Search

Modern cancer research depends heavily on the identification and validation of biomarkers because they provide important information about the diagnosis, prognosis, and response to treatment of the cancer. This review will provide a comprehensive overview of cancer biomarkers, including their development phases and recent breakthroughs in transcriptomics and computational techniques for detecting these biomarkers. Blood-based biomarkers have great potential for non-invasive tumor dynamics and treatment response monitoring. These include circulating tumor DNA, exosomes, and microRNAs. Comprehensive molecular profiles are provided by multi-omic technologies, which combine proteomics, metabolomics, and genomes to support the identification of biomarkers and the targeting of therapeutic interventions. Genetic changes are detected by next-generation sequencing, and patterns of protein expression are found by protein arrays and mass spectrometry. Tumor heterogeneity and clonal evolution can be understood using metabolic profiling and single-cell studies. It is projected that the use of several biomarkers-genetic, protein, mRNA, microRNA, and DNA profiles, among others-will rise, enabling multi-biomarker analysis and improving individualised treatment plans. Biomarker identification and patient outcome prediction are further improved by developments in AI algorithms and imaging techniques. Robust biomarker validation and reproducibility require cooperation between industry, academia, and doctors. Biomarkers can provide individualized care, meet unmet clinical needs, and enhance patient outcomes despite some obstacles. Precision medicine will continue to take shape as scientific research advances and the integration of biomarkers with cutting-edge technologies continues to offer a more promising future for personalized cancer care., Competing Interests: Declaration of Competing Interest The authors declare that they have no conflict of interest., (Copyright © 2024 Elsevier GmbH. All rights reserved.)

Endometriosis is an estrogen-dependent chronic inflammatory disorder involving the placement and growth of endometrial tissue outside the uterine cavity. It is the most common multifactorial disease that affects the life quality of women in reproductive age. Due to its multicomponent nature, early diagnosis of the disease is challenging. Since many genetic, epigenetic alterations and non-genetic factors contribute to the pathology of endometriosis, devising a drug therapy that directly acts on the ectopic tissue is extremely difficult. Endometriosis is a hormone-driven disease with estrogen considered as a primary driver for the development of endometriotic lesions. This study aims to identify biosignatures involved in endometriosis with and without gonadotropin releasing hormone agonists (GnRHa). GnRHa is a short peptide analog of GnRH that causes inhibition of estrogen and androgen synthesis. Microarray based-gene expression profiling was performed on total RNA extracted from endometriotic tissue samples with and without GnRHa-treated patients already published in our previous paper. The untreated group were considered as the control. Genes were then selected for validation by quantitative real-time polymerase chain reaction (qRT-PCR). qRT-PCR analysis confirmed significant downregulation in(p < 0.05) expression of DARC (p = 0.0042), CDH1 (p = 0.0027), CDH5 (p = 0.0283), ATP2A3 (p < 0.001), RGS5 (p = 0.0032), and CD36 (p = 0.0162) in endometriosis patients treated with GnRHa analogs. Although, CTNNAL1 (p = 0.0136) also showed significant results but there was upregulation in their expression levels after GnRHa treatment. Thus, an altered expression of these genes makes them a possible candidate determinant of endometriosis treated with GnRHa., Competing Interests: Declaration of Competing Interest The authors declare no potential conflict of interest that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier GmbH. All rights reserved.)

Endometriotic cells exhibit a notable degree of invasiveness and some characteristics of tissue remodeling underlying lesion formation. In this regard, do matrix metalloproteinases 14 (MMP14) and other related genes such as SPARC-like protein 1 (SPARCL1), caveolin 2 (CAV2), and clusterin (CLU) exert any significant influence in the processes of endometriosis development and pathophysiology is not apparent. We aim to assess whether these genes could serve as potential diagnostic biomarkers in endometriosis. Microarray-based gene expression analysis was performed on total RNA extracted from endometriotic tissue samples treated with and without gonadotropin-releasing hormone agonist (GnRHa). The GnRHa untreated patients were considered the control group. The validation of genes was performed using quantitative real-time polymerase chain reaction (qRT-PCR). qRT-PCR analysis showed significant downregulation in the expression of MMP14 (p = 0.024), CAV2 (p = 0.017), and upregulation of CLU (p = 0.005) in endometriosis patients treated with GnRHa. SPARCL1 did not show any significant (p = 0.30) change in the expression compared to the control group. These data have the potential to contribute to the comprehension of the molecular pathways implicated in the remodeling of the extracellular matrix, which is a vital step for the physiology of the endometrium. Based on the result, it is concluded that changes in the expression of MMP14, CAV2, and CLU post-treatment imply their role in the pathophysiology of endometriosis and may serve as a potential diagnostic biomarker of endometriosis in response to GnRHa treatment in patients with ovarian endometrioma., Competing Interests: Declaration of Competing Interest The authors declare no potential conflict of interest that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier GmbH. All rights reserved.)

Breast cancer is one of the major reason for death of women worldwide. As per the International Agency for Research on Cancer (IARC) statistics, the number of cases of breast cancer is increasing year by year in many parts of the world. As per the recent global cancer burden figures, in 2020, there were 2.26 million incidences of breast cancer cases and it is one of the main causes of mortality due to cancer in women in the world. Biomarkers of breast cancer would prove to be very beneficial to screen women who are at higher risk and for detection of disease recurrence. Here, studies carried out on biomarkers of breast cancer and susceptibility to the disease have been reviewed. Various databases like Google Scholar, ScienceDirect and PubMed have been used for searching and majorly literature from the last 10 years have been considered. Potential biomarkers of breast cancer including blood based angiogenic factors, glycoprotein-based biomarkers, hormone receptor biomarkers and other biomarkers that were identified from various studies have been summarized., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier GmbH. All rights reserved.)