Review of the Tumor Microenvironment in Basal and Squamous Cell Carcinoma

An updated review of immune checkpoint inhibitors in cutaneous oncology: Beyond melanoma

Over the last decade, immune checkpoint inhibitors (ICIs) have been established as an integral component of the contemporary anticancer armamentarium. In dermatology, ICIs are most established as treatment of advanced melanoma. However, emerging evidence has demonstrated that their utility in cutaneous oncology extends to a variety of other non-melanoma malignancies. This review provides an update of the evidence from clinical trials, real world analyses, and translational research over the last three years in cutaneous malignancies beyond melanoma. Special focus is presented on areas warranting further evaluation - including populations underrepresented in or excluded from clinical trials; new and emerging treatment scenarios beyond patients with metastatic disease; novel combination approaches; and the urgent need for reliable predictive biomarkers to identify predictors of response. Collaboration between oncologists, dermatologists and dermatological surgeons is essential to progress our understanding and treatment of patients with advanced cutaneous malignancies.

Basal Cell Carcinoma Cleft: The Missing Piece of the Puzzle

BACKGROUND

This study aims to explore the tumor-stroma separation or the cleft characterizing basal cell carcinoma (BCC).

METHODOLOGY

In this retrospective cohort investigation, we enrolled 244 patients who received a confirmed diagnosis of BCC through histopathological examination in the period of 2019-2020 at the Pathology Laboratory of the "Sfântul Apostol Andrei" Emergency Clinical Hospital located in Galați, Romania. The identification of patients was accomplished by utilizing electronic health records, and relevant clinical, demographic, and histopathological data were retrieved from the physical database of the Pathology Laboratory. Key tumor characteristics were gathered, and an in-depth analysis of case slides was performed.

RESULTS

The average tumor-stroma cleft's width measurement was 48.136 µm, while its respective tumor island's width was on average 952.587 µm. The cleft's width and its respective tumor island's width are dependent on the BCC subtype, just like the ratio between the tumor island's measurement and its cleft's width are, being larger in basosquamous BCC, micronodular BCC, infiltrative BCC, and morpheaform BCC.

CONCLUSION

The BCC tumor islands were found to have a minimal approximately equal measurement to the tumor-stroma separation cleft, but they were always larger than the latter. Large clefts and their respective tumor islands were found in specific tumor subtypes such as basosquamous BCC, micronodular BCC, infiltrative BCC, and morpheaform BCC, but in nodular BCC also.

Immune Checkpoints and Cellular Landscape of the Tumor Microenvironment in Non-Melanoma Skin Cancer (NMSC)

Non-melanoma skin cancer (NMSC) is primarily categorized into basal cell carcinoma (BCC), the most prevalent form of skin cancer, and cutaneous squamous cell carcinoma (cSCC), the second most common type. Both BCC and cSCC represent a significant health burden, particularly in immunocompromised individuals and the elderly. The immune system plays a pivotal role in the development and progression of NMSC, making it a critical focus for therapeutic interventions. This review highlights key immunological targets in BCC and cSCC, with a focus on immune checkpoint molecules such as PD-1/PD-L1 and CTLA-4, which regulate T cell activity and contribute to immune evasion. This review also highlights anti-tumor immune cell subsets within the tumor microenvironment (TME), such as tumor-infiltrating lymphocytes (TILs) and dendritic cells. Additionally, it examines the immunosuppressive elements of the TME, including regulatory T cells (Tregs), myeloid-derived suppressor cells (MDSCs), tumor-associated macrophages (TAMs), and cancer-associated fibroblasts (CAFs), as well as their roles in NMSC progression and resistance to therapy. Emerging strategies targeting these immune elements, such as monoclonal antibodies, are also discussed for their potential to enhance anti-tumor immune responses and improve clinical outcomes. By elucidating the immunological landscape of BCC and cSCC and drawing comparisons to melanoma, this review highlights the transformative potential of immunotherapy in treating these malignancies.

Therapeutic Advances in Advanced Basal Cell Carcinoma

Basal cell carcinoma (BCC) is the most common type of cancer with an estimated 3.6 million cases diagnosed annually in the US alone. While most cases are treatable with low recurrence rates, 1-10% progress to an advanced stage which can behave aggressively, leading to local destruction and posing substantial challenges in management. The pathogenesis often involves dysregulation of the patched/hedgehog protein family, a pivotal pathway targeted by recently approved therapies. Furthermore, the role of immunotherapy is evolving in this type of tumor as we learn more about tumor microenvironment dynamics. In recent years, there have been advancements in the therapeutic landscape of advanced BCC, offering patients new hope and options for managing this complex and potentially life-threatening condition. In this review, we aim to provide a comprehensive overview of this disease, including the risk factors, underlying pathogenesis, current treatment options of advanced disease, and the ongoing exploration and development of novel therapies.

Basal Cell Carcinoma: Comprehensive Review with Emphasis on Scar Tissue Manifestation and Post-Vaccination Incidence

Basal cell carcinoma (BCC) arising within scar tissue is a rare but clinically significant phenomenon. This comprehensive review aims to provide a succinct overview of the current state of knowledge regarding the etiological factors, pathogenesis, clinical presentation, and management of BCC. This study constitutes a literature review pertaining to BCC, with a particular emphasis on BCC developing within scar tissue. It also provides a clinical case presentation of a patient who had developed BCC in a BCG post-vaccination scar and a review of analogous findings available in the existing literature. Despite the fact that an array of mechanisms play a role in injury-related BCC growth, the main mechanism remains ambiguous and yet to be elucidated. The review also includes a detailed description of the various therapeutic options available for BCC, ranging from surgical interventions to novel pharmacological treatments. By examining these intersections, the review seeks to elucidate the potential mechanisms, identify risk factors, and suggest considerations for clinical practice. The findings underscore the importance of vigilant dermatological assessment in patients with scar tissue and those recently vaccinated, aiming to improve early detection and optimize management strategies for BCC.

Advancements in computer vision and pathology: Unraveling the potential of artificial intelligence for precision diagnosis and beyond

The integration of computer vision into pathology through slide digitalization represents a transformative leap in the field's evolution. Traditional pathology methods, while reliable, are often time-consuming and susceptible to intra- and interobserver variability. In contrast, computer vision, empowered by artificial intelligence (AI) and machine learning (ML), promises revolutionary changes, offering consistent, reproducible, and objective results with ever-increasing speed and scalability. The applications of advanced algorithms and deep learning architectures like CNNs and U-Nets augment pathologists' diagnostic capabilities, opening new frontiers in automated image analysis. As these technologies mature and integrate into digital pathology workflows, they are poised to provide deeper insights into disease processes, quantify and standardize biomarkers, enhance patient outcomes, and automate routine tasks, reducing pathologists' workload. However, this transformative force calls for cross-disciplinary collaboration between pathologists, computer scientists, and industry innovators to drive research and development. While acknowledging its potential, this chapter addresses the limitations of AI in pathology, encompassing technical, practical, and ethical considerations during development and implementation.

Tumor-Infiltrating T Cells in Skin Basal Cell Carcinomas and Squamous Cell Carcinomas: Global Th1 Preponderance with Th17 Enrichment-A Cross-Sectional Study

Basal cell carcinomas (BCCs) and squamous cell carcinomas (SCCs) are high-incidence, non-melanoma skin cancers (NMSCs). The success of immune-targeted therapies in advanced NMSCs led us to anticipate that NMSCs harbored significant populations of tumor-infiltrating lymphocytes with potential anti-tumor activity. The main aim of this study was to characterize T cells infiltrating NMSCs. Flow cytometry and immunohistochemistry were used to assess, respectively, the proportions and densities of T cell subpopulations in BCCs (n = 118), SCCs (n = 33), and normal skin (NS, n = 30). CD8+ T cells, CD4+ T cell subsets, namely, Th1, Th2, Th17, Th9, and regulatory T cells (Tregs), CD8+ and CD4+ memory T cells, and γδ T cells were compared between NMSCs and NS samples. Remarkably, both BCCs and SCCs featured a significantly higher Th1/Th2 ratio (~four-fold) and an enrichment for Th17 cells. NMSCs also showed a significant enrichment for IFN-γ-producing CD8+T cells, and a depletion of γδ T cells. Using immunohistochemistry, NMSCs featured denser T cell infiltrates (CD4+, CD8+, and Tregs) than NS. Overall, these data favor a Th1-predominant response in BCCs and SCCs, providing support for immune-based treatments in NMSCs. Th17-mediated inflammation may play a role in the progression of NMSCs and thus become a potential therapeutic target in NMSCs.

NF-κB: Governing Macrophages in Cancer

Tumor-associated macrophages (TAMs) are the major component of the tumor microenvironment (TME), where they sustain tumor progression and or-tumor immunity. Due to their plasticity, macrophages can exhibit anti- or pro-tumor functions through the expression of different gene sets leading to distinct macrophage phenotypes: M1-like or pro-inflammatory and M2-like or anti-inflammatory. NF-κB transcription factors are central regulators of TAMs in cancers, where they often drive macrophage polarization toward an M2-like phenotype. Therefore, the NF-κB pathway is an attractive therapeutic target for cancer immunotherapy in a wide range of human tumors. Hence, targeting NF-κB pathway in the myeloid compartment is a potential clinical strategy to overcome microenvironment-induced immunosuppression and increase anti-tumor immunity. In this review, we discuss the role of NF-κB as a key driver of macrophage functions in tumors as well as the principal strategies to overcome tumor immunosuppression by targeting the NF-κB pathway.

GATA3 Positively Correlates with BCL2 Expression in Indolent and Aggressive Histological Types of Cutaneous Basal Cell Carcinoma

OBJECTIVE

Some histological basal cell carcinoma (BCC) types demonstrate more aggressive behavior than others. They are known as high-risk BCC and are more challenging in therapy, contrary to indolent (low-risk) BCC types. Identifying novel protein markers to predict aggressiveness and potential therapeutic targets in challenging cases is recommended. GATA3 is a transcription factor critical for epithelial and lymphocytic differentiation. This study investigated the immunohistochemical expression of GATA3 in indolent and aggressive BCC and its association with BCL2 expression.

MATERIAL AND METHODS

Retrospectively collected indolent and aggressive BCC groups (24 cases each) were immunohistochemically stained with anti-GATA3 and BCL2 antibodies. The mean expression score (by area percentage) and TIL counts were determined and compared using ImageJ analysis. Stromal tumor-infiltrating lymphocytes (TIL) were counted per high-power field (HPF) on hematoxylin and eosin (H&E) staining.

RESULTS

GATA3 and BCL2 expressions were significantly higher in the indolent group than in the aggressive group. GATA3 expression significantly correlated with BCL2 score and TIL counts. Higher GATA3 expression was significantly associated with a more indolent BCC histological type, higher BCL2 expression, and higher TIL count.

CONCLUSION

GATA3 is a possible target for immunomodulation experiments to improve BCC immunotherapy outcomes.

Differentiation and risk stratification of basal cell carcinoma with deep learning on histopathologic images and measuring nuclei and tumor microenvironment features

BACKGROUND

Nuclear pleomorphism and tumor microenvironment (TME) play a critical role in cancer development and progression. Identifying most predictive nuclei and TME features of basal cell carcinoma (BCC) may provide insights into which characteristics pathologists can use to distinguish and stratify this entity.

OBJECTIVES

To develop an automated workflow based on nuclei and TME features from basaloid cell tumor regions to differentiate BCC from trichoepithelioma (TE) and stratify BCC into high-risk (HR) and low-risk (LR) subtypes, and to identify the nuclear and TME characteristics profile of different basaloid cell tumors.

METHODS

The deep learning systems were trained on 161 H&E -stained sections which contained 51 sections of HR-BCC, 50 sections of LR-BCC and 60 sections of TE from one institution (D1), and externally and independently validated on D2 (46 sections) and D3 (76 sections), from 2015 to 2022. 60%, 20% and 20% of D1 data were randomly splitted for training, validation and testing, respectively. The framework comprised four stages: tumor regions identification by multi-head self-attention (MSA) U-Net, nuclei segmentation by HoVer-Net, quantitative feature by handcrafted extraction, and differentiation and risk stratification classifier construction. Pixel accuracy, precision, recall, dice score, intersection over union (IoU) and area under the curve (AUC) were used to evaluate the performance of tumor segmentation model and classifiers.

RESULTS

MSA-U-Net model detected tumor regions with 0.910 precision, 0.869 recall, 0.889 dice score and 0.800 IoU. The differentiation classifier achieved 0.977 ± 0.0159, 0.955 ± 0.0181, 0.885 ± 0.0237 AUC in D1, D2 and D3, respectively. The most discriminative features between BCC and TE contained Homogeneity, Elongation, T-T_meanEdgeLength, T-T_Nsubgraph, S-T_HarmonicCentrality, S-S_Degrees. The risk stratification model can well predict HR-BCC and LR-BCC with 0.920 ± 0.0579, 0.839 ± 0.0176, 0.825 ± 0.0153 AUC in D1, D2 and D3, respectively. The most discriminative features between HR-BCC and LR-BCC comprised IntensityMin, Solidity, T-T_minEdgeLength, T-T_Coreness, T-T_Degrees, T-T_Betweenness, S-T_Degrees.

CONCLUSIONS

This framework hold potential for future use as a second opinion helping inform diagnosis of BCC, and identify nuclei and TME features related with malignancy and tumor risk stratification.