Application of a standardized WT1 assay provides independent prognostic information in AML, lending support to incorporation of early assessment of MRD to develop more robust risk scores, to enhance risk stratification, and to identify patients who may benefit from allogeneic transplantation.

The basal molecular subtype of breast cancer (BC) is defined by the mRNA expression pattern of an intrinsic 500-gene set. It is the most homogeneous subtype in transcriptional terms, and one of the most aggressive in prognostic terms. Clinical trials testing new systemic therapeutic strategies have been launched in basal BCs. Although no proof of evidence has yet been reported, basal tumors are currently assimilated to and selected as triple-negative (TN) BCs in these trials because of their frequent immunohistochemical (IHC) negativity for hormone and ERBB2 receptors. Here, we have assessed the degrees of correlation and of homogeneity of the TN phenotype (IHC-based definition) and the basal subtype (gene expression-based definition). We analyzed 172 TN BCs defined by gene expression profile as basal (123 cases) and nonbasal (49 cases). Conversely, 160 tumors were defined as basal by their gene expression profile and included 123 TN and 37 non-TN samples. Uni-and multivariate analyses revealed that TN BCs represent a more heterogeneous group than basal BCs, including basal and nonbasal tumors very different both at the histoclinical and molecular level, notably for mRNA expression of molecules targeted by specific therapies under evaluation in clinical trials. These results call for caution in the interpretation of ongoing trials and selection of patients in future trials. They also warrant the identification of molecular markers for basal BCs more clinically applicable than gene expression profiles.

Background: The Immunoscore (IS), which prognostically classifies stage IeIII colon cancer (CC) patients, was evaluated in the International Duration Evaluation of Adjuvant Therapy (IDEA) France cohort study investigating 3 versus 6 months of oxaliplatin-based adjuvant chemotherapy in stage III CC patients. Patients and methods: Densities of CD3þ and CD8þ T cells in the tumor and invasive margin were determined by immunohistochemistry, quantified by digital pathology, and converted to IS. Mismatch repair status was determined by immunohistochemistry or by pentaplex PCR. Prediction of disease-free survival (DFS) by IS was analyzed by a multivariable Cox regression model in each study arm. Harrell's C-statistics were used to investigate the IS performance. Results: Samples of 1322 patients were available. IS Low, Intermediate (Int), and High were observed in 43.6%, 47.0%, and 9.4% of patients, respectively. IS Low identified patients at higher risk of relapse or death compared with Int þ High [hazard ratio (HR) ¼ 1.54; 95% confidence interval (CI) 1.24e1.93, P ¼ 0.0001]. The 3-year DFS was 66.80% (95% CI 62.23e70.94) for IS Low and 77.14% (95% CI 73.50e80.35) for IS Int þ High. In multivariable analysis, IS remained significantly independently associated with DFS (P ¼ 0.003) when adjusted for sex, histological grade, T/N stage, and microsatellite instability. For mFOLFOX6-treated patients (91.6% of the cohort), a statistical significant interaction was observed for the predictive value of IS for treatment duration (3 versus 6 months) in terms of DFS (P ¼ 0.057). IS Int þ High significantly predicted benefit of 6 months of treatment (HR ¼ 0.53; 95% CI 0.37e0.75; P ¼ 0.0004), including clinically low-and high-risk stage III CC (all P < 0.001). Conversely, patients with IS Low (46.4%) did not significantly benefit from the 6-month mFOLFOX6 versus the 3-month mFOLFOX6. Conclusions: The prognostic value of IS for DFS was confirmed in patients with stage III CC treated with oxaliplatinbased chemotherapy. Its predictive value for DFS benefit of longer duration of mFOLFOX6 adjuvant treatment was found in IS Int þ High. These results will be validated in an external independent cohort.

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Background The American Joint Committee on Cancer staging and other prognostic tools fail to account for stage-independent variability in outcome. We developed a prognostic classifier adding Immunoscore to clinicopathological and molecular features in patients with stage III colon cancer. Methods Patient (n = 559) data from the FOLFOX arm of adjuvant trial NCCTG N0147 were used to construct Cox models for predicting disease-free survival (DFS). Variables included age, sex, T stage, positive lymph nodes (+LNs), N stage, performance status, histologic grade, sidedness, KRAS/BRAF, mismatch repair, and Immunoscore (CD3+, CD8+ T-cell densities). After determining optimal functional form (continuous or categorical) and within Cox models, backward selection was performed to analyze all variables as candidate predictors. All statistical tests were two-sided. Results Poorer DFS was found for tumors that were T4 vs T3 (hazard ratio [HR] = 1.76, 95% confidence interval [CI] = 1.19 to 2.60; P = .004), right- vs left-sided (HR = 1.52, 95% CI = 1.14 to 2.04; P = .005), BRAF V600E (HR = 1.74, 95% CI = 1.26 to 2.40; P &lt; .001), mutant KRAS (HR = 1.66, 95% CI = 1.08 to 2.55; P = .02), and low vs high Immunoscore (HR = 1.69, 95% CI = 1.22 to 2.33; P = .001) (all P &lt; .02). Increasing numbers of +LNs and lower continuous Immunoscore were associated with poorer DFS that achieved significance (both Ps&lt; .0001). After number of +LNs, T stage, and BRAF/KRAS, Immunoscore was the most informative predictor of DFS shown multivariately. Among T1–3 N1 tumors, Immunoscore was the only variable associated with DFS that achieved statistical significance. A nomogram was generated to determine the likelihood of being recurrence-free at 3 years. Conclusions The Immunoscore can enhance the accuracy of survival prediction among patients with stage III colon cancer.

BackgroundNew and fully validated tests need to be brought into clinical practice to improve the estimation of recurrence risk in patients with colon cancer. The aim of this study was to assess the analytical performances of the Immunoscore (IS) and show its contribution to prognosis prediction.MethodsImmunohistochemical staining of CD3+ and CD8+ T cells on adjacent sections of colon cancer tissues were quantified in the core of the tumor and its invasive margin with dedicated IS modules integrated into digital pathology software. Staining intensity across samples collected between 1989 and 2016 (n=595) was measured. The accuracy of the IS workflow was established by comparing optical and automatic counts. Analytical precision of the IS was evaluated within individual tumor block on distant sections and between eligible blocks. The IS interlaboratory reproducibility (n=100) and overall assay precision were assessed (n=3). Contribution of the IS to prediction of recurrence based on clinical and molecular parameters was determined (n=538).ResultsOptical and automatic counts for CD3+ or CD8+ were strongly correlated (r=0.94, p<0.001 and r=0.92, p<0.001, respectively). CD3 and CD8 staining intensities were not altered by the age of the tumor block over a period of 30 years. Neither the position of tested tissue sections within a tumor block nor the selection of the tissue blocks affected the IS. Reproducibility of the IS was not affected by multiple variables (eg, antibody lots, DAB revelation kits, immunohistochemistry automates and operators). Interassay repeatability of the IS was 100% and interlaboratory reproducibility between two testing centers was 93%. Finally, in a case series of patients with stage II–III colon cancer, the relative proportion of variance for time to recurrence was greatest for the IS (53% of prognostic variability) in a model that included IS, T-stage, microsatellite instability status and total number of lymph nodes.ConclusionIS is a robust and validated clinical assay leveraging immune scoring to predict recurrence risk of patient with localized colon cancer. The strong and independent prognostic value of IS should pave the way for it use in clinical practice.

Additional information FundingThe clinical trial was funded by Lytix Biopharma AS.

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