The advent of immune-checkpoint inhibitors (ICI) in modern oncology has significantly improved survival in several cancer settings. A subgroup of women with breast cancer (BC) has immunogenic infiltration of lymphocytes with expression of programmed death-ligand 1 (PD-L1). These patients may potentially benefit from ICI targeting the programmed death 1 (PD-1)/PD-L1 signaling axis. The use of tumor-infiltrating lymphocytes (TILs) as predictive and prognostic biomarkers has been under intense examination. Emerging data suggest that TILs are associated with response to both cytotoxic treatments and immunotherapy, particularly for patients with triple-negative BC. In this review from The International Immuno-Oncology Biomarker Working Group, we discuss (a) the biological understanding of TILs, (b) their analytical and clinical validity and efforts toward the clinical utility in BC, and (c) the current status of PD-L1 and TIL testing across different continents, including experiences from low-to-middle-income countries, incorporating also the view of a patient advocate. This information will help set the stage for future approaches to optimize the understanding and clinical utilization of TIL analysis in patients with BC.

F. nucleatum-high was associated with poor survival in metastatic CRC. In addition, we identified mutational characteristics of colorectal cancer according to F. nucleatum amount.

The prognostic significance of tumor-infiltrating lymphocytes and immune signals has been described previously in triple-negative breast cancer (TNBC). Furthermore, recent studies have shown that immunologic parameters are relevant for the response to neoadjuvant chemotherapy (NAC) in breast cancer as well as for outcomes after adjuvant chemotherapy. However, immune signals are variable, and which signals are important is largely unknown. We, therefore, evaluated the expression of immune-related genes in TNBC treated with NAC. We retrospectively evaluated biopsy tissue from 55 patients with primary TNBC treated with NAC (anthracycline, cyclophosphamide, and docetaxel) against the NanoString nCounter GX Human Immunology Panel (579 immune-related genes). Higher expression of cytotoxic molecules, T cell receptor signaling pathway components, cytokines related to T helper cell type 1 (Th1), and B cell markers was associated with a pathologic complete response (pCR). Higher expression of NFKB1, MAPK1, TRAF1, CXCL13, GZMK, and IL7R was significantly associated with pCR, higher Miller-Payne grade, and lower residual cancer burden class. Expression of NFKB1, TRAF1, and CXCL13genes, in particular, was significantly correlated with a longer disease-free survival rate. Conversely, patients those who failed to achieve a pCR showed increased expression of genes related to neutrophils. Higher expression of cytotoxic molecules, T cell receptor signaling pathway components, Th1-related cytokines, and B cell markers is correlated with pCR and survival in TNBC patients treated with NAC. Our results suggest that the activation status of neutrophils may provide additional predictive information for TNBC patients treated with NAC.

Growing evidence suggests that the efficacy of immunotherapy in non-small cell lung cancers (NSCLCs) is associated with the immune microenvironment within the tumor. We aimed to explore radiologic phenotyping using a radiomics approach to assess the immune microenvironment in NSCLC. Two independent NSCLC cohorts (training and test sets) were included. Single-sample gene set enrichment analysis was used to determine the tumor microenvironment, where type 1 helper T (Th1) cells, type 2 helper T (Th2) cells, and cytotoxic T cells were the targets for prediction with computed tomographic (CT) radiomic features. Multiple algorithms were in the modeling followed by final model selection. The training dataset comprised 89 NSCLCs and the test set included 60 cases of lung squamous cell carcinoma and adenocarcinoma. A total of 239 CT radiomic features were used. A linear discriminant analysis model was selected for the final model of Th2 cell group prediction. The area under the curve value of the final model on the test set was 0.684. Predictors of the linear discriminant analysis model were skewness (total and outer pixels), kurtosis, variance (subsampled from delta [subtraction inner pixels from outer pixels]), and informational measure of correlation. The performances of radiomics on test set of Th1 and cytotoxic T cell were not accurate enough to be predictable. A radiomics approach can be used to interrogate an entire tumor in a noninvasive manner and provide added diagnostic value to identify the immune microenvironment of NSCLC, in particular, Th2 cell signatures. Fig 3. Distributions of type 1 helper T-cell, type 2 helper T-cell, and cytotoxic T cell signatures of the test set (TCGA cohort) and training set ("Lung3" cohort).