Needs and Challenges for Radiation Oncology in the Era of Precision Medicine

Quon, Harry; McNutt, Todd; Lee, Junghoon; Bowers, Michael R.; Jiang, Wei; Lakshminarayanan, P.; Cheng, Zhi; Han, Peijin; Hui, Xuan; Shah, Veeraj; Moore, Joseph A.; Nakatsugawa, Munehide; Robertson, Scott P.; Cecil, E.; Page, B.R.; Kiess, Ana P.; Wong, John W.; DeWeese, Theodore L.

doi:10.1016/j.ijrobp.2018.11.017

Cited by 12 publications

(6 citation statements)

References 37 publications

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“…The present overview has illustrated the potentialities of molecular sub-types and genomic profiling but also uncertain results and lack of definitive conclusions. To overcome today’s lack of over-arching strategy, research groups are advised to collaborate on a shared approach, bearing in mind that achieving personalized radiation oncology in breast cancer will require specific infra-structure, networking and investment ( 104 ). Besides focusing on clinical biomarkers, molecular signatures, tumor phenotypes, and genomics, research will also need to incorporate RT technical aspects, imaging, radiomics as well as patient-related factors like genetics and genetic predisposition, comorbidities, lifestyle, and environmental features.…”

Section: Discussionmentioning

confidence: 99%

Personalization in Modern Radiation Oncology: Methods, Results and Pitfalls. Personalized Interventions and Breast Cancer

Aristei

Perrucci²,

Alì

et al. 2021

Front. Oncol.

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Breast cancer, the most frequent malignancy in women worldwide, is a heterogeneous group of diseases, characterized by distinct molecular aberrations. In precision medicine, radiation oncology for breast cancer aims at tailoring treatment according to tumor biology and each patient’s clinical features and genetics. Although systemic therapies are personalized according to molecular sub-type [i.e. endocrine therapy for receptor-positive disease and anti-human epidermal growth factor receptor 2 (HER2) therapy for HER2-positive disease] and multi-gene assays, personalized radiation therapy has yet to be adopted in the clinical setting. Currently, attempts are being made to identify prognostic and/or predictive factors, biomarkers, signatures that could lead to personalized treatment in order to select appropriate patients who might, or might not, benefit from radiation therapy or whose radiation therapy might be escalated or de-escalated in dosages and volumes. This overview focuses on what has been achieved to date in personalized post-operative radiation therapy and individual patient radiosensitivity assessments by means of tumor sub-types and genetics.

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Section: Discussionmentioning

confidence: 99%

Personalization in Modern Radiation Oncology: Methods, Results and Pitfalls. Personalized Interventions and Breast Cancer

Aristei

Perrucci²,

Alì

et al. 2021

Front. Oncol.

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“…Progress in the field of molecular diagnostics has led to a highlight of peculiar biological "fingerprints" from which the efficacy of a specific therapeutic plan depends. Especially for cancer therapy, both for chemotherapy and RT, clinicians should consider that the success of the treatment cannot be independent from the personal genetic assets of the patient to be treated [34]. It follows that a therapeutic approach generally based on the standard guidelines for a given neoplasm must necessarily imply a personalized path, also taking into account the biological features of patients.…”

Section: Discussionmentioning

confidence: 99%

Local Disease-Free Survival Rate (LSR) Application to Personalize Radiation Therapy Treatments in Breast Cancer Models

Savoca

Calvaruso

Minafra

et al. 2020

JPM

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Cancer heterogeneity represents the main issue for defining an effective treatment in clinical practice, and the scientific community is progressively moving towards the development of more personalized therapeutic regimens. Radiotherapy (RT) remains a fundamental therapeutic treatment used for many neoplastic diseases, including breast cancer (BC), where high variability at the clinical and molecular level is known. The aim of this work is to apply the generalized linear quadratic (LQ) model to customize the radiant treatment plan for BC, by extracting some characteristic parameters of intrinsic radiosensitivity that are not generic, but may be exclusive for each cell type. We tested the validity of the generalized LQ model and analyzed the local disease-free survival rate (LSR) for breast RT treatment by using four BC cell cultures (both primary and immortalized), irradiated with clinical X-ray beams. BC cells were chosen on the basis of their receptor profiles, in order to simulate a differential response to RT between triple negative breast and luminal adenocarcinomas. The MCF10A breast epithelial cell line was utilized as a healthy control. We show that an RT plan setup based only on α and β values could be limiting and misleading. Indeed, two other parameters, the doubling time and the clonogens number, are important to finely predict the tumor response to treatment. Our findings could be tested at a preclinical level to confirm their application as a variant of the classical LQ model, to create a more personalized approach for RT planning.

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“…A Kaplan-Meier Plotter was used to test for survival prediction capacity. A combination of letters (A-G) and numbers (1)(2)(3)(4)(5) were used to number all the results. Correspondingly, the patients with an immune score greater than zero were defined as positive (+), and those with a score below zero were defined as negative (-).…”

Section: Immune Cell Subpopulations and Rt Outcomesmentioning

confidence: 99%

“…However, due to differences in tumor radiosensitivity, not all patients derive survival benefit from RT, while suffering serious adverse consequences [3,4]. Thus, radiosensitivity prediction has always been a topic of primary importance in the field of biologically guided personalized treatment strategies in radiation oncology [5,6].…”

Section: Introductionmentioning

confidence: 99%

Pan-Cancer Analysis of Radiotherapy Benefits and Immune Infiltration in Multiple Human Cancers

Wen

Gao

Chen

et al. 2020

Cancers

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Response to radiotherapy (RT) in cancers varies widely among patients. Therefore, it is very important to predict who will benefit from RT before clinical treatment. Consideration of the immune tumor microenvironment (TME) could provide novel insight into tumor treatment options. In this study, we investigated the link between immune infiltration status and clinical RT outcome in order to identify certain leukocyte subsets that could potentially influence the clinical RT benefit across cancers. By integrally analyzing the TCGA data across seven cancers, we identified complex associations between immune infiltration and patients RT outcomes. Besides, immune cells showed large differences in their populations in various cancers, and the most abundant cells were resting memory CD4 T cells. Additionally, the proportion of activated CD4 memory T cells and activated mast cells, albeit at low number, were closely related to RT overall survival in multiple cancers. Furthermore, a prognostic model for RT outcomes was established with good performance based on the immune infiltration status. Summarized, immune infiltration was found to be of significant clinical relevance to RT outcomes. These findings may help to shed light on the impact of tumor-associated immune cell infiltration on cancer RT outcomes, and identify biomarkers and therapeutic targets.

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Needs and Challenges for Radiation Oncology in the Era of Precision Medicine

Cited by 12 publications

References 37 publications

Personalization in Modern Radiation Oncology: Methods, Results and Pitfalls. Personalized Interventions and Breast Cancer

Personalization in Modern Radiation Oncology: Methods, Results and Pitfalls. Personalized Interventions and Breast Cancer

Local Disease-Free Survival Rate (LSR) Application to Personalize Radiation Therapy Treatments in Breast Cancer Models

Pan-Cancer Analysis of Radiotherapy Benefits and Immune Infiltration in Multiple Human Cancers

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