The Landscape of Biomarkers: From Traditional Measures to Multi-Omics Powerhouses

A biomarker is an indicator that can be quantified to show whether a biological process is pathogenic, normal, or responding to an intervention or exposure. Regarding the basic definitions and concepts involved in their application in clinical practice and research, there is a great deal of misunderstanding. Therefore in the spring of 2015 at a joint leadership conference of the National Institutes of Health (NIH) and the U.S. Food and Drug Administration (FDA), a collaborative task force was established with the goal of creating shared definitions and disseminating to the general public via an online document known as "Biomarkers, EndpointS, and other Tools" (BEST), which is updated on a regular basis. The idea behind BEST is to increase collective capacity to match a biomarker with its appropriate use in order to be able to develop diagnostic and therapeutic technologies and strategies more quickly, efficiently, and precisely. This will also help with the creation and application of public health policies. [1]

When employed as endpoints in clinical trials, biomarkers and COAs acquire added complexity and a commensurate requirement for scientific rigor. An endpoint is a well-defined variable that is meant to represent a desired result that is statistically evaluated in order to answer a specific research question.   Biomarkers can be obtained from molecular, histologic, radiographic, or physiological features and includes therapeutic actions. It is not the same as objective measurements of an individual's survival, feelings, or functioning—a type of measurement called a clinical outcome assessment (COA). A contextual linkage between a biomarker and its intended usage is provided by summarizing the biological, physiological, or pathological mechanism for the biomarker's association with the disease or condition of interest. This is referred as biological plausibility. This data aids in defining the ways in which different biomarkers may interact for a shared purpose (e.g., common biochemical pathways leading to a common biologic or clinical phenotype). Name, unique identification, acronym, source, kind, biological plausibility, and a specified testing method are used to identify a biomarker. For instance, it has been noted that the presence of drug-induced acute tubular kidney injury increases when a molecular biomarker called Kidney Injury Molecule 1, or KIM-1, is detected in urine (pg/mL) using ELISA testing. KIM-1 biomarker falls under predictive biomarkers since it forecasts the outcome of exposure to a medicinal medication. [2]

Similarly, based on their potential uses, biomarkers can be classified into several kinds. A diagnostic biomarker finds or validates the existence of a condition or disease of interest, or it pinpoints a person who has a certain disease subtype. Tumor markers that are examined by immunophenotyping and immunohistochemistry to aid in the diagnosis of cancer and the differentiation of various cancer types are the most commonly used diagnostic markers. For instance, blood and/or tumor analysis is used to identify BRCA1 and BRCA2 gene mutations for cancer types, such as breast, ovarian, pancreatic, and prostate cancers. This analysis aids in choosing the best course of treatment.[3]

A biomarker is a monitoring biomarker if it can be evaluated repeatedly to determine the state of a disease or medical condition, look for signs of exposure to a biological agent or medical product in the environment, or analyze the impact of a biological agent or medical product.HIV-RNA, for instance, can be utilized as a monitoring biomarker to assess and direct antiretroviral therapy (ART) or In drug addiction prevention and treatment trials, blood concentrations of addictive drugs can be employed as monitoring biomarkers to assess compliance and sobriety. Prostate-specific antigen (PSA) or cancer antigen 125 (CA 125) can be utilized as monitoring biomarkers to determine the disease burden or status in patients with prostate or ovarian cancer, respectively. [4]

Pharmacodynamic/surrogate end-point biomarkers are those whose levels alter in response to exposure to pharmaceuticals or environmental agents. These biomarkers are incredibly helpful for early treatment development as well as clinical practice. For instance, Fluoroestradiol F 18 levels visualized by positron emission tomography (PET) may be used as a pharmacodynamic biomarker to detect the response of estrogen receptor (ER)-positive lesions to endocrine therapy in patients with recurrent or metastatic breast cancer. Hemoglobin A1c (HbA1c) reduction is a validated surrogate endpoint for reduction of microvascular complications associated with diabetes mellitus and has been used as the basis for approval of drugs intended to treat diabetes mellitus.[5]

In individuals with a disease or medical condition of interest, a prognostic biomarker is used to determine the probability of a clinical event, disease recurrence, or disease progression. The BEST working groups came to the conclusion that prognostic biomarkers should be distinguished from susceptibility/risk biomarkers, which deal with associations with the change from a healthy state to disease, even though this distinction is not universally accepted. Both differ from predictive biomarkers as discussed, which pinpoint variables related to the outcome of an exposure or intervention. Prognostic biomarkers are found in clinical settings when a patient receives a diagnosis and there is a desire to determine the probability of a subsequent clinical occurrence. Future events can include things like dying, getting sicker, getting sicker again, or getting sicker again. Biomarkers for prognosis in oncology have historically included tumor size, the number of lymph nodes positive for tumor cells, and the occurrence of metastases. Molecular signatures or indicators assessed on tumors are increasingly being used in place of or in addition to these clinicopathologic features. Biomarkers that signal a higher risk of future heart attack include low HDL cholesterol, raised LDL cholesterol, elevated blood pressure, and signs of diabetes in heart attack patients. Mutations in the BRCA1/2 genes can be used as a susceptibility/risk biomarker to identify those who are more likely to develop breast cancer or Human papillomavirus (HPV) infection with specific subtypes can be used to identify people who are more likely to develop cervical cancer or to identify adult patients with an increased chance of incident coronary disease, the amount of C-reactive protein (CRP) can be used as susceptibility/risk biomarkers.[2]

Exposure to the environment and medical procedures may have unfavorable, hazardous, or obviously poisonous effects. The capacity to identify or forecast these negative medication or exposure effects is a feature shared by all safety biomarkers. When assessing patients receiving cytotoxic chemotherapy, neutrophil count can be utilized as a safety biomarker to modify dosage, decide whether to stop treatment, or even explore the use of growth factors. The HLA-B*1502 allele has a risk of significant and deadly skin responses, hence it may be utilized as a safety biomarker to screen individuals before starting carbamazepine medication. Carbamazepine shouldn't be administered to patients who test positive for the HLA-B*1502 allele unless the advantages of the medication clearly exceed the risks. [1]

The topic of digital biomarkers is one that is expanding quickly.These days, sensors and portable electronics allow for the quick and continuous assimilation of personal data that sheds light on a variety of intricate metrics, including eating habits, tremor, exercise level, psychological state, and cognitive capacities. Standards for assessing these biomarkers are still developing since a major portion of this data come from innovative sources, such as wearable electronics and smartphones, and because new technologies enable the streaming and storing of complicated data. [1]

The systems in biology are multifaceted and intricate. With the development of more complex biological models, it is evident that assessing one biomarker without considering others can result in incorrect findings. Additionally, because several biomarkers each contribute slightly to the summative outcome of interest, measuring composite or complex biomarkers may allow for more accurate predictions. For instance, an effective inhibitor of poly ADP-ribose polymerase (PARP) is olaparib, brand name LynparzaTM. DNA single-strand breaks (SSBs) require PARP enzymes to be repaired; if PARP is blocked, these SSBs develop into DNA double-strand breaks (DSBs). These DSBs cause genomic instability and cell death if they are not repaired by a suitable mechanism, such as homologous recombination repair (HRR). Thus, tumors with defects in HRR, including those containing BRCA1/2 (BRCA1 or BRCA2) mutations, are susceptible to the effects of PARP inhibition. The delivery of complex biomarkers was made possible by the simultaneous approval of Myriad's BRACAnalysis CDx and AstraZeneca's olaparib in 2014 as the first regulatory approval of a laboratory developed test (LDT) and the first approval of a mutation test for complex tumor suppressor genes as CDx under a pre-market approval (PMA).[6]

A new class of biological indicators called "next-generation biomarkers" have the potential to completely transform the medical field. They provide a better insight of health and disease than traditional biomarkers since they are more complex and advanced. Multi-omics provide a more complete view of biological processes by measuring a variety of biological substances, including lipids, proteins, metabolites, and genes. High-throughput enable large-scale research and customized medicine techniques by rapidly and effectively analyzing vast amounts of data. By obtaining non invasive from readily available sources like blood, saliva, or urine, patients' pain and risk are reduced. These have dynamic ability to record alterations in biological processes throughout time, which enables the early identification and tracking of the course of disease. Next-generation biomarkers include, cancer cells known as circulating tumor cells (CTCs) have left their tumors and entered the bloodstream. They can be applied to prognosis prediction, therapy response monitoring, and early cancer identification. Exosomes are microscopic vesicles secreted by cells that are packed with different biomolecules, such as DNA, RNA, and proteins. Numerous illnesses, including as cancer, neurological diseases, and autoimmune diseases, can be diagnosed and tracked with them. The group of bacteria that reside in our stomach and other bodily regions is known as our microbiome. The microbiome's makeup has been connected to a number of diseases, and researchers are looking at it as a possible source for biomarkers in the future. [7]

In conclusion, precision medicine over traditional medicine could be advanced by the development of next-generation biomarkers of immunotherapy, such as DNA repair genes, microbiome, and integration of machine learning-based methodologies, by leveraging clinical, omics, and imaging data to improve diagnostic, staging, predictive, and prognostic approaches.

References: 

1. Califf RM. Biomarker definitions and their applications. Exp Biol Med (Maywood). 2018 Feb;243(3):213-221. doi: 10.1177/1535370217750088. PMID: 29405771; PMCID: PMC5813875.

2. FDA-NIH Biomarker Working Group. BEST (Biomarkers, EndpointS, and other Tools) Resource [Internet]. Silver Spring (MD): Food and Drug Administration (US); 2016-. Contents of a Biomarker Description. 2020 Dec 28. Available from: https://www.ncbi.nlm.nih.gov/books/NBK566059/ Co published by National Institutes of Health (US), Bethesda (MD).

3. Tumor Marker Tests in Common Use, National cancer institute. Reviewed: December 7, 2023; Accessed: February 9, 2024 URL : https://www.cancer.gov/about-cancer/diagnosisstaging/diagnosis/tumor-markers-list

4. FDA-NIH Biomarker Working Group. BEST (Biomarkers, EndpointS, and other Tools) Resource [Internet]. Silver Spring (MD): Food and Drug Administration (US); 2016-. Monitoring Biomarker. 2016 Dec 22 [Updated 2021 Jan 25]. Available from: https://www.ncbi.nlm.nih.gov/books/NBK402282/ Co published by National Institutes of Health (US), Bethesda (MD).

5. FDA-NIH Biomarker Working Group. BEST (Biomarkers, EndpointS, and other Tools) Resource [Internet]. Silver Spring (MD): Food and Drug Administration (US); 2016-. Response Biomarker. 2016 Dec 22 [Updated 2021 Sep 17]. Available from: https://www.ncbi.nlm.nih.gov/books/NBK402286/ Co published by National Institutes of Health (US), Bethesda (MD).

6. Maria C. M. Orr, Simon P. Dearden Delivering Companion Diagnostics for Complex Biomarkers The BRCA Companion Diagnostic Story for LYNPARZA− (Olaparib). Handbook of Biomarkers and Precision Medicine, 1st Edition First Published 2019 Pages 14 ISBN 9780429202872.

7. Hassan Abushukair, Obada Ababneh, Ayah Al-Bzour, Ibrahim Halil Sahin & Anwaar Saeed (2023) Next generation immuno-oncology biomarkers in gastrointestinal cancer: what does the future hold?, Expert Review of Molecular Diagnostics, 23:10, 863-873, DOI: 10.1080/14737159.2023.2252739

About the Author:

Shruti Talshi

Ms. Shruti  Talashi  boasts a dual mastery of lab research and writing. Her doctoral study outcome as M.Phil in biomedical science while studying breast cancer and an extraordinary masters degrees dissertation work on exploring role of Gal-lectin in cancer metastasis fuels her extensive research interests. She has gained few publication in journals. Bridging the science-public gap is her passion, aided by expertise in diverse techniques. From oncology to antibiotic/drugs production, she's led and managed complex projects, even clinical trials. Now, as a freelance Content Coordinator for Sinoexpo Pharmasource.com, her industry knowledge shines through valuable insights on cutting-edge topics like GMP, QbD, and biofoundry.