Precision Medicine In Cancer

Lung cancer is an exceedingly malignant tumor reported as having the highest morbidity and mortality of any cancer worldwide, thus posing a great threat to global health. Despite the growing demand for precision medicine, current methods for early clinical detection, treatment and prognosis monitoring in lung cancer are hampered by certain bottlenecks. Studies have found that during the formation and development of a tumor, molecular substances carrying tumor-related genetic information can be released into body fluids...

Electroceuticals have evolved beyond devices manipulating neuronal signaling for symptomatic treatment, becoming more precise and disease modulating and expanding beyond the nervous system. These advancements promise transformative applications in arthritis, cancer treatment, tissue regeneration, and more. Here, we discuss these recent advances and offer insights for future research.

BACKGROUND: The utilization of Chinese medicine as an adjunctive therapy for cancer has recently gained significant attention. Ferroptosis, a newly regulated cell death process depending on the ferrous ions, has been proved to be participated in glioma stem cells inactivation. PURPOSE: We aim to study whether ginsenoside Rg5 exerted inhibitory effects on crucial aspects of glioma stem cells, including cell viability, tumor initiation, invasion, self-renewal ability, neurosphere formation, and stemness...

BACKGROUND: Poly(ADP-ribose) polymerase (PARP) inhibitors have emerged as promising chemotherapeutic drugs primarily against BRCA1/2-associated tumours, known as synthetic lethality. However, recent clinical trials reported patients' survival benefits from PARP inhibitor treatments, irrelevant to homologous recombination deficiency. Therefore, revealing the therapeutic mechanism of PARP inhibitors beyond DNA damage repair is urgently needed, which can facilitate precision medicine. METHODS: A CRISPR-based knock-in technology was used to establish stable BRCA1 mutant cancer cells...

Predicting the response of tumor cells to anti-tumor drugs is critical to realizing cancer precision medicine. Currently, most existing methods ignore the regulatory relationships between genes and thus have unsatisfactory predictive performance. In this paper, we propose to predict anti-tumor drug efficacy via learning the activity representation of tumor cells based on a priori knowledge of gene regulation networks (GRNs). Specifically, the method simulates the cellular biosystem by synthesizing a cell-gene activity network and then infers a new low-dimensional activity representation for tumor cells from the raw high-dimensional expression profile...

In response to the high incidence and poor prognosis of lung cancer, this study tends to develop a generalizable lung-cancer prediction model by using machine learning to define high-risk groups and realize the early identification and prevention of lung cancer. We included 467,888 participants from UK Biobank, using lung cancer incidence as an outcome variable, including 49 previously known high-risk factors and less studied or unstudied predictors. We developed multivariate prediction models using multiple machine learning models, namely logistic regression, naïve Bayes, random forest, and extreme gradient boosting models...

With the rise of precision medicine, the continuous expansionWith the rise of precision medicine, the continuous expansion the collective push from many other the application of Artificial Intelligence (AI) in prostate cancer diagnosis is increasingly becoming a focal point. AI technology can effectively utilize diverse detection methods such as Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET), and whole pathology slide imaging to efficiently identify and differentiate between benign and malignant lesions...

Gastrointestinal cancers account for approximately one-third of the total global cancer incidence and mortality with a poor prognosis. It is one of the leading causes of cancer-related deaths worldwide. Most of these diseases lack effective treatment, occurring as a result of inappropriate models to develop safe and potent therapies. As a novel preclinical model, tumor patient-derived organoids (PDOs), can be established from patients' tumor tissue and cultured in the laboratory in 3D architectures. This 3D model can not only highly simulate and preserve key biological characteristics of the source tumor tissue in vitro but also reproduce the in vivo tumor microenvironment through co-culture...

Despite affecting ~11-13% of women globally, polycystic ovary syndrome (PCOS) is a substantially understudied condition. PCOS, possibly extending to men's health, imposes a considerable health and economic burden worldwide. Diagnosis in adults follows the International Evidence-based Guideline for the Assessment and Management of Polycystic Ovary Syndrome, requiring two out of three criteria - clinical or biochemical hyperandrogenism, ovulatory dysfunction, and/or specific ovarian morphological characteristics or elevated anti-Müllerian hormone...

Esophageal adenocarcinoma is the most common histological subtype of esophageal cancer in Western countries and shows poor prognosis with rapid growth. EAC is characterized by a strong male predominance and racial disparity. EAC is up to fivefold more common among Whites than Blacks, yet Black patients with EAC have poorer survival rates. The racial disparity remains largely unknown, and there is limited knowledge of mutations in EAC regarding racial disparities. We used whole-exome sequencing to show somatic mutation profiles derived from tumor samples from 18 EAC male patients...

In contemporary oncologic diagnostics, molecular imaging modalities are pivotal for precise local and metastatic staging. Recent studies identified fibroblast activation protein as a promising target for molecular imaging across various malignancies. Therefore, we aimed to systematically evaluate the current literature on the utility of fibroblast activation protein inhibitor (FAPI) PET/CT for staging patients with genitourinary malignancies. Methods: A systematic Embase and Medline search was conducted, according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) process, on August 1, 2023...

Medical image segmentation is a crucial field of computer vision. Obtaining correct pathological areas can help clinicians analyze patient conditions more precisely. We have observed that both CNN-based and attention-based neural networks often produce rough segmentation results around the edges of the regions of interest. This significantly impacts the accuracy of obtaining the pathological areas. Without altering the original data and model architecture, further refining the initial segmentation outcomes can effectively address this issue and lead to more satisfactory results...

BACKGROUND: In the era of precision medicine, determining reliable renal function assessment remains a critical and debatable issue, especially in nephrology and oncology. SUMMARY: This paper delves into the significance of accurately measured Glomerular Filtration Rate (mGFR) in clinical practice, highlighting its essential role in guiding medical decisions and managing kidney health, particularly in the context of renal cancer (RC) patients undergoing nephrotoxic anti-cancer drugs...

Novel strategies in intratumoral injection and emerging immunotherapies have heralded a new era of precise cancer treatments. The affinity of SARS-CoV-2 to ACE2 receptors, a feature which facilitates virulent human infection, is leveraged in this research. Colon cancer cells, with their high ACE2 expression, provide a potentially strategic target for using this SARS-CoV-2 feature. While the highly expression of ACE2 is observed in several cancer types, the idea of using the viral spike protein for targeting colon cancer cells offers a novel approach in cancer treatment...

Accurately predicting tumor T-cell antigen (TTCA) sequences is a crucial task in the development of cancer vaccines and immunotherapies. TTCAs derived from tumor cells, are presented to immune cells (T cells) through major histocompatibility complex (MHC), via the recognition of specific portions of their structure known as epitopes. More specifically, MHC class I introduces TTCAs to T-cell receptors (TCR) which are located on the surface of CD8+ T cells. However, TTCA sequences are varied and lead to struggles in vaccine design...

PURPOSE: The multicenter, open-label, randomized phase 2 NCI-9944 study (NCT02595892) demonstrated that addition of ATR inhibitor (ATRi) berzosertib to gemcitabine increased progression-free survival (PFS) compared to gemcitabine alone (hazard ratio [HR]=0.57, one-sided log-rank P = .044, which met the one-sided significance level of 0.1 used for sample size calculation). METHODS: We report here the final overall survival (OS) analysis and biomarker correlations (ATM expression by immunohistochemistry, mutational signature 3 and a genomic biomarker of replication stress) along with post-hoc exploratory analyses to adjust for crossover from gemcitabine to gemcitabine/berzosertib...

PURPOSE: To understand the mutational landscape of circulating tumor DNA (ctDNA) and tumor tissue of patients with hormone receptor-positive (HR+), human epidermal growth factor receptor-2-negative (HER2-) metastatic breast cancer (MBC) treated with abemaciclib + endocrine therapy (ET). METHODS: Blood samples for ctDNA and/or tissue samples were collected from abemaciclib-treated patients with HR+/HER2- MBC enrolled in the SCRUM-Japan MONSTAR-SCREEN project. Blood samples were collected before abemaciclib initiation (baseline) and at disease progression/abemaciclib discontinuation (post abemaciclib treatment)...

PURPOSE: Few studies have explored the potential for pharmacological interventions to delay disease progression in patients undergoing active surveillance (AS). This preplanned transcriptomic analysis of patient samples from the ENACT trial aims to identify biomarkers in patients on AS who are at increased risk for disease progression or who may derive the greatest benefit from enzalutamide treatment. PATIENTS AND METHODS: In the phase II ENACT (ClinicalTrials.gov identifier: NCT02799745) trial, patients on AS were randomly assigned 1:1 to 160 mg orally once daily enzalutamide monotherapy or continued AS for 1 year...

PURPOSE: High-grade neuroendocrine carcinoma (HGNEC) of the lung is an aggressive cancer with a complex biology. We aimed to explore the prognostic value of genetic aberrations and poly(ADP-ribose) polymerase-1 (PARP1) expression in HGNEC and to establish a novel prognostic model. MATERIALS AND METHODS: We retrospectively enrolled 191 patients with histologically confirmed HGNEC of the lung. Tumor tissues were analyzed using PARP1 immunohistochemistry (IHC; N = 191) and comprehensive cancer panel sequencing (n = 102)...

Pancreatic cancer is a fatal illness caused by mutations in multiple genes. Pancreatic cancer damages the organ that helps in digestion, resulting in symptoms including fatigue, bloating, and nausea. The use of medicinal plants has been crucial in the treatment of numerous disorders. The medicinal plant Calliandra Harrisi has been widely exploited for its possibilities in biology and medicine. The current study aimed to assess the biopotential of biologically active substances against pancreatic cancer. The GC-MS data of these phytochemicals from Calliandra Harrisi were further subjected to computational approaches with pancreatic cancer genes to evaluate their potential as therapeutic candidates...