Article
Dermatology
R. Varaljai, S. Elouali, S. S. Lueong, K. Wistuba-Hamprecht, T. Seremet, J. T. Siveke, J. C. Becker, A. Sucker, A. Paschen, P. A. Horn, B. Neyns, B. Weide, D. Schadendorf, A. Roesch
Summary: This study demonstrates that high cfDNA concentration can serve as a biomarker for melanoma regardless of tumor genotype, providing information on tumor burden, risk of progression, and risk of death.
JOURNAL OF THE EUROPEAN ACADEMY OF DERMATOLOGY AND VENEREOLOGY
(2021)
Review
Biochemistry & Molecular Biology
Qasem Al-Tashi, Maliazurina B. Saad, Amgad Muneer, Rizwan Qureshi, Seyedali Mirjalili, Ajay Sheshadri, Xiuning Le, Natalie I. Vokes, Jianjun Zhang, Jia Wu
Summary: The identification of biomarkers is crucial in personalized medicine, but differentiating between predictive and prognostic biomarkers can be challenging due to overlap. Prognostic biomarkers predict cancer outcomes regardless of treatment, while predictive biomarkers assess the effectiveness of therapeutic interventions. Misclassifying them can have serious consequences for patients. This study provides an in-depth analysis of recent advancements, challenges, and future prospects in biomarker identification, using a systematic search of studies published between 2017 and 2023. The review aims to serve as a valuable resource for researchers in understanding biomarker discovery methods and identifying future research opportunities.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Genetics & Heredity
Huifang Xu, Linfang Zhang, Xiujuan Xia, Wei Shao
Summary: This study identified five mRNA biomarkers associated with survival in glioblastoma patients and successfully verified their prognostic value. These findings provide new prospective prognostic biomarkers for glioblastoma.
FRONTIERS IN GENETICS
(2022)
Article
Multidisciplinary Sciences
Jian Ouyang, Guangrong Qin, Zhenhao Liu, Xingxing Jian, Tieliu Shi, Lu Xie
Summary: Patients with different molecular characteristics and subtypes of cancer have different responses to treatment and survival rates. Identifying features associated with prognosis is crucial for precision medicine and can provide clues for target identification and drug discovery. The tumor online prognostic analysis platform (ToPP) integrates multi-omics features and clinical data, and offers various approaches for customized prognostic studies and services.
Article
Endocrinology & Metabolism
Chunguang Li, Cheng Gong, Wenhao Chen, Daojiang Li, Youli Xie, Wenhui Tao
Summary: A study identified nine genes associated with gastric cancer prognosis using genomic data and constructed a machine learning model for predicting gastric cancer prognosis. The model showed high accuracy in internal and external validation, outperforming five existing prediction models.
JOURNAL OF BIOLOGICAL REGULATORS AND HOMEOSTATIC AGENTS
(2023)
Article
Genetics & Heredity
Huanlong Liu, Chao Chen, Long Liu, Zengtao Wang
Summary: This study aimed to use a long noncoding RNA (lncRNA) risk signature for predicting the survival of osteosarcoma patients and investigate its potential functions. Four lncRNAs were identified as independent prognostic factors and a reliable risk signature was constructed. Functional enrichment analysis provided new insights into the role of these lncRNAs in osteosarcoma.
FRONTIERS IN GENETICS
(2023)
Article
Genetics & Heredity
Zhiying Lin, Rongsheng Wang, Cuilan Huang, Huiwei He, Chenghong Ouyang, Hainan Li, Zhiru Zhong, Jinghua Guo, Xiaohong Chen, Chunli Yang, Xiaogang Yang
Summary: The study identified five hub genes that are important for the prognosis of GBM patients through differential expression, mutation analysis, and weighted gene co-expression network analysis. The risk model constructed from these genes was found to be positively correlated with immune cell infiltration in the tumor microenvironment and the expression of critical immune checkpoints, suggesting a potential association with poor prognosis due to TIDE.
FRONTIERS IN GENETICS
(2022)
Review
Oncology
Craig T. Wallington-Beddoe, Rachel L. Mynott
Summary: New approaches are needed to stratify multiple myeloma patients based on prognosis and therapeutic decision-making, however, insufficient information currently exists to utilize biomarkers to tweak treatment. With the increasing complexity of drug classes used to treat multiple myeloma, clinically useful biomarkers are crucial in guiding personalized patient management.
JOURNAL OF HEMATOLOGY & ONCOLOGY
(2021)
Review
Cell Biology
Oluwaseyi Adeuyan, Emily R. Gordon, Divya Kenchappa, Yadriel Bracero, Ajay Singh, Gerardo Espinoza, Larisa J. Geskin, Yvonne M. Saenger
Summary: The approval of immunotherapy for stage II-IV melanoma has highlighted the need for improved immune-based predictive and prognostic biomarkers. Several techniques are currently under investigation for the detection of prognostic and predictive immune biomarkers in melanoma.
FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY
(2023)
Review
Biochemistry & Molecular Biology
Paulina Sledzinska, Marek G. Bebyn, Jacek Furtak, Janusz Kowalewski, Marzena A. Lewandowska
Summary: The latest research on prognostic and predictive biomarkers in gliomas has been compiled, highlighting the importance of prognostic markers in adult and pediatric patients and the clinical significance in predicting treatment responses. Further work is needed to implement novel technologies such as liquid biopsies in clinical practice.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2021)
Review
Oncology
Qiaorui Tan, Sha Yin, Dongdong Zhou, Yajing Chi, Xiaochu Man, Huihui Li
Summary: Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with poor prognosis and limited effective treatment options. Immunotherapy based on immune checkpoint inhibition shows promise, but its efficacy varies among TNBC patients. Therefore, identifying predictive biomarkers for immunotherapy response is crucial.
FRONTIERS IN ONCOLOGY
(2022)
Review
Biochemistry & Molecular Biology
Galateia Liouta, Maria Adamaki, Antonis Tsintarakis, Panagiotis Zoumpourlis, Anastasia Liouta, Sofia Agelaki, Vassilis Zoumpourlis
Summary: Head and neck squamous cell carcinoma (HNSCC) is a term used to describe cancers in the head and neck region. Most cases are diagnosed at a late stage and have poor prognosis. DNA methylation has been identified as a potential biomarker for HNSCC, and this study summarizes the current knowledge on how abnormally methylated DNA profiles may contribute to the development and progression of HNSCC, with the aim of improving management and survival outcomes for patients.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Review
Oncology
Sandra Pavicevic, Sophie Reichelt, Deniz Uluk, Isabella Lurje, Cornelius Engelmann, Dominik P. Modest, Uwe Pelzer, Felix Krenzien, Nathanael Raschzok, Christian Benzing, Igor M. Sauer, Sebastian Stintzing, Frank Tacke, Wenzel Schoening, Moritz Schmelzle, Johann Pratschke, Georg Lurje
Summary: Cholangiocarcinoma is a rapidly increasing global malignancy of the biliary tract, often presenting with advanced or unresectable disease. Biomarkers obtained from patients' serum or tumor tissue could help guide therapy and identify those at higher risk of recurrence. Genetic aberrations in cholangiocarcinoma have also been linked with improved response to targeted therapies. This review provides an overview of prognostic and predictive biomarkers in cholangiocarcinoma.
Article
Multidisciplinary Sciences
Xiuqiong Chen, Zhaona Li, Jing Zhou, Qianhui Wei, Xinyue Wang, Richeng Jiang
Summary: This study aimed to explore the association between baseline characteristics of lung cancer patients and the efficacy of immunotherapy. The results showed that age, white blood cell count, lymphocyte count, monocyte count, hemoglobin, lactate dehydrogenase, albumin, and treatment line were significantly associated with progression-free survival (PFS) after immunotherapy. A nomogram based on age, albumin, monocyte count, lactate dehydrogenase, and treatment line was established to predict the prognosis of lung cancer patients receiving immunotherapy.
Article
Genetics & Heredity
Shengnan Gao, Xinjie Wu, Xiaoying Lou, Wei Cui
Summary: This study classified breast cancer samples into three groups based on glycosylation patterns and identified 23 key molecules to construct a prognostic model. The model showed promising performance in predicting breast cancer prognosis and immune infiltration. This research has important implications for personalized treatment and understanding the heterogeneity of breast cancer.
FRONTIERS IN GENETICS
(2022)
