Our goal was to determine whether tumour radiosensitivity is associated with activation of the immune system across all tumour types as measured by two gene expression signatures (GESs).
We ...identified 10,240 genomically profiled distinct solid primary tumours with gene expression analysis available from an institutional de-identified database. Two separate GESs were included in the analysis, the radiosensitivity index (RSI) GES (a 10-gene GES as a measure of radiosensitivity) and the 12-chemokine (12-CK) signature (a 12-gene GES as a measure of immune activation). We tested whether the RSI and 12-CK were associated with each other across all tumour samples and, in an exploratory analysis, their prognostic significance in predicting distant metastasis-free survival (DMFS) among a well-characterised, independent cohort of 282 early-stage breast cancer cases treated with surgery and post-operative radiation alone without systemic therapy. The lower the RSI score, the higher the tumour radiosensitivity; whereas, the higher the 12-CK score the higher the immune activation.
Using an RSI cut-point of ≤0.3745, RSI-low tumours (n = 4,291, 41.9%) had a significantly higher median 12-CK GES value (0.54 −0.136, 1.095) compared with RSI-high tumours (−0.17 –0.82, 0.42; p < 0.001) across all tumour samples, indicating that radiosensitivity is associated with immune activation. In an exploratory analysis of early-stage breast cancer cases, a multivariable model with patient age, RSI and 12-CK provided a strong composite model for DMFS (p = 0.02), with RSI (hazard ratio HR 0.63 95% confidence interval 0.36, 1.09) and 12-CK (HR 0.66 0.41, 1.04) each providing comparable contributions.
Tumour radiosensitivity is associated with immune activation as measured by the two GESs.
•There are data that suggest an interplay between response to radiation therapy and immune activation.•If a gene expression signature (GES) could improve the identification of this interplay it would likely be deemed a success.•We compared two GES for tumour radiosensitivity index (RSI) and immune activation (12-CK).•RSI and 12-CK GES are associated across all tumour types.•The combined RSI and 12-CK GES phenotype has the potential to improve our prognostic ability.
Abstract Background and purpose Adjuvant radiation therapy for resectable pancreatic cancer remains controversial. Sub-populations of radiosensitive tumors might exist given the genetic heterogeneity ...of pancreatic cancers. We evaluated whether RSI is predictive of survival in pancreatic cancer treated with radiation. Materials and methods We identified 73 genomically-profiled pancreas cancer patients treated with upfront surgery between 2000 and 2011 (48 radiation, 25 no radiation). Briefly, RSI score is derived from the expression of 10 specific genes and a linear regression algorithm modeled on SF2 of 48 cancer cells. The primary endpoint was to assess the association of RSI with overall survival. Results Median follow-up was 67 months for surviving patients. On multivariate analysis, patients with radioresistant tumors had a trend toward worse survival (Hazard ratio HR 2.1 95% CI 1.0–4.3, p = 0.054). Among high-risk, irradiated patients (positive margins, positive lymph nodes, or a post-operative CA19-9 >90; n = 31), radiosensitive patients had significantly improved survival compared with radioresistant patients (median 31.2 vs. 13.2 months; HR 0.42 0.19, 0.94, p = 0.04). Among irradiated patients ( n = 48), low-risk patients lived longer than both high-risk patients with radiosensitive tumors and radioresistant tumors (HR 2.7 1.0, 7.2, p = 0.04 and HR 6.3 2.3, 17.0, p < 0.001, respectively). Conclusions Integrating RSI with standard high-risk variables has the potential to refine the classification of high-risk resected pancreatic cancer patients treated with radiation therapy.
To summarize important talking points from a 2016 symposium focusing on real-world challenges to advancing precision medicine in radiation oncology, and to help radiation oncologists navigate the ...practical challenges of precision, radiation oncology.
The American Society for Radiation Oncology, American Association of Physicists in Medicine, and National Cancer Institute cosponsored a meeting on precision medicine in radiation oncology. In June 2016 numerous scientists, clinicians, and physicists convened at the National Institutes of Health to discuss challenges and future directions toward personalized radiation therapy. Various breakout sessions were held to discuss particular components and approaches to the implementation of personalized radiation oncology. This article summarizes the genomically guided radiation therapy breakout session.
A summary of existing genomic data enabling personalized radiation therapy, ongoing clinical trials, current challenges, and future directions was collected. The group attempted to provide both a current overview of data that radiation oncologists could use to personalize therapy, along with data that are anticipated in the coming years. It seems apparent from the provided review that a considerable opportunity exists to truly bring genomically guided radiation therapy into clinical reality.
Genomically guided radiation therapy is a necessity that must be embraced in the coming years. Incorporating these data into treatment recommendations will provide radiation oncologists with a substantial opportunity to improve outcomes for numerous cancer patients. More research focused on this topic is needed to bring genomic signatures into routine standard of care.
Background
Following wide excision of Merkel cell carcinoma (MCC), postoperative radiation therapy (RT) is typically recommended. Controversy remains as to whether RT can be avoided in selected ...cases, such as those with negative margins. Additionally, there is evidence that RT can influence survival.
Methods
We included 171 patients treated for non-metastatic MCC from 1994 through 2012 at a single institution. Patients without pathologic nodal evaluation (clinical N0 disease) were excluded to reflect modern treatment practice. The endpoints included local control (LC), locoregional control (LRC), disease-free survival (DFS), overall survival (OS), and disease-specific survival (DSS).
Results
Median follow-up was 33 months. Treatment with RT was associated with improved 3-year LC (91.2 vs. 76.9 %, respectively;
p
= 0.01), LRC (79.5 vs. 59.1 %;
p
= 0.004), DFS (57.0 vs. 30.2 %;
p
< 0.001), and OS (73 vs. 66 %;
p
= 0.02), and was associated with improved 3-year DSS among node-positive patients (76.2 vs. 48.1 %;
p
= 0.035), but not node-negative patients (90.1 vs. 80.8 %;
p
= 0.79). On multivariate analysis, RT was associated with improved LC hazard ratio (HR) 0.18, 95 % confidence interval (CI) 0.07–0.46;
p
< 0.001, LRC (HR 0.28, 95 % CI 0.14–0.56;
p
< 0.001), DFS (HR 0.42, 95 % CI 0.26–0.70;
p
= 0.001), OS (HR 0.53, 95 % CI 0.31–0.93;
p
= 0.03), and DSS (HR 0.42, 95 % CI 0.26–0.70;
p
= 0.001). Patients with negative margins had significant improvements in 3-year LC (90.1 vs. 75.4 %;
p
< 0.001) with RT. Deaths not attributable to MCC were relatively evenly distributed between the RT and no RT groups (28.5 and 29.3 % of patients, respectively).
Conclusions
RT for MCC was associated with improved LRC and survival. RT appeared to be beneficial regardless of margin status.
The treatment of oligometastatic disease has become common as imaging techniques have advanced and the management of systemic disease has improved. Use of highly targeted, hypofractionated regimens ...of stereotactic body radiotherapy (SBRT) is now a primary management option for patients with oligometastatic disease.
The properties of SBRT are summarized and the results of retrospective and prospective studies of SBRT use in the management of oligometastases are reviewed. Future directions of SBRT, including optimizing dose and fractionation schedules, are also discussed.
SBRT can deliver highly conformal, dosed radiation treatments for ablative tumors in a few treatment sessions. Phase 1/2 trials and retrospective institutional results support use of SBRT as a treatment option for oligometastatic disease metastasized to the lung, liver, and spine, and SBRT offers adequate toxicity profiles with good rates of local control. Future directions will involve optimizing dose and fractionation schedules for select histologies to improve rates of local control while limiting toxicity to normal structures.
SBRT offers an excellent management option for patients with oligometastases. However, additional research is still needed to optimize dose and fractionation schedules.
Cancer sequencing efforts have revealed that cancer is the most complex and heterogeneous disease that affects humans. However, radiation therapy (RT), one of the most common cancer treatments, is ...prescribed on the basis of an empirical one-size-fits-all approach. We propose that the field of radiation oncology is operating under an outdated null hypothesis: that all patients are biologically similar and should uniformly respond to the same dose of radiation.
We have previously developed the genomic-adjusted radiation dose, a method that accounts for biological heterogeneity and can be used to predict optimal RT dose for an individual patient. In this article, we use genomic-adjusted radiation dose to characterize the biological imprecision of one-size-fits-all RT dosing schemes that result in both over- and under-dosing for most patients treated with RT. To elucidate this inefficiency, and therefore the opportunity for improvement using a personalized dosing scheme, we develop a patient-specific competing hazards style mathematical model combining the canonical equations for tumor control probability and normal tissue complication probability. This model simultaneously optimizes tumor control and toxicity by personalizing RT dose using patient-specific genomics.
Using data from two prospectively collected cohorts of patients with NSCLC, we validate the competing hazards model by revealing that it predicts the results of RTOG 0617. We report how the failure of RTOG 0617 can be explained by the biological imprecision of empirical uniform dose escalation which results in 80% of patients being overexposed to normal tissue toxicity without potential tumor control benefit.
Our data reveal a tapestry of radiosensitivity heterogeneity, provide a biological framework that explains the failure of empirical RT dose escalation, and quantify the opportunity to improve clinical outcomes in lung cancer by incorporating genomics into RT.
Letter Response Sedor, Geoffrey; Scott, Jacob G.; Kattan, Michael W. ...
Journal of thoracic oncology,
20/May , Letnik:
16, Številka:
5
Journal Article
The development of a successful radiation sensitivity predictive assay has been a major goal of radiation biology for several decades. We have developed a radiation classifier that predicts the ...inherent radiosensitivity of tumor cell lines as measured by survival fraction at 2 Gy (SF2), based on gene expression profiles obtained from the literature. Our classifier correctly predicts the SF2 value in 22 of 35 cell lines from the National Cancer Institute panel of 60, a result significantly different from chance (P = 0.0002). In our approach, we treat radiation sensitivity as a continuous variable, significance analysis of microarrays is used for gene selection, and a multivariate linear regression model is used for radiosensitivity prediction. The gene selection step identified three novel genes (RbAp48, RGS19, and R5PIA) of which expression values are correlated with radiation sensitivity. Gene expression was confirmed by quantitative real-time PCR. To biologically validate our classifier, we transfected RbAp48 into three cancer cell lines (HS-578T, MALME-3M, and MDA-MB-231). RbAp48 overexpression induced radiosensitization (1.5- to 2-fold) when compared with mock-transfected cell lines. Furthermore, we show that HS-578T-RbAp48 overexpressors have a higher proportion of cells in G2-M (27% versus 5%), the radiosensitive phase of the cell cycle. Finally, RbAp48 overexpression is correlated with dephosphorylation of Akt, suggesting that RbAp48 may be exerting its effect by antagonizing the Ras pathway. The implications of our findings are significant. We establish that radiation sensitivity can be predicted based on gene expression profiles and we introduce a genomic approach to the identification of novel molecular markers of radiation sensitivity.
Due to its rarity and lack of prospective studies, clinical evidence for the management of the inguinal lymphatic nodal basin with radiation therapy in penile cancer (PeCa) has been limited. In this ...report, we review the current literature and further investigated the landscape of radiation sensitivity in nodal metastases of PeCa utilizing our well-established genome-based radiosensitivity index (RSI) platform. We hypothesized that optimal therapeutic gain could be achieved in PeCa stratified by the combination of clinicopathological parameters, genomic heterogeneity, and RSI-based radiation dose prescription (RxRSI). Similar to primary PeCa lesions, we found that the majority of PeCa nodal metastases are genomically radioresistant with significant heterogeneity. RxRSI should be considered to inform and optimize the radiation therapy dose prescription to the individual tumor biology.
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