Predictive biomarkers aid selection of personalized therapy targeted to molecular alterations within an individual's tumor. Patients' responses to targeted therapies are commonly followed by ...treatment resistance. Here, we survey liquid biopsies as alternatives to tumor biopsies to assess predictive and therapy response biomarkers. We examine the potential of liquid biopsies to meet the challenges of minimal residual disease monitoring after curative intent treatment for earlier detection of disease recurrence. We focus on blood, the most commonly collected minimally invasive clinical sample, and on the two most widely studied assays, circulating tumor DNA and circulating tumor cells.
Predictive biomarkers aid selection of personalized therapy targeted to molecular alterations within an individual's tumor. Patients' responses to targeted therapies are commonly followed by treatment resistance. Here, we survey liquid biopsies as alternatives to tumor biopsies to assess predictive and therapy response biomarkers. We examine the potential of liquid biopsies to meet the challenges of minimal residual disease monitoring after curative intent treatment for earlier detection of disease recurrence. We focus on blood, the most commonly collected minimally invasive clinical sample, and on the two most widely studied assays, circulating tumor DNA and circulating tumor cells.
The role of heat shock proteins in cancer Lianos, Georgios D; Alexiou, George A; Mangano, Alberto ...
Cancer letters,
05/2015, Volume:
360, Issue:
2
Journal Article
Peer reviewed
Highlights • HSPs have been reported significantly elevated in a plethora of human cancers. • HSPs may have important therapeutic implications and they can be targeted by specific drugs. • The ...association of HSP27, HSP40, HSP60, HSP70, HSP90 with cancer is discussed here. • Among them, the most promising constitutes the HSP90 inhibitors, since they can inhibit several oncogenic proteins.
Breast cancer in young women: an overview Anastasiadi, Zoi; Lianos, Georgios D.; Ignatiadou, Eleftheria ...
Updates in surgery,
09/2017, Volume:
69, Issue:
3
Journal Article
Peer reviewed
Despite dramatic advances in cancer research setting, breast cancer remains a major health problem and represents currently a top biomedical research priority. Worldwide, breast cancer is the most ...common cancer affecting women, and its incidence and mortality rates are expected to increase significantly the next years. Recently the researchers’ interest has been attracted by breast cancer arising in young women. Current evidence suggests that in women aged <45 years, breast cancer is unquestionably the leading cause of cancer-related deaths. This type of cancer seems to be highly heterogeneous and has potentially aggressive and complex biological features. However, management strategies, recommendations and options are not age based and the ‘complex’ biology of this type of cancer remains uncertain and unexplored. In this review, we summarize the latest scientific information on breast cancer arising in young women highlighting the heterogeneity and the complex nature of this type of cancer.
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Quantum dots (QDs) have attracted attention for their application and commercialization in all industrial fields, including communications, displays, and solar cells, due to their ...excellent optical properties based on the quantum size effect. In recent years, the development of QDs that do not contain cadmium which is toxic to cells and living organisms, has progressed, and they have attracted considerable attention in the bio-imaging field for targeting molecules and cells. Furthermore, recently, the need for diagnostics and treatment at the single molecule and single cell level in the medical field has been increasing, and the application of QDs in the medical field is also accelerating. Therefore, this paper outlines the frontiers of diagnostic and therapeutic applications (theranostics) of QDs, especially in advanced medical fields such as regenerative medicine, oncology, and infectious diseases.
Acquired resistance to BH3 mimetic antagonists of BCL-2 and MCL-1 is an important clinical problem. Using acute myelogenous leukemia (AML) patient-derived xenograft (PDX) models of acquired ...resistance to BCL-2 (venetoclax) and MCL-1 (S63845) antagonists, we identify common principles of resistance and persistent vulnerabilities to overcome resistance. BH3 mimetic resistance is characterized by decreased mitochondrial apoptotic priming as measured by BH3 profiling, both in PDX models and human clinical samples, due to alterations in BCL-2 family proteins that vary among cases, but not to acquired mutations in leukemia genes. BCL-2 inhibition drives sequestered pro-apoptotic proteins to MCL-1 and vice versa, explaining why in vivo combinations of BCL-2 and MCL-1 antagonists are more effective when concurrent rather than sequential. Finally, drug-induced mitochondrial priming measured by dynamic BH3 profiling (DBP) identifies drugs that are persistently active in BH3 mimetic-resistant myeloblasts, including FLT-3 inhibitors and SMAC mimetics.
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•Reduced mitochondrial apoptotic priming drives acquired resistance to BH3 mimetics•BH3 profiling predicts clinical response to venetoclax and HMA combinations•Simultaneous BCL-2 and MCL-1 antagonism outperforms alternating regimens•Dynamic BH3 profiling identifies drug vulnerabilities in BH3 mimetic-resistant AML
Bhatt et al. demonstrate that resistance to BCL-2 and MCL-1 antagonists emerges via selection for reduced mitochondrial apoptotic priming. Rapid measurements of drug-induced apoptotic signaling measured by dynamic BH3 profiling identify targeted agents with in vivo efficacy. BCL-2 and MCL-1 antagonist combinations overcome resistance to either single agent.
Personalized cancer therapy applies specific treatments to each patient. Using personalized tumor models with similar characteristics to the original tumors may result in more accurate predictions of ...drug responses in patients. Tumor organoid models have several advantages over pre-existing models, including conserving the molecular and cellular composition of the original tumor. These advantages highlight the tremendous potential of tumor organoids in personalized cancer therapy, particularly preclinical drug screening and predicting patient responses to selected treatment regimens. Here, we highlight the advantages, challenges, and translational potential of tumor organoids in personalized cancer therapy and focus on gene–drug associations, drug response prediction, and treatment selection. Finally, we discuss how microfluidic technology can contribute to immunotherapy drug screening in tumor organoids.
Personalized cancer medicine is an approach to tailoring effective therapeutic strategies for each patient according to a tumor’s genomic characterization. There is an urgent demand for research in personalized tumor modeling to confirm the functional aspects of genomic drug response predictions in the preclinical setting.
While different tumor models, such as tumor cell lines and patient-derived tumor xenografts, have been proposed, the drawbacks of each model have limited their applications as personalized tumor models.
A tumor organoid, in which cellular and molecular heterogeneity of tumor cells is preserved, has emerged as a promising platform.
Recently, numerous studies highlighted the application of tumor organoids in personalized cancer medicine in terms of gene–drug association treatment, the identification of new therapies, and prediction of patient outcome.
A small fraction of cancer patients with advanced disease survive significantly longer than patients with clinically comparable tumors. Molecular mechanisms for exceptional responses to therapy have ...been identified by genomic analysis of tumor biopsies from individual patients. Here, we analyzed tumor biopsies from an unbiased cohort of 111 exceptional responder patients using multiple platforms to profile genetic and epigenetic aberrations as well as the tumor microenvironment. Integrative analysis uncovered plausible mechanisms for the therapeutic response in nearly a quarter of the patients. The mechanisms were assigned to four broad categories—DNA damage response, intracellular signaling, immune engagement, and genetic alterations characteristic of favorable prognosis—with many tumors falling into multiple categories. These analyses revealed synthetic lethal relationships that may be exploited therapeutically and rare genetic lesions that favor therapeutic success, while also providing a wealth of testable hypotheses regarding oncogenic mechanisms that may influence the response to cancer therapy.
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•Genomics of 110 patients with exceptional response to therapy profiled•Plausible molecular mechanisms related to therapy identified in ∼23% of cases•Proposed mechanisms involve DNA damage, signaling, and the immune response•Synthetic lethality with temozolomide in tumors with a defective DNA damage response
Profiling multi-platform genomics of 110 cancer patients with an exceptional therapeutic response, Wheeler et al. identify putative molecular mechanisms explaining this survival phenotype in ∼23% of cases. Therapeutic success is related to rare molecular features of responding tumors, exploiting synthetic lethality and oncogene addiction.
Many Black breast cancer patients experience chemotherapy-induced peripheral neuropathy (CIPN). Our study assessed Black breast cancer patients’ questions about a biomarker test that can predict ...likelihood of CIPN.
Nineteen Black women who were previous/current breast cancer patients participated in focus groups. Researchers briefly explained CIPN and the biomarker test, and then participants were asked what questions they would have about the test and its use in treatment decisions. These participant-voiced questions composed the data for this study and were analyzed using thematic analysis.
Participants’ questions centered on six themes: reasons for the test, effect on timeline of breast cancer treatment, testing procedure, limits of test (including accuracy), research done to develop this test (including research participants), and concerns about personal information connected to the test (including DNA).
This study provides an exploratory look at questions that Black breast cancer patients may have about toxicity biomarker testing use in breast cancer treatment decisions.
These findings provide a starting point for developing patient-centered approaches for integrating this precision medicine tool into clinical care. The methodological choice to generate participants’ questions (rather than answers to a question) led to robust, actionable data.
The ability to predict the future behavior of an individual cancer is crucial for precision cancer medicine. The discovery of extensive intratumor heterogeneity and ongoing clonal adaptation in human ...tumors substantiated the notion of cancer as an evolutionary process. Random events are inherent in evolution and tumor spatial structures hinder the efficacy of selection, which is the only deterministic evolutionary force. This review outlines how the interaction of these stochastic and deterministic processes, which have been extensively studied in evolutionary biology, limits cancer predictability and develops evolutionary strategies to improve predictions. Understanding and advancing the cancer predictability horizon is crucial to improve precision medicine outcomes.
Large-scale genomic cancer medicine initiatives are under way in several countries across the globe.
However, it remains a major challenge to use genomic information to make accurate predictions for individual cancer patients.
Multiple genomic studies substantiated the notion of cancer as an evolutionary process that can readily adapt within the lifetime of a patient.
Evolutionary adaptation results from the interplay of mutation generation and genetic drift, which are both stochastic processes, and clonal selection, which is deterministic in nature.
The influence of stochastic factors fundamentally limits the predictability of cancer evolution.
Understanding the limits of predictability and the development of more accurate prediction algorithms using evolutionary models is key to improving outcomes through genomic cancer medicine.
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