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Application and Importance of Theranostics in the Diagnosis and Treatment of Cancer

Jeyamogan S, Khan NA, Siddiqui R

Arch Med Res, 2021 02;52(2):131-142.
PMID: 33423803 DOI: 10.1016/j.arcmed.2020.10.016

The number of cancer cases worldwide in terms of morbidity and mortality is a serious concern, despite the presence of therapeutic interventions and supportive care. Limitations in the current available diagnosis methods and treatments methods may contribute to the increase in cancer mortality. Theranostics, is a novel approach that has opened avenues for the simultaneous precise diagnosis and treatment for cancer patients. Although still in the early development stage, theranostic agents such as quantum dots, radioisotopes, liposomes and plasmonic nanobubbles can be bound to anticancer drugs, cancer cell markers and imaging agents, with the support of available imaging techniques, provide the potential to facilitate diagnosis, treatment and management of cancer patients. Herein, we discuss the potential benefits of several theranostic tools for the management of cancer. Specifically, quantum dots, radio-labelled isotopes, liposomes and plasmonic nanobubbles coupled with targeting agents and/or anticancer molecules and imaging agents as theranostic agents are deliberated upon in this review. Overall, the use of theranostic agents shows promise in cancer management. Nevertheless, intensive research is required to realize these expectations.

Matched MeSH terms: Precision Medicine/methods*
Fulltext Next-generation, personalised, model-based critical care medicine: a state-of-the art review of in silico virtual patient models, methods, and cohorts, and how to validation them

Chase JG, Preiser JC, Dickson JL, Pironet A, Chiew YS, Pretty CG, et al.

Biomed Eng Online, 2018 Feb 20;17(1):24.
PMID: 29463246 DOI: 10.1186/s12938-018-0455-y

Critical care, like many healthcare areas, is under a dual assault from significantly increasing demographic and economic pressures. Intensive care unit (ICU) patients are highly variable in response to treatment, and increasingly aging populations mean ICUs are under increasing demand and their cohorts are increasingly ill. Equally, patient expectations are growing, while the economic ability to deliver care to all is declining. Better, more productive care is thus the big challenge. One means to that end is personalised care designed to manage the significant inter- and intra-patient variability that makes the ICU patient difficult. Thus, moving from current "one size fits all" protocolised care to adaptive, model-based "one method fits all" personalised care could deliver the required step change in the quality, and simultaneously the productivity and cost, of care. Computer models of human physiology are a unique tool to personalise care, as they can couple clinical data with mathematical methods to create subject-specific models and virtual patients to design new, personalised and more optimal protocols, as well as to guide care in real-time. They rely on identifying time varying patient-specific parameters in the model that capture inter- and intra-patient variability, the difference between patients and the evolution of patient condition. Properly validated, virtual patients represent the real patients, and can be used in silico to test different protocols or interventions, or in real-time to guide care. Hence, the underlying models and methods create the foundation for next generation care, as well as a tool for safely and rapidly developing personalised treatment protocols over large virtual cohorts using virtual trials. This review examines the models and methods used to create virtual patients. Specifically, it presents the models types and structures used and the data required. It then covers how to validate the resulting virtual patients and trials, and how these virtual trials can help design and optimise clinical trial. Links between these models and higher order, more complex physiome models are also discussed. In each section, it explores the progress reported up to date, especially on core ICU therapies in glycemic, circulatory and mechanical ventilation management, where high cost and frequency of occurrence provide a significant opportunity for model-based methods to have measurable clinical and economic impact. The outcomes are readily generalised to other areas of medical care.

Matched MeSH terms: Precision Medicine/methods*
Fulltext A non-printed integrated-circuit textile for wireless theranostics

Yang Y, Wei X, Zhang N, Zheng J, Chen X, Wen Q, et al.

Nat Commun, 2021 08 12;12(1):4876.
PMID: 34385436 DOI: 10.1038/s41467-021-25075-8

While the printed circuit board (PCB) has been widely considered as the building block of integrated electronics, the world is switching to pursue new ways of merging integrated electronic circuits with textiles to create flexible and wearable devices. Herein, as an alternative for PCB, we described a non-printed integrated-circuit textile (NIT) for biomedical and theranostic application via a weaving method. All the devices are built as fibers or interlaced nodes and woven into a deformable textile integrated circuit. Built on an electrochemical gating principle, the fiber-woven-type transistors exhibit superior bending or stretching robustness, and were woven as a textile logical computing module to distinguish different emergencies. A fiber-type sweat sensor was woven with strain and light sensors fibers for simultaneously monitoring body health and the environment. With a photo-rechargeable energy textile based on a detailed power consumption analysis, the woven circuit textile is completely self-powered and capable of both wireless biomedical monitoring and early warning. The NIT could be used as a 24/7 private AI "nurse" for routine healthcare, diabetes monitoring, or emergencies such as hypoglycemia, metabolic alkalosis, and even COVID-19 patient care, a potential future on-body AI hardware and possibly a forerunner to fabric-like computers.

Matched MeSH terms: Precision Medicine/methods
Stage-directed individualized therapy in esophageal cancer

Goense L, van Rossum PS, Kandioler D, Ruurda JP, Goh KL, Luyer MD, et al.

Ann N Y Acad Sci, 2016 10;1381(1):50-65.
PMID: 27384385 DOI: 10.1111/nyas.13113

Esophageal cancer is the eighth most common cancer worldwide, and the incidence of esophageal carcinoma is rapidly increasing. With the advent of new staging and treatment techniques, esophageal cancer can now be managed through various strategies. A good understanding of the advances and limitations of new staging techniques and how these can guide in individualizing treatment is important to improve outcomes for esophageal cancer patients. This paper outlines the recent progress in staging and treatment of esophageal cancer, with particularly attention to endoscopic techniques for early-stage esophageal cancer, multimodality treatment for locally advanced esophageal cancer, assessment of response to neoadjuvant treatment, and the role of cervical lymph node dissection. Furthermore, advances in robot-assisted surgical techniques and postoperative recovery protocols that may further improve outcomes after esophagectomy are discussed.

Matched MeSH terms: Precision Medicine/methods*
Fulltext Towards precision medicine: from quantitative imaging to radiomics

Acharya UR, Hagiwara Y, Sudarshan VK, Chan WY, Ng KH

J Zhejiang Univ Sci B, 2018 1 9;19(1):6-24.
PMID: 29308604 DOI: 10.1631/jzus.B1700260

Radiology (imaging) and imaging-guided interventions, which provide multi-parametric morphologic and functional information, are playing an increasingly significant role in precision medicine. Radiologists are trained to understand the imaging phenotypes, transcribe those observations (phenotypes) to correlate with underlying diseases and to characterize the images. However, in order to understand and characterize the molecular phenotype (to obtain genomic information) of solid heterogeneous tumours, the advanced sequencing of those tissues using biopsy is required. Thus, radiologists image the tissues from various views and angles in order to have the complete image phenotypes, thereby acquiring a huge amount of data. Deriving meaningful details from all these radiological data becomes challenging and raises the big data issues. Therefore, interest in the application of radiomics has been growing in recent years as it has the potential to provide significant interpretive and predictive information for decision support. Radiomics is a combination of conventional computer-aided diagnosis, deep learning methods, and human skills, and thus can be used for quantitative characterization of tumour phenotypes. This paper discusses the overview of radiomics workflow, the results of various radiomics-based studies conducted using various radiological images such as computed tomography (CT), magnetic resonance imaging (MRI), and positron-emission tomography (PET), the challenges we are facing, and the potential contribution of radiomics towards precision medicine.

Matched MeSH terms: Precision Medicine/methods*
Proteogenomics: From next-generation sequencing (NGS) and mass spectrometry-based proteomics to precision medicine

Ang MY, Low TY, Lee PY, Wan Mohamad Nazarie WF, Guryev V, Jamal R

Clin Chim Acta, 2019 Nov;498:38-46.
PMID: 31421119 DOI: 10.1016/j.cca.2019.08.010

One of the best-established area within multi-omics is proteogenomics, whereby the underpinning technologies are next-generation sequencing (NGS) and mass spectrometry (MS). Proteogenomics has contributed significantly to genome (re)-annotation, whereby novel coding sequences (CDS) are identified and confirmed. By incorporating in-silico translated genome variants in protein database, single amino acid variants (SAAV) and splice proteoforms can be identified and quantified at peptide level. The application of proteogenomics in cancer research potentially enables the identification of patient-specific proteoforms, as well as the association of the efficacy or resistance of cancer therapy to different mutations. Here, we discuss how NGS/TGS data are analyzed and incorporated into the proteogenomic framework. These sequence data mainly originate from whole genome sequencing (WGS), whole exome sequencing (WES) and RNA-Seq. We explain two major strategies for sequence analysis i.e., de novo assembly and reads mapping, followed by construction of customized protein databases using such data. Besides, we also elaborate on the procedures of spectrum to peptide sequence matching in proteogenomics, and the relationship between database size on the false discovery rate (FDR). Finally, we discuss the latest development in proteogenomics-assisted precision oncology and also challenges and opportunities in proteogenomics research.

Matched MeSH terms: Precision Medicine/methods*
Fulltext A new nested allele-specific multiplex polymerase chain reaction method for haplotyping of VKORC1 gene to predict warfarin sensitivity

Chua YA, Abdullah WZ, Yusof Z, Gan SH

Biomed Res Int, 2014;2014:316310.
PMID: 24790995 DOI: 10.1155/2014/316310

The vitamin K epoxide reductase complex 1 gene (VKORC1) is commonly assessed to predict warfarin sensitivity. In this study, a new nested allele-specific multiplex polymerase chain reaction (PCR) method that can simultaneously identify single nucleotide polymorphisms (SNPs) at VKORC1 381, 861, 5808, and 9041 for haplotype analysis was developed and validated. Extracted DNA was amplified in the first PCR DNA, which was optimized by investigating the effects of varying the primer concentrations, annealing temperature, magnesium chloride concentration, enzyme concentration, and the amount of DNA template. The amplification products produced from the first round of PCR were used as templates for a second PCR amplification in which both mutant and wild-type primers were added in separate PCR tubes, followed by optimization in a similar manner. The final PCR products were resolved by agarose gel electrophoresis and further analysed by using a VKORC1 genealogic tree to infer patient haplotypes. Fifty patients were identified to have H1H1, one had H1H2, one had H1H7, 31 had either H1H7 or H1H9, one had H1H9, eight had H7H7, and one had H8H9 haplotypes. This is the first method that is able to infer VKORC1 haplotypes using only conventional PCR methods.

Matched MeSH terms: Precision Medicine/methods
Fulltext Induced pluripotent stem cells in research and therapy

Teoh HK, Cheong SK

Malays J Pathol, 2012 Jun;34(1):1-13.
PMID: 22870592 MyJurnal

Induced pluripotent stem cells (iPSC) are derived from human somatic cells through ectopic expression of transcription factors. This landmark discovery has been considered as a major development towards patient-specific iPSC for various biomedical applications. Unlimited self renewal capacity, pluripotency and ease of accessibility to donor tissues contribute to the versatility of iPSC. The therapeutic potential of iPSC in regenerative medicine, cell-based therapy, disease modelling and drug discovery is indeed very promising. Continuous progress in iPSC technology provides clearer understanding of disease pathogenesis and ultimately new optimism in developing treatment or cure for human diseases.

Matched MeSH terms: Precision Medicine/methods*
Partial remission in type 1 diabetes and associated factors: Analysis based on the insulin dose-adjusted hemoglobin A1c in children and adolescents from a regional diabetes center, Auckland, New Zealand

Chiavaroli V, Derraik JGB, Jalaludin MY, Albert BB, Ramkumar S, Cutfield WS, et al.

Pediatr Diabetes, 2019 11;20(7):892-900.
PMID: 31237756 DOI: 10.1111/pedi.12881

BACKGROUND: Partial remission (PREM) by the insulin dose-adjusted HbA1c (IDAA1c) method has not been evaluated for the combined associations of ethnicity and socioeconomic status in children and adolescents with type 1 diabetes (T1D).
OBJECTIVE: To investigate prevalence and predictors of PREM defined by IDAA1c.
METHODS: Six hundred fourteen of 678 children (aged <15 years) with new-onset T1D (2000-2013) from a regional pediatric diabetes service (Auckland, New Zealand).
RESULTS: Overall rate of PREM at 3 months was 42.4%, and lower in Māori/Pacific children (28.6%; P = .006) and those of other ethnicities (28.8%; P = .030) compared with New Zealand Europeans (50.4%). Comparing the most and least deprived socioeconomic quintiles, the odds of PREM were lower among the most deprived (adjusted odds ratio [aOR] 0.44; P = .019). Lower rates of PREM were seen in children aged 0 to 4.9 years (23.8%) and 10 to 14 years (40.9%) than in children aged 5 to 9.9 years (57.4%; P

Matched MeSH terms: Precision Medicine/methods
Fulltext Individually-tailored multifactorial intervention to reduce falls in the Malaysian Falls Assessment and Intervention Trial (MyFAIT): A randomized controlled trial

Tan PJ, Khoo EM, Chinna K, Saedon NI, Zakaria MI, Ahmad Zahedi AZ, et al.

PLoS One, 2018;13(8):e0199219.
PMID: 30074996 DOI: 10.1371/journal.pone.0199219

OBJECTIVE: To determine the effectiveness of an individually-tailored multifactorial intervention in reducing falls among at risk older adult fallers in a multi-ethnic, middle-income nation in South-East Asia.

DESIGN: Pragmatic, randomized-controlled trial.

SETTING: Emergency room, medical outpatient and primary care clinic in a teaching hospital in Kuala Lumpur, Malaysia.

PARTICIPANTS: Individuals aged 65 years and above with two or more falls or one injurious fall in the past 12 months.

INTERVENTION: Individually-tailored interventions, included a modified Otago exercise programme, HOMEFAST home hazards modification, visual intervention, cardiovascular intervention, medication review and falls education, was compared against a control group involving conventional treatment.

PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome was any fall recurrence at 12-month follow-up. Secondary outcomes were rate of fall and time to first fall.

RESULTS: Two hundred and sixty-eight participants (mean age 75.3 ±7.2 SD years, 67% women) were randomized to multifactorial intervention (n = 134) or convention treatment (n = 134). All participants in the intervention group received medication review and falls education, 92 (68%) were prescribed Otago exercises, 86 (64%) visual intervention, 64 (47%) home hazards modification and 51 (38%) cardiovascular intervention. Fall recurrence did not differ between intervention and control groups at 12-months [Risk Ratio, RR = 1.037 (95% CI 0.613-1.753)]. Rate of fall [RR = 1.155 (95% CI 0.846-1.576], time to first fall [Hazard Ratio, HR = 0.948 (95% CI 0.782-1.522)] and mortality rate [RR = 0.896 (95% CI 0.335-2.400)] did not differ between groups.

CONCLUSION: Individually-tailored multifactorial intervention was ineffective as a strategy to reduce falls. Future research efforts are now required to develop culturally-appropriate and affordable methods of addressing this increasingly prominent public health issue in middle-income nations.

TRIAL REGISTRATION: ISRCTN Registry no. ISRCTN11674947.

Study site: emergency department, medical outpatients and primary care clinic at a teaching hospital in Kuala Lumpur, Malaysia

Matched MeSH terms: Precision Medicine/methods*
Diffuse large B-cell lymphoma in Southeast Asian cohort: expression patterns of B-cell receptor (BCR) repertoire and its linkage with molecular subtypes and response to R-CHOP therapy

Masir N, Akhter A, Roshan TM, Florence CS, Abdul-Rahman F, Tumian NR, et al.

J Clin Pathol, 2019 Sep;72(9):630-635.
PMID: 31189540 DOI: 10.1136/jclinpath-2019-205837

AIMS: Heightened B-cell receptor (BCR) activity in diffuse large B-cell lymphoma (DLBCL) is well established, and a subset of patients with relapsed DLBCL can benefit from BCR-targeted therapies. Universal outreach of such emerging therapies mandates forming a global landscape of BCR molecular signalling in DLBCL, including Southeast Asia.
METHODS: 79 patients with DLBCL (nodal, 59% and extranodal, 41%) treated with rituximab combined with cyclophosphamide, doxorubicin, vincristine and prednisone (R-CHOP) therapy were selected. Expression levels of BCR and linked signalling pathway molecules were inter-related with Lymph2Cx-based cell of origin (COO) types and overall survival (OS).
RESULTS: Activated B-cell (ABC) type DLBCL constituted 49% (39/79) compared with germinal centre B-cell (GCB) type DLBCL (29/79; 37%) and revealed poor prognosis (p=0.013). In ABC-DLBCL, high BTK expression exerted poor response to R-CHOP, while OS in ABC-DLBCL with low BTK expression was similar to GCB-DLBCL subtype (p=0.004). High LYN expression coupled with a poor OS for ABC-DLBCL as well as GCB-DLBCL subtypes (p=0.001). Furthermore, high coexpression of BTK/LYN (BTKhigh/LYNhigh) showed poor OS (p=0.019), which linked with upregulation of several genes associated with BCR repertoire and nuclear factor-kappa B pathway (p<0.01). In multivariate analysis, high BTK and LYN expression retained prognostic significance against established clinical predictive factors such as age, International Prognostic Index and COO (p<0.05).
CONCLUSIONS: Our data provide a clear association between high BCR activity in DLBCL and response to therapy in a distinct population. Molecular data provided here will pave the pathway for the provision of promising novel-targeted therapies to patients with DLBCL in Southeast Asia.

Matched MeSH terms: Precision Medicine/methods*

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