Personalized Medicine: Recent Progress in Cancer Therapy

It Is All in the Genes: A Story of Unexpected Survival in a 67-Year-Old Male with Metastatic Pancreatic Cancer

Background

We describe a case report of a 67-year-old male with PDAC who experienced an exceptional survival outcome during systemic therapy and its implications in precision medicine. We hypothesize that his outcomes are attributable, in part, to a germline BRCA2 deletion and somatic GNAS substitution.

Methods

Retrospective single-patient chart review was performed at the London Regional Cancer Program, as well as a structured literature search spanning all years in PubMed of BRCA and GNAS mutations in pancreatic cancer.

Results

The case described herein represents a 67-year-old male who survived over 27 months after third-line treatment with gemcitabine, docetaxel, and capecitabine (GTX) chemotherapy for metastatic PDAC after progression on gemcitabine and Abraxane and then on FOLFIRINOX. His survival far exceeded the median overall survival metrics. Genetic testing revealed a pathogenic heterozygous germline BRCA2 6643delT p.(Tyr2215Thrfs∗14) frameshift mutation and somatic GNAS 2531G > A p.(Arg844His) mutation.

Conclusions

This case highlights the urgent need to expand our knowledge of cancer biology to advance personalized cancer treatment and therapy development.

Navigating the Blood-Brain Barrier: Challenges and Therapeutic Strategies in Breast Cancer Brain Metastases

Breast cancer (BC) is the most common cancer in women, with metastatic BC being responsible for the highest number of deaths. A frequent site for BC metastasis is the brain. Brain metastasis derived from BC involves the cooperation of multiple genetic, epigenetic, angiogenic, and tumor-stroma interactions. Most of these interactions provide a unique opportunity for development of new therapeutic targets. Potentially targetable signaling pathways are Notch, Wnt, and the epidermal growth factor receptors signaling pathways, all of which are linked to driving BC brain metastasis (BCBM). However, a major challenge in treating brain metastasis remains the blood-brain barrier (BBB). This barrier restricts the access of unwanted molecules, cells, and targeted therapies to the brain parenchyma. Moreover, current therapies to treat brain metastases, such as stereotactic radiosurgery and whole-brain radiotherapy, have limited efficacy. Promising new drugs like phosphatase and kinase modulators, as well as BBB disruptors and immunotherapeutic strategies, have shown the potential to ease the disease in preclinical studies, but remain limited by multiple resistance mechanisms. This review summarizes some of the current understanding of the mechanisms involved in BC brain metastasis and highlights current challenges as well as opportunities in strategic designs of potentially successful future therapies.

Targeting Transcription Factor YY1 for Cancer Treatment: Current Strategies and Future Directions

Cancer represents a significant and persistent global health burden, with its impact underscored by its prevalence and devastating consequences. Whereas numerous oncogenes could contribute to cancer development, a group of transcription factors (TFs) are overactive in the majority of tumors. Targeting these TFs may also combat the downstream oncogenes activated by the TFs, making them attractive potential targets for effective antitumor therapeutic strategy. One such TF is yin yang 1 (YY1), which plays crucial roles in the development and progression of various tumors. In preclinical studies, YY1 inhibition has shown efficacy in inhibiting tumor growth, promoting apoptosis, and sensitizing tumor cells to chemotherapy. Recent studies have also revealed the potential of combining YY1 inhibition with immunotherapy for enhanced antitumor effects. However, clinical translation of YY1-targeted therapy still faces challenges in drug specificity and delivery. This review provides an overview of YY1 biology, its role in tumor development and progression, as well as the strategies explored for YY1-targeted therapy, with a focus on their clinical implications, including those using small molecule inhibitors, RNA interference, and gene editing techniques. Finally, we discuss the challenges and current limitations of targeting YY1 and the need for further research in this area.

Carving joints into nature: reengineering scientific concepts in light of concept-laden evidence

A new wave of proposals suggests that scientists must reassess scientific concepts in light of accumulated evidence. However, reengineering scientific concepts in light of data is challenging because scientific concepts affect the evidence itself in multiple ways. Among other possible influences, concepts (i) prime scientists to overemphasize within-concept similarities and between-concept differences; (ii) lead scientists to measure conceptually relevant dimensions more accurately; (iii) serve as units of scientific experimentation, communication, and theory-building; and (iv) affect the phenomena themselves. When looking for improved ways to carve nature at its joints, scholars must take the concept-laden nature of evidence into account to avoid entering a vicious circle of concept-evidence mutual substantiation.

Oncogenic metabolic reprogramming in breast cancer: focus on signaling pathways and mitochondrial genes

Oncogenic metabolic reprogramming impacts the abundance of key metabolites that regulate signaling and epigenetics. Metabolic vulnerability in the cancer cell is evident from the Warburg effect. The research on metabolism in the progression and survival of breast cancer (BC) is under focus. Oncogenic signal activation and loss of tumor suppressor are important regulators of tumor cell metabolism. Several intrinsic and extrinsic factors contribute to metabolic reprogramming. The molecular mechanisms underpinning metabolic reprogramming in BC are extensive and only partially defined. Various signaling pathways involved in the metabolism play a significant role in the modulation of BC. Notably, PI3K/AKT/mTOR pathway, lactate-ERK/STAT3 signaling, loss of the tumor suppressor Ras, Myc, oxidative stress, activation of the cellular hypoxic response and acidosis contribute to different metabolic reprogramming phenotypes linked to enhanced glycolysis. The alterations in mitochondrial genes have also been elaborated upon along with their functional implications. The outcome of these active research areas might contribute to the development of novel therapeutic interventions and the remodeling of known drugs.

Evaluation of in vitro and in vivo personalized cancer treatment assays for oral squamous cell carcinoma

BACKGROUND

Oral squamous cell carcinoma (OSCC) is a common cancer with a high heterogeneity and few approved treatments. OSCC is one of the least explored areas for precision oncology. In this study, we aimed to test the reliability of our three established rapid cancer systemic treatment-testing assays: human tumour-derived matrix (Myogel)-coated well-plates, zebrafish xenografts, and 3D microfluidic chips.

METHODS

Chemo-, radio- and targeted-therapy testing in Myogel-coated wells and zebrafish xenografts was conducted nine times using five samples; two primary and three metastatic lymph node samples from three OSCC patients. Peripheral blood mononuclear cells (PBMNCs) were isolated from the patients' blood. The response of the tumour cells to radio-, chemo-, and targeted therapy was tested using Myogel-coated wells and zebrafish larvae xenografts. The tumour cells' response to immunotherapy was tested using 3D microfluidic chips. The cells' sensitivity to the treatments was compared with the patients' clinical response. Primary and metastatic lymph node tissue-derived DNA samples from two patients underwent whole exome sequencing to compare the mutational profiles of the samples.

RESULTS

Test results were in line with patients' responses in 7/9 (77%) zebrafish xenograft assays and 5/9 (55%) Myogel-coated wells assays. Immunotherapy testing was done using one metastatic patient sample which matched the patients' response. Differences in responses to treatments between primary and metastatic samples of the same patient were detected in 50% of the zebrafish larvae assays.

CONCLUSIONS

Our results show the potential of using personalized cancer treatment testing assays - specifically zebrafish xenografts that revealed promising results - in OSCC patient samples.

Recent Advances with Precision Medicine Treatment for Breast Cancer including Triple-Negative Sub-Type

Breast cancer is a heterogeneous disease with different molecular subtypes. Breast cancer is the second leading cause of mortality in woman due to rapid metastasis and disease recurrence. Precision medicine remains an essential source to lower the off-target toxicities of chemotherapeutic agents and maximize the patient benefits. This is a crucial approach for a more effective treatment and prevention of disease. Precision-medicine methods are based on the selection of suitable biomarkers to envision the effectiveness of targeted therapy in a specific group of patients. Several druggable mutations have been identified in breast cancer patients. Current improvements in omics technologies have focused on more precise strategies for precision therapy. The development of next-generation sequencing technologies has raised hopes for precision-medicine treatment strategies in breast cancer (BC) and triple-negative breast cancer (TNBC). Targeted therapies utilizing immune checkpoint inhibitors (ICIs), epidermal growth factor receptor inhibitor (EGFRi), poly(ADP-ribose) polymerase inhibitor (PARPi), antibody-drug conjugates (ADCs), oncolytic viruses (OVs), glucose transporter-1 inhibitor (GLUT1i), and targeting signaling pathways are potential treatment approaches for BC and TNBC. This review emphasizes the recent progress made with the precision-medicine therapy of metastatic breast cancer and TNBC.

Enhancing clinical potential of liquid biopsy through a multi-omic approach: A systematic review

In the last years, liquid biopsy gained increasing clinical relevance for detecting and monitoring several cancer types, being minimally invasive, highly informative and replicable over time. This revolutionary approach can be complementary and may, in the future, replace tissue biopsy, which is still considered the gold standard for cancer diagnosis. "Classical" tissue biopsy is invasive, often cannot provide sufficient bioptic material for advanced screening, and can provide isolated information about disease evolution and heterogeneity. Recent literature highlighted how liquid biopsy is informative of proteomic, genomic, epigenetic, and metabolic alterations. These biomarkers can be detected and investigated using single-omic and, recently, in combination through multi-omic approaches. This review will provide an overview of the most suitable techniques to thoroughly characterize tumor biomarkers and their potential clinical applications, highlighting the importance of an integrated multi-omic, multi-analyte approach. Personalized medical investigations will soon allow patients to receive predictable prognostic evaluations, early disease diagnosis, and subsequent ad hoc treatments.

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.

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.

Structure-Based Profiling of Potential Phytomolecules with AKT1 a Key Cancer Drug Target

Identifying cancer biomarkers is imperative, as upregulated genes offer a better microenvironment for the tumor; hence, targeted inhibition is preferred. The theme of our study is to predict molecular interactions between cancer biomarker proteins and selected natural compounds. We identified an overexpressed potential molecular target (AKT1) and computationally evaluated its inhibition by four dietary ligands (isoliquiritigenin, shogaol, tehranolide, and theophylline). The three-dimensional structures of protein and phytochemicals were retrieved from the RCSB PDB database (4EKL) and NCBI’s PubChem, respectively. Rational structure-based docking studies were performed using AutoDock. Results were analyzed based primarily on the estimated free binding energy (kcal/mol), hydrogen bonds, and inhibition constant, Ki, to identify the most effective anti-cancer phytomolecule. Toxicity and drug-likeliness prediction were performed using OSIRIS and SwissADME. Amongst the four phytocompounds, tehranolide has better potential to suppress the expression of AKT1 and could be used for anti-cancer drug development, as inhibition of AKT1 is directly associated with the inhibition of growth, progression, and metastasis of the tumor. Docking analyses reveal that tehranolide has the most efficiency in inhibiting AKT1 and has the potential to be used for the therapeutic management of cancer. Natural compounds targeting cancer biomarkers offer less rejection, minimal toxicity, and fewer side effects.

A Review of Major Danish Biobanks: Advantages and Possibilities of Health Research in Denmark

Biobank research may lead to an improved understanding of disease etiology and advance personalized medicine. Denmark (population ~5.9 million) provides a unique setting for population-based health research. The country is a rich source of biobanks and the universal, tax-funded healthcare system delivers routinely collected data to numerous registries and databases. By virtue of the civil registration number (assigned uniquely to all Danish citizens), biological specimens stored in biobanks can be combined with clinical and demographic data from these population-based health registries and databases. In this review, we aim to provide an understanding of advantages and possibilities of biobank research in Denmark. As knowledge about the Danish setting is needed to grasp the full potential, we first introduce the Danish healthcare system, the Civil Registration System, the population-based registries, and the interface with biobanks. We then describe the biobank infrastructures, comprising the Danish National Biobank Initiative, the Bio- and Genome Bank Denmark, and the Danish National Genome Center. Further, we briefly provide an overview of fourteen selected biobanks, including: The Danish Newborn Screening Biobank; The Danish National Birth Cohort; The Danish Twin Registry Biobank; Diet, Cancer and Health; Diet, Cancer and Health - Next generations; Danish Centre for Strategic Research in Type 2 Diabetes; Vejle Diabetes Biobank; The Copenhagen Hospital Biobank; The Copenhagen City Heart Study; The Copenhagen General Population Study; The Danish Cancer Biobank; The Danish Rheumatological Biobank; The Danish Blood Donor Study; and The Danish Pathology Databank. Last, we inform on practical aspects, such as data access, and discuss future implications.

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.

Disease mechanisms as Subtypes: Mitochondrial and bioenergetic dysfunction

Parkinson disease (PD) is the second most common neurodegenerative disease in the world. Despite its enormous human and societal cost, there is no disease-modifying therapy for PD. This unmet medical need reflects our limited understanding of PD pathogenesis. One of the most important clues comes from the recognition that PD motor symptoms arises from the dysfunction and degeneration of a very select group of neurons in the brain. These neurons have a distinctive set of anatomic and physiologic traits that reflect their role in brain function. These traits elevate mitochondrial stress, potentially making them particularly vulnerable to age, as well as to genetic mutations and environmental toxins linked to PD incidence. In this chapter, the literature supporting this model is outlined, along with gaps in our knowledge base. The translational implications of this hypothesis are then discussed, with a focus on why disease-modification trials have failed to date and what this means for the development of new strategies for altering disease course.

Precision and personalized medicine: What their current definition says and silences about the model of health they promote. Implication for the development of personalized health

The US National Human Genome Research Institute defines precision medicine as follows: "Precision medicine (generally considered analogous to personalized medicine or individualized medicine) is an innovative approach that uses information about an individual's genomic, environmental, and lifestyle information to guide decisions related to their medical management. The goal of precision medicine is to provide a more precise approach for the prevention, diagnosis, and treatment of disease." In this perspective article, we question this definition of precision medicine and the risks linked to its current practice and development. We highlight that in practice, precision medicine is based on the use of large volumes of biological data for individual purposes mostly in line with the biomedical model of health, which carries the risk of the biological reductionism of the person. A more comprehensive, precise, and even "personal" approach to health would require taking into account environmental, socio-economic, psychological, and biological determinants, an approach more in line with the biopsychosocial model of health. The role of environmental exposures, in a broad sense, is highlighted more and more, notably in the field of exposome research. Not considering the conceptual framework in which precision medicine is deployed leads to the concealment of the different responsibilities that can be mobilized within the health system. Anchoring precision medicine in a model that does not limit its definition to its biological and technical components makes it possible to envisage a personalized and more precise medicine, integrating a greater share of interventions centered on the skills and life contexts of individuals.

Sex differences in the diagnosis, treatment and prognosis of cancer: the rationale for an individualised approach

BACKGROUND

Precision medicine in oncology aims to identify the most beneficial interventions based on a patient's individual features and disease. However, disparities exist when providing cancer care to patients based on an individual's sex.

OBJECTIVE

To discuss how sex differences impact the epidemiology, pathophysiology, clinical manifestations, disease progression, and response to treatment, with a focus on data from Spain.

RESULTS

Genetic and environmental factors (social or economic inequalities, power imbalances, and discrimination) that contribute to these differences adversely affect cancer patient health outcomes. Increased health professional awareness of sex differences is essential to the success of translational research and clinical oncological care.

CONCLUSIONS

The Sociedad Española de Oncología Médica created a Task Force group to raise oncologists' awareness and to implement measures to address sex differences in cancer patient management in Spain. This is a necessary and fundamental step towards optimizing precision medicine that will benefit all individuals equally and equitably.

Clinical Utility and Application of Liquid Biopsy Genotyping in Lung Cancer: A Comprehensive Review

Precision medicine has revolutionized the therapeutic management of cancer patients with a major impact on non-small cell lung cancer (NSCLC), particularly lung adenocarcinoma, where advances have been remarkable. Tissue biopsy, required for tumor molecular testing, has significant limitations due to the difficulty of the biopsy site or the inadequacy of the histological specimen. In this context, liquid biopsy, consisting of the analysis of tumor-released materials circulating in body fluids, such as blood, is increasingly emerging as a valuable and non-invasive biomarker for detecting circulating tumor DNA (ctDNA) carrying molecular tumor signatures. In advanced/metastatic NSCLC, liquid biopsy drives target therapy by monitoring response to treatment and identifying eventual genomic mechanisms of resistance. In addition, recent data have shown a significant ability to detect minimal residual disease in early-stage lung cancer, underlying the potential application of liquid biopsy in the adjuvant setting, in early detection of recurrence, and also in the screening field. In this article, we present a review of the currently available data about the utility and application of liquid biopsy in lung cancer, with a particular focus on the approach to different techniques of analysis for liquid biopsy and a comparison with tissue samples as well as the potential practical uses in early and advanced/metastatic NSCLC.

A 3D, Compartmental Tumor-Stromal Microenvironment Model of Patient-Derived Bone Metastasis

Bone is a frequent site of tumor metastasis. The bone-tumor microenvironment is heterogeneous and complex in nature. Such complexity is compounded by relations between metastatic and bone cells influencing their sensitivity/resistance to chemotherapeutics. Standard chemotherapeutics may not show efficacy for every patient, and new therapeutics are slow to emerge, owing to the limitations of existing 2D/3D models. We previously developed a 3D interface model for personalized therapeutic screening, consisting of an electrospun poly lactic acid mesh activated with plasma species and seeded with stromal cells. Tumor cells embedded in an alginate-gelatin hydrogel are overlaid to create a physiologic 3D interface. Here, we applied our 3D model as a migration assay tool to verify the migratory behavior of different patient-derived bone metastasized cells. We assessed the impact of two different chemotherapeutics, Doxorubicin and Cisplatin, on migration of patient cells and their immortalized cell line counterparts. We observed different migratory behaviors and cellular metabolic activities blocked with both Doxorubicin and Cisplatin treatment; however, higher efficiency or lower IC50 was observed with Doxorubicin. Gene expression analysis of MDA-MB231 that migrated through our 3D hybrid model verified epithelial-mesenchymal transition through increased expression of mesenchymal markers involved in the metastasis process. Our findings indicate that we can model tumor migration in vivo, in line with different cell characteristics and it may be a suitable drug screening tool for personalized medicine approaches in metastatic cancer treatment.

Looking into the black box of "Medical Innovation": rising health expenditures by illness type

There is agreement among health economists that on the whole medical innovation causes health care expenditures (HCE) to rise. This paper analyzes for which diagnoses HCE per patient have grown significantly faster than average HCE. We distinguish decedents (patients in their last 4 years of life) from survivors and use a unique dataset comprising detailed HCE of all members of a regional health insurance fund in Upper Austria for the period 2005-2018. Our results indicate that among decedents in particular, the expenditures for treatment of neoplasms have exceeded the general trend in HCE. This confirms that medical innovation for this group of diseases has been particularly strong over the last 15 years. For survivors, we find a noticeable growth in cases and cost per case for pregnancies and childbirth, and also for treatment of mental and behavioral disorders. We discuss whether these findings contradict the widespread interpretation of cost-increasing innovations as "medical progress" and offer some policy recommendations.

Predictive genomic tools in disease stratification and targeted prevention: a recent update in personalized therapy advancements

In the current era of medical revolution, genomic testing has guided the healthcare fraternity to develop predictive, preventive, and personalized medicine. Predictive screening involves sequencing a whole genome to comprehensively deliver patient care via enhanced diagnostic sensitivity and specific therapeutic targeting. The best example is the application of whole-exome sequencing when identifying aberrant fetuses with healthy karyotypes and chromosomal microarray analysis in complicated pregnancies. To fit into today's clinical practice needs, experimental system biology like genomic technologies, and system biology viz., the use of artificial intelligence and machine learning is required to be attuned to the development of preventive and personalized medicine. As diagnostic techniques are advancing, the selection of medical intervention can gradually be influenced by a person's genetic composition or the cellular profiling of the affected tissue. Clinical genetic practitioners can learn a lot about several conditions from their distinct facial traits. Current research indicates that in terms of diagnosing syndromes, facial analysis techniques are on par with those of qualified therapists. Employing deep learning and computer vision techniques, the face image assessment software DeepGestalt measures resemblances to numerous of disorders. Biomarkers are essential for diagnostic, prognostic, and selection systems for developing personalized medicine viz. DNA from chromosome 21 is counted in prenatal blood as part of the Down's syndrome biomarker screening. This review is based on a detailed analysis of the scientific literature via a vigilant approach to highlight the applicability of predictive diagnostics for the development of preventive, targeted, personalized medicine for clinical application in the framework of predictive, preventive, and personalized medicine (PPPM/3 PM). Additionally, targeted prevention has also been elaborated in terms of gene-environment interactions and next-generation DNA sequencing. The application of 3 PM has been highlighted by an in-depth analysis of cancer and cardiovascular diseases. The real-time challenges of genome sequencing and personalized medicine have also been discussed.

Cell-Derived Vesicles for Nanoparticles' Coating: Biomimetic Approaches for Enhanced Blood Circulation and Cancer Therapy

Cancer nanomedicines are designed to encapsulate different therapeutic agents, prevent their premature release, and deliver them specifically to cancer cells, due to their ability to preferentially accumulate in tumor tissue. However, after intravenous administration, nanoparticles immediately interact with biological components that facilitate their recognition by the immune system, being rapidly removed from circulation. Reports show that less than 1% of the administered nanoparticles effectively reach the tumor site. This suboptimal pharmacokinetic profile is pointed out as one of the main factors for the nanoparticles' suboptimal therapeutic effectiveness and poor translation to the clinic. Therefore, an extended blood circulation time may be crucial to increase the nanoparticles' chances of being accumulated in the tumor and promote a site-specific delivery of therapeutic agents. For that purpose, the understanding of the forces that govern the nanoparticles' interaction with biological components and the impact of the physicochemical properties on the in vivo fate will allow the development of novel and more effective nanomedicines. Therefore, in this review, the nano-bio interactions are summarized. Moreover, the application of cell-derived vesicles for extending the blood circulation time and tumor accumulation is reviewed, focusing on the advantages and shortcomings of each cell source.

RET fusion mutation detected by re-biopsy 7 years after initial cytotoxic chemotherapy: A case report

Personalized medicine using molecular-targeted drugs to achieve better therapeutic response and long-term prognosis is common practice for lung cancer treatment. However, in cases before gene batch tests were available, medical treatment continued without the detection of rare mutations. We report a sixty-seven-old year man diagnosed with adenocarcinoma T1cN3M1a, stage IVA. Initial screening performed 7 years earlier using EGFR mutation and ALK immunohistochemical tests were negative. Although first-line cytotoxic combination chemotherapy was remarkably effective, a gradual regression of the primary lesion was noted. After a recent bronchoscopic re-biopsy, RET fusion was detected by gene panel test. In addition, we were able to confirm RET from FFPE specimens obtained from 7-year-old pleural effusion cell blocks. Subsequent administration of the molecular-targeted drug selpercatinib, was highly effective for the primary lesion and all metastatic lesions including brain metastases. We describe a case of RET fusion-positive lung cancer where molecular targeted therapy and cytotoxic drug showed a drastic response and long-term therapy was well maintained. Next generation sequencing was able to correctly diagnose RET fusion mutation using re-biopsy specimen after going undiagnosed for 7 years.

Selectively Targeting Breast Cancer Stem Cells by 8-Quinolinol and Niclosamide

Cancer maintenance, metastatic dissemination and drug resistance are sustained by cancer stem cells (CSCs). Triple negative breast cancer (TNBC) is the breast cancer subtype with the highest number of CSCs and the poorest prognosis. Here, we aimed to identify potential drugs targeting CSCs to be further employed in combination with standard chemotherapy in TNBC treatment. The anti-CSC efficacy of up to 17 small drugs was tested in TNBC cell lines using cell viability assays on differentiated cancer cells and CSCs. Then, the effect of 2 selected drugs (8-quinolinol -8Q- and niclosamide -NCS-) in the cancer stemness features were evaluated using mammosphere growth, cell invasion, migration and anchorage-independent growth assays. Changes in the expression of stemness genes after 8Q or NCS treatment were also evaluated. Moreover, the potential synergism of 8Q and NCS with PTX on CSC proliferation and stemness-related signaling pathways was evaluated using TNBC cell lines, CSC-reporter sublines, and CSC-enriched mammospheres. Finally, the efficacy of NCS in combination with PTX was analyzed in vivo using an orthotopic mouse model of MDA-MB-231 cells. Among all tested drug candidates, 8Q and NCS showed remarkable specific anti-CSC activity in terms of CSC viability, migration, invasion and anchorage independent growth reduction in vitro. Moreover, specific 8Q/PTX and NCS/PTX ratios at which both drugs displayed a synergistic effect in different TNBC cell lines were identified. The sole use of PTX increased the relative presence of CSCs in TNBC cells, whereas the combination of 8Q and NCS counteracted this pro-CSC activity of PTX while significantly reducing cell viability. In vivo, the combination of NCS with PTX reduced tumor growth and limited the dissemination of the disease by reducing circulating tumor cells and the incidence of lung metastasis. The combination of 8Q and NCS with PTX at established ratios inhibits both the proliferation of differentiated cancer cells and the viability of CSCs, paving the way for more efficacious TNBC treatments.

CUB Domain-Containing Protein 1 (CDCP1) is a rational target for the development of imaging tracers and antibody-drug conjugates for cancer detection and therapy

Rationale: An antibody-drug conjugate (ADC) is a targeted therapy consisting of a cytotoxic payload that is linked to an antibody which targets a protein enriched on malignant cells. Multiple ADCs are currently used clinically as anti-cancer agents significantly improving patient survival. Herein, we evaluated the rationale of targeting the cell surface oncoreceptor CUB domain-containing protein 1 (CDCP1) using ADCs and assessed the efficacy of CDCP1-directed ADCs against a range of malignant tumors.

Methods: CDCP1 mRNA expression was evaluated using large transcriptomic datasets of normal/tumor samples for 23 types of cancer and 15 other normal organs, and CDCP1 protein expression was examined in 34 normal tissues, >300 samples from six types of cancer, and in 49 cancer cell lines. A recombinant human/mouse chimeric anti-CDCP1 antibody (ch10D7) was labelled with ⁸⁹Zirconium or monomethyl auristatin E (MMAE) and tested in multiple pre-clinical cancer models including 36 cancer cell lines and three mouse xenograft models.

Results: Analysis of CDCP1 expression indicates elevated CDCP1 expression in the majority of the cancers and restricted expression in normal human tissues. Antibody ch10D7 demonstrates a high affinity and specificity for CDCP1 inducing cell signalling via Src accompanied by rapid internalization of ch10D7/CDCP1 complexes in cancer cells.⁸⁹Zirconium-labelled ch10D7 accumulates in CDCP1 expressing cells enabling detection of pancreatic cancer xenografts in mice by PET imaging. Cytotoxicity of MMAE-labelled ch10D7 against kidney, colorectal, lung, ovarian, pancreatic and prostate cancer cells in vitro, correlates with the level of CDCP1 on the plasma membrane. ch10D7-MMAE displays robust anti-tumor effects against mouse xenograft models of pancreatic, colorectal and ovarian cancer.

Conclusion: CDCP1 directed imaging agents will be useful for selecting cancer patients for personalized treatment with cytotoxin-loaded CDCP1 targeting agents including antibody-drug conjugates.

Unblinding the watchmaker: cancer treatment and drug design in the face of evolutionary pressure

INTRODUCTION

Death due to cancer is mostly associated with therapy ineffectiveness, i.e. tumor cells no longer responding to treatment. The underlying dynamics that facilitate this mutational escape from selective pressure are well studied in several other fields and several interesting approaches exist to combat this phenomenon, for example in the context of antibiotic-resistance in bacteria.

AREAS COVERED

Ninety percent of all cancer-related deaths are associated with treatment failure. Here, we discuss the common treatment modalities and prior attempts to overcome acquired resistance to therapy. The underlying molecular mechanisms are discussed and the implications of emerging resistance in other systems, such as bacteria, are discussed in the context of cancer.

EXPERT OPINION

Reevaluating emerging therapy resistance in tumors as an evolutionary mechanism to survive in a rapidly and drastically altering fitness landscape leads to novel treatment strategies and distinct requirements for new drugs. Here, we propose a scheme of considerations that need to be applied prior to the discovery of novel therapeutic drugs.

A Prospective Validation Study of Lung Cancer Gene Panel Testing Using Cytological Specimens

Background: Genetic panel tests require sufficient tissue samples, and therefore, cannot always be performed. Although collecting cytological specimens is easier than tissue collection, there are no validation studies on the diagnostic accuracy of lung cancer gene panel tests using cytology samples. Methods: Using an amplicon-based high-sensitivity next-generation sequencing panel test capable of measuring eight druggable genes, we prospectively enrolled consecutive patients who underwent diagnostic procedures. We evaluated the analysis accuracy rate, nucleic acid yield, and the quality of cytological specimens under brushing, needle aspiration, and pleural effusion. We then compared these specimens with collected tissue samples. Results: In 163 prospectively enrolled cases, nucleic acid extraction and analysis accuracy was 100% in cases diagnosed with adenocarcinoma. Gene mutations were found in 68.7% of cases with 99.5% (95% CI: 98.2-99.9) concordance to companion diagnostics. The median DNA/RNA yield and DNA/RNA integrity number were 475/321 ng and 7.9/5.7, respectively. The correlation coefficient of the gene allele ratio in 64 cases compared with tissue samples was 0.711. Conclusion: The success of gene analysis using cytological specimens was high, and the yield and quality of the extracted nucleic acid were sufficient for panel analysis. Moreover, the allele frequency of gene mutations in cytological specimens showed high correlations with tissue specimens.

The transmission and toxicity of polymer-bound doxorubicin-containing exosomes derived from human adenocarcinoma cells

Background: Exosomes are extracellular vesicles with the ability to encapsulate bioactive molecules, such as therapeutics. This study identified a new exosome mediated route of doxorubicin and poly(N-(2-hydroxypropyl)methacrylamide) (pHPMA)-bound doxorubicin trafficking in the tumor mass. Materials & methods: Exosome loading was achieved via incubation of the therapeutics with an adherent human breast adenocarcinoma cell line and its derived spheroids. Exosomes were characterized using HPLC, nanoparticle tracking analysis (NTA) and western blotting. Results: The therapeutics were successfully loaded into exosomes. Spheroids secreted significantly more exosomes than adherent cells and showed decreased viability after treatment with therapeutic-loaded exosomes, which confirmed successful transmission. Conclusion: To the best of our knowledge, this study provides the first evidence of pHPMA-drug conjugate secretion by extracellular vesicles.

Zebrafish Is a Powerful Tool for Precision Medicine Approaches to Neurological Disorders

Personalized medicine is currently one of the most promising tools which give hope to patients with no suitable or no available treatment. Patient-specific approaches are particularly needed for common diseases with a broad phenotypic spectrum as well as for rare and yet-undiagnosed disorders. In both cases, there is a need to understand the underlying mechanisms and how to counteract them. Even though, during recent years, we have been observing the blossom of novel therapeutic techniques, there is still a gap to fill between bench and bedside in a patient-specific fashion. In particular, the complexity of genotype-to-phenotype correlations in the context of neurological disorders has dampened the development of successful disease-modifying therapeutics. Animal modeling of human diseases is instrumental in the development of therapies. Currently, zebrafish has emerged as a powerful and convenient model organism for modeling and investigating various neurological disorders. This model has been broadly described as a valuable tool for understanding developmental processes and disease mechanisms, behavioral studies, toxicity, and drug screening. The translatability of findings obtained from zebrafish studies and the broad prospect of human disease modeling paves the way for developing tailored therapeutic strategies. In this review, we will discuss the predictive power of zebrafish in the discovery of novel, precise therapeutic approaches in neurosciences. We will shed light on the advantages and abilities of this in vivo model to develop tailored medicinal strategies. We will also investigate the newest accomplishments and current challenges in the field and future perspectives.

The economic value of liquid biopsy for genomic profiling in advanced non-small cell lung cancer

Background

Liquid biopsy (LB) can detect actionable genomic alterations in plasma circulating tumor circulating tumor DNA beyond tissue testing (TT) alone in advanced non-small cell lung cancer (NSCLC) patients. We estimated the cost-effectiveness of adding LB to TT in the Canadian healthcare system.

Methods

A cost-effectiveness analysis was conducted using a decision analytic Markov model from the Canadian public payer (Ontario) perspective and a 2-year time horizon in patients with treatment-naïve stage IV non-squamous NSCLC and ⩽10 pack-year smoking history. LB was performed using the comprehensive genomic profiling Guardant360™ assay. Standard of care TT for each participating institution was performed. Costs and outcomes of molecular testing by LB + TT were compared to TT alone. Transition probabilities were calculated from the VALUE trial (NCT03576937). Sensitivity analyses were undertaken to assess uncertainty in the model.

Results

Use of LB + TT identified actionable alterations in more patients, 68.5 versus 52.7% with TT alone. Use of the LB + TT strategy resulted in an incremental cost savings of $3065 CAD per patient (95% CI, 2195-3945) and a gain in quality-adjusted life-years of 0.02 (95% CI, 0.01-0.02) versus TT alone. More patients received chemo-immunotherapy based on TT with higher overall costs, whereas more patients received targeted therapy based on LB + TT with net cost savings. Major drivers of cost-effectiveness were drug acquisition costs and prevalence of actionable alterations.

Conclusion

The addition of LB to TT as initial molecular testing of clinically selected patients with advanced NSCLC did not increase system costs and led to more patients receiving appropriate targeted therapy.

Phase-Field Model for Drug Release of Water-Swellable Filaments for Fused Filament Fabrication

This paper treats the drug release process as a phase-field problem and a phase-field model capable of simulating the dynamics of multiple moving fronts, transient drug fluxes, and fractional drug release from swellable polymeric systems is proposed and validated experimentally. The model can not only capture accurately the positions and movements of the distinct fronts without tracking the locations of fronts explicitly but also predict well the release profile to the completion of the release process. The parametric study has shown that parameters including water diffusion coefficient, drug saturation solubility, drug diffusion coefficient, initial drug loading ratio, and initial porosity are critical in regulating the drug release kinetics. It has been also demonstrated that the model can be applied to the study of swellable filaments and has wide applicability for different materials. Due to explicit boundary position tracking being eliminated, the model paves the way for practical use and can be extended for dealing with geometrically complex drug delivery systems. It is a useful tool to guide the design of new controlled delivery systems fabricated by fused filament fabrication.

Tissue-specific identification of multi-omics features for pan-cancer drug response prediction

Current statistical models for drug response prediction and biomarker identification fall short in leveraging the shared and unique information from various cancer tissues and multi-omics profiles. We developed mix-lasso model that introduces an additional sample group penalty term to capture tissue-specific effects of features on pan-cancer response prediction. The mix-lasso model takes into account both the similarity between drug responses (i.e., multi-task learning), and the heterogeneity between multi-omics data (multi-modal learning). When applied to large-scale pharmacogenomics dataset from Cancer Therapeutics Response Portal, mix-lasso enabled accurate drug response predictions and identification of tissue-specific predictive features in the presence of various degrees of missing data, drug-drug correlations, and high-dimensional and correlated genomic and molecular features that often hinder the use of statistical approaches in drug response modeling. Compared to tree lasso model, mix-lasso identified a smaller number of tissue-specific features, hence making the model more interpretable and stable for drug discovery applications.

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Pan-cancer cell lines provide a test bench for exploring gene-drug relationships

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Multi-omics data were integrated with pharmacological profiles for joint modeling

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Mix-lasso identifies tissue-specific biomarkers predictive of multi-drug responses

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Mix-lasso provides small number of stable features for drug discovery applications

Longitudinal Monitoring of Circulating Tumor DNA to Predict Treatment Outcomes in Advanced Cancers

PURPOSE

The response to cancer therapies is typically assessed with radiologic imaging 6-10 weeks after treatment initiation. Circulating tumor DNA (ctDNA), however, has a short half-life, and dynamic changes in ctDNA quantity may allow for earlier assessment of the therapeutic response.

METHODS

Patients with advanced solid tumors referred to the Department of Investigational Cancer Therapeutics at The University of Texas MD Anderson Cancer Center were invited to participate in a liquid biopsy protocol for which serial blood samples were collected before, during, and after systemic therapy. We isolated ctDNA from serially collected plasma samples at baseline, mid-treatment, and first restaging. Genomically informed droplet digital polymerase chain reaction (ddPCR) was performed, and ctDNA quantities were reported as aggregate variant allele frequencies for all detected molecular aberrations.

RESULTS

We included 204 patients receiving 260 systemic therapies. The ctDNA detection rate was higher in progressors (patients with progressive disease) compared with nonprogressors (patients with stable disease, partial responses, or complete responses) at all time points (P < .009). Moreover, ctDNA detection was associated with a shorter median time-to-treatment failure (P ≤ .001). Positive delta and slope values for changes in ctDNA quantity were more frequent in progressors (P ≤ .03 and P < .001, respectively) and were associated with a shorter median time-to-treatment failure (P ≤ .014 and P < .001, respectively). Increasing ctDNA quantity was predictive of clinical and/or radiologic progressive disease in 73% of patients (median lead time, 23 days).

CONCLUSION

Detection of ctDNA and early dynamic changes in its quantity can predict the clinical outcomes of systemic therapies in patients with advanced solid tumors.

Adult medulloblastoma in an Australian population

Medulloblastoma in adult patients is a rare condition with limited contemporary demographic and treatment outcome data available in an Australian population. We conducted a retrospective review of patterns of care and outcomes of adult patients diagnosed with medulloblastoma treated at major neuro-oncology centres across Australia between January 2010 and December 2019. A total of 80 patients were identified and the median follow-up after diagnosis was 59.2 (range 0.5-204) months. A variety of chemotherapy regimens were used in the adjuvant and recurrent settings. The median overall survival (mOS) was 78 months (IQR 17.5-94.8). Patients who had no residual disease post-resection or with SHH-subtype tumours had a numerically longer 5-year survival rate than those with residual disease post resection or non-SHH subtypes respectively. The median time to recurrence from diagnosis was 18.4 months. The median OS from 1st relapse was 22.1 months (95% CI 11.7-31.4) and mOS from second relapse was 10.2 months (95% CI 6.6 - NR). This is the largest dataset examining patterns of care of adult patients with medulloblastoma in an Australian population. Substantial variation existed in the chemotherapy agents used in the adjuvant and recurrent setting. As has been demonstrated in a paediatric population, trials such as the upcoming EORTC 1634-BTG/NOA-23 trial (PersoMed-1 study) which are tailoring treatments to molecular profiles are likely to improve outcome in adult medulloblastoma.

Canine models of human cancer: Bridging the gap to improve precision medicine

Dogs are remarkable, adaptable, and dependable creatures that have evolved alongside humans while contributing tremendously to our survival. Our canine companions share many similarities to human disease, particularly cancer. With the advancement of next-generation sequencing technology, we are beginning to unravel the complexity of cancer and the vast intra- and intertumoral heterogeneity that makes treatment difficult. Consequently, precision medicine has emerged as a therapeutic approach to improve patient survival by evaluating and classifying an individual tumor's molecular profile. Many canine and human cancers share striking similarities in terms of genotypic, phenotypic, clinical, and histological presentations. Dogs are superior to rodent models of cancer because they are a naturally heterogeneous population in which tumors occur spontaneously, are exposed to similar environmental conditions, and show more similarities in key modulators of tumorigenesis and clinical response, including the immune system, drug metabolism, and gut microbiome. In this chapter, we will explore various canine models of human cancers and emphasize the dog's critical role in advancing precision medicine and improving the survival of both man and man's best friend.

Association Between Medicaid Expansion Under the Affordable Care Act and Survival Among Newly Diagnosed Cancer Patients

BACKGROUND

Medicaid expansion under the Affordable Care Act (ACA) is associated with increased insurance coverage among patients with cancer. Whether these gains translate to improved survival is largely unknown. This study examines changes in 2-year survival among patients newly diagnosed with cancer following the ACA Medicaid expansion.

METHODS

Patients aged 18-62 years from 42 states' population-based cancer registries diagnosed pre (2010-2012) and post (2014-2016) ACA Medicaid expansion were followed through September 30, 2013, and December 31, 2017, respectively. Difference-in-differences (DD) analysis of 2-year overall survival was stratified by sex, race and ethnicity, census tract-level poverty, and rurality.

RESULTS

A total of 2 555 302 patients diagnosed with cancer were included from Medicaid expansion (n = 1 523 585) and nonexpansion (n = 1 031 717) states. The 2-year overall survival increased from 80.58% pre-ACA to 82.23% post-ACA in expansion states and from 78.71% to 80.04% in nonexpansion states, resulting in a net increase of 0.44 percentage points (ppt) (95% confidence interval [CI] = 0.24ppt to 0.64ppt) in expansion states after adjusting for sociodemographic factors. By cancer site, the net increase was greater for colorectal cancer (DD = 0.90ppt, 95% CI = 0.19ppt to 1.60ppt), lung cancer (DD = 1.29ppt, 95% CI = 0.50ppt to 2.08ppt), non-Hodgkin lymphoma (DD = 1.07ppt, 95% CI = 0.14ppt to 1.99ppt), pancreatic cancer (DD = 1.80ppt, 95% CI = 0.40ppt to 3.21ppt), and liver cancer (DD = 2.57ppt, 95% CI = 1.00ppt to 4.15ppt). The improvement in 2-year overall survival was larger among non-Hispanic Black patients (DD = 0.72ppt, 95% CI = 0.12ppt to 1.31ppt) and patients residing in rural areas (DD = 1.48ppt, 95% CI= -0.26ppt to 3.23ppt), leading to narrowing survival disparities by race and rurality.

CONCLUSIONS

Medicaid expansion was associated with greater increase in 2-year overall survival, and the increase was prominent among non-Hispanic Blacks and in rural areas, highlighting the role of Medicaid expansion in reducing health disparities. Future studies should monitor changes in longer-term health outcomes following the ACA.

Integrated, cross-sectoral psycho-oncology (isPO): a new form of care for newly diagnosed cancer patients in Germany

Background

The annual incidence of new cancer cases has been increasing worldwide for many years, and is likely to continue to rise. In Germany, the number of new cancer cases is expected to increase by 20% until 2030. Half of all cancer patients experience significant emotional and psychosocial distress along the continuum of their disease, treatment, and aftercare, and also as long-term survivors. Consequently, in many countries, psycho-oncological programs have been developed to address this added burden at both the individual and population level. These programs promote the active engagement of patients in their cancer therapy, aftercare and survivorship planning and aim to improve the patients' quality of life.

In Germany, the “new form of care isPO” (“nFC-isPO”; integrated, cross-sectoral psycho-oncology/integrierte, sektorenübergreifende Psycho-Onkologie) is currently being developed, implemented and evaluated. This approach strives to accomplish the goals devised in the National Cancer Plan by providing psycho-oncological care to all cancer patients according to their individual healthcare needs. The term “new form of care" is defined by the Innovation Fund (IF) of Germany's Federal Joint Committee as “a structured and legally binding cooperation between different professional groups and/or institutions in medical and non-medical care”.

The nFC-isPO is part of the isPO project funded by the IF. It is implemented in four local cancer centres and is currently undergoing a continuous quality improvement process. As part of the isPO project the nFC-isPO is being evaluated by an independent institution: the Institute for Medical Sociology, Health Services Research, and Rehabilitation Science (IMVR), University of Cologne, Germany.

The four-year isPO project was selected by the IF to be eligible for funding because it meets the requirements of the federal government's National Cancer Plan (NCP), in particular, the “further development of the oncological care structures and quality assurance" in the psycho-oncological domain. An independent evaluation is required by the IF to verify if the new form of care leads to an improvement in cross-sectoral care and to explore its potential for permanent integration into the German health care system.

Methods

The nFC-isPO consists of six components: a concept of care (C1), care pathways (C2), a psycho-oncological care network (C3), a care process organization plan (C4), an IT-supported documentation and assistance system (C5) and a quality management system (C6). The two components concept of care (C1) and care pathways (C2) represent the isPO clinical care program, according to which the individual cancer patients are offered psycho-oncological services within a period of 12 months after program enrolment following the diagnosis of cancer. The remaining components (C3-C6) represent the formal-administrative aspects of the nFC-isPO that are intended to meet the legally binding requirements of patient care in the German health care system. With the aim of systematic development of the nFC-isPO while at the same time enabling the external evaluators to examine its quality, effectiveness and efficiency under conditions of routine care, the project partners took into consideration approaches from translational psycho-oncology, practice-based health care research and program theory. In order to develop a structured, population-based isPO care program, reference was made to a specific program theory, to the stepped-care approach, and also to evidence-based guideline recommendations.

Results

The basic version, nFC-isPO, was created over the first year after the start of the isPO project in October 2017, and has since been subject to a continuous quality improvement process. In 2019, the nFC-isPO was implemented at four local psycho-oncological care networks in the federal state North Rhine-Westphalia, in Germany. The legal basis of the implementation is a contract for "special care" with the German statutory health insurance funds according to state law (§ 140a SCB V; Social Code Book V for the statutory health insurance funds). Besides the accompanying external evaluation by the IMVR, the nFC-isPO is subjected to quarterly internal and cross-network quality assurance and improvement measures (internal evaluation) in order to ensure continuous quality improvement process. These quality management measures are developed and tested in the isPO project and are to be retained in order to ensure the sustainability of the quality of nFC-isPO for later dissemination into the German health care system.

Discussion

Demands on quality, effectiveness and cost-effectiveness of in the German health care system are increasing, whereas financial resources are declining, especially for psychosocial services. At the same time, knowledge about evidence-based screening, assessment and intervention in cancer patients and about the provision of psychosocial oncological services is growing continuously. Due to the legal framework of the statutory health insurance in Germany, it has taken years to put sound psycho-oncological findings from research into practice. Ensuring the adequate and sustainable financing of a needs-oriented, psycho-oncological care approach for all newly diagnosed cancer patients, as required by the NCP, may still require many additional years. The aim of the isPO project is to develop a new form of psycho-oncological care for the individual and the population suffering from cancer, and to provide those responsible for German health policy with a sound basis for decision-making on the timely dissemination of psycho-oncological services in the German health care system.

Trial registration

The study was pre-registered at the German Clinical Trials Register (https://www.drks.de/DRKS00015326) under the following trial registration number: DRKS00015326; Date of registration: October 30, 2018.

Rhodamine 101 Conjugates of Triterpenoic Amides Are of Comparable Cytotoxicity as Their Rhodamine B Analogs

Pentacyclic triterpenoic acids (betulinic, oleanolic, ursolic, and platanic acid) were selected and subjected to acetylation followed by the formation of amides derived from either piperazine or homopiperazine. These amides were coupled with either rhodamine B or rhodamine 101. All of these compounds were screened for their cytotoxic activity in SRB assays. As a result, the cytotoxicity of the parent acids was low but increased slightly upon their acetylation while a significant increase in cytotoxicity was observed for piperazinyl and homopiperazinyl amides. A tremendous improvement in cytotoxicity was observed; however, for the rhodamine B and rhodamine 101 conjugates, and compound 27, an ursolic acid derived homopiperazinyl amide holding a rhodamine 101 residue showed an EC50 = 0.05 µM for A2780 ovarian cancer cells while being less cytotoxic for non-malignant fibroblasts. To date, the rhodamine 101 derivatives presented here are the first examples of triterpene derivatives holding a rhodamine residue different from rhodamine B.

Dual drug targeting to kill colon cancers

Introduction

Colorectal cancer (CRC) is driven by a small set of oncogenic and tumour suppressor mutations. However, different combinations of mutations often lead to poor tumour responses to individual anticancer drugs. We have investigated the antiproliferative and in vitro cytotoxic activity of pair‐wise combinations of inhibitors which target specific signalling pathways in colon cancer cells.

Objectives

To target specific signaling pathways pairwise with inhibitors in order to kill colon cancer cells.

Methods

The effects of different concentrations of two inhibitors on the proliferation and viability of colon cancer cell lines were measured using cell titre glow and cytotoxic assays in 2D and 3D cell micro‐cultures. One successful drug combination was used to treat a colon cancer cell line growing as a xenograft in nude mice.

Results

Colon cancer cells in non‐adherent cultures were killed more effectively by combinations of pyrvinium pamoate (a Wnt pathway inhibitor) and ABT263 (a pro‐apoptotic Bcl‐2 family inhibitor) or Ly29004 (a PI3kinase inhibitor). However, in a mouse xenograft model, the formulation and toxicity of the ABT737/PP combination prevent the use of these drugs for treatment of tumours. Fortunately, oral analogues of PP (pyrvinium phosphate, PPh) and ABT737(ABT263) have equivalent activity and can be used for treatment of mice carrying SW620 colorectal cancer xenografts. The PPh/ABT263 induced SW620 tumour cell apoptosis and reduced the rate of SW620 tumour growth.

Conclusion

By combining a Wnt signaling inhibitor (pyrvinium phosphate) and a pro‐survival inhibitor (ABT263) colon cancer cells can be killed. Combinations of Wnt signalling inhibitors with an inhibitor of the Bcl pro‐survival protein family should be considered for the treatment of patients with precancerous colon adenomas or advanced colorectal cancers with APC mutations.

Genome editing via non-viral delivery platforms: current progress in personalized cancer therapy

Cancer is a severe disease that substantially jeopardizes global health. Although considerable efforts have been made to discover effective anti-cancer therapeutics, the cancer incidence and mortality are still growing. The personalized anti-cancer therapies present themselves as a promising solution for the dilemma because they could precisely destroy or fix the cancer targets based on the comprehensive genomic analyses. In addition, genome editing is an ideal way to implement personalized anti-cancer therapy because it allows the direct modification of pro-tumor genes as well as the generation of personalized anti-tumor immune cells. Furthermore, non-viral delivery system could effectively transport genome editing tools (GETs) into the cell nucleus with an appreciable safety profile. In this manuscript, the important attributes and recent progress of GETs will be discussed. Besides, the laboratory and clinical investigations that seek for the possibility of combining non-viral delivery systems with GETs for the treatment of cancer will be assessed in the scope of personalized therapy.

Updated Understanding of the Causes of Cancer, and a New Theoretical Perspective of Combinational Cancer Therapies, a Hypothesis

We present an integrative understanding of cancer as a metabolic multifactorial, multistage disease. We focus on underlying genetics-environmental interactions, evidenced by telomere changes. A range of genetic and epigenetic factors, including physical agents and predisposing factors such as diet and lifestyle are included. We present a structured model of the causes of cancer, methods of investigations, approaches to cancer prevention, and polypharmaceutical multidisciplinary complex treatment within a framework of personalized medicine. We searched PubMed, National Cancer Institute online, and other databases for publications regarding causes of cancer, reports of novel mitochondrial reprogramming, epigenetic, and telomerase therapies and state-of-the-art investigations. We focused on multistep treatment protocols to enhance early detection of cancer, and elimination or neutralization of the causes and factors associated with cancer formation and progression.Our aim is to suggest a model therapeutic protocol that incorporates the patient's genome, metabolism, and immune system status; stage of tumor development; and comorbidity(ies), if any. Investigation and treatment of cancer is a challenge that requires further holistic studies that improve the quality of life and survival rates, but are most likely to aid prevention.

Molecular Subtyping Resource: a user-friendly tool for rapid biological discovery from transcriptional data

Generation of transcriptional data has dramatically increased in the past decade, driving the development of analytical algorithms that enable interrogation of the biology underpinning the profiled samples. However, these resources require users to have expertise in data wrangling and analytics, reducing opportunities for biological discovery by 'wet-lab' users with a limited programming skillset. Although commercial solutions exist, costs for software access can be prohibitive for academic research groups. To address these challenges, we have developed an open source and user-friendly data analysis platform for on-the-fly bioinformatic interrogation of transcriptional data derived from human or mouse tissue, called Molecular Subtyping Resource (MouSR). This internet-accessible analytical tool, https://mousr.qub.ac.uk/, enables users to easily interrogate their data using an intuitive 'point-and-click' interface, which includes a suite of molecular characterisation options including quality control, differential gene expression, gene set enrichment and microenvironmental cell population analyses from RNA sequencing. The MouSR online tool provides a unique freely available option for users to perform rapid transcriptomic analyses and comprehensive interrogation of the signalling underpinning transcriptional datasets, which alleviates a major bottleneck for biological discovery. This article has an associated First Person interview with the first author of the paper.

A liquid chromatography tandem mass spectrometry method for a semiquantitative screening of cellular acyl-CoA

This study describes LC-ESI-MS/MS method that covers the analysis of various cellular acyl-CoA in a single injection. The method is based on a quick extraction step eliminating LLE/SPE clean up. Method performance characteristics were determined after spiking acyl-CoA standards in different concentrations into a surrogate matrix. The extensive matrix effect for most acyl-CoA except for palmitoyl-CoA was compensated by using isotopically labeled internal standard and matrix-matched calibration. As a result of the high matrix effect, the accuracy for palmitoyl-CoA at the low concentration deviated from the target range of ±20%. The developed method was applied to identify twenty-one cellular acyl-CoA in SK-HEP-1 cells and screening for alterations in acyl-CoA levels post Mito Q antioxidant intervention.

Recent Advances in 3D Printing of Biomedical Sensing Devices

Additive manufacturing, also called 3D printing, is a rapidly evolving technique that allows for the fabrication of functional materials with complex architectures, controlled microstructures, and material combinations. This capability has influenced the field of biomedical sensing devices by enabling the trends of device miniaturization, customization, and elasticity (i.e., having mechanical properties that match with the biological tissue). In this paper, the current state-of-the-art knowledge of biomedical sensors with the unique and unusual properties enabled by 3D printing is reviewed. The review encompasses clinically important areas involving the quantification of biomarkers (neurotransmitters, metabolites, and proteins), soft and implantable sensors, microfluidic biosensors, and wearable haptic sensors. In addition, the rapid sensing of pathogens and pathogen biomarkers enabled by 3D printing, an area of significant interest considering the recent worldwide pandemic caused by the novel coronavirus, is also discussed. It is also described how 3D printing enables critical sensor advantages including lower limit-of-detection, sensitivity, greater sensing range, and the ability for point-of-care diagnostics. Further, manufacturing itself benefits from 3D printing via rapid prototyping, improved resolution, and lower cost. This review provides researchers in academia and industry a comprehensive summary of the novel possibilities opened by the progress in 3D printing technology for a variety of biomedical applications.

Microsatellite Status and IκBα Expression Levels Predict Sensitivity to Pharmaceutical Curcumin in Colorectal Cancer Cells

Simple Summary

The global burden of colorectal cancer is high. Chemotherapy has been the backbone of colorectal cancer therapy for decades. Toxic side effects and frequently occurring drug resistances remain challenging problems. Therefore, exploring natural compounds with low or even no toxicity holds great potential. However, natural curcumin is poorly absorbed, limiting its clinical use. Therefore, our focus was to screen different molecular types of colorectal cancer to find the ones with the highest sensitivity to curcumin. We observed very individual responses to curcumin for various colorectal cancer cell lines. Most curcumin-sensitive cell lines were of the microsatellite-stable molecular type, and expressed high baseline levels of the IκBα protein. Contrarily, curcumin-resistant lines were mainly microsatellite instable, with low baseline IκBα levels. Considering all of the data obtained, we conclude that patients with microsatellite-stable tumors and high baseline IκBα protein expression would benefit from treatment with novel curcumin formulations and derivatives.

Abstract

Clinical utilization of curcumin in colorectal cancer (CRC) was revived as a result of the development of novel curcumin formulations with improved bioavailability. Additionally, identification of biomarkers for curcumin sensitivity would also promote successful clinical applications. Here, we wanted to identify such biomarkers in order to establish a predictive model for curcumin sensitivity. Thirty-two low-passage CRC cell lines with specified tumor characteristics were included. Curcumin suppressed cell proliferation, yet sensitivity levels were distinct. Most curcumin-sensitive CRC cell lines were microsatellite stable and expressed high levels of IκBα. The predictive capacity of this biomarker combination possessed a statistical significance of 72% probability to distinguish correctly between curcumin-sensitive and -resistant CRC cell lines. Detailed functional analyses were performed with three sensitive and three resistant CRC cell lines. As curcumin’s mode of action, inhibition of NF-κB p65 activation via IκBα was identified. In consequence, we hypothesize that novel curcumin formulations—either alone or, more likely, in combination with standard therapeutics—can be expected to prove clinically beneficial for CRC patients with high IκBα expression levels.

Association of State Medicaid Income Eligibility Limits and Long-Term Survival After Cancer Diagnosis in the United States

PURPOSE

To examine the association between historic state Medicaid income eligibility limits and long-term survival among patients with cancer.

METHODS

1,449,144 adults age 18-64 years newly diagnosed with 19 common cancers between 2010 and 2013 were identified from the National Cancer Database. States' Medicaid income eligibility limits were categorized as ≤ 50%, 51%-137%, and ≥ 138% of federal poverty level (FPL). Survival time was measured from diagnosis date through December 31, 2017, for up to an 8-year follow-up. Multivariable Cox proportional hazards models with age as time scale were used to assess associations of eligibility limits and stage-specific survival, adjusting for the effects of sex, metropolitan statistical area, comorbidities, year of diagnosis, facility type and volume, and state.

RESULTS

Among patients with newly diagnosed cancer age 18-64 years, patients living in states with lower Medicaid income eligibility limits had worse survival for most cancers in both early and late stages, compared with those living in states with Medicaid income eligibility limits ≥ 138% FPL. A dose-response relationship was observed for most cancers with lower income limits associated with worse survival (13 of 17 cancers evaluated for early-stage cancers, and 11 of 17 cancers evaluated for late-stage cancers, and leukemia and brain tumors with P-trend < .05).

CONCLUSION

Lower Medicaid income eligibility limits were associated with worse long-term survival within stage; increasing Medicaid income eligibility may improve survival after cancer diagnosis.

Metabolic therapy and bioenergetic analysis: The missing piece of the puzzle

BACKGROUND

Aberrant metabolism is recognized as a hallmark of cancer, a pillar necessary for cellular proliferation. Regarding bioenergetics (ATP generation), most cancers display a preference not only toward aerobic glycolysis ("Warburg effect") and glutaminolysis (mitochondrial substrate level-phosphorylation) but also toward other metabolites such as lactate, pyruvate, and fat-derived sources. These secondary metabolites can assist in proliferation but cannot fully cover ATP demands.

SCOPE OF REVIEW

The concept of a static metabolic profile is challenged by instances of heterogeneity and flexibility to meet fuel/anaplerotic demands. Although metabolic therapies are a promising tool to improve therapeutic outcomes, either via pharmacological targets or press-pulse interventions, metabolic plasticity is rarely considered. Lack of bioenergetic analysis in vitro and patient-derived models is hindering translational potential. Here, we review the bioenergetics of cancer and propose a simple analysis of major metabolic pathways, encompassing both affordable and advanced techniques. A comprehensive compendium of Seahorse XF bioenergetic measurements is presented for the first time.

MAJOR CONCLUSIONS

Standardization of principal readouts might help researchers to collect a complete metabolic picture of cancer using the most appropriate methods depending on the sample of interest.

Brain Cancer Drug Discovery: Clinical Trials, Drug Classes, Targets, and Combinatorial Therapies

Brain cancer is a formidable challenge for drug development, and drugs derived from many cutting-edge technologies are being tested in clinical trials. We manually characterized 981 clinical trials on brain tumors that were registered in ClinicalTrials.gov from 2010 to 2020. We identified 582 unique therapeutic entities targeting 581 unique drug targets and 557 unique treatment combinations involving drugs. We performed the classification of both the drugs and drug targets based on pharmacological and structural classifications. Our analysis demonstrates a large diversity of agents and targets. Currently, we identified 32 different pharmacological directions for therapies that are based on 42 structural classes of agents. Our analysis shows that kinase inhibitors, chemotherapeutic agents, and cancer vaccines are the three most common classes of agents identified in trials. Agents in clinical trials demonstrated uneven distribution in combination approaches; chemotherapy agents, proteasome inhibitors, and immune modulators frequently appeared in combinations, whereas kinase inhibitors, modified immune effector cells did not as was shown by combination networks and descriptive statistics. This analysis provides an extensive overview of the drug discovery field in brain cancer, shifts that have been happening in recent years, and challenges that are likely to come. SIGNIFICANCE STATEMENT: This review provides comprehensive quantitative analysis and discussion of the brain cancer drug discovery field, including classification of drug, targets, and therapies.

Personalization of medical treatments in oncology: time for rethinking the disease concept to improve individual outcomes

The agenda of pharmacology discovery in the field of personalized oncology was dictated by the search of molecular targets assumed to deterministically drive tumor development. In this perspective, genes play a fundamental "causal" role while cells simply act as causal proxies, i.e., an intermediate between the molecular input and the organismal output. However, the ceaseless genomic change occurring across time within the same primary and metastatic tumor has broken the hope of a personalized treatment based only upon genomic fingerprint. Indeed, current models are unable in capturing the unfathomable complexity behind the outbreak of a disease, as they discard the contribution of non-genetic factors, environment constraints, and the interplay among different tiers of organization. Herein, we posit that a comprehensive personalized model should view at the disease as a "historical" process, in which different spatially and timely distributed factors interact with each other across multiple levels of organization, which collectively interact with a dynamic gene-expression pattern. Given that a disease is a dynamic, non-linear process - and not a static-stable condition - treatments should be tailored according to the "timing-frame" of each condition. This approach can help in detecting those critical transitions through which the system can access different attractors leading ultimately to diverse outcomes - from a pre-disease state to an overt illness or, alternatively, to recovery. Identification of such tipping points can substantiate the predictive and the preventive ambition of the Predictive, Preventive and Personalized Medicine (PPPM/3PM). However, an unusual effort is required to conjugate multi-omics approaches, data collection, and network analysis reconstruction (eventually involving innovative Artificial Intelligent tools) to recognize the critical phases and the relevant targets, which could help in patient stratification and therapy personalization.