Relevance of Spatial Heterogeneity of Immune Infiltration for Predicting Risk of Recurrence After Endocrine Therapy of ER+ Breast Cancer

Nuclear shape and orientation features from H&E images predict survival in early-stage estrogen receptor-positive breast cancers

Early-stage estrogen receptor-positive (ER+) breast cancer (BCa) is the most common type of BCa in the United States. One critical question with these tumors is identifying which patients will receive added benefit from adjuvant chemotherapy. Nuclear pleomorphism (variance in nuclear shape and morphology) is an important constituent of breast grading schemes, and in ER+ cases, the grade is highly correlated with disease outcome. This study aimed to investigate whether quantitative computer-extracted image features of nuclear shape and orientation on digitized images of hematoxylin-stained and eosin-stained tissue of lymph node-negative (LN-), ER+ BCa could help stratify patients into discrete (<10 years short-term vs. >10 years long-term survival) outcome groups independent of standard clinical and pathological parameters. We considered a tissue microarray (TMA) cohort of 276 ER+, LN- patients comprising 150 patients with long-term and 126 patients with short-term overall survival, wherein 177 randomly chosen cases formed the modeling set, and 99 remaining cases the test set. Segmentation of individual nuclei was performed using multiresolution watershed; subsequently, 615 features relating to nuclear shape/texture and orientation disorder were extracted from each TMA spot. The Wilcoxon's rank-sum test identified the 15 most prognostic quantitative histomorphometric features within the modeling set. These features were then subsequently combined via a linear discriminant analysis classifier and evaluated on the test set to assign a probability of long-term vs. short-term disease-specific survival. In univariate survival analysis, patients identified by the image classifier as high risk had significantly poorer survival outcome: hazard ratio (95% confident interval) = 2.91(1.23-6.92), p = 0.02786. Multivariate analysis controlling for T-stage, histology grade, and nuclear grade showed the classifier to be independently predictive of poorer survival: hazard ratio (95% confident interval) = 3.17(0.33-30.46), p = 0.01039. Our results suggest that quantitative histomorphometric features of nuclear shape and orientation are strongly and independently predictive of patient survival in ER+, LN- BCa.

TIM-3 expression in breast cancer

Tumor-infiltrating lymphocytes (TILs) are predominantly present in breast cancer patients with estrogen receptor negative tumors, among whom increasing levels correlate with favorable outcomes. Nevertheless, currently available immune checkpoint inhibitors appear to benefit only a small number of women with breast cancer. Upregulation of additional immune checkpoint markers is one mechanism of resistance to current inhibitors that might be amenable to targeting with newer agents. T-cell Immunoglobulin and Mucin domain-containing molecule 3 (TIM-3) is an immune checkpoint receptor that is an emerging target for cancer immunotherapy. We investigated TIM-3 immunohistochemical expression in 3,992 breast cancer specimens assembled into tissue microarrays, linked to detailed outcome, clinico-pathological parameters and biomarkers including CD8, PD-1, PD-L1 and LAG-3. We scored and reported absolute counts for TIM-3+ intra-epithelial and stromal TILs (iTILs and sTILs), and find that breast cancer patients with TIM-3+ iTILs (≥ 1) represent a minority of cases (11%), with a predilection for basal-like breast cancers (among which 28% had TIM-3+ iTILs). TIM-3+ sTILs (≥ 2) represented 20% of cases and included more non-basal cases. The presence of TIM-3+ iTILs highly correlates with hematoxylin and eosin-stained stromal TILs and with other immune checkpoint markers (PD-1+ iTILs, LAG-3+ iTILs and PD-L1+ tumors). In prognostic analyses, early breast cancer patients with TIM-3+ iTILs have significantly improved breast cancer-specific survival whereas TIM-3+ sTILs did not reach statistical significance. In multivariate analyses, the presence of TIM-3+ iTILs is an independent favorable prognostic factor in the whole cohort as well as among ER negative patients. Our study supports TIM-3 as a target for breast cancer immunotherapy.

Histogram analysis of quantitative pharmacokinetic parameters on DCE-MRI: correlations with prognostic factors and molecular subtypes in breast cancer

BACKGROUND

Breast cancer heterogeneity influences poor prognoses thorough therapy resistance. This study quantitatively evaluated intratumoral heterogeneity through a histogram analysis of dynamic contrast-enhanced MRI (DCE-MRI) pharmacokinetic parameters, and determined correlations with prognostic factors and molecular subtypes.

METHODS

We retrospectively investigated 101 invasive ductal breast cancers from 99 women who underwent preoperative DCE-MRI between July 2012 and November 2014. Pharmacokinetic parameters (K^trans, k_ep, and v_e) were obtained by the Tofts model. For each parameter, the mean, standard deviation, coefficient of variation, skewness, and kurtosis values of tumor were calculated, and prognostic factors and subtypes associations were assessed.

RESULTS

The mean of v_e was lower in cancers with high Ki-67 than in cancers with low Ki-67 (P = 0.002). The coefficient of variation of v_e was higher in cancers with estrogen receptor negativity than in cancers with estrogen receptor positivity (P < 0.001). The coefficient of variation of v_e was also higher in cancers with high Ki-67 than in cancers with low Ki-67 (P < 0.001). The skewness of v_e was higher in cancers with high nuclear grade than in cancers with low nuclear grade (P = 0.006). Triple-negative cancers showed higher v_e coefficient of variation than did those with luminal A (P < 0.001) and B (P = 0.006).

CONCLUSIONS

Various v_e parameters correlated with breast cancer prognostic factors and molecular subtypes.

Invasive lobular and ductal breast carcinoma differ in immune response, protein translation efficiency and metabolism

Invasive lobular carcinoma (ILC) is the second most common histological subtype of breast cancer following invasive ductal carcinoma (IDC). ILC differs from IDC in a number of histological and clinical features, such as single strand growth, difficulty in detection, and frequent late recurrences. To understand the molecular pathways involved in the clinical characteristics of ILC, we compared the gene expression profiles of luminal A ILC and luminal A IDC using data from TCGA and utilized samples from METABRIC as a validation data set. Top pathways that were significantly enriched in ILC were related to immune response. ILC exhibited a higher activity of almost all types of immune cells based on cell type-specific signatures compared to IDC. Conversely, pathways that were less enriched in ILC were related to protein translation and metabolism, which we functionally validated in cell lines. The higher immune activity uncovered in our study highlights the currently unexplored potential of a response to immunotherapy in a subset of patients with ILC. Furthermore, the lower rates of protein translation and metabolism - known features of tumor dormancy - may play a role in the late recurrences of ILC and lower detection rate in mammography and PET scanning.

Immuno-oncology-101: overview of major concepts and translational perspectives

Cancer immunotherapy is demonstrating impressive clinical benefit in different malignancies and clinical oncologists are increasingly turning their attention to immune-oncology. It is now well recognized that innate and adaptive immune cells infiltrating tumors are associated with clinical outcomes and responses to treatments, and can be harnessed to patients' benefit. Considerable advances have also been made in understanding how cancers escape from immune attack. Targeting of immunological escape processes regulated by the expression of immune checkpoint receptors and ligands and the down-modulation of tumor antigen presentation is the basis of immuno-oncology treatments. Despite recent achievements, there remain a number of unresolved issues in order to successfully implement cancer immunotherapy in many cancers. Importantly, clinical biomarkers are still needed for better optimization of emerging combination immunotherapies and better treatment tailoring. In this review, we summarize the function of innate and adaptive immune cells in anti-tumor immunity and the general mechanisms exploited by tumor cells to escape and inhibit immune responses as well as therapeutic strategies developed to overcome these mechanisms and discuss emerging biomarkers in immuno-oncology.