Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group.

Funder: U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)Funder: National Center for Research Resources under award number 1 C06 RR12463-01, VA Merit Review Award IBX004121A from the United States Department of Veterans Affairs Biomedical Laboratory Research and Development Service, the DOD Prostate Cancer Idea Development Award (W81XWH-15-1-0558), the DOD Lung Cancer Investigator-Initiated Translational Research Award (W81XWH-18-1-0440), the DOD Peer Reviewed Cancer Research Program (W81XWH-16-1-0329), the Ohio Third Frontier Technology Validation Fund, the Wallace H. Coulter Foundation Program in the Department of Biomedical Engineering and the Clinical and Translational Science Award Program (CTSA) at Case Western Reserve University.Funder: Susan G Komen Foundation (CCR CCR18547966) and a Young Investigator Grant from the Breast Cancer Alliance.Funder: The Canadian Cancer SocietyFunder: Breast Cancer Research Foundation (BCRF), Grant No. 17-194Assessment 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

Pitfalls in assessing stromal tumor infiltrating lymphocytes (sTILs) in breast cancer

Abstract: 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

Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group

Funder: U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)Funder: National Center for Research Resources under award number 1 C06 RR12463-01, VA Merit Review Award IBX004121A from the United States Department of Veterans Affairs Biomedical Laboratory Research and Development Service, the DOD Prostate Cancer Idea Development Award (W81XWH-15-1-0558), the DOD Lung Cancer Investigator-Initiated Translational Research Award (W81XWH-18-1-0440), the DOD Peer Reviewed Cancer Research Program (W81XWH-16-1-0329), the Ohio Third Frontier Technology Validation Fund, the Wallace H. Coulter Foundation Program in the Department of Biomedical Engineering and the Clinical and Translational Science Award Program (CTSA) at Case Western Reserve University.Funder: Susan G Komen Foundation (CCR CCR18547966) and a Young Investigator Grant from the Breast Cancer Alliance.Funder: The Canadian Cancer SocietyFunder: Breast Cancer Research Foundation (BCRF), Grant No. 17-194Abstract: 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

Application of a risk-management framework for integration of stromal tumor-infiltrating lymphocytes in clinical trials

Funder: Breast Cancer Research Foundation (BCRF); doi: https://doi.org/10.13039/100001006Abstract: 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

Tumour sidedness and intrinsic subtypes in patients with stage II/III colon cancer: analysis of NSABP C-07 (NRG Oncology)

We tested the association of colon tumour sidedness with prognosis and with molecular subtypes recently shown to be predictive of oxaliplatin benefit in stage III colon cancer.NSABP/NRG C-07 trial (N=1603) was used to determine association of tumour sidedness with molecular subtypes and recurrence-free survival (RFS) and overall survival (OS).Sidedness was associated with molecular subtypes except stem-like/CMS4 subtype. Patients with stage III, left-sided tumours showed superior OS but not RFS. Sidedness was not associated with prediction of oxaliplatin benefit when combined with 5-Fu+LV. However, greater benefit from oxaliplatin was observed in a small subset of stage III patients with left-sided, enterocyte-subtype tumours (interaction HR=0.17, P=0.01).Sidedness was associated with molecular subtypes and was predictive of OS in stage III colon cancer but was not predictive of RFS or oxaliplatin benefit in C-07. Molecular subtypes may provide more predictive value for oxaliplatin benefit than tumour sidedness

A rapid, sensitive, reproducible and cost-effective method for mutation profiling of colon cancer and metastatic lymph nodes.

An increasing number of studies show that genetic markers can aid in refining prognostic information and predicting the benefit from systemic therapy. Our goal was to develop a high throughput, cost-effective and simple methodology for the detection of clinically relevant hot spot mutations in colon cancer.Journal ArticleResearch Support, N.I.H. ExtramuralResearch Support, Non-U.S. Gov'tinfo:eu-repo/semantics/publishe

Clinical outcome from oxaliplatin treatment in stage II/III colon cancer according to intrinsic subtypes: Secondary analysis of NSABP C-07/NRG oncology randomized clinical trial

Oxaliplatin added to fluorouracil plus leucovorin therapy for patients with colon cancer has been shown to provide significant but modest absolute benefit for disease-free survival. However, acute and chronic neurotoxic effects from this regimen underscore the need for markers that predict oxaliplatin benefit.To test our hypothesis that molecular subtypes of colon cancer would be associated with differential prognosis and benefit from oxaliplatin added to fluorouracil plus leucovorin therapy.Participants in the NSABP C-07 trial were divided into discovery (n = 848) and validation (n = 881) cohorts based on the order of tissue block submission. A reestimated centroid using 72 genes was used to determine Colorectal Cancer Assigner subtypes and their association with oxaliplatin benefit in the discovery cohort. The validation cohort was examined with a locked-down algorithm for subtype classification and statistical analysis plan. Post hoc analysis included examination of the entire cohort with Colorectal Cancer Assigner, Colorectal Cancer Subtype (CCS), and Consensus Molecular Subtype (CMS) methods.Fluorouracil plus leucovorin with or without oxaliplatin.Percent recurrence-free survival.Among 1729 patients, 744 (43%) were female and mean (SD) age was 58 (11) years. Although C-07 participants with stage III disease with an enterocyte subtype showed a statistically significant benefit from oxaliplatin in the discovery cohort (hazard ratio, 0.22 [95% CI, 0.09-0.56]; P = .001 [N = 65]), no statistically significant benefit was observed in the validation cohort (hazard ratio, 0.53 [95% CI, 0.22-1.24]; P = .14 [N = 70]). The stemlike subtype was associated with poor prognosis and lack of benefit from oxaliplatin treatment (HR, 0.99 [95% CI, 0.73-1.34]; P = .96 [N = 367]). Examination of the different subtyping methods shows that all 3 methods robustly identified patients with poor prognosis (stemlike, CCS-3, and CMS-4) in both stage II and III.Patients with stemlike tumors may be appropriate for clinical trials testing experimental therapies because stemlike tumors were robustly identified and associated with a poor prognosis regardless of stage or chemotherapy regimen. The clinical utility of using subtyping for the identification of patients for treatment with oxaliplatin requires validation in independent clinical trial cohorts.clinicaltrials.gov Identifier: NCT00004931