Lung Squamous cell carcinoma (LSCC) represents the second most common non-small cell lung cancer. Although studies identified adenocarcinoma-like driver mutations in LSCC using next-generation sequencing (NGS), the disease is challenging to treat due to the limited number of detectable mutations for targeted drug therapy. This study aimed to evaluate the mutation profiles of LSCC detected by NGS to assess the relationships between different driver mutations and clinicopathological parameters.

NGS with a panel of 72 cancer-related genes was used to evaluate the driver mutation profiles of 41 lung resection specimens from patients with LSCC at the Molecular Pathology Laboratory of Aydın Adnan Menderes University in Türkiye. Clinical and histopathological features were recorded for analysis.

Detection of 94 mutations in 23 genes in DNA extracted from the tissue samples of 36 patients revealed that the most prevalent mutations were TP53 (30.85%), NF1 (20.20%), PTEN (11.70%), PIK3CA (5.31%), FBXW7 (4.25%), KRAS (3.20%), respectively. We identified statistically significant relationships between PIK3CA and lower mean age (p = 0.007) and between PTEN and mild inflammatory reaction (p = 0.004). PTEN was associated with central localization (p = 0.13), NF1 with visceral pleural involvement (p = 0.09), and PIK3CA with severe inflammatory reaction (p = 0.053), as well as with advanced pathological T stage (p = 0.09) and pathological N stage (p = 0.057) according to the TNM staging system.

Our study highlights the importance of assessing mutation profiles in LSCC patients to identify driver mutations as potential therapeutic targets. Certain histopathological features are associated with these mutations, serving as indicators for treatment and follow-up decisions.

With the increasing use of artificial intelligence (AI) in diagnostics, AI algorithms have shown great potential in aiding diagnostics. As more of these algorithms are developed, there is overwhelming enthusiasm for implementing digital and artificial intelligence-based pathology (DAIP), but doubts and pitfalls are also emerging. However, few original or review articles address the limitations and practical aspects of implementing DAIP. In this review, we briefly examine the evidence related to the benefits and pitfalls of DAIP implementation and argue that DAIP is not suitable for every clinical laboratory.

We searched the PubMed database using the following keywords: “digital pathology,” “digital AI pathology,” and “AI pathology.”. Additionally, we incorporated personal experiences and manually searched related papers.

Ninety-two publications were found, of which 24 met the inclusion criteria. Many advantages of DAIP were discussed, including improved diagnostic accuracy and equity. However, several limitations of implementing DAIP exist, such as financial constraints, technical challenges, and legal/ethical concerns.

We found a generally favorable but cautious outlook for the implementation of DAIP in the pathology workflow. Many studies have reported promising outcomes in using AI for diagnosis and analysis; however, there are also several noteworthy limitations in implementing DAIP. Therefore, a balance between the benefits and pitfalls of DAIP must be thoroughly articulated and examined in light of the institution’s needs and goals before making the decision to implement DAIP. Approaches for mitigating machine learning biases were also proposed, and the adaptation and growth of the pathology profession were discussed in light of DAIP development and advances.

FMS-like tyrosine kinase 3 (FLT3) mutations are among the most common genetic alterations in acute myeloid leukemia (AML) and play a pivotal role in leukemogenesis. The two primary mutation types, internal tandem duplications (ITDs) and tyrosine kinase domain point mutations, serve as key prognostic markers and therapeutic targets. Advances in next-generation sequencing (NGS) have revolutionized FLT3 mutation detection by providing precise insights into mutation architecture, enhancing risk stratification, and enabling personalized treatment strategies. Additionally, these advancements have facilitated molecular minimal residual disease (MRD) testing, which is instrumental in guiding post-remission management. This review summarizes the molecular characteristics, diagnostic approaches, and therapeutic implications of FLT3 mutations in hematologic malignancies.

A narrative review of the current literature on FLT3 mutations was conducted, incorporating data from original research articles, clinical trials, and recent reviews. Relevant studies were identified through a PubMed literature search and manually curated.

FLT3 mutations are detected in approximately 30% of AML cases and occur at lower frequencies in myelodysplastic syndromes, chronic myelomonocytic leukemia, acute lymphoblastic leukemia, and mixed phenotype acute leukemia. NGS enables comprehensive mutation profiling, revealing rare variants and subclonal complexity while supporting MRD detection with high analytic sensitivity. FLT3-ITD-based MRD positivity is strongly associated with relapse and poor survival in AML. Clinical trial data support FLT3 inhibitors, including midostaurin, gilteritinib, and quizartinib, in FLT3-mutated AML. Additionally, MRD-guided therapy and combination treatment strategies are promising approaches to overcoming resistance.

FLT3 mutations play a central role in the pathogenesis and treatment of AML and related malignancies. NGS-based testing and MRD monitoring transform clinical decision-making by refining risk stratification and enabling personalized therapeutic interventions. Establishing standardized testing protocols and the broader integration of FLT3-targeted therapies will be essential for optimizing patient outcomes.

The International Academy of Cytology Yokohama System for Reporting Breast Fine-Needle Aspiration Biopsy Cytology was developed by a group of expert cytopathologists and clinicians in the breast field. Five categories are defined to stratify breast lesions by their risks of malignancy and managed accordingly. Clinical and radiologic information (triple test) are critical for further management. Ultrasound guidance, and rapid on-site evaluation are valuable for improving the rate of definitive diagnosis. Ancillary studies can be tested on cytologic samples to provide prognostic, predictive information as well as diagnostic clues. Based on many published studies in different institutions worldwide, the implementation of the system appears to have been successful. However, further studies are important for improvements and modifications to the current system.

The Paris System for Reporting Urinary Cytology (TPS 1.0, published in 2016) is the first standardized, evidence-based reporting system established as an international reporting system for urine specimens after the International Congress of Cytology in Paris. Its primary purpose is to reduce the rate of unnecessary indeterminate diagnoses but maintain the excellent performance of urine cytology, in detecting high-grade urothelial carcinoma. The reporting system comprises six diagnostic categories, as well as each category’s diagnostic criteria, estimated risk of malignancy, and management recommendations. After six years, TPS 2.0 was applied in 2022 upon the unfolding of new data. TPS 2.0 clarifies the diagnosis categories and updates the risk of malignancy in each category and developments of molecular tests. This review provides an updated summary of TPS 2.0. Some diagnostic pitfalls and molecular tests were also discussed.

The Bethesda System for Reporting Thyroid Cytopathology is the first reporting system established in non-gynecologic cytopathology after the Bethesda System for Reporting Cervical Cytopathology. It adopts the same concept of providing a uniform reporting system for all pathologists and clinicians to follow in thyroid cytology. The reporting system is composed of six diagnostic categories. There are defined diagnostic criteria, estimated risk of malignancy, and management recommendations for each category. The reporting system has undergone two revisions upon the emergence of a new entity, updated terminology in histology, and development and refinement of molecular testing. The third edition is soon to be published in 2023. This review will provide an updated summary of the reporting system. Potential diagnostic pitfalls and molecular testing are also discussed.