Gastric cancer (GC) ranks as the fifth most prevalent malignant neoplasm globally, with an increased death rate despite recent advancements in research and therapeutic options. Different molecular subtypes of GC have distinct interactions with the immune system, impacting the tumor microenvironment (TME), prognosis, and reaction to immunotherapy. Tumor-infiltrating lymphocytes (TILs) in the TME are crucial for preventing tumor growth and metastasis, as evidenced by research showing that patients with GC who have a significant density of TILs have better survival rates. But cancer cells have evolved a variety of mechanisms to evade immune surveillance, both sialic acid-binding immunoglobulin-like lectin 15 (Siglec-15) and Programmed Death-Ligand 1 (PD-L1) playing a pivotal role in the development of an immunosuppressive TME. They prevent T cell activation and proliferation resulting in a decrease in the immune system’s capacity to recognize and eliminate malignant cells. These immune checkpoint molecules function via different but complementary mechanisms, the expression of Siglec-15 being mutually exclusive with PD-L1 and, therefore, providing a different therapeutic approach. The review explores how TILs affect tumor growth and patient outcomes in GC, with particular emphasis on their interactions within the TME and potential targeting of the PD-L1 and Siglec-15 pathways for immunotherapy.

Gastric cancer (GC) ranks as the fifth most prevalent malignant neoplasm globally, with an increased death rate despite recent advancements in research and therapeutic options. Different molecular subtypes of GC have distinct interactions with the immune system, impacting the tumor microenvironment (TME), prognosis, and reaction to immunotherapy. Tumor-infiltrating lymphocytes (TILs) in the TME are crucial for preventing tumor growth and metastasis, as evidenced by research showing that patients with GC who have a significant density of TILs have better survival rates. But cancer cells have evolved a variety of mechanisms to evade immune surveillance, both sialic acid-binding immunoglobulin-like lectin 15 (Siglec-15) and Programmed Death-Ligand 1 (PD-L1) playing a pivotal role in the development of an immunosuppressive TME. They prevent T cell activation and proliferation resulting in a decrease in the immune system’s capacity to recognize and eliminate malignant cells. These immune checkpoint molecules function via different but complementary mechanisms, the expression of Siglec-15 being mutually exclusive with PD-L1 and, therefore, providing a different therapeutic approach. The review explores how TILs affect tumor growth and patient outcomes in GC, with particular emphasis on their interactions within the TME and potential targeting of the PD-L1 and Siglec-15 pathways for immunotherapy.

Tuberculosis is the primary cause of death due to infection in the world. Identification of Mycobacterium tuberculosis in sputum is a diagnostic test, which can be used in screening programs—especially in countries with a high incidence of tuberculosis—to identify and treat those persons with the highest risk of disseminating the infection. We previously developed an algorithm which is able to automatically detect mycobacteria on tissue; in particular, our algorithm identified acid-fast bacilli on tissue with 100% specificity, 95.65% sensitivity, and 98.33% accuracy. We tested this algorithm on 1059 Ziehl–Neelsen-stained sputum smears to evaluate its results as a possible tool for screening. The results were displayed as a heat map of 32 × 32 pixel patches. Analysis of the positive patches revealed a good specificity (86.84%) and 100% sensitivity for patches with a level of confidence over 90; furthermore, the accuracy remained over 95% for all levels of confidence over 80, except the class (95–100]. The modest specificity is caused by the peculiarities of smears (uneven thickness, dust contamination, lack of coverslip). We will train the algorithm on sputum smears to increase the specificity to over 95%. However, as our algorithm showed no false negatives, it is suitable for screening.

Gastric cancer remains a major global health burden, with limited response rates to current immunotherapies targeting the programmed death-ligand 1 (PD-1/PD-L1) axis. Recent studies have identified sialic acid-binding immunoglobulin-like lectin 15 (SIGLEC-15) as a novel immune checkpoint molecule that may drive immune evasion through PD-L1–independent pathways. This study aimed to evaluate the expression patterns of SIGLEC-15 and PD-L1 in gastric adenocarcinoma and to investigate their associations with clinicopathological features and patient outcomes. We retrospectively analyzed 133 consecutive cases of gastric adenocarcinoma with complete clinicopathologic and follow-up data. Immunohistochemical staining was performed on formalin-fixed tumor samples; SIGLEC-15 expression on tumor cells was quantified by H-score (high expression defined as ≥110) and PD-L1 status by combined positive score (CPS, positive if ≥1). High SIGLEC-15 expression correlated with multiple adverse pathological features, including lymphatic (p = 0.003), venous (p = 0.030), and perineural invasion (p = 0.010), and was associated with significantly poorer 3-year overall survival (hazard ratio = 3.36, p < 0.001). While SIGLEC-15 and PD-L1 expression were not mutually exclusive, an inverse relationship was generally observed. Patients with dual positivity (SIGLEC-15 high/PD-L1 CPS ≥ 1) showed the lowest 36-month survival (32%), compared to 56% in the dual-negative group (SIGLEC-15 low/PD-L1 CPS < 1). These results highlight the clinical relevance of SIGLEC-15 as an independent marker of tumor aggressiveness and poor prognosis in gastric adenocarcinoma. Moreover, stratification based on combined SIGLEC-15 and PD-L1 CPS expression revealed that patients co-expressing high levels of both markers experienced the poorest survival outcomes. These findings suggest that the dual assessment of SIGLEC-15 and PD-L1 may enhance prognostic accuracy and support immunotherapeutic decision-making in gastric cancer.

The presence of lymphovascular invasion (LVI) in urothelial carcinoma (UC) is a poor prognostic finding. This is difficult to identify on routine hematoxylin–eosin (H&E)-stained slides, but considering the costs and time required for examination, immunohistochemical stains for the endothelium are not the recommended diagnostic protocol. We developed an AI-based automated method for LVI identification on H&E-stained slides. We selected two separate groups of UC patients with transurethral resection specimens. Group A had 105 patients (100 with UC; 5 with cystitis); group B had 55 patients (all with high-grade UC; D2-40 and CD34 immunohistochemical stains performed on each block). All the group A slides and 52 H&E cases from group B showing LVI using immunohistochemistry were scanned using an Aperio GT450 automatic scanner. We performed a pixel-per-pixel semantic segmentation of selected areas, and we trained InternImage to identify several classes. The DiceCoefficient and Intersection-over-Union scores for LVI detection using our method were 0.77 and 0.52, respectively. The pathologists’ H&E-based evaluation in group B revealed 89.65% specificity, 42.30% sensitivity, 67.27% accuracy, and an F1 score of 0.55, which is much lower than the algorithm’s DCC of 0.77. Our model outlines LVI on H&E-stained-slides more effectively than human examiners; thus, it proves a valuable tool for pathologists.