Sir Peter MacCallum Department of Oncology - Research Publications

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    Clinical implications of prospective genomic profiling of metastatic breast cancer patients (vol 22, 91, 2020)
    van Geelen, CT ; Savas, P ; Teo, ZL ; Luen, SJ ; Weng, C-F ; Ko, Y-A ; Kuykhoven, KS ; Caramia, F ; Salgado, R ; Francis, PA ; Dawson, S-J ; Fox, SB ; Fellowes, A ; Loi, S (BMC, 2022-07-15)
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    The path to a better biomarker: application of a risk management framework for the implementation of PD-L1 and TILs as immuno-oncology biomarkers in breast cancer clinical trials and daily practice
    Gonzalez-Ericsson, P ; Stovgaard, ES ; Sua, LF ; Reisenbichler, E ; Kos, Z ; Carter, JM ; Michiels, S ; Le Quesne, J ; Nielsen, TO ; Laenkholm, A-V ; Fox, SB ; Adam, J ; Bartlett, JMS ; Rimm, DL ; Quinn, C ; Peeters, D ; Dieci, M ; Vincent-Salomon, A ; Cree, I ; Hida, A ; Balko, JM ; Haynes, HR ; Frahm, I ; Acosta-Haab, G ; Balancin, M ; Bellolio, E ; Yang, W ; Kirtani, P ; Sugie, T ; Ehinger, A ; Castaneda, CA ; Kok, M ; McArthur, H ; Siziopikou, K ; Badve, S ; Fineberg, S ; Gown, A ; Viale, G ; Schnitt, SJ ; Pruneri, G ; Penault-Llorca, F ; Hewitt, S ; Thompson, EA ; Allison, KH ; Symmans, WF ; Bellizzi, AM ; Brogi, E ; Moore, DA ; Larsimont, D ; Dillon, DA ; Lazar, A ; Lien, H ; Goetz, MP ; Broeckx, G ; El Bairi, K ; Harbeck, N ; Cimino-Mathews, A ; Sotiriou, C ; Adams, S ; Liu, S-W ; Loibl, S ; Chen, I-C ; Lakhani, SR ; Juco, JW ; Denkert, C ; Blackley, EF ; Demaria, S ; Leon-Ferre, R ; Gluz, O ; Zardavas, D ; Emancipator, K ; Ely, S ; Loi, S ; Salgado, R ; Sanders, M (WILEY, 2020-04-01)
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    Immune system and angiogenesis-related potential surrogate biomarkers of response to everolimus-based treatment in hormone receptor-positive breast cancer: an exploratory study
    Schettini, F ; Sobhani, N ; Ianza, A ; Triulzi, T ; Molteni, A ; Lazzari, MC ; Strina, C ; Milani, M ; Corona, SP ; Sirico, M ; Bernocchi, O ; Giudici, F ; Cappelletti, MR ; Ciruelos, E ; Jerusalem, G ; Loi, S ; Fox, SB ; Generali, D (SPRINGER, 2020-08-07)
    PURPOSE: mTOR inhibitor everolimus is used for hormone receptor-positive (HR+)/HER2-negative metastatic breast cancer (mBC). No reliable predictive biomarker of response is available. Following evidences from other solid tumors, we aimed to assess the association between treatment-associated immune system features and everolimus activity. METHODS: We retrospectively explored a correlation with the therapeutic activity of everolimus and tumor-associated immune pathways with ingenuity pathway analysis (IPA), neutrophil-to-lymphocyte ratio (NLR), circulating lymphocytes, and endothelial cells (CECs) in 3 different HR+ mBC studies, including the BALLET phase IIIb study. RESULTS: The circulating levels of CD3+/CD8+, CD3+/CD4+, and overall T lymphocytes were higher in responders versus non-responders at baseline (p = 0.017, p < 0.001, p = 0.034) and after treatment (p = 0.01, p = 0.003, p = 0.023). Reduced CECs, a tumor neoangiogenesis marker, were observed in responders after treatment (p < 0.001). Patients with low NLR (≤ 4.4) showed a better progression-free survival compared to patients with high NLR (> 4.4) (p = 0.01). IPA showed that the majority of immunity-related genes were found upregulated in responders compared to non-responders before treatment, but not after. CONCLUSIONS: Lymphocytes subpopulations, CECs and NLR could be interesting biomarkers predictive of response to everolimus-based regimens, potentially useful in daily clinical practice to select/monitor everolimus-based treatment in mBC. Further studies to confirm such hypotheses are warranted.
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    Pitfalls in assessing stromal tumor infiltrating lymphocytes (sTILs) in breast cancer
    Kos, Z ; Roblin, E ; Kim, RS ; Michiels, S ; Gallas, BD ; Chen, W ; van de Vijver, KK ; Goel, S ; Adams, S ; Demaria, S ; Viale, G ; Nielsen, TO ; Badve, SS ; Symmans, WF ; Sotiriou, C ; Rimm, DL ; Hewitt, S ; Denkert, C ; Loibl, S ; Luen, SJ ; Bartlett, JMS ; Savas, P ; Pruneri, G ; Dillon, DA ; Cheang, MCU ; Tutt, A ; Hall, JA ; Kok, M ; Horlings, HM ; Madabhushi, A ; van der Laak, J ; Ciompi, F ; Laenkholm, A-V ; Bellolio, E ; Gruosso, T ; Fox, SB ; Araya, JC ; Floris, G ; Hudecek, J ; Voorwerk, L ; Beck, AH ; Kerner, J ; Larsimont, D ; Declercq, S ; Van den Eynden, G ; Pusztai, L ; Ehinger, A ; Yang, W ; AbdulJabbar, K ; Yuan, Y ; Singh, R ; Hiley, C ; al Bakir, M ; Lazar, AJ ; Naber, S ; Wienert, S ; Castillo, M ; Curigliano, G ; Dieci, M-V ; Andre, F ; Swanton, C ; Reis-Filho, J ; Sparano, J ; Balslev, E ; Chen, I-C ; Stovgaard, EIS ; Pogue-Geile, K ; Blenman, KRM ; Penault-Llorca, F ; Schnitt, S ; Lakhani, SR ; Vincent-Salomon, A ; Rojo, F ; Braybrooke, JP ; Hanna, MG ; Soler-Monso, MT ; Bethmann, D ; Castaneda, CA ; Willard-Gallo, K ; Sharma, A ; Lien, H-C ; Fineberg, S ; Thagaard, J ; Comerma, L ; Gonzalez-Ericsson, P ; Brogi, E ; Loi, S ; Saltz, J ; Klaushen, F ; Cooper, L ; Amgad, M ; Moore, DA ; Salgado, R (NATURE RESEARCH, 2020-05-12)
    Stromal tumor-infiltrating lymphocytes (sTILs) are important prognostic and predictive biomarkers in triple-negative (TNBC) and HER2-positive breast cancer. Incorporating sTILs into clinical practice necessitates reproducible assessment. Previously developed standardized scoring guidelines have been widely embraced by the clinical and research communities. We evaluated sources of variability in sTIL assessment by pathologists in three previous sTIL ring studies. We identify common challenges and evaluate impact of discrepancies on outcome estimates in early TNBC using a newly-developed prognostic tool. Discordant sTIL assessment is driven by heterogeneity in lymphocyte distribution. Additional factors include: technical slide-related issues; scoring outside the tumor boundary; tumors with minimal assessable stroma; including lymphocytes associated with other structures; and including other inflammatory cells. Small variations in sTIL assessment modestly alter risk estimation in early TNBC but have the potential to affect treatment selection if cutpoints are employed. Scoring and averaging multiple areas, as well as use of reference images, improve consistency of sTIL evaluation. Moreover, to assist in avoiding the pitfalls identified in this analysis, we developed an educational resource available at www.tilsinbreastcancer.org/pitfalls.
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    Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group
    Amgad, M ; Stovgaard, ES ; Balslev, E ; Thagaard, J ; Chen, W ; Dudgeon, S ; Sharma, A ; Kerner, JK ; Denkert, C ; Yuan, Y ; AbdulJabbar, K ; Wienert, S ; Savas, P ; Voorwerk, L ; Beck, AH ; Madabhushi, A ; Hartman, J ; Sebastian, MM ; Horlings, HM ; Hudecek, J ; Ciompi, F ; Moore, DA ; Singh, R ; Roblin, E ; Balancin, ML ; Mathieu, M-C ; Lennerz, JK ; Kirtani, P ; Chen, I-C ; Braybrooke, JP ; Pruneri, G ; Demaria, S ; Adams, S ; Schnitt, SJ ; Lakhani, SR ; Rojo, F ; Comerma, L ; Badve, SS ; Khojasteh, M ; Symmans, WF ; Sotiriou, C ; Gonzalez-Ericsson, P ; Pogue-Geile, KL ; Kim, RS ; Rimm, DL ; Viale, G ; Hewitt, SM ; Bartlett, JMS ; Penault-Llorca, F ; Goel, S ; Lien, H-C ; Loibl, S ; Kos, Z ; Loi, S ; Hanna, MG ; Michiels, S ; Kok, M ; Nielsen, TO ; Lazar, AJ ; Bago-Horvath, Z ; Kooreman, LFS ; van der Laak, JAWM ; Saltz, J ; Gallas, BD ; Kurkure, U ; Barnes, M ; Salgado, R ; Cooper, LAD (NATURE RESEARCH, 2020-05-12)
    Assessment of tumor-infiltrating lymphocytes (TILs) is increasingly recognized as an integral part of the prognostic workflow in triple-negative (TNBC) and HER2-positive breast cancer, as well as many other solid tumors. This recognition has come about thanks to standardized visual reporting guidelines, which helped to reduce inter-reader variability. Now, there are ripe opportunities to employ computational methods that extract spatio-morphologic predictive features, enabling computer-aided diagnostics. We detail the benefits of computational TILs assessment, the readiness of TILs scoring for computational assessment, and outline considerations for overcoming key barriers to clinical translation in this arena. Specifically, we discuss: 1. ensuring computational workflows closely capture visual guidelines and standards; 2. challenges and thoughts standards for assessment of algorithms including training, preanalytical, analytical, and clinical validation; 3. perspectives on how to realize the potential of machine learning models and to overcome the perceptual and practical limits of visual scoring.
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    Clinical implications of prospective genomic profiling of metastatic breast cancer patients
    van Geelen, CT ; Savas, P ; Teo, ZL ; Luen, SJ ; Weng, C-F ; Ko, Y-A ; Kuykhoven, KS ; Caramia, F ; Salgado, R ; Francis, PA ; Dawson, S-J ; Fox, SB ; Fellowes, A ; Loi, S (BMC, 2020-08-18)
    BACKGROUND: Metastatic breast cancer remains incurable. Next-generation sequencing (NGS) offers the ability to identify actionable genomic alterations in tumours which may then be matched with targeted therapies, but the implementation and utility of this approach is not well defined for patients with metastatic breast cancer. METHODS: We recruited patients with advanced breast cancer of any subtype for prospective targeted NGS of their most recent tumour samples, using a panel of 108 breast cancer-specific genes. Genes were classified as actionable or non-actionable using the European Society of Medical Oncology Scale for Clinical Actionability of Molecular Targets (ESCAT) guidelines. RESULTS: Between February 2014 and May 2019, 322 patients were enrolled onto the study, with 72% (n = 234) of patients successfully sequenced (n = 357 samples). The majority (74%, n = 171) of sequenced patients were found to carry a potentially actionable alteration, the most common being a PIK3CA mutation. Forty-three percent (n = 74) of patients with actionable alterations were referred for a clinical trial or referred for confirmatory germline testing or had a change in therapy outside of clinical trials. We found alterations in AKT1, BRCA2, CHEK2, ESR1, FGFR1, KMT2C, NCOR1, PIK3CA and TSC2 to be significantly enriched in our metastatic population compared with primary breast cancers. Concordance between primary and metastatic samples for key driver genes (TP53, ERBB2 amplification) was > 75%. Additionally, we found that patients with a higher number of mutations had a significantly worse overall survival. CONCLUSION: Genomic profiling of patients with metastatic breast cancer can have clinical implications and should be considered in all suitable patients.
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    Application of a risk-management framework for integration of stromal tumor-infiltrating lymphocytes in clinical trials
    Hudecek, J ; Voorwerk, L ; van Seijen, M ; Nederlof, I ; de Maaker, M ; van den Berg, J ; van de Vijver, KK ; Sikorska, K ; Adams, S ; Demaria, S ; Viale, G ; Nielsen, TO ; Badve, SS ; Michiels, S ; Symmans, WF ; Sotiriou, C ; Rimm, DL ; Hewitt, SM ; Denkert, C ; Loibl, S ; Loi, S ; Bartlett, JMS ; Pruneri, G ; Dillon, DA ; Cheang, MCU ; Tutt, A ; Hall, JA ; Kos, Z ; Salgado, R ; Kok, M ; Horlings, HM (NATURE RESEARCH, 2020-05-12)
    Stromal tumor-infiltrating lymphocytes (sTILs) are a potential predictive biomarker for immunotherapy response in metastatic triple-negative breast cancer (TNBC). To incorporate sTILs into clinical trials and diagnostics, reliable assessment is essential. In this review, we propose a new concept, namely the implementation of a risk-management framework that enables the use of sTILs as a stratification factor in clinical trials. We present the design of a biomarker risk-mitigation workflow that can be applied to any biomarker incorporation in clinical trials. We demonstrate the implementation of this concept using sTILs as an integral biomarker in a single-center phase II immunotherapy trial for metastatic TNBC (TONIC trial, NCT02499367), using this workflow to mitigate risks of suboptimal inclusion of sTILs in this specific trial. In this review, we demonstrate that a web-based scoring platform can mitigate potential risk factors when including sTILs in clinical trials, and we argue that this framework can be applied for any future biomarker-driven clinical trial setting.