Modelling recurrence and second cancer risks induced by proton therapy

Advances in personalized radiotherapy

Radiotherapy is a mainstay of cancer treatment. The clinical response to radiotherapy is heterogeneous, from a complete response to early progression. Recent studies have explored the importance of patient characteristics in response to radiotherapy. In this editorial, we invite contributions for a BMC Cancer collection of articles titled 'Advances in personalized radiotherapy' towards the improvement of treatment response.

Gene expression signature predicts radiation sensitivity in cell lines using the integral of dose-response curve

BACKGROUND

Although substantial efforts have been made to build molecular biomarkers to predict radiation sensitivity, the ability to accurately stratify the patients is still limited. In this study, we aim to leverage large-scale radiogenomics datasets to build genomic predictors of radiation response using the integral of the radiation dose-response curve.

METHODS

Two radiogenomics datasets consisting of 511 and 60 cancer cell lines were utilized to develop genomic predictors of radiation sensitivity. The intrinsic radiation sensitivity, defined as the integral of the dose-response curve (AUC) was used as the radioresponse variable. The biological determinants driving AUC and SF2 were compared using pathway analysis. To build the predictive model, the largest and smallest datasets consisting of 511 and 60 cancer cell lines were used as the discovery and validation cohorts, respectively, with AUC as the response variable.

RESULTS

Utilizing a compendium of three pathway databases, we illustrated that integral of the radiobiological model provides a more comprehensive characterization of molecular processes underpinning radioresponse compared to SF2. Furthermore, more pathways were found to be unique to AUC than SF2-30, 288 and 38 in KEGG, REACTOME and WIKIPATHWAYS, respectively. Also, the leading-edge genes driving the biological pathways using AUC were unique and different compared to SF2. With regards to radiation sensitivity gene signature, we obtained a concordance index of 0.65 and 0.61 on the discovery and validation cohorts, respectively.

CONCLUSION

We developed an integrated framework that quantifies the impact of physical radiation dose and the biological effect of radiation therapy in interventional pre-clinical model systems. With the availability of more data in the future, the clinical potential of this signature can be assessed, which will eventually provide a framework to integrate genomics into biologically-driven precision radiation oncology.

Second Cancers in Classical Hodgkin Lymphoma and Diffuse Large B-Cell Lymphoma: A Systematic Review by the Fondazione Italiana Linfomi

BACKGROUND

The increase of lymphoma patient survival led to a modification of the incidence of long-term sequelae, including second malignancies (SM). Several groups have dealt with the incidence of SM, according to the primary treatment; however, a standardized approach for the early detection and screening of SM in the population of lymphoma survivors should be implemented.

METHODS

A systematic review was conducted by Fondazione Italiana Linfomi (FIL), in order to define the incidence of SM, the impact of modern radiotherapy on SM risk, and the usefulness of tailored follow-up and screening strategies for early diagnosis of SM. Classical Hodgkin lymphoma (cHL) and diffuse large B-cell lymphoma (DLBCL) survivors were investigated. The MEDLINE, Embase, and Cochrane Library databases were checked for relevant reports published up to January 2020. The selection process was reported according to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines.

RESULTS

A total of 27 full-text manuscripts resulted as eligible for the analysis. The incidence of SM in cHL patients treated with ABVD was higher compared to the general population and was even higher in patients treated with intensified regimens. The risk increased over time, as well as after 10-15 years from therapy, and was augmented by radiotherapy exposure. In DLBCL, more intensive regimens (i.e., R-CHOEP or R-MegaCHOEP) vs. R-CHOP were associated with a higher SM incidence. Salvage chemotherapy and autologous stem cell transplants increased the risk of SM in both cHL and DLBCL cohorts. A lower incidence of SM, particularly of breast cancer (BC), was shown in cohorts of cHL survivors treated with reduced radiation volumes and doses (involved fields vs. extended fields), but robust trials are still lacking. Considering the advantage of a structured screening for early detection of SM, all the included studies regarded cHL survivors and screening strategy for early BC detection. Moreover, the authors discuss additional papers, to guide the early diagnosis of lung, colorectal, skin, and thyroid cancer in patients at risk due to family history, drug or RT exposure, or unhealthy lifestyles. These screening strategies all passed through patient awareness.

CONCLUSION

A modern approach to chemotherapy and radiotherapy led to a lower risk of SM, which should be confirmed over time. Early detection of secondary cancers could be achieved through a tailored screening program, according to the individual risk profile.

Development and validation of genomic predictors of radiation sensitivity using preclinical data

Background

Radiation therapy is among the most effective and commonly used therapeutic modalities of cancer treatments in current clinical practice. The fundamental paradigm that has guided radiotherapeutic regimens are ‘one-size-fits-all’, which are not in line with the dogma of precision medicine. While there were efforts to build radioresponse signatures using OMICS data, their ability to accurately predict in patients is still limited.

Methods

We proposed to integrate two large-scale radiogenomics datasets consisting of 511 with 23 tissues and 60 cancer cell lines with 9 tissues to build and validate radiation response biomarkers. We used intrinsic radiation sensitivity, i.e., surviving fraction of cells (SF2) as the radiation response indicator. Gene set enrichment analysis was used to examine the biological determinants driving SF2. Using SF2 as a continuous variable, we used five different approaches, univariate, rank gene ensemble, rank gene multivariate, mRMR and elasticNet to build genomic predictors of radiation response through a cross-validation framework.

Results

Through the pathway analysis, we found 159 pathways to be statistically significant, out of which 54 and 105 were positively and negatively enriched with SF2. More importantly, we found cell cycle and repair pathways to be enriched with SF2, which are inline with the fundamental aspects of radiation biology. With regards to the radiation response gene signature, we found that all multivariate models outperformed the univariate model with a ranking based approach performing well compared to other models, indicating complex biological processes underpinning radiation response.

Conclusion

To summarize, we found biological processes underpinning SF2 and systematically compared different machine learning approaches to develop and validate predictors of radiation response. With more patient data available in the future, the clinical value of these biomarkers can be assessed that would allow for personalization of radiotherapy.

What can space radiation protection learn from radiation oncology?

Protection from cosmic radiation of crews of long-term space missions is now becoming an urgent requirement to allow a safe colonization of the moon and Mars. Epidemiology provides little help to quantify the risk, because the astronaut group is small and as yet mostly involved in low-Earth orbit mission, whilst the usual cohorts used for radiation protection on Earth (e.g. atomic bomb survivors) were exposed to a radiation quality substantially different from the energetic charged particle field found in space. However, there are over 260,000 patients treated with accelerated protons or heavier ions for different types of cancer, and this cohort may be useful for quantifying the effects of space-like radiation in humans. Space radiation protection and particle therapy research also share the same tools and devices, such as accelerators and detectors, as well as several research topics, from nuclear fragmentation cross sections to the radiobiology of densely ionizing radiation. The transfer of the information from the cancer radiotherapy field to space is manifestly complicated, yet the two field should strengthen their relationship and exchange methods and data.

Subsequent malignant neoplasms among children with Hodgkin lymphoma: a report from the Children's Oncology Group

Survivors of Hodgkin lymphoma (HL) have an increased risk of subsequent malignant neoplasms (SMNs). Response-adapted treatment may decrease this risk by reducing exposure to therapy associated with SMN risk. The Children's Oncology Group study AHOD0031 evaluated response-adapted therapy for children and adolescents with intermediate-risk HL. We report the SMNs among 1711 patients enrolled in AHOD0031. Patients were treated with 4 cycles of doxorubicin, bleomycin, vincristine, etoposide, prednisone, and cyclophosphamide with or without involved-field radiation therapy (RT). Patients with a slow early response to initial chemotherapy were randomized to 2 additional cycles of dexamethasone, etoposide, cisplatin and cytarabine or no additional chemotherapy, and all received RT. At a median follow-up of 7.3 years, an analysis of SMNs was performed. The 10-year cumulative incidence of SMN was 1.3% (95% confidence interval [CI], 0.6-2.0). SMNs included 3 patients with acute myeloid leukemia (AML), 11 with solid tumors, and 3 with non-Hodgkin lymphoma. Sixteen of 17 patients with an SMN had received combined modality therapy. The standardized incidence ratio for SMN was 9.5 (95% CI, 4.5-15.2) with an excess absolute risk of 1.2 per 1000 person-years. The cumulative incidence of SMNs was higher among patients who received RT (P = .037). In multivariate analysis, RT, B symptoms, and race were associated with SMN risk. Given the latency from exposure, we have likely captured all cases of secondary leukemia and myelodysplastic syndrome (MDS). Longer follow-up is needed to determine the risk of solid tumors. Avoidance of RT without sacrificing disease control should remain a goal for future therapeutic approaches. This trial was registered at www.clinicaltrials.gov as #NCT00025259.