Gene mutation-based and specific therapies in precision medicine

Schizophrenia Interactome-Derived Repurposable Drugs and Randomized Controlled Trials of Two Candidates

There is a substantial unmet need for effective and patient-acceptable drugs to treat severe mental illnesses such as schizophrenia (SZ). Computational analysis of genomic, transcriptomic, and pharmacologic data generated in the past 2 decades enables repurposing of drugs or compounds with acceptable safety profiles, namely those that are U.S. Food and Drug Administration approved or have reached late stages in clinical trials. We developed a rational approach to achieve this computationally for SZ by studying drugs that target the proteins in its protein interaction network (interactome). This involved contrasting the transcriptomic modulations observed in the disorder and the drug; our analyses resulted in 12 candidate drugs, 9 of which had additional supportive evidence whereby their target networks were enriched for pathways relevant to SZ etiology or for genes that had an association with diseases pathogenically similar to SZ. To translate these computational results to the clinic, these shortlisted drugs must be tested empirically through randomized controlled trials, in which their previous safety approvals obviate the need for time-consuming phase 1 and 2 studies. We selected 2 among the shortlisted candidates based on likely adherence and side-effect profiles. We are testing them through adjunctive randomized controlled trials for patients with SZ or schizoaffective disorder who experienced incomplete resolution of psychotic features with conventional treatment. The integrated computational analysis for identifying and ranking drugs for clinical trials can be iterated as additional data are obtained. Our approach could be expanded to enable disease subtype-specific drug discovery in the future and should also be exploited for other psychiatric disorders.

Diagnostic Accuracy of FluoroCycler XT MTBDR Assay for Detection of Rifampicin and Isoniazid-resistant Mycobacteria tuberculosis in Clinical Isolates from Kenya

BACKGROUND

Drug-resistant tuberculosis (DR-TB) poses a major global challenge to public health and therapeutics. It is an emerging global concern associated with increased morbidity and mortality mostly seen in the low- and middle-income countries. Molecular techniques are highly sensitive and offer timely and accurate results for TB drug resistance testing, thereby positively influencing patient management plan.

METHODS

The study was carried out at the National Tuberculosis Reference Laboratory (NTRL) in Kenya in the period between January and October 2022. A total of 243 Mycobacterium tuberculosis (M.tb) clinical isolates were included in the study. These isolates comprised of 50 isolates with mutations in rpoB, 51 isolates with katG mutations, 51 isolates with mutations in inhA, and 91 M.tb isolates lacking mutations in these genes based on Genotype MTBDRplus results. DNA from the isolates was extracted using the FluoroLyse extraction kit. Real-time polymerase chain reaction targeting the rpoB, InhA, and katG genes was performed using the FluoroType MTBDR amplification mix. Isolates with discordant results between Genotype MTBDRplus and FluoroCycler® MTBDR assays underwent targeted sequencing for the respective genes, then, sequences were analyzed for mutations using Geneious version 11.0 software.

RESULTS

The sensitivity of the Fluorocycler XT MTBDR assay for the detection of mutations that confer drug resistance was 86% (95% confidence interval [CI] 73.0-94.0) for rpoB, 96% (95% CI 87-100) for katG and 92% (95% CI 81-98) for inhA. The assay's specificity was 97% (95% CI 93-99) for rpoB, 98% (95% CI 96-100) for katG, and 97% (95% CI 93-99) for inhA.

CONCLUSION

The diagnostic accuracy of FluoroType MTBDR for the detection of mutations conferring resistance to rifampicin and isoniazid was high compared with that of Genotype MTBDRplus and demonstrates its suitability as a replacement assay for Genotype MTBDRplus.

Precision Medicine in Depression: The Role of Proteomics and Metabolomics in Personalized Treatment Approaches

Depression, or major depressive disorder (MDD), is a widespread mental health condition marked by enduring feelings of sorrow and loss of interest. Treatment of depression frequently combines psychotherapy, medication, and lifestyle modifications. However, the occurrence of treatment resistance in certain individuals makes it difficult for physicians to effectively manage this disorder, calling for the implementation of alternative therapeutic strategies. Recently, precision medicine has gained increased attention in the field of mental health, paving the way for more personalized and effective therapeutic interventions in depression. Also known as personalized medicine, this approach relies on genetic composition, molecular profiles, and environmental variables to customize therapies to individual patients. In particular, precision medicine has offered novel viewpoints on depression through two specific domains: proteomics and metabolomics. On one hand, proteomics is the thorough study of proteins in a biological system, while metabolomics focuses on analyzing the complete set of metabolites in a living being. In the past few years, progress in research has led to the identification of numerous depression-related biomarkers using proteomics and metabolomics techniques, allowing for early identification, precise diagnosis, and improved clinical outcome. However, despite significant progress in these techniques, further efforts are required for advancing precision medicine in the diagnosis and treatment of depression. The overarching goal of this chapter is to provide the current state of knowledge regarding the use of proteomics and metabolomics in identifying biomarkers related to depression. It also highlights the potential of proteomics and metabolomics in elucidating the intricate processes underlying depression, opening the door for tailored therapies that could eventually enhance clinical outcome in depressed patients. This chapter finally discusses the main challenges in the use of proteomics and metabolomics and discusses potential future research directions.

The molecular landscape of oculocutaneous albinism in India and its therapeutic implications

Oculocutaneous albinism is an inherited disorder of melanin biosynthesis, characterized by absent or reduced pigmentation of the skin, hair, and eyes. Molecular alterations of genes that cause non-syndromic albinism in Asian Indians are poorly characterized. This information would be useful for developing therapies for this disorder. We analyzed 164 persons with non-syndromic albinism, belonging to unrelated families from all parts of India, for molecular changes in the causative genes. Subjects with white hair, white skin, and red iris had their tyrosinase gene sequenced and were also tested by MLPA for deletions/duplications. Subjects with negative results or with darker skin, golden/brown or darker hair had sequencing of TYR, P, TYRP1, SLC45A2 and GPR143 genes. Pathogenic variants in TYR (OCA1) were observed in 139 (84.7%) patients, in the P gene (OCA2) in 20 (12.2%), in TYRP1 (OCA3) in two (1.2%), in SLC45A2 (OCA 4) in one (0.61%), and in GPR143 (X-linked ocular albinism) in two (1.2%) patients. Of 278 alleles with variants in TYR, 179 (64.3%) alleles had (p.R278*) alteration, suggesting the possibility of therapy with a stop codon readthrough molecule. We report 20 patients with 13 disease associated variants in the P gene and 18 novel pathogenic variants in TYR, P, TYRP1, SLC45A2 and GPR143 genes. The data are compared with those reported from India, Pakistan and rest of the world. The therapeutic options in albinism are briefly described, opening this field for future therapies.

Precision Medicine: Steps along the Road to Combat Human Cancer

The diagnosis and treatment of diseases such as cancer is becoming more accurate and specialized with the advent of precision medicine techniques, research and treatments. Reaching down to the cellular and even sub-cellular level, diagnostic tests can pinpoint specific, individual information from each patient, and guide providers to a more accurate plan of treatment. With this advanced knowledge, researchers and providers can better gauge the effectiveness of drugs, radiation, and other therapies, which is bound to lead to a more accurate, if not more positive, prognosis. As precision medicine becomes more established, new techniques, equipment, materials and testing methods will be required. Herein, we will examine the recent innovations in assays, devices and software, along with next generation sequencing in genomics diagnostics which are in use or are being developed for personalized medicine. So as to avoid duplication and produce the fullest possible benefit, all involved must be strongly encouraged to collaborate, across national borders, public and private sectors, science, medicine and academia alike. In this paper we will offer recommendations for tools, research and development, along with ideas for implementation. We plan to begin with discussion of the lessons learned to date, and the current research on pharmacogenomics. Given the steady stream of advances in imaging mass spectrometry and nanoLC-MS/MS, and use of genomic, proteomic and metabolomics biomarkers to distinguish healthy tissue from diseased cells, there is great potential to utilize pharmacogenomics to tailor a drug or drugs to a particular cohort of patients. Such efforts very well may bring increased hope for small groups of non-responders and those who have demonstrated adverse reactions to current treatments.

Meta-analysis of cardiomyopathy-associated variants in troponin genes identifies loci and intragenic hot spots that are associated with worse clinical outcomes

INTRODUCTION

Troponin (TNN)-encoded cardiac troponins (Tn) are critical for sensing calcium and triggering myofilament contraction. TNN variants are associated with development of cardiomyopathy; however, recent advances in genetic analysis have identified rare population variants. It is unclear how certain variants are associated with disease while others are tolerated.

OBJECTIVE

To compare probands with TNNT2, TNNI3, and TNNC1 variants and utilize high-resolution variant comparison mapping of pathologic and rare population variants to identify loci associated with disease pathogenesis.

METHODS

Cardiomyopathy-associated TNN variants were identified in the literature and topology mapping conducted. Clinical features were compiled and compared. Rare population variants were obtained from the gnomAD database. Signal-to-noise (S:N) normalized pathologic variant frequency against population variant frequency. Abstract review of clinical phenotypes was applied to "significant" hot spots.

RESULTS

Probands were compiled (N = 70 studies, 224 probands) as were rare variants (N = 125,748 exomes; 15,708 genomes, MAF <0.001). TNNC1-positive probands demonstrated the youngest age of presentation (20.0 years; P = .016 vs TNNT2; P = .004 vs TNNI3) and the highest death, transplant, or ventricular fibrillation events (P = .093 vs TNNT2; P = .024 vs TNNI3; Kaplan Meir: P = .025). S:N analysis yielded hot spots of diagnostic significance within the tropomyosin-binding domains, α-helix 1, and the N-Terminus in TNNT2 with increased sudden cardiac death and ventricular fibrillation (P = .004). The inhibitory region and C-terminal region in TNNI3 exhibited increased restrictive cardiomyopathy (P =.008). HCM and RCM models tended to have increased calcium sensitivity and DCM decreased sensitivity (P < .001). DCM and HCM studies typically showed no differences in Hill coefficient which was decreased in RCM models (P < .001). CM models typically demonstrated no changes to Fmax (P = .239).

CONCLUSION

TNNC1-positive probands had younger ages of diagnosis and poorer clinical outcomes. Mapping of TNN variants identified locations in TNNT2 and TNNI3 associated with heightened pathogenicity, RCM diagnosis, and increased risk of sudden death.

Clinical lipidomics in understanding of lung cancer: Opportunity and challenge

Disordered lipid metabolisms have been evidenced in lung cancer as well as its subtypes. Lipidomics with in-depth mining is considered as a critical member of the multiple omics family and a lipid-specific tool to understand disease-associated lipid metabolism and disease-specific dysfunctions of lipid species, discover biomarkers and targets for monitoring therapeutic strategies, and provide insights into lipid profiling and pathophysiological mechanisms in lung cancer. The present review describes the characters and patterns of lipidomic profiles in patients with different lung cancer subtypes, important values of comprehensive lipidomic profiles in understanding of lung cancer heterogeneity, urgent needs of standardized methodologies, potential mechanisms by lipid-associated enzymes and proteins, and the importance of integration between clinical phenomes and lipidomic profiles. The characteristics of lipidomic profiles in different lung cancer subtypes are extremely varied among study designs, objects, methods, and analyses. Preliminary data from recent studies demonstrate the specificity of lipidomic profiles specific for lung cancer stage, severity, subtype, and response to drugs. The heterogeneity of lipidomic profiles and lipid metabolism may be part of systems heterogeneity in lung cancer and be responsible for the development of drug resistance, although there are needs for direct evidence to show the existence of intra- or inter-lung cancer heterogeneity of lipidomic profiles. With an increasing understanding of expression profiles of genes and proteins, lipidomic profiles should be associated with activities of enzymes and proteins involved in the processes of lipid metabolism, which can be profiled with genomics and proteomics, and to provide the opportunity for the integration of lipidomic profiles with gene and protein expression profiles. The concept of clinical trans-omics should be emphasized to integrate data of lipidomics with clinical phenomics to identify disease-specific and phenome-specific biomarkers and targets, although there are still a large number of challenges to be overcome in the integration between clinical phenomes and lipidomic profiles.

Utilization of Archived Plasma to Detect Epidermal Growth Factor Receptor Mutation in Non-Small Cell Lung Cancer Patients

Precision medicine has received increased attention as an effective approach for the treatment of cancer patients. Because of challenges associated with the availability of archived tissue, liquid biopsies are often performed to detect cancer-specific mutations. One of the major advantages of the liquid biopsy is that the treatment can be monitored longitudinally, even after the tumor tissue is no longer available. In a clinical setting, one component of precision medicine is the detection of cancer-specific mutations using archived samples. In this study, we evaluated the epidermal growth factor receptor (EGFR) mutation status of samples of lung cancer patients stored before introduction of the plasma EGFR test at our institution. The aim of this study was to validate the utility of archived plasma samples for detection of the EGFR mutation in nonsmall cell lung cancer (NSCLC) patients. The Cobas^® EGFR Mutation Test v2 was the first liquid biopsy test approved as a companion diagnostic test for patients with NSCLC treated with tyrosine kinase inhibitors. We tested for the EGFR mutation in 116 plasma samples archived in the biobank, and the results were compared with those obtained in the tissue or cytology EGFR mutation test. The EGFR mutation-positive rate from archived plasma was lower than that determined from tissue or cytology at 19.0% and 53.4%, respectively, and the concordance rate between the two tests was 58.6%. Of interest, five (4.3%) samples showed the T790M mutation in the plasma test, whereas this mutation was only detected in two (1.7%) tissue/cytology samples. Five (4.3%) samples were additionally positive in the plasma test. Overall, these results indicate that archived plasma samples can serve as an alternative source for the plasma EGFR mutation test when tissue samples are not available, and can improve precision medicine and long-term follow-up in a noninvasive manner.

The advances in CRISPR technology and 3D genome

The clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein (Cas) system is a prokaryotic immune system that used to resist foreign genetic factors. It rapidly becomes the hot technology in life sciences and is applies for genome editing to solve the problem of genome-derived diseases. Using CRISPR/Cas technique, the biological DNA sequence can be repaired, cut, replaced, or added. It can effectively change the human stem cells and is expected to achieve results in the treatment. Compared with ZFN and TALEN genome editing techniques, CRISPR is more effective, accurate, and convenient. The application of CRISPR technique in three dimensional (3D) genome structure makes us understand the relationship between linear DNA sequence and 3D chromatin structure. Utilizing CRISPR/Cas9 genome editing to reverse or delete CTCF binding sites, to recognize changes of topological isomerism of the genome and interactions between chromatin loops. The purpose of this review is to introduce the characteristics and classification of the current CRISPR/Cas system, multiple functions, and potential therapeutic uses, as well as to outline the effect of the technique on chromatin loops by changing CTCF sites in 3D genomes. We will also briefly describe the importance of ethical dilemmas to be faced in CRISPR applications and provide a perspective for potential CRISPR considerations.

Application of Single Cell Sequencing in Cancer

Cancer is a heterogenetic disease at both the level of clinical manifestation and the level of the genome. Single-cell sequencing provides an unprecedented means of characterizing the intra-tumor heterogeneity and detecting and analyzing the genomes of cancer cells. These data will help to reconstruct the understanding of the evolutionary lineage of cancer cells. In the future, single-cell technology is believed to be a useful tool in diagnostic and prognostic application in oncology. The application of single cell technology in clinics will make it possible to detect cancer non-invasively at early stages and to develop precision medicine. In this chapter, we review the research and application status of the single cell technology in cancer.

Role of precision medicine in pancreatic cancer

Pancreatic cancer is one of the most challenging problems in modern oncology. Due to difficultly in early diagnosis and early distant metastasis of pancreatic cancer, surgical resection rate is less than 20% and patients' prognosis is very poor. Despite long-term efforts taken to develop treatments for pancreatic cancer, the survival rate did not significantly improve. Therefore, early diagnosis and treatment are the key to improve the survival rate of patients with pancreatic cancer. The advent of big-data genomic era and the rapid development of biotechnology have led to the recent proposal of a new concept of precise medicine, which has quickly become the focus of world medical conferences. Here, we describe the new progress and challenges of precision medicine in pancreatic cancer, with an aim to provide new ideas for improving the survival rate of patients with pancreatic cancer.

Gene heterogeneity in metastasis of colorectal cancer to the lung

Colorectal cancer (CRC) as a heterogeneous disease, is one of the most common and serious cancers with high metastases and mortality. Lung is one of the most common sites of CRC metastases with high heterogeneity between cells, pathways, or molecules. The present review will focus on potential roles of gene heterogeneity in KRAS pathway in the development of CRC metastasis to lung and clinical therapies, which would lead to better understanding of the metastatic control and benefit to the treatment of metastases. KRAS is the central relay for pathways originating at the epidermal growth factor receptor (EGFR) family. KRAS mutation exists in about 40% CRC, associated with higher cumulative incidence of CRC lung metastasis, and acts as an independent predictor of metastasis to lung. Mutations in KRAS can lead to poor response of patients to panitumumab, and inferior progression-free survival. However, most patients with KRAS wild-type tumors still do not respond, which indicates other mutations. Phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA) mutation was associated with lung metastases in metastatic colorectal cancer. PIK3CA mutation in exon 20 was found to be correlated with patient survival in the metastatic setting after the treatment with cetuximab and chemotherapy. The heterogeneity of KRAS pathway was found in the phosphatase and tensin homologue deleted on chromosome ten loss, disheveled binding antagonist of beta catenin 2 overexpression and increased dual-specificity protein phosphatase 4 expression of CRC lung metastasis.

Systems heterogeneity: An integrative way to understand cancer heterogeneity

The concept of systems heterogeneity was firstly coined and explained in the Special Issue, as a new alternative to understand the importance and complexity of heterogeneity in cancer. Systems heterogeneity can offer a full image of heterogeneity at multi-dimensional functions and multi-omics by integrating gene or protein expression, epigenetics, sequencing, phosphorylation, transcription, pathway, or interaction. The Special Issue starts with the roles of epigenetics in the initiation and development of cancer heterogeneity through the interaction between permanent genetic mutations and dynamic epigenetic alterations. Cell heterogeneity was defined as the difference in biological function and phenotypes between cells in the same organ/tissue or in different organs, as well as various challenges, as exampled in telocytes. The single cell heterogeneity has the value of identifying diagnostic biomarkers and therapeutic targets and clinical potential of single cell systems heterogeneity in clinical oncology. A number of signaling pathways and factors contribute to the development of systems heterogeneity. Proteomic heterogeneity can change the strategy and thinking of drug discovery and development by understanding the interactions between proteins or proteins with drugs in order to optimize drug efficacy and safety. The association of cancer heterogeneity with cancer cell evolution and metastasis was also overviewed as a new alternative for diagnostic biomarkers and therapeutic targets in clinical application.

Tumor Heterogeneity, Single-Cell Sequencing, and Drug Resistance

Tumor heterogeneity has been compared with Darwinian evolution and survival of the fittest. The evolutionary ecosystem of tumors consisting of heterogeneous tumor cell populations represents a considerable challenge to tumor therapy, since all genetically and phenotypically different subpopulations have to be efficiently killed by therapy. Otherwise, even small surviving subpopulations may cause repopulation and refractory tumors. Single-cell sequencing allows for a better understanding of the genomic principles of tumor heterogeneity and represents the basis for more successful tumor treatments. The isolation and sequencing of single tumor cells still represents a considerable technical challenge and consists of three major steps: (1) single cell isolation (e.g., by laser-capture microdissection), fluorescence-activated cell sorting, micromanipulation, whole genome amplification (e.g., with the help of Phi29 DNA polymerase), and transcriptome-wide next generation sequencing technologies (e.g., 454 pyrosequencing, Illumina sequencing, and other systems). Data demonstrating the feasibility of single-cell sequencing for monitoring the emergence of drug-resistant cell clones in patient samples are discussed herein. It is envisioned that single-cell sequencing will be a valuable asset to assist the design of regimens for personalized tumor therapies based on tumor subpopulation-specific genetic alterations in individual patients.