المؤلفون: Milligan, Kirsty, Van Nest, Samantha J., Deng, Xinchen, Ali‐Adeeb, Ramie, Shreeves, Phillip, Punch, Samantha, Costie, Nathalie, Pavey, Nils, Crook, Juanita M., Berman, David M., Brolo, Alexandre G., Lum, Julian J., Andrews, Jeffrey L., Jirasek, Andrew

المصدر: Journal of Biophotonics; Nov2022, Vol. 15 Issue 11, p1-16, 16p

مستخلص: High‐dose‐rate‐brachytherapy (HDR‐BT) is an increasingly attractive alternative to external beam radiation‐therapy for patients with intermediate risk prostate cancer. Despite this, no bio‐marker based method currently exists to monitor treatment response, and the changes which take place at the biochemical level in hypo‐fractionated HDR‐BT remain poorly understood. The aim of this pilot study is to assess the capability of Raman spectroscopy (RS) combined with principal component analysis (PCA) and random‐forest classification (RF) to identify radiation response profiles after a single dose of 13.5 Gy in a cohort of nine patients. We here demonstrate, as a proof‐of‐concept, how RS‐PCA‐RF could be utilised as an effective tool in radiation response monitoring, specifically assessing the importance of low variance PCs in complex sample sets. As RS provides information on the biochemical composition of tissue samples, this technique could provide insight into the changes which take place on the biochemical level, as result of HDR‐BT treatment. [ABSTRACT FROM AUTHOR]

: Copyright of Journal of Biophotonics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

المؤلفون: Kalina, Jennifer L., Neilson, David S., Comber, Alexandra P., Rauw, Jennifer M., Alexander, Abraham S., Vergidis, Joanna, Lum, Julian J.

مصطلحات موضوعية: androgen deprivation therapy, radiation therapy, immunotherapy, prostate cancer, cancer vaccines, checkpoint inhibitors

الوصف: Prostate cancer patients often receive androgen deprivation therapy (ADT) in combination with radiation therapy (RT). Recent evidence suggests that both ADT and RT have immune modulatory properties. First, ADT can cause infiltration of lymphocytes into the prostate, although it remains unclear whether the influx of lymphocytes is beneficial, particularly with the advent of new classes of androgen blockers. Second, in rare cases, radiation can elicit immune responses that mediate regression of metastatic lesions lying outside the field of radiation, a phenomenon known as the abscopal response. In light of these findings, there is emerging interest in exploiting any potential synergy between ADT, RT, and immunotherapy. Here, we provide a comprehensive review of the rationale behind combining immunotherapy with ADT and RT for the treatment of prostate cancer, including an examination of the current clinical trials that employ this combination. The reported outcomes of several trials demonstrate the promise of this combination strategy; however, further scrutiny is needed to elucidate how these standard therapies interact with immune modulators. In addition, we discuss the importance of synchronizing immune modulation relative to ADT and RT, and provide insight into elements that may impact the ability to achieve maximum synergy between these treatments. ; We are grateful for funding from the Prostate Cancer Canada Discovery Grant (Julian J. Lum), WestCoast Ride to Live (Julian J. Lum, Joanna Vergidis, Abraham S. Alexander) and the Prostate Cancer Fight Foundation (Julian J. Lum). The funds cover personnel salaries and research consumable costs but not open access fees for publication. ; Faculty ; Reviewed

وصف الملف: application/pdf

العلاقة: Kalina, J. L.; Neilson, D. S.; Comber, A. P.; Rauw, J. M.; Alexander, A. S.; Vergidis, J.; & Lum, J. J. (2017). Immune modulation by androgen deprivation and radiation therapy: Implications for prostate cancer immunotherapy. Cancers, 9(2), 13. https://doi.org/10.3390/cancers9020013Test; https://doi.org/10.3390/cancers9020013Test; https://dspace.library.uvic.ca//handle/1828/9821Test

الإتاحة: https://doi.org/10.3390/cancers9020013Test
https://dspace.library.uvic.ca//handle/1828/9821Test

المؤلفون: Vrbik, Irene, Van Nest, Samantha J., Meksiarun, Phiranuphon, Loeppky, Jason, Brolo, Alexandre, Lum, Julian J., Jirasek, Andrew

المصدر: PLoS ONE; 2/15/2019, Vol. 14 Issue 2, p1-12, 12p

مصطلحات موضوعية: RADIATION, HETEROGENEITY, ENTROPY, IRRADIATION, GLYCOGEN

مستخلص: Tumour heterogeneity plays a large role in the response of tumour tissues to radiation therapy. Inherent biological, physical, and even dose deposition heterogeneity all play a role in the resultant observed response. We here implement the use of Haralick textural analysis to quantify the observed glycogen production response, as observed via Raman spectroscopic mapping, of tumours irradiated within a murine model. While an array of over 20 Haralick features have been proposed, we here concentrate on five of the most prominent features: homogeneity, local homogeneity, contrast, entropy, and correlation. We show that these Haralick features can be used to quantify the inherent heterogeneity of the Raman spectroscopic maps of tumour response to radiation. Furthermore, our results indicate that Haralick-calculated textural features show a statistically significant dose dependent variation in response heterogeneity, specifically, in glycogen production in tumours irradiated with clinically relevant doses of ionizing radiation. These results indicate that Haralick textural analysis provides a quantitative methodology for understanding the response of murine tumours to radiation therapy. Future work in this area can, for example, utilize the Haralick textural features for understanding the heterogeneity of radiation response as measured by biopsied patient tumour samples, which remains the standard of patient tumour investigation. [ABSTRACT FROM AUTHOR]

: Copyright of PLoS ONE is the property of Public Library of Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

المؤلفون: Milligan, Kirsty¹ (AUTHOR), Scarrott, Kendra² (AUTHOR), Andrews, Jeffrey L.³ (AUTHOR), Brolo, Alexandre G.⁴ (AUTHOR), Lum, Julian J.⁵ (AUTHOR), Jirasek, Andrew¹ (AUTHOR) andrew.jirasek@.ubc.ca

المصدر: Applied Spectroscopy. Jul2023, Vol. 77 Issue 7, p698-709. 12p.

مصطلحات موضوعية: *MATRIX decomposition, *NONNEGATIVE matrices, *CHEMICAL models, *PRINCIPAL components analysis, *RADIATION measurements, *MIXTURES, *RAMAN spectroscopy

مستخلص: Raman spectroscopy is a useful tool for obtaining biochemical information from biological samples. However, interpretation of Raman spectroscopy data in order to draw meaningful conclusions related to the biochemical make up of cells and tissues is often difficult and could be misleading if care is not taken in the deconstruction of the spectral data. Our group has previously demonstrated the implementation of a group- and basis-restricted non-negative matrix factorization (GBR-NMF) framework as an alternative to more widely used dimensionality reduction techniques such as principal component analysis (PCA) for the deconstruction of Raman spectroscopy data as related to radiation response monitoring in both cellular and tissue data. While this method provides better biological interpretability of the Raman spectroscopy data, there are some important factors which must be considered in order to provide the most robust GBR-NMF model. We here evaluate and compare the accuracy of a GBR-NMF model in the reconstruction of three mixture solutions of known concentrations. The factors assessed include the effect of solid versus solutions bases spectra, the number of unconstrained components used in the model, the tolerance of different signal to noise thresholds, and how different groups of biochemicals compare to each other. The robustness of the model was assessed by how well the relative concentration of each individual biochemical in the solution mixture is reflected in the GBR-NMF scores obtained. We also evaluated how well the model can reconstruct original data, both with and without the inclusion of an unconstrained component. Overall, we found that solid bases spectra were generally comparable to solution bases spectra in the GBR-NMF model for all groups of biochemicals. The model was found to be relatively tolerant of high levels of noise in the mixture solutions using solid bases spectra. Additionally, the inclusion of an unconstrained component did not have a significant effect on the deconstruction, on the condition that all biochemicals in the mixture were included as bases chemicals in the model. We also report that some groups of biochemicals achieve a more accurate deconstruction using GBR-NMF than others, likely due to similarity in the individual bases spectra. Graphical Abstract This is a visual representation of the abstract. [ABSTRACT FROM AUTHOR]

المؤلفون: Deng, Xinchen¹ (AUTHOR) alison.deng@ubc.ca, Ali-Adeeb, Ramie¹ (AUTHOR), Andrews, Jeffrey L.² (AUTHOR), Shreeves, Phillip² (AUTHOR), Lum, Julian J.^3,4 (AUTHOR), Brolo, Alexandre⁵ (AUTHOR), Jirasek, Andrew¹ (AUTHOR)

المصدر: Applied Spectroscopy. Jun2020, Vol. 74 Issue 6, p701-711. 11p.

مصطلحات موضوعية: *NONNEGATIVE matrices, *MATRIX decomposition, *RAMAN spectroscopy, *LEAST squares, *PRINCIPAL components analysis, *BREAST cancer prognosis

مستخلص: Radiation therapy (RT) is one of the most commonly prescribed cancer treatments. New tools that can accurately monitor and evaluate individual patient responses would be a major advantage and lend to the implementation of personalized treatment plans. In this study, Raman spectroscopy (RS) was applied to examine radiation-induced cellular responses in H460, MCF7, and LNCaP cancer cell lines across different dose levels and times post-irradiation. Previous Raman data analysis was conducted using principal component analysis (PCA), which showed the ability to extract biological information of glycogen. In the current studies, the use of non-negative matrix factorization (NMF) allowed for the discovery of multiplexed biological information, specifically uncovering glycogen-like and lipid-like component bases. The corresponding scores of glycogen and previously unidentified lipids revealed the content variations of these two chemicals in the cellular data. The NMF decomposed glycogen and lipid-like bases were able to separate the cancer cell lines into radiosensitive and radioresistant groups. A further lipid phenotype investigation was also attempted by applying non-negative least squares (NNLS) to the lipid-like bases decomposed individually from three cell lines. Qualitative differences found in lipid weights for each lipid-like basis suggest the lipid phenotype differences in the three tested cancer cell lines. Collectively, this study demonstrates that the application of NMF and NNLS on RS data analysis to monitor ionizing radiation-induced cellular responses can yield multiplexed biological information on bio-response to RT not revealed by conventional chemometric approaches. [ABSTRACT FROM AUTHOR]