Purpose The discovery of effective biomarkers is a fundamental goal of molecular medicine. Developing a systems-biology understanding of radiosensitivity can enhance our ability of identifying radiation-specific biomarkers. Methods and Materials Radiosensitivity, as represented by the Survival Fraction at 2 Gy (SF2) was modeled in 48 human cancer cell lines. We apply a linear regression algorithm that integrates gene expression with biological variables including: ras status (mut/wt), tissue of origin (TO) and p53 status (mut/wt). Results The biomarker discovery platform is a network representation of the top 500 genes identified by linear regression. This network was reduced to a 10-hub network that includes: c-Jun, HDAC1, RELA (p65 subunit of NFKB), PKC-beta, SUMO-1, c-Abl, STAT1, AR, CDK1 and IRF1. Nine targets associated with radiosensitization drugs link to the network, demonstrating clinical relevance. Furthermore, the model identifies four significant radiosensitivity clusters of terms and genes. Ras was a dominant variable in the analysis along with TO and their interaction with gene expression but not p53. Overrepresented biological pathways differed between clusters but included: DNA repair, cell cycle, apoptosis and metabolism. The c-Jun network hub was validated using a knockdown approach in 8 human cell lines representing lung, colon and breast cancers. Conclusions We developed a novel radiation-biomarker discovery platform using a systems biology modeling approach. We propose this platform will play a central role in the integration of biology into clinical radiation oncology practice.
Purpose/Objective Recently, we developed RSI, a clinically-validated molecular signature that estimates tumor radiosensitivity. Here, we test whether integrating RSI with molecular subtype refines the classification of local recurrence risk in breast cancer Methods and Materials RSI and molecular subtype were evaluated in 343 patients treated with breast-conserving therapy including whole-breast RT plus/minus tumor bed boost (dose range, 45 – 72 Gy). The follow up for patients without recurrence was 10 years. Clinical endpoint was local recurrence-free survival (LRFS). Results While RSI did not uniformly predict for local recurrence across the entire cohort, combining RSI and molecular subtype identifies a subpopulation with an increased risk of local recurrence: triple negative (TN) and radioresistant (TN-R) (Ref –TN-R, HR=0.37 (0.15, 0.92) p=0.02). TN patients that were RSI-Sensitive/Intermediate (RSI-S/Int) had similar LR rates as LUM patients (HR=0.86 (0.47, 1.57) p=0.63). On multivariate analysis (MVA) combined RSI-Molecular Subtype (p=0.004), along with age (p=0.001) were the most significant predictors of LR. In contrast, integrating RSI into the LUM subtype did not identify additional risk groups. We hypothesized that RT dose escalation was impacting radioresistance in the LUM subtype and serving as a confounder. Indeed, increased RT dose decreased LR only in the LUM-R subset (HR = 0.23 (0.05, 0.98), p=0.03). On MVA, RT dose was an independent variable only in the LUMA/B-RR subset (HR=0.025 (0.001, 0.946), p=0.046), along with age (p=0.008), T stage (p=0.004) and chemotherapy (p=0.008). Conclusions Combined molecular subtype-RSI identifies a novel molecular sub-population (Triple Negative and Radioresistant) with an increased risk of local recurrence after BCT. We propose RSI-molecular subtype may be useful in guiding RT-based decisions in breast cancer.
Purpose/Objectives We have previously developed a multigene expression model of tumor radiosensitivity (RSI) with clinical validation in multiple independent cohorts (breast, rectal, esophageal, and head and neck). The purpose of this study was to assess differences in RSI scores between primary colon cancer and metastases. Methods and Materials Patients were identified from our institutional IRB approved prospective observational protocol. A total of 704 metastatic and 1,362 primary lesions were obtained from a de-identified meta-data pool. RSI was calculated using the previously published ranked based algorithm. An independent cohort of 29 lung or liver colon metastases treated with 60 Gy in 5 fractions stereotactic body radiotherapy (SBRT) was used for validation. Results The most common sites of metastases included liver (n=374; 53%), lung (n=116; 17%), and lymph nodes (n=40; 6%). Sixty percent of metastatic tumors compared with 54% of primaries were in the RSI-radioresistant (RSI-RR) peak, suggesting that, metastatic tumors may be slightly more radioresistant than primaries (p=0.01). In contrast, when we analyzed metastases based on anatomical site, we uncovered large differences in RSI. The median RSIs for metastases in descending order of radioresistance were ovary (0.48), abdomen (0.47), liver (0.43), brain (0.42), lung (0.32), and lymph nodes (0.31), p<0.0001. These findings were confirmed when the analysis was restricted to lesions from the same patient (n=139). In our independent cohort of treated lung and liver metastases, lung metastases had an improved local control (LC) rate over patients with liver metastases (2 yr LC 100% vs. 73.0%, p=0.026). Conclusions Assessment of radiosensitivity between primary and metastatic tissues of colon cancer histology, reveals significant differences based on anatomical location of metastases. These initial results warrant validation in a larger clinical cohort.
Local radiotherapy plus intratumoral syngeneic dendritic cell injection can mediate apoptosis/cell death and immunological tumor eradication in murine models. A novel method of coordinated intraprostatic, autologous dendritic cell injection together with radiation therapy was prospectively evaluated in five HLA-A2+ subjects with high-risk, localized prostate cancer, using androgen suppression, 45 Gy external beam radiation therapy in 25 fractions over 5 weeks, dendritic cell injections after fractions 5, 15 and 25 and then interstitial radioactive seed placement. Serial prostate biopsies before and during treatment showed increased apoptotic cells and parenchymal distribution of CD8+ cells. CD8+ T-cell responses to test peptides were assessed using an enzyme-linked immunosorbent spot IFN-γ production assay, demonstrating some prostate cancer-specific protein-derived peptides associated with increased titer. In conclusion, the technique was feasible and well-tolerated and specific immune responses were observable. Future trials could further test the utility of this approach and improve on temporal coordination of intratumoral dendritic cell introduction with particular timelines of therapy-induced apoptosis.
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