Absence of correlation between radiation-induced CD8 T-lymphocyte apoptosis and sequelae in patients with prostate cancer accidentally overexposed to radiation

Assessment of the predictive power the radiation-induced lymphocyte apoptosis method in prostate cancer patients

Due to the better survival of patients with tumorous diseases, it is increasingly important to predict the side effects of radiotherapy, for which the Radiation-Induced Lymphocyte Apoptosis (RILA) method is proving to be effective in multicentric studies. Prostate cancer is the leading cause of cancer-related deaths among men worldwide, which is usually treated with radiotherapy. We recruited 49 patients with localized prostate cancer and performed RILA measurements before radiotherapy. Patients were treated with CyberKnife (35-40 Gy) or high-dose-rate brachytherapy (1 × 21 Gy). We performed chromosome aberration test for five years and graded side effects, IPSS and QoL questionnaire scores were recorded. We found that RILA% correlated with the IPSS increase (p = 0.0016, r=-0.44), which was confirmed with negative binomial regression (p = 0.0013). The negative predictive value for severe urinary side effects according to the IPSS questionnaire was 87.9% at the lower tertile of RILA values. Chromosome aberrations also correlated with side effects, but when we built models including variables of baseline and treatment characteristics of the patients, RILA, and chromosome aberrations, only RILA predicted a late increase in IPSS score (p < 0.0001, adjusted R2 = 68%). The RILA method was shown to be predictive of urinary side effects especially of patient-reported outcomes.

Normal Tissue Toxicity Prediction: Clinical Translation on the Horizon

Improvements in radiotherapy delivery have enabled higher therapeutic doses and improved efficacy, contributing to the growing number of long-term cancer survivors. These survivors are at risk of developing late toxicity from radiotherapy, and the inability to predict who is most susceptible results in substantial impact on quality of life and limits further curative dose escalation. A predictive assay or algorithm for normal tissue radiosensitivity would allow more personalized treatment planning, reducing the burden of late toxicity, and improving the therapeutic index. Progress over the last 10 years has shown that the etiology of late clinical radiotoxicity is multifactorial and informs development of predictive models that combine information on treatment (eg, dose, adjuvant treatment), demographic and health behaviors (eg, smoking, age), co-morbidities (eg, diabetes, collagen vascular disease), and biology (eg, genetics, ex vivo functional assays). AI has emerged as a useful tool and is facilitating extraction of signal from large datasets and development of high-level multivariable models. Some models are progressing to evaluation in clinical trials, and we anticipate adoption of these into the clinical workflow in the coming years. Information on predicted risk of toxicity could prompt modification of radiotherapy delivery (eg, use of protons, altered dose and/or fractionation, reduced volume) or, in rare instances of very high predicted risk, avoidance of radiotherapy. Risk information can also be used to assist treatment decision-making for cancers where efficacy of radiotherapy is equivalent to other treatments (eg, low-risk prostate cancer) and can be used to guide follow-up screening in instances where radiotherapy is still the best choice to maximize tumor control probability. Here, we review promising predictive assays for clinical radiotoxicity and highlight studies that are progressing to develop an evidence base for clinical utility.

Circulating microvesicles correlate with radiation proctitis complication after radiotherapy

In a large retrospective study, we assessed the putative use of circulating microvesicles (MVs), as innovative biomarkers of radiation toxicity in a cohort of 208 patients with prostate adenocarcinoma overexposed to radiation. The level of platelet (P)-, monocyte (M)- and endothelial (E)-derived MVs were assessed by flow cytometry. Rectal bleeding toxicity scores were collected at the time of blood sampling and during the routine follow-up and were tested for association with MVs using a multivariate logistic regression. MVs dosimetric correlation was investigated using dose volume histograms information available for a subset of 36 patients. The number of PMVs was significantly increased in patients with highest toxicity grades compared to lower grades. Risk prediction analysis revealed that increased numbers of PMVs, and an increased amount of MMVs relative to EMVs, were associated with worst rectal bleeding grade compared to the time of blood sampling. Moreover, a significant correlation was found between PMV and MMV numbers, with the range of doses up to the median exposure (40 Gy) of bladder/rectum and anterior rectal wall, respectively. MVs could be considered as new biomarkers to improve the identification of patients with high toxicity grade and may be instrumental for the prognosis of radiation therapy complications.

Association of polymorphisms in TGFB1, XRCC1, XRCC3 genes and CD8 T-lymphocyte apoptosis with adverse effect of radiotherapy for prostate cancer

The genetic background of each person might affect the severity of radiotherapy (RT)-induced normal tissue toxicity. The aim of study was to evaluate the influence of TGFB1 C-509T and Leu10Pro, XRCC1 Arg280His and XRCC3 Thr241Met polymorphisms as well as the level of radiation-induced CD8 T-lymphocyte apoptosis (RILA) on adverse effects of RT for prostate cancer (PCa). The study included 88 patients with localized or locally advanced PCa who were treated with RT. The polymorphisms were determined by PCR-RFLP analysis on DNA from peripheral blood mononuclear cells. RILA values were measured by flow cytometry. We found that CT genotype of TGFB1 C-509T could be protective biomarker for acute genitourinary (GU) and gastrointestinal (GI) radiotoxicity, while Thr variant of XRCC3 Thr241Met could predict the risk for acute GU radiotoxicity. Correlation between RILA values and toxicity was not detected. Univariate logistic regression analysis showed that Gleason score and risk group were risk factors for late GU, while for late GI radiotoxicity it was diabetes mellitus type 2. However, in multivariate model those were not proven to be significant and independent risk factors. Identification of assays combination predicting individual radiosensitivity is a crucial step towards personalized RT approach.

Improving Patients' Life Quality after Radiotherapy Treatment by Predicting Late Toxicities

Personalized treatment and precision medicine have become the new standard of care in oncology and radiotherapy. Because treatment outcomes have considerably improved over the last few years, permanent side-effects are becoming an increasingly significant issue for cancer survivors. Five to ten percent of patients will develop severe late toxicity after radiotherapy. Identifying these patients before treatment start would allow for treatment adaptation to minimize definitive side effects that could impair their long-term quality of life. Over the last decades, several tests and biomarkers have been developed to identify these patients. However, out of these, only the Radiation-Induced Lymphocyte Apoptosis (RILA) assay has been prospectively validated in multi-center cohorts. This test, based on a simple blood draught, has been shown to be correlated with late radiation-induced toxicity in breast, prostate, cervical and head and neck cancer. It could therefore greatly improve decision making in precision radiation oncology. This literature review summarizes the development and bases of this assay, as well as its clinical results and compares its results to the other available assays.

RILA blood biomarker as a predictor of radiation-induced sarcoma in a matched cohort study

Purpose

Radiation-induced sarcoma (RIS) is a rare but serious event. Its occurrence has been discussed during the implementation of new radiation techniques and justified appropriate radioprotection requirements. New approaches targeting intrinsic radio-sensitivity have been described, such as radiation-induced CD8 T-lymphocyte apoptosis (RILA) able to predict late radio-induced toxicities. We studied the role of RILA as a predisposing factor for RIS as a late adverse event following radiation therapy (RT).

Patients and methods

In this prospective biological study, a total of 120 patients diagnosed with RIS were matched with 240 control patients with cancer other than sarcoma, for age, sex, primary tumor location and delay after radiation. RILA was prospectively assessed from blood samples using flow cytometry.

Results

Three hundred and forty-seven patients were analyzed (118 RIS patients and 229 matched control patients). A majority (74%) were initially treated by RT for breast cancer. The mean RT dose was comparable with a similar mean (± standard deviation) for RIS (53.7 ± 16.0 Gy) and control patients (57.1 ± 15.1 Gy) (p = .053). Median RILA values were significantly lower in RIS than in control patients with respectively 18.5% [5.5–55.7] and 22.3% [3.8–52.2] (p = .0008). Thus, patients with a RILA >21.3% are less likely to develop RIS (p < .0001, OR: 0.358, 95%CI [0.221–0.599].

Conclusion

RILA is a promising indicator to predict an individual risk of developing RIS. Our results should be followed up and compared with molecular and genomic testing in order to better identify patients at risk. A dedicated strategy could be developed to define and inform high-risk patients who require a specific approach for primary tumor treatment and long term follow-up.