of p53 transcriptional activity, enhanced autophagy, increased the LC3-II level and inhibited apoptotic cell death. These findings provide new clues to the potential action of MG as a possible anti-tumor phytomolecule for colon cancer treatment.

Anti-Inflammatory and Cytotoxic Activities of Clerodane-Type Diterpenes

The secondary metabolites of clerodane diterpenoids have been found in several plant species from various families and in other organisms. In this review, we included articles on clerodanes and neo-clerodanes with cytotoxic or anti-inflammatory activity from 2015 to February 2023. A search was conducted in the following databases: PubMed, Google Scholar and Science Direct, using the keywords clerodanes or neo-clerodanes with cytotoxicity or anti-inflammatory activity. In this work, we present studies on these diterpenes with anti-inflammatory effects from 18 species belonging to 7 families and those with cytotoxic activity from 25 species belonging to 9 families. These plants are mostly from the Lamiaceae, Salicaceae, Menispermaceae and Euphorbiaceae families. In summary, clerodane diterpenes have activity against different cell cancer lines. Specific antiproliferative mechanisms related to the wide range of clerodanes known today have been described, since many of these compounds have been identified, some of which we barely know their properties. It is very possible that there are even more compounds than those described today, in such a way that makes it an open field to discover. Furthermore, some diterpenes presented in this review have already-known therapeutic targets, and therefore, their potential adverse effects can be predicted in some way.

The INFINITY study protocol: a retrospective cohort study on decision making and clinical impact of biomarker-driven precision oncology in routine clinical practice

BACKGROUND

Precision oncology, defined as treatment of patients with targeted therapies matched to specific molecular alterations, has entered routine clinical practice. Particularly in patients with advanced cancer or hematologic malignancies, for whom no further standard therapies are available, this approach is increasingly applied as last resort option outside of the approved indication. However, data on patient outcomes are not systematically collected, analyzed, reported, and shared. We have initiated the INFINITY registry to provide evidence from routine clinical practice to fill this knowledge gap.

METHODS

INFINITY is a retrospective, non-interventional cohort study conducted at approximately 100 sites in Germany (office-based oncologists/hematologists and hospitals). We aim to include 500 patients with advanced solid tumors or hematologic malignancies who received a non-standard targeted therapy based on potentially actionable molecular alterations or biomarkers. INFINITY aims to provide insights into the use of precision oncology in routine clinical practice within Germany. We systematically collect details on patient and disease characteristics, molecular testing, clinical decision-making, treatment, and outcome.

DISCUSSION

INFINITY will provide evidence on the current biomarker landscape driving treatment decisions in routine clinical care. It will also provide insights on effectiveness of precision oncology approaches in general, and of specific drug class/alteration matches used outside their approved indications.

TRIAL REGISTRATION

The study is registered at ClinicalTrials.gov, NCT04389541.

Stress granules: functions and mechanisms in cancer

Stress granules (SGs) are non-enveloped structures formed primarily via protein and RNA aggregation under various stress conditions, including hypoxia and viral infection, as well as oxidative, osmotic, and heat-shock stress. SGs assembly is a highly conserved cellular strategy to reduce stress-related damage and promote cell survival. At present, the composition and dynamics of SGs are well understood; however, data on the functions and related mechanisms of SGs are limited. In recent years, SGs have continued to attract attention as emerging players in cancer research. Intriguingly, SGs regulate the biological behavior of tumors by participating in various tumor-associated signaling pathways, including cell proliferation, apoptosis, invasion and metastasis, chemotherapy resistance, radiotherapy resistance, and immune escape. This review discusses the roles and mechanisms of SGs in tumors and suggests novel directions for cancer treatment.

A cyanine-based NIR fluorescent Vemurafenib analog to probe BRAFV600E in cancer cells

BRAF represents one of the most frequently mutated protein kinase genes and BRAF^V600E mutation may be found in many types of cancer, including hairy cell leukemia (HCL), anaplastic thyroid cancer (ATC), colorectal cancer and melanoma. Herein, a fluorescent probe, based on the structure of the highly specific BRAF^V600E inhibitor Vemurafenib (Vem, 1) and featuring the NIR fluorophore cyanine-5 (Cy5), was straightforwardly synthesized and characterized (Vem-L-Cy5, 3), showing promising spectroscopic properties. Biological validation in BRAF^V600E-mutated cancer cells evidenced the ability of 3 to penetrate inside the cells, specifically binding to its elective target BRAF^V600E with high affinity, and inhibiting MEK phosphorylation and cell growth with a potency comparable to that of native Vem 1. Taken together, these data highlight Vem-L-Cy5 3 as a useful tool to probe BRAF^V600E mutation in cancer cells, and suitable to acquire precious insights for future developments of more informed BRAF inhibitors-centered therapeutic strategies.

Personalizing neoadjuvant immune-checkpoint inhibition in patients with melanoma

Neoadjuvant immune-checkpoint inhibition is a promising emerging treatment approach for patients with surgically resectable macroscopic stage III melanoma. The neoadjuvant setting provides an ideal platform for personalized therapy owing to the very homogeneous nature of the patient population and the opportunity for pathological response assessments within several weeks of starting treatment, thereby facilitating the efficient identification of novel biomarkers. A pathological response to immune-checkpoint inhibitors has been shown to be a strong surrogate marker of both recurrence-free survival and overall survival, enabling timely analyses of the efficacy of novel therapies in patients with early stage disease. Patients with a major pathological response (defined as the presence of ≤10% viable tumour cells) have a very low risk of recurrence, which offers an opportunity to adjust the extent of surgery and any subsequent adjuvant therapy and follow-up monitoring. Conversely, patients who have only a partial pathological response or who do not respond to neoadjuvant therapy still might benefit from therapy escalation and/or class switch during adjuvant therapy. In this Review, we outline the concept of a fully personalized neoadjuvant treatment approach exemplified by the current developments in neoadjuvant therapy for patients with resectable melanoma, which could provide a template for the development of similar approaches for patients with other immune-responsive cancers in the near future.

Hope in the era of precision oncology: a qualitative study of informal caregivers' experiences

OBJECTIVES

To explore informal caregivers' perspectives on precision medicine in cancer care.

DESIGN

Semi-structured interviews with the informal caregivers of people living with cancer and receiving targeted/immunotherapies. Interview transcripts were analysed thematically using a framework approach.

SETTING

Recruitment was facilitated by two hospitals and five Australian cancer community groups.

PARTICIPANTS

Informal caregivers (n=28; 16 men, 12 women; aged 18-80) of people living with cancer and receiving targeted/immunotherapies.

RESULTS

Thematic analysis identified three findings, centred largely on the pervasive theme of hope in relation to precision therapies including: (1) precision as a key component of caregivers' hope; (2) hope as a collective practice between patients, caregivers, clinicians and others, which entailed work and obligation for caregivers; and (3) hope as linked to expectations of further scientific progress, even if there may be no personal, immediate benefit.

CONCLUSIONS

Innovation and change in precision oncology are rapidly reconfiguring the parameters of hope for patients and caregivers, creating new and difficult relational moments and experiences in everyday life and in clinical encounters. In the context of a shifting therapeutic landscape, caregivers' experiences illustrate the need to understand hope as collectively produced, as emotional and moral labour, and as entangled in broader cultural expectations of medical advances. Such understandings may help clinicians as they guide patients and caregivers through the complexities of diagnosis, treatment, emerging evidence and possible futures in the precision era. Developing a better understanding of informal caregivers' experiences of caring for patients receiving precision therapies is important for improving support to patients and their caregivers.

Combining cell-free RNA with cell-free DNA in liquid biopsy for hematologic and solid tumors

Current use of liquid biopsy is based on cell-free DNA (cfDNA) and the evaluation of mutations or methylation pattern. However, expressed RNA can capture mutations, changes in expression levels due to methylation, and provide information on cell of origin, growth, and proliferation status. We developed an approach to isolate cell-free total nucleic acid (cfDNA) and used targeted next generation sequencing to sequence cell-free RNA (cfRNA) and cfDNA as new approach in liquid biopsy. We demonstrate that cfRNA is overall more sensitive than cfDNA in detecting mutations. We show that cfRNA is reliable in detecting fusion genes and cfDNA is reliable in detecting chromosomal gains and losses. cfRNA levels of various solid tumor biomarkers were significantly higher (P < 0.0001) in samples from solid tumors as compared with normal control. Similarly, cfRNA lymphoid markers and cfRNA myeloid markers were all higher in lymphoid and myeloid neoplasms, respectively as compared with control (P < 0.0001). Using machine learning we demonstrate cfRNA was highly predictive of diagnosis (AUC >0.98) of solid tumors, B-cell lymphoid neoplasms, T-cell lymphoid neoplasms, and myeloid neoplasms. In evaluating the host immune system, cfRNA CD4:CD8B and CD3D:CD19 ratios in normal controls were as expected (median: 5.92 and 6.87, respectively) and were significantly lower in solid tumors (P < 0.0002). This data suggests that liquid biopsy combining analysis of cfRNA with cfDNA is practical and may provide helpful information in predicting genomic abnormalities, diagnosis of neoplasms and evaluating both the tumor biology and the host response.

Automated Dashboards for the Identification of Pathogenic Circulating Tumor DNA Mutations in Longitudinal Blood Draws of Cancer Patients

The longitudinal monitoring of patient circulating tumor DNA (ctDNA) provides a powerful method for tracking the progression, remission, and recurrence of several types of cancer. Often, clinical and research approaches involve the manual review of individual liquid biopsy reports after sampling and genomic testing. Here, we describe a process developed to integrate techniques utilized in data science within a cancer research framework. Using data collection, an analysis that classifies genetic cancer mutations as pathogenic, and a patient matching methodology that identifies the same donor within all liquid biopsy reports, the manual work for research personnel is drastically reduced. Automated dashboards provide longitudinal views of patient data for research studies to investigate tumor progression and treatment efficacy via the identification of ctDNA variant allele frequencies over time.

Slide-to-Slide Tissue Transfer and Array Assembly From Limited Samples for Comprehensive Molecular Profiling

Tissue microarrays (TMA) have become an important tool in high-throughput molecular profiling of tissue samples in the translational research setting. Unfortunately, high-throughput profiling in small biopsy specimens or rare tumor samples (eg, orphan diseases or unusual tumors) is often precluded owing to limited amounts of tissue. To overcome these challenges, we devised a method that allows tissue transfer and construction of TMAs from individual 2- to 5-μm sections for subsequent molecular profiling. We named the technique slide-to-slide (STS) transfer, and it requires a series of chemical exposures (so-called xylene-methacrylate exchange) in combination with rehydrated lifting, microdissection of donor tissues into multiple small tissue fragments (methacrylate-tissue tiles), and subsequent remounting on separate recipient slides (STS array slide). We developed the STS technique by assessing the efficacy and analytical performance using the following key metrics: (a) dropout rate, (b) transfer efficacy, (c) success rates using different antigen-retrieval methods, (d) success rates of immunohistochemical stains, (e) fluorescent in situ hybridization success rates, and (f) DNA and (g) RNA extraction yields from single slides, which all functioned appropriately. The dropout rate ranged from 0.7% to 6.2%; however, we applied the same STS technique successfully to fill these dropouts ("rescue" transfer). Hematoxylin and eosin assessment of donor slides confirmed a transfer efficacy of >93%, depending on the size of the tissue (range, 76%-100%). Fluorescent in situ hybridization success rates and nucleic acid yields were comparable with those of traditional workflows. In this study, we present a quick, reliable, and cost-effective method that offers the key advantages of TMAs and other molecular techniques-even when tissue is sparse. The perspectives of this technology in biomedical sciences and clinical practice are promising, given that it allows laboratories to create more data with less tissue.

Impact of Biomarker-Matched Therapies on Outcomes in Patients with Sarcoma Enrolled in Early-Phase Clinical Trials (SAMBA 101)

PURPOSE

Developing new therapeutics for any of the more than 100 sarcoma subtypes presents a challenge. After progression from standard therapies, patients with sarcoma may be referred for enrollment in early-phase trials. This study aimed to investigate whether enrollment in biomarker-matched early-phase clinical trials leads to better outcomes for patients with advanced sarcoma.

EXPERIMENTAL DESIGN

In this retrospective analysis, investigational treatment characteristics and longitudinal survival outcomes were analyzed in patients with biopsy-confirmed sarcoma enrolled in early-phase trials at MD Anderson Cancer Center from May 2006 to July 2021.

RESULTS

Five hundred eighty-seven patients were included [405 soft tissue, 122 bone, 60 gastrointestinal stromal tumor (GIST); median of three prior lines of therapy]. Most common subtypes were leiomyosarcoma (17.2%), liposarcoma (14.0%), and GIST (10.2%). Molecular testing was available for 511 patients (87.1%); 221 patients (37.6%) were treated in matched trials. Overall response rate was 13.1% matched compared with 4.9% in unmatched (P < 0.001); the clinical benefit rate at 6 months was 43.9% vs. 19.9% (P < 0.001). Progression-free survival was longer for patients in matched trials (median, 5.5 vs. 2.4 months; P < 0.001), and overall survival was also superior for patients in matched trials (median, 21.5 vs. 12.3 months; P < 0.001). The benefit of enrollment in matched trials was maintained when patients with GIST were excluded from the analysis.

CONCLUSIONS

Enrollment in biomarker-matched early-phase trials is associated with improved outcomes in heavily pretreated patients with metastatic sarcoma. Molecular testing of tumors from patients with advanced sarcoma and enrollment in matched trials is a reasonable therapeutic strategy.

Profile of the multicenter cohort of the German Cancer Consortium's Clinical Communication Platform

Treatment concepts in oncology are becoming increasingly personalized and diverse. Successively, changes in standards of care mandate continuous monitoring of patient pathways and clinical outcomes based on large, representative real-world data. The German Cancer Consortium's (DKTK) Clinical Communication Platform (CCP) provides such opportunity. Connecting fourteen university hospital-based cancer centers, the CCP relies on a federated IT-infrastructure sourcing data from facility-based cancer registry units and biobanks. Federated analyses resulted in a cohort of 600,915 patients, out of which 232,991 were incident since 2013 and for which a comprehensive documentation is available. Next to demographic data (i.e., age at diagnosis: 2.0% 0-20 years, 8.3% 21-40 years, 30.9% 41-60 years, 50.1% 61-80 years, 8.8% 81+ years; and gender: 45.2% female, 54.7% male, 0.1% other) and diagnoses (five most frequent tumor origins: 22,523 prostate, 18,409 breast, 15,575 lung, 13,964 skin/malignant melanoma, 9005 brain), the cohort dataset contains information about therapeutic interventions and response assessments and is connected to 287,883 liquid and tissue biosamples. Focusing on diagnoses and therapy-sequences, showcase analyses of diagnosis-specific sub-cohorts (pancreas, larynx, kidney, thyroid gland) demonstrate the analytical opportunities offered by the cohort's data. Due to its data granularity and size, the cohort is a potential catalyst for translational cancer research. It provides rapid access to comprehensive patient groups and may improve the understanding of the clinical course of various (even rare) malignancies. Therefore, the cohort may serve as a decisions-making tool for clinical trial design and contributes to the evaluation of scientific findings under real-world conditions.

Photoacoustic/ultrasound-guided gene silencing: Multifunctional microbubbles for treating adjuvant-induced arthritis

AIMS

To effectively deliver small interfering RNA (siRNA) to inflammatory tissues for treating rheumatoid arthritis (RA), we developed the multifunctional microbubbles (MBs) to perform photoacoustic/ultrasound-guided gene silencing.

METHODS

Fluorescein amidite (FAM)-labelled tumour necrosis factor-α (TNF-α)-siRNA and cationic MBs were mixed to fabricate FAM-TNF-α-siRNA-cMBs. The cell transfection efficacy of FAM-TNF-α-siRNA-cMBs was evaluated in vitro on RAW264.7 cells. Subsequently, wistar rats with adjuvant-induced arthritis (AIA) were injected intravenously with MBs and simultaneously subjected to low-frequency ultrasound for ultrasound-targeted microbubble destruction (UTMD). Photoacoustic imaging (PAI) was utilized to visualize the distribution of siRNA. And the clinical and pathological changes of AIA rats was estimated.

RESULTS

FAM-TNF-α-siRNA-cMBs were evenly distributed within the RAW264.7 cells and significantly reduced TNF-α mRNA levels of the cells. For AIA rats, the entering and collapsing of MBs was visualized by contrast-enhanced ultrasound (CEUS). Photoacoustic imaging showed markedly enhanced signals following injection, indicating localization of the FAM-labelled siRNA. The articular tissues of the AIA rats treated with TNF-α-siRNA-cMBs and UTMD showed decreased TNF-α expression levels.

CONCLUSIONS

The theranostic MBs exhibited a TNF-α gene silencing effect under the guidance of CEUS and PAI. The theranostic MBs served as vehicles for delivering siRNA as well as contrast agents for CEUS and PAI.

Assessing patient-level knowledge of precision medicine in a community health center setting

As precision medicine approaches are implemented, cancer treatment decisions have come to require comprehension of genetic tests and their role in risk stratification and treatment options. Acceptance and implementation of precision medicine requires patient understanding of numeracy, genetic literacy, health literacy, and medical trust. Implementing precision medicine in a US federally qualified community health center (FQCHC) setting has received little attention. Using a mixed-methods approach, we sought to identify patient-level factors influencing the understanding of cancer risk and precision medicine among FQCHC patients. We enrolled 26 English-speaking adults aged 40-79 years. Participants enrolled in focus groups and completed surveys to assess patient-level understanding of precision medicine, numeracy, and health literacy. The majority of participants were female (77%) and self-identified as African American (89%). Approximately one-third reported having a high school degree or less. While health literacy was generally high, 42% felt that genes or genetics had little impact on health and most (69%) reported little familiarity with precision medicine. Many participants reported that trust in their providers was extremely or very important when receiving genetic tests. Numeracy levels were moderate, with nearly half reporting some discomfort working with fractions and 38% finding numerical information only occasionally useful. Findings suggest that patients may lack familiarity with precision medicine concepts relevant for understanding cancer treatment decisions. Future educational efforts may help bridge the gap in patient understanding and facilitate equitable opportunities for precision medicine for all patients, including those seeking care from community health centers.

Histology-Agnostic Drugs: A Paradigm Shift-A Narrative Review

Cancer diagnosis and therapeutics have been traditionally based on pathologic classification at the organ of origin. The availability of an unprecedented amount of clinical and biologic data provides a unique window of opportunity for the development of new drugs. What was once treated as a homogeneous disease with a one-size-fits-all approach was shown to be a rather heterogeneous condition, with multiple targetable mutations that can vary during the course of the disease. Clinical trial designs have had to adapt to the exponential growth of targetable mechanisms and new agents, with ensuing challenges that are closer to those experienced with rare diseases and orphan medicines. To face these problems, precision/enrichment and other novel trial designs have been developed, and the concept of histology-agnostic targeted therapeutic agents has emerged. Patients are selected for a specific agent based on specific genomic or molecular alterations, with the same compound used to potentially treat a multiplicity of cancers, granted that the actionable driver alteration is present. There are currently approved drugs for such indications, but this approach has raised issues on multiple levels. This review aims to address the challenges of this new concept and provide insights into possible solutions and frameworks on how to tackle them.

Chemotherapy-induced phlebitis via the GBP5/NLRP3 inflammasome axis and the therapeutic effect of aescin

BACKGROUND AND PURPOSE

Intravenous infusion of chemotherapy drugs can cause severe chemotherapy-induced phlebitis (CIP) in patients. However, the underlying mechanism of CIP development remains unclear.

EXPERIMENTAL APPROACH

RNA-sequencing analysis was used to identify potential disease targets in CIP. Guanylate binding protein-5 (GBP5) genetic deletion approaches also were used to investigate the role of GBP5 in NLR family pyrin domain containing 3 (NLRP3) inflammasome activation in lipopolysaccharide (LPS) primed murine bone-marrow-derived macrophages (BMDMs) induced by vinorelbine (VIN) in vitro and in mouse models of VIN-induced CIP in vivo. The anti-CIP effect of aescin was evaluated, both in vivo and in vivo.

KEY RESULTS

Here, we show that the expression of GBP5 was upregulated in human peripheral blood mononuclear cells from CIP patients. Genetic ablation of GBP5 in murine macrophages significantly alleviated VIN-induced CIP in the experimental mouse model. Mechanistically, GBP5 contributed to the inflammatory responses through activating NLRP3 inflammasome and driving the production of the inflammatory cytokine IL-1β. Moreover, aescin, a mixture of triterpene saponins extracted from horse chestnut seed, can alleviate CIP by inhibiting the GBP5/NLRP3 axis.

CONCLUSION AND IMPLICATIONS

These findings suggest that GBP5 is an important regulator of NLRP3 inflammasome in CIP mouse model. Our work further reveals that aescin may serve as a promising candidate in the clinical treatment of CIP.

Translocations and Gene Fusions in Sinonasal Malignancies

PURPOSE OF REVIEW

During the past few years there has been an expansion in our understanding of gene fusions and translocations involved in cancer of the sinonasal tract. Here we review the downstream biologic effects, clinical characteristics, and pathologic features of these tumors. The molecular consequences and neo-antigens resulting from these chromosomal aberrations are considered and targets for current and future clinical trials discussed.

RECENT FINDINGS

Several new, clinically relevant, chromosomal aberrations have been discovered and evaluated to varying degrees in sinonasal tumors including DEK::AFF2, BRD4::NUT, ADCK4::NUMBL, and ETV6::NTRK3. Sinonasal malignancies demonstrate a diverse genetic landscape and varying clinical courses. Recent studies illustrate that gene fusions and translocations may play a role in carcinogenesis in certain sinonasal tumor subtypes and may be used to develop new biomarker-driven and patient-centered treatments.

Opinion paper on the systematic application of integrated bioinformatic tools to actuate routine precision medicine in poly-treated patients

Precision Medicine is a reality in selected medical areas, as oncology, or in excellent healthcare structures, but it is still far to reach million patients who could benefit from this medical concept. Here, we sought to highlight how the time is ripe to achieve horizontal delivery to a significant larger audience of patients, represented by the poly-treated patients. Combination therapies are frequent (especially in the elderly, to treat comorbidities) and are related to decreased drug safety and efficacy, disease's exacerbation, additional treatments, hospitalization. But the recent development and validation of bioinformatic tools, aimed to automatic evaluation and optimization of poly-therapies, according to the unique individual characteristics (including genotype), is ready to change the daily approach to pharmacological prescription.

Prognostic Mutational Signatures of NSCLC Patients treated with chemotherapy, immunotherapy and chemoimmunotherapy

Different types of therapy are currently being used to treat non-small cell lung cancer (NSCLC) depending on the stage of tumor and the presence of potentially druggable mutations. However, few biomarkers are available to guide clinicians in selecting the most effective therapy for all patients with various genetic backgrounds. To examine whether patients' mutation profiles are associated with the response to a specific treatment, we collected comprehensive clinical characteristics and sequencing data from 524 patients with stage III and IV NSCLC treated at Atrium Health Wake Forest Baptist. Overall survival based Cox-proportional hazard regression models were applied to identify mutations that were "beneficial" (HR < 1) or "detrimental" (HR > 1) for patients treated with chemotherapy (chemo), immune checkpoint inhibitor (ICI) and chemo+ICI combination therapy (Chemo+ICI) followed by the generation of mutation composite scores (MCS) for each treatment. We also found that MCS is highly treatment specific that MCS derived from one treatment group failed to predict the response in others. Receiver operating characteristics (ROC) analyses showed a superior predictive power of MCS compared to TMB and PD-L1 status for immune therapy-treated patients. Mutation interaction analysis also identified novel co-occurring and mutually exclusive mutations in each treatment group. Our work highlights how patients' sequencing data facilitates the clinical selection of optimized treatment strategies.

Precision Oncology: Evolving Clinical Trials across Tumor Types

Advances in molecular technologies and targeted therapeutics have accelerated the implementation of precision oncology, resulting in improved clinical outcomes in selected patients. The use of next-generation sequencing and assessments of immune and other biomarkers helps optimize patient treatment selection. In this review, selected precision oncology trials including the IMPACT, SHIVA, IMPACT2, NCI-MPACT, TAPUR, DRUP, and NCI-MATCH studies are summarized, and their challenges and opportunities are discussed. Brief summaries of the new ComboMATCH, MyeloMATCH, and iMATCH studies, which follow the example of NCI-MATCH, are also included. Despite the progress made, precision oncology is inaccessible to many patients with cancer. Some patients' tumors may not respond to these treatments, owing to the complexity of carcinogenesis, the use of ineffective therapies, or unknown mechanisms of tumor resistance to treatment. The implementation of artificial intelligence, machine learning, and bioinformatic analyses of complex multi-omic data may improve the accuracy of tumor characterization, and if used strategically with caution, may accelerate the implementation of precision medicine. Clinical trials in precision oncology continue to evolve, improving outcomes and expediting the identification of curative strategies for patients with cancer. Despite the existing challenges, significant progress has been made in the past twenty years, demonstrating the benefit of precision oncology in many patients with advanced cancer.

Computational Methods Summarizing Mutational Patterns in Cancer: Promise and Limitations for Clinical Applications

Since the rise of next-generation sequencing technologies, the catalogue of mutations in cancer has been continuously expanding. To address the complexity of the cancer-genomic landscape and extract meaningful insights, numerous computational approaches have been developed over the last two decades. In this review, we survey the current leading computational methods to derive intricate mutational patterns in the context of clinical relevance. We begin with mutation signatures, explaining first how mutation signatures were developed and then examining the utility of studies using mutation signatures to correlate environmental effects on the cancer genome. Next, we examine current clinical research that employs mutation signatures and discuss the potential use cases and challenges of mutation signatures in clinical decision-making. We then examine computational studies developing tools to investigate complex patterns of mutations beyond the context of mutational signatures. We survey methods to identify cancer-driver genes, from single-driver studies to pathway and network analyses. In addition, we review methods inferring complex combinations of mutations for clinical tasks and using mutations integrated with multi-omics data to better predict cancer phenotypes. We examine the use of these tools for either discovery or prediction, including prediction of tumor origin, treatment outcomes, prognosis, and cancer typing. We further discuss the main limitations preventing widespread clinical integration of computational tools for the diagnosis and treatment of cancer. We end by proposing solutions to address these challenges using recent advances in machine learning.

Specific High-Sensitivity Enzymatic Reporter UnLOCKing-Mediated Detection of Oncogenic BCR::ABL1 and EGFR Rearrangements

Advances in molecular medicine have placed nucleic acid detection methods at the center of an increasing number of clinical applications. Polymerase chain reaction (PCR)-based diagnostics have been widely adopted for their versatility, specificity, and sensitivity. However, recently reported clustered regularly interspaced short palindromic repeats-based methods have demonstrated equivalent to superior performance, with increased portability and reduced processing time and cost. In this study, we applied Specific High-Sensitivity Enzymatic Reporter UnLOCKing (SHERLOCK) technology to the detection of oncogenic rearrangements. We implemented SHERLOCK for the detection of BCR::ABL1 mRNA, a hallmark of chronic myeloid leukemia (CML), and EGFR DNA oncogenic alleles, frequently detected in glioblastoma and non-small cell lung cancer (NSCLC). SHERLOCK enabled rapid, sensitive, and variant-specific detection of BCR::ABL1 and EGFR alterations. Compared with the gold-standard PCR-based methods currently used in clinic, SHERLOCK achieved equivalent to greater sensitivity, suggesting it could be a new tool in CML and NSCLC, to detect low level of molecular residual disease.

Quantitative cost‑effectiveness index of cancer treatments

In spite of advancements being made in technology and treatment strategies, which have markedly improved the survival rate of patients, the cost of cancer care worldwide has increased over the past decades. The presence of several cost-effectiveness ratios has provided significant indexes to assess the balance between cost and effectiveness. However, the currently available indexes still fail to provide a comprehensive and objective evaluation of cancer treatment. Therefore, the present study developed a novel approach, namely a quantitative cost-effectiveness index of cancer treatment, based on the calculation of the hospitalization expense index and efficacy evaluation index. The present study used the data of 16 patients with childhood acute myeloid leukemia who received the high-dose chemotherapy as an example, and the quantitative cost-effectiveness index was used to evaluate the value of this approach. As the increasing prevalence of cancer and the rising cost of pharmaceuticals have contributed to the expenditure, the development of this index may help to solve the current dilemma of cancer treatment and may prove to be essential for the development of an effective approach which may be accessible to and affordable by common persons; thus would then lead to a higher cure rate.

The role of long non-coding RNA HCG18 in cancer

The incidence of cancer is increasing worldwide and is becoming the most common cause of death. Identifying new biomarkers for cancer diagnosis and prognosis is important for developing cancer treatment strategies and reducing mortality. Long non-coding RNAs (lncRNAs) are non-coding, single-stranded RNAs that play an important role as oncogenes or tumor suppressors in the occurrence and development of human tumors. Abnormal expression of human leukocyte antigen complex group 18 (HCG18) is observed in many types of cancer, and its imbalance is closely related to cancer progression. HCG18 regulates cell proliferation, invasion, metastasis, and anti-apoptosis through a variety of mechanisms. Therefore, HCG18 is a potential tumor biomarker and therapeutic target. However, the therapeutic significance of HCG18 has not been well studied, and future research may develop new intervention strategies to combat cancer. In this study, we reviewed the biological function, mechanism, and potential clinical significance of HCG18 in various cancers to provide a reference for future research.

Novel therapeutic approaches for pleural mesothelioma identified by functional ex vivo drug sensitivity testing

OBJECTIVES

Pleural mesothelioma (PM) is an aggressive malignancy with limited treatment options. The first-line therapy has remained unchanged for two decades and consists of pemetrexed in combination with cisplatin. Immune-checkpoint inhibitors (nivolumab plus ipilimumab) have high response rates, resulting in recent updates in treatment recommendations by the U.S. Food and Drug Administration. However, the overall benefits of combination treatment are modest, suggesting that other targeted therapy options should be investigated.

MATERIALS AND METHODS

We employed high-throughput drug sensitivity and resistance testing on five established PM cell lines using 527 cancer drugs in a 2D setting. Drugs of the greatest potential (n = 19) were selected for further testing in primary cell models derived from pleural effusions of seven PM patients.

RESULTS

All established and primary patient-derived PM cell models were sensitive to the mTOR inhibitor AZD8055. Furthermore, another mTOR inhibitor (temsirolimus) showed efficacy in most of the primary patient-derived cells, although a less robust effect was observed when compared with the established cell lines. Most of the established cell lines and all patient-derived primary cells exhibited sensitivity to the PI3K/mTOR/DNA-PK inhibitor LY3023414. The Chk1 inhibitor prexasertib showed activity in 4/5 (80%) of the established cell lines and in 2/7 (29%) of the patient-derived primary cell lines. The BET family inhibitor JQ1 showed activity in four patient-derived cell models and in one established cell line.

CONCLUSION

mTOR and Chk1 pathways had promising results with established mesothelioma cell lines in an ex vivo setting. In patient-derived primary cells, drugs targeting mTOR pathway in particular showed efficacy. These findings may inform novel treatment strategies for PM.

Understanding the Current Landscape of Kidney Disease in Canada to Advance Precision Medicine Guided Personalized Care

Purpose of Review

To understand the impact of kidney disease in Canada and the priority areas of kidney research that can benefit from patient-oriented, precision medicine research using novel technologies.

Sources of Information

Information was collected through discussions between health care professionals, researchers, and patient partners. Literature was compiled using search engines (PubMed, PubMed central, Medline, and Google) and data from the Canadian Organ Replacement Register.

Methods

We reviewed the impact, prevalence, economic burden, causes of kidney disease, and priority research areas in Canada. After reviewing the priority areas for kidney research, potential avenues for future research that can integrate precision medicine initiatives for patient-oriented research were outlined.

Key Findings

Chronic kidney disease (CKD) remains among the top causes of morbidity and mortality in the world and exerts a large financial strain on the health care system. Despite the increasing number of people with CKD, funding for basic kidney research continues to trail behind other diseases. Current funding strategies favor existing clinical treatment and patient educational strategies. The identification of genetic factors for various forms of kidney disease in the adult and pediatric populations provides mechanistic insight into disease pathogenesis. Allocation of resources and funding toward existing high-yield personalized research initiatives have the potential to significantly affect patient-oriented research outcomes but will be difficult due to a constant decline of funding for kidney research.

Limitations

This is an overview primarily focused on Canadian-specific literature rather than a comprehensive systematic review of the literature. The scope of our findings and conclusions may not be applicable to health care systems in other countries.

Personalized downstaging treatment with ADT, chemotherapy and add-on zimberelimab for very-high-risk clinically localized prostate cancer: A case report

RATIONALE

Very-high-risk prostate cancer (PCa) is associated with poor prognosis. Radical prostatectomy (RP) is an option for selected high-risk PCa cases, especially in younger, healthier patients. However, a high Gleason score and high T stage can increase the risk of RP. Neoadjuvant therapy has been reported in high- or very-high-risk PCa, but its clinical use remains controversial.

DIAGNOSES AND PATIENT CONCERNS

A 53-year-old male patient diagnosed with PCa was referred to our hospital. The patient's Gleason score was 4 + 5, and the clinical stage was T4N0M0, with an abnormally enlarged prostate adhering to the rectum and leading to decreased mobility of the rectum, suggesting a very-high-risk PCa inappropriate for RP. However, instead of external beam radiation therapy, which is the standard treatment for inoperable PCa, the patient insisted on RP.

INTERVENTIONS

Androgen deprivation therapy plus docetaxel was chosen as the first downstaging treatment; however, the tumor was too slightly downsized to undergo RP. Therefore, zimberelimab was added after confirmation of a genomic feature of high microsatellite instability and high tumor mutational burden status.

OUTCOMES

After 4 doses of zimberelimab, the prostate shrank significantly. The patient successfully completed RP after another dose of zimberelimab, and achieved a pathological complete response (pCR).

LESSONS

Our case represents a successful attempt at personalized treatment and provides preliminary evidence for the clinical use of downstaging therapy of androgen deprivation therapy, chemotherapy, and add-on zimberelimab for very-high-risk clinically localized PCa.

Prognostic significance of ING3 expression in patients with cancer: A systematic review and meta-analysis

Background

It has been reported that ING3 inhibits the progression of various cancers. However, some studies have shown that it promotes the development of prostate cancer. The purpose of this study was to investigate whether ING3 expression is associated with the prognosis of patients with cancer.

Materials and methods

PubMed, Cochrane Database, Embase, Medline, ScienceDirect, Scopus and Web of Science were searched until September 2022. The hazard ratio (HR)/odds ratio (OR) and 95% confidence interval (95% CI) were calculated using Stata 17 software. We used the Newcastle-Ottawa Scale (NOS) to assess the risk of bias.

Result

Seven studies involving 2371 patients with five types of cancer were included. The results showed that high expression of ING3 was negatively associated with a more advanced TNM stage (III-IV vs. I-II) (OR=0.61, 95% CI: 0.43-0.86), lymph node metastasis (OR=0.67, 95% CI: 0.49-0.90) and disease-free survival (HR=0.63, 95% CI: 0.37-0.88). However, ING3 expression was not associated with overall survival (HR=0.77, 95% CI: 0.41-1.12), tumor size (OR=0.67, 95% CI: 0.33-1.37), tumor differentiation (OR=0.86, 95% CI: 0.36-2.09) and gender (OR=1.14, 95% CI: 0.78-1.66).

Conclusion

This study showed that the expression of ING3 was associated with better prognosis, suggesting that ING3 may be a potential biomarker for cancer prognosis.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, identifier (CRD42022306354).