Onco

Background: There are approximately 5.4 M basal cell (BCC) and squamous cell (SCC) carcinomas diagnosed each year, and the number is increasing. Currently, the gold standard for skin cancer diagnosis is histopathology, which requires the surgical excision of the tumor followed by pathological evaluation of a tissue biopsy. The three-dimensional (3D) nature of human tissue suggests that two-dimensional (2D) cross sections may be insufficient in some cases to represent the complex structure due to sampling bias. There is a need for new techniques that can be used to classify skin lesion types and margins noninvasively. Methods: We use optical coherence tomography volume scan images and AI to noninvasively create 3D images of basal cell and squamous cell carcinomas. Results: Three-dimensional optical coherence tomography images can be broken down into a series of cross sections that can be classified as benign or cancerous using convolutional neural network models developed in this study. These models can identify cancerous regions as well as clear edges. Cancerous regions can also be verified based on visual review of the color-coded images and the loss of the green and blue subchannel pixel intensities. Conclusions: Three-dimensional optical coherence tomography cross sections of cancerous lesions can be collected noninvasively, and AI can be used to classify skin lesions and detect clear lesion edges. These images may provide a means to speed up treatment and promote better patient screening, especially in older patients who will likely develop several lesions as they age.

The tumor microenvironment (TME) plays an important role in the development, progression, and treatment response of pediatric cancers, yet remains less elucidated compared to adult malignancies. Pediatric tumors are unique with a low mutational burden, an immature immune landscape, and unique stromal interactions. The resultant “cold” immune microenvironments limits the effectiveness of conventional immunotherapies. This review summarizes the key cellular and non-cellular components of the pediatric TME—including T cells, NK cells, tumor-associated macrophages, cancer-associated fibroblasts, extracellular matrix remodeling, angiogenesis, and hypoxia—and describes how these elements shape tumor behavior and therapy resistance. The role of TME in common pediatric cancers like leukemia, lymphoma, neuroblastoma, brain tumors, renal tumors, and sarcomas is discussed. Emerging therapeutic strategies targeting immune checkpoints, macrophage polarization, angiogenic pathways, and stromal barriers are discussed.

Background: Melanoma and triple-negative breast cancer (TNBC) are the most aggressive skin and breast cancers, often diagnosed at late stages with limited treatment options. The melanoma-associated antigen melanotransferrin (MTf) is overexpressed in these solid tumors, where it drives tumorigenesis, progression, and chemoresistance. Its inhibition correlates with tumor regression, making MTf a promising therapeutic target. This study aimed to develop a novel, selectively targeted antibody–drug conjugate (ADC) against MTf-expressing melanoma and TNBC cancer cells using SNAP-tag fusion protein conjugation technology. Methods: We generated an L49(scFv)-SNAP-tag antibody fusion protein engineered through the genetic fusion of a humanized anti-MTf single-chain variable fragment (scFv) with a SNAP-tag fusion protein capable of site-specific self-labelling with O⁶-benzylguanine (BG) modified substrates in 1:1 stoichiometry. Binding and internalization of the conjugate labeled with BG-Alexa 488 (L49(scFv)-SNAP-Alexa488) were assessed by confocal microscopy and flow cytometry in MTf-overexpressing cell lines. Cytotoxicity was evaluated using the cell viability XTT assay after conjugating the SNAP-fusion protein to the potent monomethyl auristatin-F (BG-AURIF). Results: The L49(scFv)-SNAP-Alexa488 conjugate demonstrated specific binding and internalization into MTf-positive melanoma and TNBC cells. The corresponding ADC, L49(scFv)-SNAP-Linker-AURIF, exerted potent, antigen and dose-dependent cytotoxicity, with IC₅₀ values in the nanomolar range (4.77–34.43 nM). Conclusions: We successfully generated a novel SNAP-tag-based ADC that selectively eliminates MTf-overexpressing tumor cells. This proof-of-concept highlights MTF’s value as a therapeutic target and demonstrates that a smaller-format, non-cleavable linker SNAP-tag-based ADC can achieve potent nanomolar cytotoxicity, supporting further development of MTF-targeted immunotherapies for melanoma and TNBC.