In the past decade, breast pathology in China has made significant progress in diagnostic standards, technological applications, scientific research, and discipline development. The histopathological diagnostic system has been continuously refined, with the implementation of relevant guidelines and expert consensus enhancing standardization and reproducibility of diagnostic results. Immunohistochemistry and molecular testing technologies have become increasingly sophisticated, with emerging biomarkers such as low HER2 expression and PIK3CA mutations gradually integrated into clinical decision-making, promoting the advancement of precision therapy. The application of digital pathology and image-assisted analysis has steadily expanded, providing new tools to improve diagnostic efficiency and consistency. The national breast pathology group has actively advanced the development of tiered diagnostic systems, workforce training, and public education, effectively strengthening diagnostic capabilities at the grassroots level. Looking ahead, the integration of multidimensional data, optimization of auxiliary diagnostic systems, and interdisciplinary collaboration are expected to drive the continued development of breast pathology in China.

Pediatric tumors differ significantly from adult cancers, possessing unique developmental origins, histological features, and molecular genetic changes. With the rapid advancement of multi-omics technologies, such as genomics, transcriptomics, proteomics, and epigenetic analyses, the molecular characteristics of pediatric tumors have been extensively revealed, providing new possibilities for precision medicine. Concurrently, the integration of artificial intelligence and digital pathology has effectively enhanced diagnostic accuracy, presenting a broad scope for future development. While this progress positively impacts the pathological diagnosis of pediatric tumors, it also presents challenges related to data complexity, technology integration, and the promotion of clinical applications. This article aims to discuss the influence of molecular and artificial intelligence, as well as multimodal integrated pathological models on diagnosis and prognostic prediction of pediatric tumor, with the goal of fostering further exploration and in-depth research.

Colorectal cancer (CRC) is one of the most malignant tumors with high morbidity and mortality worldwide. Early diagnosis and accurate pathological evaluation are of great significance for improving patient prognosis. Endoscopic resection is the main treatment for early CRC. Pathological parameters-such as margin status, lymphatic vascular invasion (LVI), tumor grade, depth of submucosal invasion and tumor budding are the key to determine whether curative resection is achieved. At present, the measurement method of submucosal invasion depth of pT1 CRC is controversial. Submucosal invasion depth measurement adopts different measurement methods for pedunculated and sessile lesions, mainly including measurement from the surface of the lesion or the lower edge of the mucosal muscle layer. Especially for sessile lesions, due to different observers different understandings of the position of the mucosal muscle layer that can be identified or evaluated in the guidelines, observers may apply different criteria to evaluate the integrity of the mucosal muscle layer. In recent years, more and more evidence has shown that the association between the depth of submucosal invasion and the risk of lymph node metastasis may be overestimated, while other pathological parameters (such as LVI, high-grade tumor budding, and poorly differentiated components) have equal or more important significance in prognostic stratification. Therefore, the current measurement of the depth of submucosal invasion of pT1 CRC and its prognostic value are facing challenges, which deserve our attention and further exploration.

Advances in targeted therapy and immunotherapy have significantly improved clinical outcomes for patients with advanced non-small cell lung cancer (NSCLC), reshaping treatment paradigms. However, most patients ultimately face drug resistance, with limited options for subsequent therapies and suboptimal treatment efficacy, presenting a prominent challenge in current clinical practice. Antibody-drug conjugates (ADCs), characterized by high efficacy and favorable safety profiles, have emerged as a promising therapeutic frontier in recent years. This systematic review provides a comprehensive overview of the latest advancements in ADCs-based therapies for lung cancer, alongside discussions of the prevailing challenges in this rapidly evolving domain.
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Human epidermal growth factor receptor 2 (HER2) mutations play a role as a driver gene in non-small cell lung cancer (NSCLC). Patients with advanced NSCLC harboring HER2 mutations exhibit poor responses to conventional chemotherapy and immunotherapy, hence targeted therapies against HER2 are under extensive investigation. This review analyzes the biological characteristics of HER2, an overview of clinical trials for targeted therapy drugs, including monoclonal antibodies, tyrosine kinase inhibitors (TKIs), and antibody-drug conjugate, and research directions for drug resistance in NSCLC. Currently, Pyrotinib and Trastuzumab deruxtecan have been approved for the treatment of advanced NSCLC with HER2 mutations, suitable for patients who have failed standard therapy, which is far from meeting the clinical demands. Novel selective HER2 TKIs are gradually emerging. Future exploration trends are gradually shifting from single drugs to combination strategies, and are exploring more precise selection strategies as well as research on resistance mechanisms. These studies will provide a theoretical basis for clinical treatment strategies for advanced NSCLC with HER2 mutations, promoting the development of personalized therapy.
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With the rising incidence of breast cancer among women, neoadjuvant chemotherapy (NAC) is becoming increasingly crucial as a preoperative treatment modality, enabling tumor downstaging and volume reduction. However, its efficacy varies significantly among patients, underscoring the importance of predicting pathological complete response (pCR) following NAC. Early research relied on statistical methods to integrate clinical data for predicting treatment outcomes. With the advent of artificial intelligence (AI), traditional machine learning approaches were subsequently employed for efficacy prediction. Deep learning emerged to dominate this field, and demonstrated the capability to automatically extract imaging features and integrate multimodal data for pCR prediction. This review comprehensively examined the applications and limitations of these three methodologies in predicting breast cancer pCR. Future efforts must prioritize the development of superior predictive models to achieve precise predictions, integrate them into clinical workflows, enhance patient care, and ultimately improve therapeutic outcomes and quality of life.

Objective: To analyze the clinical features and prognosis of patients with lymphoplasmacytic lymphoma/Waldenström macroglobulinemia (LPL/WM) transformed into diffuse large B-cell lymphoma (DLBCL) . Methods: This study retrospectively analyzed the clinical data of five patients with LPL/WM transformed to DLBCL diagnosed and treated at a multicenter hospital in Hunan Province from December 2020 to April 2023. Clinical manifestations, treatment regimens, and therapeutic efficacy before and after the transformation were compared. Results: Of the five patients, four were male and one was female, with a median age of 64.0 (57.0-80.0) years, all of whom had abnormally increased β(2)-microglobulin levels at diagnosis, and two were combined with increased lactate dehydrogenase levels. The MYD88(L265P) mutation was detected in 4 patients, whereas 1 carried the FAT1 and NOTCH1 mutations, and none demonstrated CXCR4 mutations. Three patients were negative for the TP53 mutation, and two were not tested. Before transformation, three patients were treated with Bruton tyrosine kinase inhibitor therapy, and one patient was treated with the bendamustine plus rituximab regimen. All patients eventually transformed into non-growth center-derived DLBCL, with a median time to conversion of 11.8 (4.0-19.0) months, and most of them presented with weight loss, lymph node enlargement, splenomegaly, and extranodal involvement. Posttransformation, the patients were mainly treated with the rituximab, cyclophosphamide, hydroxydaunorubicin, oncovin, and prednisone (R-CHOP) regimen, with an optimal outcome of partial remission. Disease progression occurred in 4 of the patients, with a median overall survival of 16.8 (10.0-26.0) months. Conclusion: Transformation from LPL/WM to DLBCL is rare. Patients should remain highly vigilant for transformation if they develop rapidly enlarging lymph nodes and/or newly involved lymph nodes, worsening systemic symptoms, and declining body mass. R-CHOP regimen may induce a partial response in some cases; however, the overall prognosis remains poor.

Objectives: Cases from our hospital and a systematic review were performed in this paper to get a better understanding on the diagnosis and therapies for primary pulmonary NUT carcinoma (PPNC) patients. Methods: The clinical features, pathological diagnosis, treatment and outcomes of PPNC patients from 2020-2025, including four cases from the First Affiliated Hospital of Soochow University, were collected delicately. The Kaplan-Meier method and Cox proportional hazard regression model were used to calculate cumulative survival and prognostic factors. Results: The male-to-female ratio of PPNC was 18∶15, the left to right ratio was 14∶19, the median age was 36 years old and the median tumor diameter was 6.1 cm. Most patients were already at an advanced stage with the clinical features-cough (16/33) and chest or back pain (13/33) when they first came to the hospital. The tumor cells were arranged in nest pattern with small-medium size, round to oval shape, and nuclei were deeply stained. The high positive staining of NUT (32/32) and CK-pan (16/19) was observed, NUTM1 gene translocation in 24 cases was detected by fluorescence in situ hybridization (FISH), and different gene rearrangements were located by NGS-NUTM1-BRD4 (8/12), NUTM1-BRD3 (2/12), NUTM1-BRD2 (1/12) and NUTM1-ZNF532 (1/12). Most patients accepted different chemotherapy regimens (25/29), including paclitaxel albumin and platinum (13/25), etoposide and platinum (8/25). Meanwhile, 12 cases were treated with PD-1/PD-L1 antibody during the therapy. The median follow-up time was 7 months in 28 cases tracked from 2-90 months. Univariate Cox regression analysis showed that metastasis of this disease affected patient prognosis (HR=2.55, 95% CI: 0.974-6.677, P=0.057) and the cumulative survival rate was lower in the older ones. Conclusions: PPNC, more often found in middle-aged patients, no difference in sex, can be diagnosed by pathmorphology and immunophenotype, while NUTM1 molecular test is highly suggested for the accurate therapy. Metastasis can be recognized as the prognostic risk factor. Early detection of the cancer improves the chances of successful treatment, especially in patients with older age.

The classic principles of oncological surgery were accepted based the procedures from radical surgery for breast cancer described by Halsted in 1894, which can be summarized as tumor en bolc resection, clean surgical margin, regional lymph nodes dissection, and tumor-free technique. The classic principles of oncological surgery are the cornerstone of cancer surgical treatment and have significantly promoted the development of oncological surgery. The minimally invasive surgery is the trend of contemporary oncological surgery for the characteristics of minimal invasion, better tissue identification, precise manipulation, and fast postoperative recovery. Head and neck cancers are usually related to the upper aerodigestive tract, as well as important nerves and blood vessels in head and neck. The anatomical structures of the relative organs are intricate and delicate, and their functions are crucial. Therefore, there is an urgent need for minimally invasive surgical techniques. However, the head and neck cancers which are larger or located in some special sites such as the skull base have to be removed by piecemeal resection in minimally invasive surgery. The piecemeal resection of tumor increases the risks of tumor positive surgical margins and tumor implantation metastasis. The goal of radical surgery for cancers is to completely remove the tumor and obtain a really clean surgical margin. If head and neck cancer is indication for radical surgery, appropriate operative manipulation (en bloc or piecemeal resection) is able to achieve the goal of radical surgery. Giving attention to both the advantages of the principles of oncological surgery and minimally invasive surgical techniques benefits more patients with head and neck cancers from better survival rate and minor invasive morbidities.

Lacrimal gland adenoid cystic carcinoma (LGACC), the most prevalent malignant epithelial tumor of the lacrimal gland, exhibits high invasiveness and poor prognosis. Despite aggressive local therapies, the 5-year and 10-year survival rates remain at 50% and 20% respectively. This review comprehensively synthesizes histopathological features, molecular mechanisms, and therapeutic advances in LGACC. Histopathological analysis highlights three classical subtypes (tubular, cribriform, and solid) with distinct prognostic implications, particularly emphasizing the detrimental survival impact of tumors undergoing high-grade transformation. At the molecular level, in-depth elucidation reveals the pivotal roles of NOTCH pathway mutations and MYB overexpression in driving oncogenesis through hyperactivation of receptor tyrosine kinase, PIP3/AKT, and ATR/BRCA signaling cascades. Current evidence demonstrates persistent therapeutic challenges: expanded surgical resection fails to significantly improve survival outcomes, while local excision combined with adjuvant therapies still faces substantial recurrence (80% at 5 years) and metastasis rates (66.9%). Emerging breakthroughs in targeted therapies warrant attention, including antisense oligonucleotides targeting MYB-NFIB fusion genes, clinical trial data of NOTCH inhibitors (e.g., AL101), and PARP inhibitor-based combinatorial regimens leveraging DNA damage repair mechanisms. By integrating fundamental research and clinical translational evidence, this review provides a theoretical framework for optimizing LGACC diagnosis and treatment paradigms.

Lung cancer remains a leading cause of cancer-related mortality. In non-small cell lung cancer (NSCLC) treated with epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs), histological transformation to small cell lung cancer (SCLC) can occur, leading to EGFR-TKI resistance. SCLC transformation not only challenges existing treatment strategies but also severely impacts patients prognosis. Here, we explore the underlying mechanisms of SCLC transformation, focusing on RB1/TP53 genes, MYC gene, and the Notch and Wnt/β-catenin signaling pathways. We propose a hypothesis for SCLC transformation: co-mutation of RB1/TP53 genes serves as a prerequisite, while combined abnormalities, such as aberrant MYC activation and dysregulated Notch or Wnt/β-catenin signaling, will further drive the transformation process. Currently, therapies for transformed SCLC are still exploratory. We discuss multimodal strategies, including chemotherapy, chemotherapy combined with EGFR-TKIs, chemotherapy combined with anti-angiogenic therapy, chemotherapy combined with immunotherapy, and radiotherapy. Finally, we outline future research directions. Future studies should unravel transformation mechanisms, conduct rigorous randomized trials, and develop precision interventions, paving new avenues for improved patient outcomes.​.

In recent years, with the rapid development of artificial intelligence technology, the application of deep learning in the field of pathology has been continuously expanding. Particularly, the rise of multimodal data fusion methods has opened up new technical paths for the precise diagnosis, prognosis assessment, and individualized treatment of tumors. By integrating multi-level and multi-source data such as clinical information, pathological omics, molecular omics, and imaging omics, deep learning models can identify potential associated features and key biological mechanisms that are difficult to reveal by a single modality, thereby significantly improving the accuracy of disease classification and the scientific nature of risk stratification. This article systematically reviews the research progress of multimodal data fusion methods based on deep learning in the field of pathology in recent years, focuses on sorting out different types of fusion strategies, evaluates their advantages and challenges in practical clinical applications, and looks forward to future development trends.

Medullary thyroid carcinoma (MTC) is the most common neuroendocrine carcinoma within the thyroid gland, characterized by strong invasiveness, high metastasis and recurrence rates. It is relatively rare among thyroid malignancies. The cytological and histological features of MTC are diverse and disperse, presenting as papillary, follicular, solid, trabecular, and spindle cell patterns. Immunohistochemical staining shows variable expression of calcitonin, carcinoembryonic antigen, and neuroendocrine markers. MTC can be classified into hereditary and sporadic types, with most cases caused by germline or somatic mutations in the RET gene located on chromosome 10. The 5th edition World Health Organization classification of endocrine and neuroendocrine tumors categorizes MTC into low-grade and high-grade based on tumor necrosis, mitotic figures, and Ki-67 proliferation index, highlighting that histological grading and RET gene mutations are independent prognostic predictors. This paper summarizes the recent advances in the pathological diagnosis of MTC, focusing on the key roles of the MTC grading system, molecular characteristics, and genetic screening and counseling in risk stratification for recurrence and targeted therapy.

The spatio-temporal heterogeneity of breast cell subsets forms the fundamental biological basis for physiological development and pathological progression, including tumorigenesis; however, its complex regulatory mechanisms are not yet fully elucidated. With its high-resolution capabilities, single-cell RNA sequencing (scRNA-seq) technology offers a powerful tool for dissecting this cellular heterogeneity. This technology enables the construction of high-precision breast cell atlases, the accurate identification of distinct cell subsets, and the reconstruction of differentiation trajectories from stem/progenitor cells to functional epithelial cells. By resolving the transcriptional regulatory networks that govern cell fate determination, intercellular communication patterns, and dynamic microenvironmental interactions, scRNA-seq has unveiled the molecular foundations of breast development and provided new perspectives on the pathogenesis of related diseases such as breast cancer and macromastia. Furthermore, scRNA-seq demonstrates significant potential for discovering early molecular markers of disease, deciphering tumor heterogeneity, and elucidating mechanisms of therapeutic resistance. The continued application of scRNA-seq for dissecting breast cell heterogeneity, combined with its integration with multi-modal data such as spatial omics, promises to provide critical evidence and new insights for revealing the molecular mechanisms of breast development-related diseases and for formulating precision therapeutic strategies.

Stathmin 1 (STMN1) is a microtubule-binding cytoplasmic phosphoprotein that promotes microtubule depolymerization or inhibits microtubule assembly, thereby regulating cytoskeletal organization and cell cycle progression. STMN1 is upregulated in a variety of malignant tumors, where it drives proliferation, invasion, metastasis, and angiogenesis through classic pathways such as nuclear factor-κB (NF-κB), mitogen-activated protein kinase (MAPK), and ferroptosis. STMN1 can also modulate the function of immune cells, thereby influencing antitumor immunity. Clinical data show that its high expression correlates positively with tumor drug resistance and poor prognosis, suggesting that STMN1 has potential as a tumor biomarker and therapeutic molecular target with important clinical significance.

The number of lymph nodes detected in colon cancer is influenced by various factors. The arbitrary application of the 12-lymph node detection threshold as a quality control standard is unreasonable. Overemphasis on the number of lymph nodes may result in an unnecessarily extensive dissection, while existing evidence shows no survival benefit from routine D3 lymphadenectomy. This article systematically reviews the origin, rationale, influencing factors, and common misconceptions surrounding the lymph node detection threshold. It also looks ahead to the trend of narrowing the scope of lymphadenectomy in colon cancer and the potential for personalized dissection strategies.