Specificity of Genetic Biomarker Studies in Cancer Research: A Systematic Review

Green, Garrett; Carmona, Ruben; Zakeri, Kaveh; Lee, Chih Han; Borgan, Saif M.; Marhoon, Zaid A; Sharabi, Andrew B.; Mell, Loren K.

doi:10.1371/journal.pone.0156489

Cited by 5 publications

(5 citation statements)

References 21 publications

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“…Indeed, a recent survey highlights that the majority of high-impact studies associating genetic biomarkers with cancer outcomes did not define or identify the primary endpoint of interest, or report effects on a cause-specific outcome. Among these studies, less than half reported effects on a cancer-specific endpoint [67]. This methodology leaves open the possibility that observed associations are unrelated to cancer.…”

Section: Discussionmentioning

confidence: 99%

“…To sum up, we may confidently conclude that mutations are associated with tumors, even if they might be irrelevant as a primary cause [65], and hence "are not likely to play a dominant part in cancer" [66]. As a consequence, many studies claiming a relationship between gene expression and clinical outcomes, "avoid to identify the primary endpoint of interest, or report effects on a cause-specific outcome" [67].…”

Section: Mutationsmentioning

confidence: 99%

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Paradoxical Behavior of Oncogenes Undermines the Somatic Mutation Theory

et al. 2022

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The currently accepted theory on the influence of DNA mutations on carcinogenesis (the Somatic Mutation Theory, SMT) is facing an increasing number of controversial results that undermine the explanatory power of mutated genes considered as “causative” factors. Intriguing results have demonstrated that several critical genes may act differently, as oncogenes or tumor suppressors, while phenotypic reversion of cancerous cells/tissues can be achieved by modifying the microenvironment, the mutations they are carrying notwithstanding. Furthermore, a high burden of mutations has been identified in many non-cancerous tissues without any apparent pathological consequence. All things considered, a relevant body of unexplained inconsistencies calls for an in depth rewiring of our theoretical models. Ignoring these paradoxes is no longer sustainable. By avoiding these conundrums, the scientific community will deprive itself of the opportunity to achieve real progress in this important biomedical field. To remedy this situation, we need to embrace new theoretical perspectives, taking the cell–microenvironment interplay as the privileged pathogenetic level of observation, and by assuming new explanatory models based on truly different premises. New theoretical frameworks dawned in the last two decades principally focus on the complex interaction between cells and their microenvironment, which is thought to be the critical level from which carcinogenesis arises. Indeed, both molecular and biophysical components of the stroma can dramatically drive cell fate commitment and cell outcome in opposite directions, even in the presence of the same stimulus. Therefore, such a novel approach can help in solving apparently inextricable paradoxes that are increasingly observed in cancer biology.

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Section: Discussionmentioning

confidence: 99%

Section: Mutationsmentioning

confidence: 99%

Paradoxical Behavior of Oncogenes Undermines the Somatic Mutation Theory

et al. 2022

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“…Some mechanisms, such as oncogenes, existed in all neoplasia types [59] . By 2010, more than 50,000 research articles on the performance of cancer biomarkers have been reported [60] . Biomarkers utilization is critical for early diagnosis, stratification of patient, staging, prognosis, as well as evaluation of drug efficacy and toxicity and disease risk.…”

Section: Using Biomarkers For Implementation Of Personalized Medicinementioning

confidence: 99%

Exploitation of Gene Expression and Cancer Biomarkers in Paving the Path to Era of Personalized Medicine

Kamel

Al-Amodi

2017

Genomics, Proteomics &Amp; Bioinformatics

100

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Cancer therapy agents have been used extensively as cytotoxic drugs against tissue or organ of a specific type of cancer. With the better understanding of molecular mechanisms underlying carcinogenesis and cellular events during cancer progression and metastasis, it is now possible to use targeted therapy for these molecular events. Targeted therapy is able to identify cancer patients with dissimilar genetic defects at cellular level for the same cancer type and consequently requires individualized approach for treatment. Cancer therapy begins to shift steadily from the traditional approach of “one regimen for all patients” to a more individualized approach, through which each patient will be treated specifically according to their specific genetic defects. Personalized medicine accordingly requires identification of indicators or markers that guide in the decision making of such therapy to the chosen patients for more effective therapy. Cancer biomarkers are frequently used in clinical practice for diagnosis and prognosis, as well as identification of responsive patients and prediction of treatment response of cancer patient. The rapid breakthrough and development of microarray and sequencing technologies is probably the main tool for paving the way toward “individualized biomarker-driven cancer therapy” or “personalized medicine”. In this review, we aim to provide an updated knowledge and overview of the current landscape of cancer biomarkers and their role in personalized medicine, emphasizing the impact of genomics on the implementation of new potential targeted therapies and development of novel cancer biomarkers in improving the outcome of cancer therapy.

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“…In clinical practice, cancer biomarkers, a substance or process indicative of cancer, can be used for cancer epidemiology, diagnosis, progression surveillance, and prognosis prediction (Hung et al, 2022;Chen et al, 2023). Previously discovered cancer biomarkers included genetic, epigenetic, glycomic, proteomic, and imaging (Varghese et al, 2008;Green et al, 2016;Stone, 2017;Black et al, 2019;Dimitrakopoulos et al, 2019;Kang, 2021;Essa et al, 2022;Han et al, 2022;Yao and Zhang, 2023). Cancer biomarkers have been applied in early cancer detection, tumor progression surveillance, and prognosis prediction clinically (Kazmierczak-Siedlecka et al, 2021;Cong et al, 2023;Jiang et al, 2023;LoRusso and Freidlin, 2023).…”

Section: Introductionmentioning

confidence: 99%

Development of a monoclonal antibody to ITPRIPL1 for immunohistochemical diagnosis of non-small cell lung cancers: accuracy and correlation with CD8+ T cell infiltration

Deng,

Shi,

Sun

et al. 2023

Front. Cell Dev. Biol.

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Introduction: Cancer biomarkers are substances or processes highly associated with the presence and progression of cancer, which are applicable for cancer screening, progression surveillance, and prognosis prediction in clinical practice. In our previous studies, we discovered that cancer cells upregulate inositol 1,4,5-triphosphate receptor-interacting protein-like 1 (ITPRIPL1), a natural CD3 ligand, to evade immune surveillance and promote tumor growth. We also developed a monoclonal ITPRIPL1 antibody with high sensitivity and specificity. Here, we explored the application of anti-ITPRIPL1 antibody for auxiliary diagnosis of non-small cell lung cancer (NSCLC).Methods: NSCLC patient tissue samples (n = 75) were collected and stained by anti-ITPRIPL1 or anti-CD8 antibodies. After excluding the flaked samples (n = 15), we evaluated the expression by intensity (0-3) and extent (0-100%) of staining to generate an h-score for each sample. The expression status was classified into negative (h-score < 20), low-positive (20-99), and high-positive (≥ 100). We compared the h-scores between the solid cancer tissue and stroma and analyzed the correlation between the h-scores of the ITPRIPL1 and CD8 expression in situ in adjacent tissue slices.Results: The data suggested ITPRIPL1 is widely overexpressed in NSCLC and positively correlates with tumor stages. We also found that ITPRIPL1 expression is negatively correlated with CD8 staining, which demonstrates that ITPRIPL1 overexpression is indicative of poorer immune infiltration and clinical prognosis. Therefore, we set 50 as the cutoff point of ITPRIPL1 expression H scores to differentiate normal and lung cancer tissues, which is of an excellent sensitivity and specificity score (100% within our sample collection).Discussion: These results highlight the potential of ITPRIPL1 as a proteomic immunohistochemical NSCLC biomarker with possible advantages over the existing NSCLC biomarkers, and the ITPRIPL1 antibody can be applied for accurate diagnosis and prognosis prediction.

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Specificity of Genetic Biomarker Studies in Cancer Research: A Systematic Review

Cited by 5 publications

References 21 publications

Paradoxical Behavior of Oncogenes Undermines the Somatic Mutation Theory

Paradoxical Behavior of Oncogenes Undermines the Somatic Mutation Theory

Exploitation of Gene Expression and Cancer Biomarkers in Paving the Path to Era of Personalized Medicine

Development of a monoclonal antibody to ITPRIPL1 for immunohistochemical diagnosis of non-small cell lung cancers: accuracy and correlation with CD8+ T cell infiltration

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