Publicly available datasets of breast histopathology H&E whole-slide images: A scoping review.

Advancements in digital pathology and computing resources have made a significant impact in the field of computational pathology for breast cancer diagnosis and treatment. However, access to high-quality labeled histopathological images of breast cancer is a big challenge that limits the development of accurate and robust deep learning models. In this scoping review, we identified the publicly available datasets of breast H&E-stained whole-slide images (WSIs) that can be used to develop deep learning algorithms. We systematically searched 9 scientific literature databases and 9 research data repositories and found 17 publicly available datasets containing 10 385 H&E WSIs of breast cancer. Moreover, we reported image metadata and characteristics for each dataset to assist researchers in selecting proper datasets for specific tasks in breast cancer computational pathology. In addition, we compiled 2 lists of breast H&E patches and private datasets as supplementary resources for researchers. Notably, only 28% of the included articles utilized multiple datasets, and only 14% used an external validation set, suggesting that the performance of other developed models may be susceptible to overestimation. The TCGA-BRCA was used in 52% of the selected studies. This dataset has a considerable selection bias that can impact the robustness and generalizability of the trained algorithms. There is also a lack of consistent metadata reporting of breast WSI datasets that can be an issue in developing accurate deep learning models, indicating the necessity of establishing explicit guidelines for documenting breast WSI dataset characteristics and metadata.

High Expression of IRS-1, RUNX3 and SMAD4 Are Positive Prognostic Factors in Stage I-III Colon Cancer.

Colon cancer is a common malignancy and a major contributor to human morbidity and mortality. In this study, we explore the expression and prognostic impact of IRS-1, IRS-2, RUNx3, and SMAD4 in colon cancer. Furthermore, we elucidate their correlations with miRs 126, 17-5p, and 20a-5p, which are identified as potential regulators of these proteins. Tumor tissue from 452 patients operated for stage I-III colon cancer was retrospectively collected and assembled into tissue microarrays. Biomarkers' expressions were examined by immunohistochemistry and analyzed using digital pathology. In univariate analyses, high expression levels of IRS1 in stromal cytoplasm, RUNX3 in tumor (nucleus and cytoplasm) and stroma (nucleus and cytoplasm), and SMAD4 in tumor (nucleus and cytoplasm) and stromal cytoplasm were related to increased disease-specific survival (DSS). In multivariate analyses, high expression of IRS1 in stromal cytoplasm, RUNX3 in tumor nucleus and stromal cytoplasm, and high expression of SMAD4 in tumor and stromal cytoplasm remained independent predictors of improved DSS. Surprisingly, with the exception of weak correlations (0.2 < r < 0.25) between miR-126 and SMAD4, the investigated markers were mostly uncorrelated with the miRs. However, weak to moderate/strong correlations (0.3 < r < 0.6) were observed between CD3 and CD8 positive lymphocyte density and stromal RUNX3 expression. High expression levels of IRS1, RUNX3, and SMAD4 are positive prognostic factors in stage I-III colon cancer. Furthermore, stromal expression of RUNX3 is associated with increased lymphocyte density, suggesting that RUNX3 is an important mediator during recruitment and activation of immune cells in colon cancer.

Cohort profile: The Clinical and Multi-omic (CAMO) cohort, part of the Norwegian Women and Cancer (NOWAC) study.

INTRODUCTION: Breast cancer is the most common cancer worldwide and the leading cause of cancer related deaths among women. The high incidence and mortality of breast cancer calls for improved prevention, diagnostics, and treatment, including identification of new prognostic and predictive biomarkers for use in precision medicine. MATERIAL AND METHODS: With the aim of compiling a cohort amenable to integrative study designs, we collected detailed epidemiological and clinical data, blood samples, and tumor tissue from a subset of participants from the prospective, population-based Norwegian Women and Cancer (NOWAC) study. These study participants were diagnosed with invasive breast cancer in North Norway before 2013 according to the Cancer Registry of Norway and constitute the Clinical and Multi-omic (CAMO) cohort. Prospectively collected questionnaire data on lifestyle and reproductive factors and blood samples were extracted from the NOWAC study, clinical and histopathological data were manually curated from medical records, and archived tumor tissue collected. RESULTS: The lifestyle and reproductive characteristics of the study participants in the CAMO cohort (n = 388) were largely similar to those of the breast cancer patients in NOWAC (n = 10 356). The majority of the cancers in the CAMO cohort were tumor grade 2 and of the luminal A subtype. Approx. 80% were estrogen receptor positive, 13% were HER2 positive, and 12% were triple negative breast cancers. Lymph node metastases were present in 31% at diagnosis. The epidemiological dataset in the CAMO cohort is complemented by mRNA, miRNA, and metabolomics analyses in plasma, as well as miRNA profiling in tumor tissue. Additionally, histological analyses at the level of proteins and miRNAs in tumor tissue are currently ongoing. CONCLUSION: The CAMO cohort provides data suitable for epidemiological, clinical, molecular, and multi-omics investigations, thereby enabling a systems epidemiology approach to translational breast cancer research.

A Pragmatic Machine Learning Approach to Quantify Tumor-Infiltrating Lymphocytes in Whole Slide Images.

Increased levels of tumor-infiltrating lymphocytes (TILs) indicate favorable outcomes in many types of cancer. The manual quantification of immune cells is inaccurate and time-consuming for pathologists. Our aim is to leverage a computational solution to automatically quantify TILs in standard diagnostic hematoxylin and eosin-stained sections (H&E slides) from lung cancer patients. Our approach is to transfer an open-source machine learning method for the segmentation and classification of nuclei in H&E slides trained on public data to TIL quantification without manual labeling of the data. Our results show that the resulting TIL quantification correlates to the patient prognosis and compares favorably to the current state-of-the-art method for immune cell detection in non-small cell lung cancer (current standard CD8 cells in DAB-stained TMAs HR 0.34, 95% CI 0.17-0.68 vs. TILs in HE WSIs: HoVer-Net PanNuke Aug Model HR 0.30, 95% CI 0.15-0.60 and HoVer-Net MoNuSAC Aug model HR 0.27, 95% CI 0.14-0.53). Our approach bridges the gap between machine learning research, translational clinical research and clinical implementation. However, further validation is warranted before implementation in a clinical setting.

High expression of miR-17-5p and miR-20a-5p predicts favorable disease-specific survival in stage I-III colon cancer.

In many types of cancer, microRNAs (miRs) are aberrantly expressed. The aim of this study was to explore the prognostic impact of miR-17-5p and miR-20a-5p in colon cancer. Tumor tissue from 452 stage I-III colon cancer patients was retrospectively collected and tissue microarrays constructed. miR-17-5p and miR-20a-5p expression was evaluated by in situ hybridization and analyzed using digital pathology. Cell line experiments, using HT-29 and CACO-2, were performed to assess the effect of miR-17-5p and miR-20a-5p over expression on viability, invasion and migration. In multivariate analyses, high miR-17-5p expression in tumor (HR = 0.43, CI 0.26-0.71, p < 0.001) and high expression of miR-20a-5p in tumor (HR = 0.60, CI 0.37-0.97, p = 0.037) and stroma (HR = 0.63, CI 0.42-0.95, p = 0.027) remained independent predictors of improved disease-specific survival. In cell lines, over expression of both miRs resulted in mitigated migration without any significant effect on viability or invasion. In conclusion, in stage I-III colon cancer, high expression of both miR-17-5p and miR-20a-5p are independent predictors of favorable prognosis.

The blood transcriptome prior to ovarian cancer diagnosis: A case-control study in the NOWAC postgenome cohort.

Epithelial ovarian cancer (EOC) has a 5-year relative survival of 50%, partly because markers of early-stage disease are not available in current clinical diagnostics. The aim of the present study was to investigate whether EOC is associated with transcriptional profiles in blood collected up to 7 years before diagnosis. For this, we used RNA-stabilized whole blood, which contains circulating immune cells, from a sample of EOC cases from the population-based Norwegian Women and Cancer (NOWAC) postgenome cohort. We explored case-control differences in gene expression in all EOC (66 case-control pairs), as well as associations between gene expression and metastatic EOC (56 pairs), serous EOC (45 pairs, 44 of which were metastatic), and interval from blood sample collection to diagnosis (≤3 or >3 years; 34 and 31 pairs, respectively). Lastly, we assessed differential expression of genes associated with EOC in published functional genomics studies that used blood samples collected from newly diagnosed women. After adjustment for multiple testing, this nested case-control study revealed no significant case-control differences in gene expression in all EOC (false discovery rate q>0.96). With the exception of a few probes, the log2 fold change values obtained in gene-wise linear models were below ±0.2. P-values were lowest in analyses of metastatic EOC (80% of which were serous EOC). No common transcriptional profile was indicated by interval to diagnosis; when comparing the 100 genes with the lowest p-values in gene-wise tests in samples collected ≤3 and >3 years before EOC diagnosis, no overlap in these genes was observed. Among 86 genes linked to ovarian cancer in previous publications, our data contained expression values for 42, and of these, tests of LIME1, GPR162, STAB1, and SKAP1, resulted in unadjusted p<0.05. Although limited by sample size, our findings indicated less variation in blood gene expression between women with similar tumor characteristics.

High expression of microRNA-126 relates to favorable prognosis for colon cancer patients.

miR-126 has been identified both as a tumor suppressor and an oncogene in different types of cancer. The aim of this study was to investigate the prognostic impact of miR-126-expression in colon cancer patients. Tumor tissue from 452 patients operated for stage I-III colon cancer was retrospectively collected and tissue microarrays were constructed. miR-126 expression was evaluated by in situ hybridization and analyzed using digital pathology. To isolate the compartment specific contribution of miR-126, tumor and adjacent tumor stroma were considered separately. In univariate analyses, high expression of miR-126 in tumor and stroma was related to increased disease-specific survival (p < 0.001 and p = 0.005, respectively). In multivariate analyses, high miR-126 expression in tumor remained a significant independent predictor of improved disease-specific survival (HR = 0.42, CI 0.23-0.75, p = 0.004). Within different TNM-stages there was a tendency towards the same results, but with statistically significant results in stage II only (p = 0.007). High expression of miR-126 is an independent positive prognostic factor in stage I-III colon cancer. This finding may be used to identify patients in need of adjuvant chemotherapy.

Tertiary lymphoid structure score: a promising approach to refine the TNM staging in resected non-small cell lung cancer.

BACKGROUND: We previously proposed an immune cell score (tumour node metastasis (TNM)-Immune cell score) classifier as an add-on to the existing TNM staging system for non-small cell lung cancer (NSCLC). Herein, we examined how to reliably assess a tertiary lymphoid structure (TLS) score to refine the TNM staging system. METHODS: Using immunohistochemistry (CD8/cytokeratin), we quantified TLS in resected NSCLC whole-tumour tissue sections with three different scoring models on two independent collections (total of 553 patients). In a pilot setting, NanoString gene expression signatures were analysed for associations with TLS. RESULTS: The number of TLSs significantly decreased in stage III patients as compared to stage II. The TLS score was an independent positive prognostic factor, regardless of the type of (semi)-quantification strategy used (four-scale semi-quantitative; absolute count of total TLS; subpopulation of mature TLS) or the endpoint (disease-specific survival; overall survival; time to recurrence). Subgroup analyses revealed a significant prognostic impact of TLS score within each pathological stage, patient cohort and main histological subtype. Targeted gene expression analysis showed that high TLS levels were associated with the expression of B cell and adaptive immunity genes/metagenes including tumour inflammation signature. CONCLUSIONS: The TLS score increases the prognostic power in each pathological stage and hence has the potential to refine TNM staging in resected NSCLC.

Digitally quantified CD8+ cells: the best candidate marker for an immune cell score in non-small cell lung cancer?

The TNM classification is well established as a state-of-the-art prognostic and treatment-decision-making tool for non-small cell lung cancer (NSCLC) patients. However, incorporation of biological data may hone the TNM system. This article focuses on choosing and incorporating subsets of tissue-infiltrating lymphocyte (TIL), detected by specific immunohistochemistry and automatically quantified by open source software, into a TNM-Immune cell score (TNM-I) for NSCLC. We use common markers (CD3, CD4, CD8, CD20 and CD45RO) of TILs to identify TIL subsets in tissue micro-arrays comprising tumor tissue from 553 patients resected for primary NSCLC. The number of TILs is automatically quantified using open source software (QuPath). Their prognostic efficacy, alone and within a TNM-I model, is evaluated in all patients and histological subgroups. Compared with previous manual semi-quantitative scoring of TILs in the same cohort, the present digital quantification proved superior. As a proof-of-concept, we construct a TNM-I, using TNM categories and the CD8+ TIL density. The TNM-I is an independent prognosticator of favorable diagnosis in both the overall cohort and in the main histological subgroups. In conclusion, CD8+ TIL density is the most promising candidate marker for a TNM-I in NSCLC. The prognostic efficacy of the CD8+ TIL density is strongest in lung squamous cell carcinomas, whereas both CD8+ TILs and CD20+ TILs, or a combination of these, may be candidates for a TNM-I in lung adenocarcinoma. Furthermore, based on the presented results, digital quantification is the preferred method for scoring TILs in the future.

Differential expression of the miR-17-92 cluster and miR-17 family in breast cancer according to tumor type; results from the Norwegian Women and Cancer (NOWAC) study.

BACKGROUND: MicroRNAs (miRNAs) are promising biomarkers due to their structural stability and distinct expression profile in various cancers. We wanted to explore the miRNA expression in benign breast tissue and breast cancer subgroups in the Norwegian Women and Cancer study. METHODS: Specimens and histopathological data from study participants in Northern Norway diagnosed with breast cancer, and benign tissue from breast reduction surgery were collected. Main molecular subtypes were based on surrogate markers; luminal A (ER+ and/or PR+, HER2- and Ki67 ≤ 30%), luminal B (ER+ and/or PR+, HER2- and Ki67 > 30% or ER+ and/or PR+ and HER2+), HER2 positive (ER- and PR- and HER2+) and triple-negative (ER-, PR- and HER2-). RNA was extracted from formalin-fixed paraffin-embedded (FFPE) tissue, and miRNAs were successfully analyzed in 102 cancers and 36 benign controls using the 7th generation miRCURY LNA microarray containing probes targeting all human miRNAs as annotated in miRBASE version 19.0. Validation with RT-qPCR was performed. RESULTS: On average, 450 miRNAs were detected in each sample, and 304 miRNAs were significantly different between malignant and benign tissue. Subgroup analyses of cancer cases revealed 23 miRNAs significantly different between ER+ and ER- tumors, and 47 miRNAs different between tumors stratified according to grade. Significantly higher levels were found in high grade tumors for miR-17-5p (p = 0.006), miR-20a-5p (p = 0.007), miR-106b-5p (p = 0.007), miR-93-5p (p = 0.007) and miR-25-3p (p = 0.015) from the paralogous clusters miR-17-92 and miR-106b-25. Expression of miR-17-5p (p = 0.0029), miR-20a-5p (p = 0.0021), miR-92a-3p (p = 0.011) and miR-106b-5p (p = 0.021) was significantly higher in triple-negative tumors compared to the rest, and miR-17-5p and miR-20a-5p were significantly lower in luminal A tumors. CONCLUSIONS: miRNA expression profiles were significantly different between malignant and benign tissue and between cancer subgroups according to ER- status, grade and molecular subtype. miRNAs in the miR-17-92 cluster and miR-17 family were overexpressed in high grade and triple-negative tumors associated with aggressive behavior. The expression and functional role of these miRNAs should be further studied in breast cancer to explore their potential as biomarkers in diagnostic pathology and clinical oncology.

Differential prognostic impact of platelet-derived growth factor receptor expression in NSCLC.

Preclinical evidence suggests that stromal expression of platelet-derived growth factor receptors (PDGFRs) stimulates tumor development and diminishes intratumoral drug uptake. In non-small cell lung cancer (NSCLC), the clinical relevance of stromal PDGFR expression remains uncertain. Tumor specimens from 553 patients with primary operable stage I-IIIB NSCLC was obtained and tissue micro-arrays (TMA) were constructed (Norwegian cohort). Immunohistochemistry (IHC) was used to evaluate the expression of PDGFRα and -ß in stromal cells and to explore their impact on patient survival. Results were validated in a non-related cohort consisting of TMAs of 367 stage I (A and B) NSCLC patients (Swedish cohort). High stromal PDGFRα expression was an independent predictor of increased survival in the overall populations and SCC (squamous cell carcinoma) subgroups of both investigated cohorts. PDGFRß was an independent predictor of poor survival in the overall Norwegian cohort and an independent predictor of increased survival in the ADC (adenocarcinoma) subgroup of the Swedish cohort. Tumors displaying the combination PDGFRα-low/PDGFRß-high exhibited inferior survival according to increasing stage in the Norwegian cohort. This study confirms that high stromal expression of PDGFRα is a predictor of increased survival in NSCLC. Further exploration of the prognostic impact of PDGFRß and the relationship between PDGFRα and -ß is warranted.

Prognostic Value of Macrophage Phenotypes in Resectable Non-Small Cell Lung Cancer Assessed by Multiplex Immunohistochemistry.

Macrophages are important inflammatory cells that regulate innate and adaptive immunity in cancer. Tumor-associated macrophages (TAMs) are thought to differentiate into two main phenotypes: proinflammatory M1 and protumorigenic M2. Currently, the prognostic impact of TAMs and their M1 and M2 phenotypes is unclear in non-small cell cancer (NSCLC). The present study was set up to evaluate an approach for identifying common M1 and M2 macrophage markers and explore their clinical significance in NSCLC. Using multiplex chromogenic immunohistochemistry, tissue microarrays of 553 primary tumors and 143 paired metastatic lymph nodes of NSCLC specimens were stained to detect various putative macrophage phenotypes: M1 (HLA-DR/CD68), M2 (CD163/CD68), M2 (CD204/CD68), and pan-macrophage (CD68/CK). Correlation analyses were performed to examine the relationship between TAMs and adaptive/innate immune infiltrates. HLA-DR+/CD68+M1 TAM level significantly decreased from pathological stage I to III. In a compartment-specific correlation analysis, moderate to strong correlations were observed between both TAM subsets (M1 and M2) with CD3-, CD8-, CD4-, and CD45RO-positive immune cells. Survival analyses, in both stromal and intratumoral compartments, revealed that high levels of HLA-DR+/CD68+M1 (stroma, hazard ratio [HR] = 0.73, P = .03; intratumor, HR = 0.7, P = .04), CD204+M2 (stroma, HR = 0.7, P = .02; intratumor, HR = 0.6, P = .004), and CD68 (stroma, HR = 0.69, P = .02; intratumor, HR = 0.73, P = .04) infiltration were independently associated with improved NSCLC-specific survival. In lymph nodes, the intratumoral level of HLA-DR+/CD68+M1 was an independent positive prognostic indicator (Cox model, HR = 0.38, P = .001). In conclusion, high levels of M1, CD204+M2, and CD68 macrophages are independent prognosticators of prolonged survival in NSCLC.