Interferon-γ (IFN-γ) plays a key role in activation of cellular immunity and subsequently, stimulation of antitumor immune-response. Based on its cytostatic, pro-apoptotic and antiproliferative functions, IFN-γ is considered potentially useful for adjuvant immunotherapy for different types of cancer. Moreover, it IFN-γ may inhibit angiogenesis in tumor tissue, induce regulatory T-cell apoptosis, and/or stimulate the activity of M1 proinflammatory macrophages to overcome tumor progression. However, the current understanding of the roles of IFN-γ in the tumor microenvironment (TME) may be misleading in terms of its clinical application. Some researchers believe it has anti-tumorigenic properties, while others suggest that it contributes to tumor growth and progression. In our recent work, we have shown that concentration of IFN-γ in the TME determines its function. Further, it was reported that tumors treated with low-dose IFN-γ acquired metastatic properties while those infused with high dose led to tumor regression. Pro-tumorigenic role may be described through IFN-γ signaling insensitivity, downregulation of major histocompatibility complexes, upregulation of indoleamine 2,3-dioxygenase, and checkpoint inhibitors such as programmed cell death ligand 1. Significant research efforts are required to decipher IFN-γ-dependent pro- and anti-tumorigenic effects. This review discusses the current knowledge concerning the roles of IFN-γ in the TME as a part of the complex immune response to cancer and highlights the importance of identifying IFN-γ responsive patients to improve their sensitivity to immuno-therapies.

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Roles of IFN-γ in tumor progression and regression: a review.

Tumor-associated macrophages (TAMs) as immune cells within the tumor microenvironment have gained much interests as basic science regarding their roles in tumor progression unfolds. Better understanding of their polarization into pro-tumoral phenotype to promote tumor growth, tumor angiogenesis, immune evasion, and tumor metastasis has prompted various studies to investigate their clinical significance as a biomarker of predictive and prognostic value across different cancer types. Yet, the methodologies to investigate the polarization phenomena in solid tumor tissue vary. Nonetheless, quantifying the ratio of M1 to M2 TAMs has emerged to be a prevailing parameter to evaluate this polarization phenomena for clinical application. This mini-review focuses on recent studies exploring clinical significance of M1/M2 TAM ratio in human cancer tissue and critically evaluates the technicalities and challenges in quantifying this parameter for routine clinical practice. Immunohistochemistry appears to be the preferred methodology for M1/M2 TAM evaluation as it is readily available in clinical laboratories, albeit with certain limitations. Recommendations are made to standardize the quantification of TAMs for better transition into clinical practice and for better comparison among studies in various populations of patients and cancer types.

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Evaluating the Polarization of Tumor-Associated Macrophages Into M1 and M2 Phenotypes in Human Cancer Tissue: Technicalities and Challenges in Routine Clinical Practice

Breast cancer (BC) is the most frequently diagnosed cancer in women worldwide with more than 2 million new cases in 2020. Its incidence and death rates have increased over the last three decades due to the change in risk factor profiles, better cancer registration, and cancer detection. The number of risk factors of BC is significant and includes both the modifiable factors and non-modifiable factors. Currently, about 80% of patients with BC are individuals aged >50. Survival depends on both stage and molecular subtype. Invasive BCs comprise wide spectrum tumors that show a variation concerning their clinical presentation, behavior, and morphology. Based on mRNA gene expression levels, BC can be divided into molecular subtypes (Luminal A, Luminal B, HER2-enriched, and basal-like). The molecular subtypes provide insights into new treatment strategies and patient stratifications that impact the management of BC patients. The eighth edition of TNM classification outlines a new staging system for BC that, in addition to anatomical features, acknowledges biological factors. Treatment of breast cancer is complex and involves a combination of different modalities including surgery, radiotherapy, chemotherapy, hormonal therapy, or biological therapies delivered in diverse sequences.

Breast Cancer—Epidemiology, Risk Factors, Classification, Prognostic Markers, and Current Treatment Strategies—An Updated Review

Oral squamous cell carcinoma (OSCC) is the most common type of head and neck (H&N) cancers with an increasing worldwide incidence and a worsening prognosis. The abundance of tumour infiltrating lymphocytes (TILs) has been shown to be a key prognostic indicator in a range of cancers with emerging evidence of its role in OSCC progression and treatment response. However, the current methods of TIL analysis are subjective and open to variability in interpretation. An automated method for quantification of TIL abundance has the potential to facilitate better stratification and prognostication of oral cancer patients. We propose a novel method for objective quantification of TIL abundance in OSCC histology images. The proposed TIL abundance (TILAb) score is calculated by first segmenting the whole slide images (WSIs) into underlying tissue types (tumour, lymphocytes, etc.) and then quantifying the co-localization of lymphocytes and tumour areas in a novel fashion. We investigate the prognostic significance of TILAb score on digitized WSIs of Hematoxylin and Eosin (H&E) stained slides of OSCC patients. Our deep learning based tissue segmentation achieves high accuracy of 96.31%, which paves the way for reliable downstream analysis. We show that the TILAb score is a strong prognostic indicator (p = 0.0006) of disease free survival (DFS) on our OSCC test cohort. The automated TILAb score has a significantly higher prognostic value than the manual TIL score (p = 0.0024). In summary, the proposed TILAb score is a digital biomarker which is based on more accurate classification of tumour and lymphocytic regions, is motivated by the biological definition of TILs as tumour infiltrating lymphocytes, with the added advantages of objective and reproducible quantification.

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A Novel Digital Score for Abundance of Tumour Infiltrating Lymphocytes Predicts Disease Free Survival in Oral Squamous Cell Carcinoma.

Survival improves when cancer is detected early. However, ~50% of cancers are at an advanced stage when diagnosed. Early detection of cancer or precancerous change allows early intervention to try to slow or prevent cancer development and lethality. To achieve early detection of all cancers, numerous challenges must be overcome. It is vital to better understand who is at greatest risk of developing cancer. We also need to elucidate the biology and trajectory of precancer and early cancer to identify consequential disease that requires intervention. Insights must be translated into sensitive and specific early detection technologies and be appropriately evaluated to support practical clinical implementation. Interdisciplinary collaboration is key; advances in technology and biological understanding highlight that it is time to accelerate early detection research and transform cancer survival. Description Detecting cancer early Many types of cancer are detected at an advanced stage, when treatment options are limited and prognosis is poor. Being able to detect cancers early can substantially improve survival, but this approach comes with challenges, including the possibility of overdiagnosis and overtreatment, which can harm people who would not have developed overt malignancy. In a Review, Crosby et al. discuss the importance of cancer early detection and the main challenges that need to be overcome to better understand the early events in tumorigenesis that are detectable in screening tests. The results of these tests can then be reliably interpreted to determine whether an individual requires treatment. —GKA A review discusses approaches to enable early detection of cancer and allow earlier intervention and increase survival. BACKGROUND When cancer is detected at the earliest stages, treatment is more effective and survival drastically improves. Yet ~50% of cancers are still only detected at an advanced stage. Improved earlier detection of cancer could substantially increase survival rates. Although recent advances in early detection have saved lives, further innovations and development of early cancer detection approaches are needed. The field is evolving rapidly, owing to advances in biological understanding and an increasing pace of technological progress. ADVANCES We highlight five challenges facing the field, current work in those areas, and where more research is needed to make early detection a reality. The first challenge is to build a greater understanding of the biology and behavior of early disease. This will help identify ways to distinguish between consequential, aggressive lesions and inconsequential lesions that will not cause harm. Such insight will be crucial to realizing the potential for early detection to inform treatment decisions and improve survival, while minimizing the risk of overtreatment. Alongside studies in human samples, better models of disease are enabling identification of early signals of tumorigenesis and clarifying the contributions of the immune system and microenvironment to tumor development. The second challenge is determining the risk of developing cancer. How can we use germline genomic susceptibility, family history, exposures, demographic, and behavioral data to build nuanced risk models to identify who should be tested for cancer and how test results should be interpreted and followed up? Progress is being made to address this challenge through improved understanding of the genomics of cancer risk, integration of that insight with other risk factors, and the development of large-scale population cohorts where risk models can be developed and validated. The third challenge is finding and validating biomarkers of early cancer. There is considerable difficulty in finding accurate signals of early cancer (which usually exist in very small amounts) amid the noise of normal human physiology. Although progress has historically been slow, many promising early detection markers are emerging, including circulating tumor DNA, circulating tumor cells, proteins, exosomes, and cancer metabolites. Advances in data analysis methodologies (such as machine learning) and integration across marker types in multimodal tests are also accelerating progress. The fourth challenge is technological. It involves both the iterative improvement of existing approaches and the development of disruptive detection technologies that can very sensitively and specifically identify early biological changes, whether in tissue structure, biochemistry, or function. Powerful molecular analytical technologies and advanced imaging and histopathological methods are increasing the ability to sensitively find earlier tumors, while the use of synthetic markers may help to amplify their signal. The fifth challenge is how to appropriately evaluate early detection approaches. Translation of biological insights into new diagnostic technologies and execution of clinical trials to validate those advances require substantial time and money. We discuss ways in which that process might be improved. OUTLOOK For early detection to deliver transformative progress in cancer survival, wider skill sets beyond cancer biology are essential, including engineers, chemists, physicists, technology developers, and behavioral and computer scientists. Integrated, interdisciplinary collaboration is key to bringing new ideas to address the challenges of early cancer detection. We believe that early detection of cancer is approaching a tipping point, as biological insight and technological capacity are increasing at an unprecedented rate and as public and private funders of research are increasingly willing to invest. This Review discusses the current state of the field and suggests constructive ways forward that build on current progress to deliver effective earlier detection of cancer and appropriate intervention. The early detection of cancer—challenges and ways forward. This figure summarizes challenges that impede the early detection of cancer and the areas of current research that are helping to overcome them.

Early detection of cancer

Disease outcomes of HER2+ breast cancers have dramatically improved after targeted therapies, such as trastuzumab became available. The main mechanism of action of trastuzumab depends on immunoactivation, while immunosuppressive tumour phenotype has been linked to adverse outcomes. Current study included metastatic HER2+ breast cancer patients treated with trastuzumab (n = 40). Immunohistochemistry was conducted to detect nitric oxide synthase 2 (iNOS) expressing M1 polarized and CD163+ M2 polarized macrophages, FoxP3+ regulatory T-cells (Tregs), CD47 and indoleamine 2,3-dioxygenase 1 (IDO1). High number of iNOS+ M1-like macrophages, both in the center of the tumour (CT) and invasive margin (IM), was significantly associated with improved survival (p = 0.009) while high expression of IDO1 or CD47 in the malignant cells was associated with worsened prognosis (p = 0.018, p = 0.046). High number of CD163+ M2-like macrophages in the CT, but not in the IM, and high number of FoxP3+ Tregs in both locations showed non-significant tendencies towards poor prognosis. Moreover, high number of iNOS+ M1-like macrophages combined with high number of CD8+ T-cells in the CT was significantly associated with improved survival (p = 0.0003), and this combined marker predicted patient’s ability to remain progression-free without trastuzumab after responding to the therapy (p = 0.003). Current study highlights the role of M1 polarized macrophages alone and in combination with CD8+ cells in HER2+ breast cancer.

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Prognostic and predictive role of tumour-associated macrophages in HER2 positive breast cancer.

Disease outcomes of HER2+ breast cancers have dramatically changed after targeted therapies, such as trastuzumab, came to clinical practice but predictive factors for trastuzumab sensitivity and resistance are frequently unknown. Current work included metastatic breast cancer patients (n = 48), who were treated with trastuzumab and had pre-treatment tumour samples available. The tumours were immunostained for T-cell (CD3, CD8), natural killer (NK)-cell (CD56) and macrophage (CD68) markers and quantitative analysis of the immune cells was carried out using a computer-assisted image analysis in different tumour locations. High number of CD3 and CD8 positive T-cells was associated with significant survival benefit in the center of the tumour (CT) (p = 0.007, p = 0.001) but not in the invasive margin. The number of NK-cells and macrophages in the CT showed non-significant tendency towards improved survival. In subgroup analyses, high density of CD8 CT cells was associated with significant survival benefit in non-bone only disease, in TX or T1-3, and in ER+ tumours (p = 0.006, p = 0.003, p = 0.001). Moreover, high CD8 CT cell density associated significantly with long trastuzumab interruption periods in response. The results suggest important prognostic and predictive role of tumour infiltrating lymphocytes in center of the tumours in metastatic HER2+ breast cancer.

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Prognostic and predictive role of spatially positioned tumour infiltrating lymphocytes in metastatic HER2 positive breast cancer treated with trastuzumab.

We have previously shown that cancer stem-like cells (CSLCs) can mediate therapy resistance in ALK translocated lung cancers. HER2 has been linked to CSLCs in breast cancers and, therefore, we wanted to assess whether HER2 has a role in CSLCs in ALK translocated cancers. ALK translocated cell lines, H3122 and H2228, with variable sensitivity to ALK inhibition were used in the study. HER2 overexpression or knockdown was induced by retro- or lentiviral infections and cells were treated with pharmacological agents targeting HER2 and ALK signaling. Furthermore, tumorigenic properties of the cells were assessed in vitro using colony and sphere formation assays. In the ALK inhibitor sensitive H3122 cells, HER2 overexpression unaltered the primary response to ALK inhibition, but increased CSLC marker expression and enhanced colony and sphere formation and late AKT and ERK1/2 signaling recovery. In the ALK inhibitor semi-sensitive H2228 cells, HER2 knockdown reduced basal expression of CSLC markers, modestly increased sensitivity to ALK inhibition in colony and sphere formation assays, and reduced late AKT and ERK1/2 signaling recovery. In addition, HER2 induced cross activation of other ErbB-members of which HER3 followed most closely the CSLC marker expression and neuregulin-1, a HER3 ligand, or pan-ErbB inhibitor afatinib, were able to alter CSLC marker expression and colony formation. the present study suggests that HER2 has an important role in the regulation of the CSLC phenotype in ALK translocated lung cancers that is mainly orchestrated by HER2/HER3 heterodimers.

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Tiia J. Honkanen

Papers

Prognostic and predictive role of tumour-associated macrophages in HER2 positive breast cancer.

Prognostic and predictive role of spatially positioned tumour infiltrating lymphocytes in metastatic HER2 positive breast cancer treated with trastuzumab.

HER2 regulates cancer stem-like cell phenotype in ALK translocated NSCLC