Preliminary development of a predictive signature for response to palliative chemotherapy in gastro-oesophageal adenocarcinoma using multilinear singular value decomposition


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Alan Bilsland1,Eilidh McCulloch2,Jennifer Walker2,Carol McCormick2,Liz-Anne Lewsley3,Antonia McMillan3,Martin MacLeod2,Jamie Stobo3,James Paul3,Patricia Roxburgh2,Sofie Degerman4,Fiona Thomson2,T. R. Jeffry Evans2,W. Nicol Keith2
1Institute of Cancer Science, Wolfson Wohl Cancer Research Centre, University of Glasgow,2Glasgow Experimental Cancer Medicines Centre, Institute of Cancer Science, University of Glasgow,3Cancer Research UK Clinical Trials Unit, Institute of Cancer Science, University of Glasgow,4Department of Medical Biosciences, Umea University

Abstract

Background

Multi-centre biomarker study UKCRN12435 is analysing multiple circulating biomarkers including plasma IL6, IL8, IL10, TNFa, and IFNg longitudinally in advanced gastro-oesophageal adenocarcinoma patients receiving palliative chemotherapy. We previously reported baseline and cycle 2 (C1/C2) survival associations for IL6, IL8, and IL10 (NCRI 2017/2018). No survival-associated cytokines relate to objective response at either time. To investigate a combinatorial signature, we analysed 71 patients with full response, clinicopathology, and C1/C2 cytokine data using multilinear singular-value decomposition.

Method

Elements Tijk of third-order tensor T represent patient i, cytokine j, at time k. Decomposition yields:

Tijk = Sabc . Uia . VTbj . WTck

Summation is implied over a, b, c; S is a rank-(10, 5, 2) tensor. Columns of U can be regarded as "building-blocks" for observed all-patient cytokine measurements. Sequential forward feature-selection using fitting-deviance of a logistic model of response with candidate covariates U, TNM-stage, gender and age, selected three columns of U, gender, T-stage, and N-stage.

Results

2/3 columns of U and all clinical covariates were significant (p<0.05). Classification accuracy was 76% (responder/non-responder) with AUC=0.835. Sensitivity and specificity were 83% and 62.5%. Neglecting U, only N-stage was significant (accuracy 69%; AUC=0.717; sensitivity 78.7%; specificity 50%). Likelihood ratio test confirmed significance of cytokine basis terms (p=0.0027). A comparator using forward-selected raw cytokine measurements performed more poorly.

Conclusion

Raw cytokine levels are poor response predictors. Though preliminary, C1/C2 tensor analysis improved accuracy modestly but significantly over clinicopathology-only; specificity was most improved. UKCRN12435 is recruiting ~400 patients, comprising 2 cohorts (biomarker discovery and validation cohorts). We have fully profiled the discovery cohort baseline (183 patients), but only 114 patients at C2. Longitudinal studies are continuing and we are also investigating additional immuno-oncology markers. A larger training set, additional markers, and/or cycle 3 data may improve classification. We await results from cohort 2 to confirm model validity.