The emergent field of digital pathology employing automated image analysis techniques is to revolutionize traditional pathology at the center of clinical diagnostics. Histological images provide important tumor features unavailable in molecular profiling or omics data-the spatial context of tumor and stromal cells at single-cell resolution. Methods to map the spatial and morphological patterns of cancer and normal cells can contribute to a more comprehensive understanding of the highly heterogeneous tumor microenvironment. This review focuses on methods that help expand our knowledge of intra-tumoral spatial heterogeneity of the tumor microenvironment and their potential synergies with molecular profiling technologies.

The abundance of tumor-infiltrating lymphocytes has been associated with a favorable prognosis in estrogen receptor-negative breast cancer. However, a high degree of spatial heterogeneity in lymphocytic infiltration is often observed and its clinical implication remains unclear. Here we combine automated histological image processing with methods of spatial statistics used in ecological data analysis to quantify spatial heterogeneity in the distribution patterns of tumor-infiltrating lymphocytes. Hematoxylin and eosin-stained sections from two cohorts of estrogen receptor-negative breast cancer patients (discovery: n = 120; validation: n = 125) were processed with our automated cell classification algorithm to identify the location of lymphocytes and cancer cells. Subsequently, hotspot analysis (Getis-Ord Gi*) was applied to identify statistically significant hotspots of cancer and immune cells, defined as tumor regions with a significantly high number of cancer cells or immune cells, respectively. We found that the amount of co-localized cancer and immune hotspots weighted by tumor area, rather than number of cancer or immune hotspots, correlates with a better prognosis in estrogen receptornegative breast cancer in univariate and multivariate analysis. Moreover, co-localization of cancer and immune hotspots further stratified patients with immune cell-rich tumors. Our study demonstrates the importance of quantifying not only the abundance of lymphocytes but also their spatial variation in the tumor specimen for which methods from other disciplines such as spatial statistics can be successfully applied.

Tumors are evolving ecosystems where cancer subclones and the microenvironment interact. This is analogous to interaction dynamics between species in their natural habitats, which is a prime area of study in ecology. Spatial statistics are frequently used in ecological studies to infer complex relations including predator-prey, resource dependency and co-evolution. Recently, the emerging field of computational pathology has enabled high-throughput spatial analysis by using image processing to identify different cell types and their locations within histological tumor samples. We discuss how these data may be analyzed with spatial statistics used in ecology to reveal patterns and advance our understanding of ecological interactions occurring among cancer cells and their microenvironment.

T e l o m e r a s e E x p r e s s i o n i n H u m a n B r e a s t C a n c e r W i t h a n d Telomerase is a ribonucleoprotein enzyme that synthesizes telomeric DNA onto the ends of chromosomes, thereby preventing the replication-dependent shortening of these ends. Telomerase activity is detected in a wide range of cancers of various tissues, and its expression may be a critical step in tumor progression. The telomeric repeat amplification protocol was used to compare telomerase activity in breast cancers with and without lymph node metastases, as well as in fibroadenomas and normal breast tissue. Expression of telomerase was detected in 22 (79%) of 28 primary breast cancers, which included 16 (73%) of 22 cancers positive and 6 (100%) of 6 cancers negative for axillary lymph node metastases. It was detected in 1 (11%) of 9 fibroadenomas but was negative in 13 normal breast tissues. There was no statistical difference in expression of telomerase between axillary node-negative primary breast cancers and similar tumors with nodal metastasis (P = .289). Further, no statistical association was found between telomerase activity and tumor size (P = .679) or hormonal status (P =.178). The difference in telomerase activity among breast cancers vs fibroadenomas and normal breast tissues, however, was statistically significant (P < .001). Although normal breast tissue does not express telomerase, both node-positive and node-negative breast cancers express telomerase. Telomerase is an essential ribonucleoprotein polymerase that a d d s telomeric DNA to the ends of eukaryotic chromosomes. 1-3 The RNA component of h u m a n telomerase, designated hTR, was recently cloned and sequenced. 4 Telomeres are specialized structures at the ends of eukaryotic chromosomes that appear to function in the protection, positioning, and replication of chromosomes. In human beings, the DNA sequence of telomeres consists of a guaninerich tandem repeat, ie, (TTAGGG) n . As normal cells divide, the replicating DNA loses a number of these repeats. Shortening of the telomere length to less than Manuscript received luly 30, 1996; revision accepted October 10,1996. W i t h o u t L y m p h N o d e M e t a s t a s e sAddress reprint requests to Dr Nawaz: Department of Pathology, B-216, University of Colorado Health Sciences Center, 4200 East Ninth Ave, Denver, CO 80262. a critical level creates a signal that stops the cell from dividing; this event is followed by cell senescence and death. Several investigators recently have shown telomerase activity in malignant tissues of various anatomic sites but not in the corresponding normal tissue; these findings suggest that this activity may be a marker for malignancy. 5Breast cancer remains the second most common cause of death in women. The most important prognostic indicator in invasive breast cancer is the presence of axillary lymph node metastases 6 ; however, molecular markers of tumor progression have failed to identify which cases of invasive breast cancer are at greatest risk for nodal metastases at t...