Acute myeloid leukemia (AML), a heterogeneous malignancy with complex molecular mechanisms, urgently requires improved prognostic biomarkers and therapeutic targets. This study investigated Hippocalcin-like 1（HPCAL1）, a calcium-binding protein with dual functionality dependent on cancer type, as a potential prognostic marker and investigated its interaction with the tumor immune microenvironment in AML. Through analyses of multiple independent cohorts (GSE13159, GSE34184, GSE24395 and institutional data), we revealed that significant HPCAL1 overexpression in AML samples was correlated with poor survival outcomes. ESTIMATE analysis revealed increased immune activity in the HPCAL1-high group, which was supported by differential expression profiling, which identified 617 genes enriched in inflammatory/immune pathways. Coexpression network and protein interaction analyses further implicated HPCAL1 in immune regulation, particularly through NOD-like receptor signaling, as confirmed by GSEA/GSVA. Single-cell RNA sequencing analysis of the GSE130756 dataset revealed monocyte-specific HPCAL1 expression with altered cellular communication patterns in AML, whereas deconvolution analysis revealed that increased monocyte proportions in HPCAL1-high samples were associated with adverse prognoses. Our findings establish HPCAL1 as a novel prognostic indicator in AML, potentially by mediating its effects through immune microenvironment modulation and monocyte population dynamics. These results provide a foundation for future mechanistic studies exploring the role of HPCAL1 in AML pathogenesis and its therapeutic potential.

Gastric cancer (GC) is a common malignant tumour and a leading cause of cancer-related deaths worldwide. Although the OAS gene family has been implicated in various tumour-related biological processes, its specific role in GC remains unclear. This study integrated bioinformatics analysis of public datasets with experimental validation using clinical GC specimens to investigate the function of the OAS gene family in GC. We found that OAS family members were significantly upregulated in GC and associated with poor patient prognosis. Furthermore, OAS expression levels correlated with genomic mutation profiles and showed positive associations with neutrophil and dendritic cell infiltration in the tumour microenvironment, but negative correlation with B cell infiltration. In vitro functional experiments demonstrated that knockdown of OAS3 or OASL inhibited GC cell proliferation and migration, while overexpression of OASL enhanced these malignant behaviors. RNA-seq analysis revealed upregulation of SFRP4 and JUN and downregulation of ACTA2. KEGG pathway analysis indicated significant enrichment in necroptosis, MAPK signaling, PI3K-Akt signaling, cAMP signaling, viral carcinogenesis, cancer pathways, neutrophil extracellular trap formation, and IL-17 signaling pathways. Additionally, OASL may regulate DNA damage response and metabolic reprogramming. Drug prediction and molecular docking identified chlorendic acid, idarubicin, PHA-848,125, and tosedostat as potential activators of the OAS family due to their strong binding affinity. Conversely, GW842166, NSC 23,766, and metolazone showed high binding affinity for OASL and may inhibit its expression. In summary, The OAS gene family, associated with poor prognosis in gastric cancer, promotes tumour progression and represents a promising therapeutic target.

Uncontrolled abnormal cell growth, referred to as cancer, can result in tumors, other fatal disabilities, and immune system deterioration. Typically, the treatment procedure is longer and extremely expensive owing to its higher recurrence and death rates. Early and precise detection and assessment of cancer are significant for improving patient survival rates. Moreover, initial cancer detection makes the treatment simpler and improves the rate of recovery, leading to a lower mortality rate. Gene expression data plays an important part in cancer classification at the initial phase. Precise cancer classification is a challenging and complex task because of the high-dimensional nature of gene expression data, coupled with the small sample size. With the help of artificial intelligence (AI), researchers have recently developed fundamental models utilizing AI methods to diagnose and predict cancer. These techniques now play a leading role in increasing the precision of survival predictions, cancer susceptibility, and recurrence. This paper presents an Artificial Intelligence-Based Multimodal Approach for Cancer Genomics Diagnosis Using Optimized Significant Feature Selection Technique (AIMACGD-SFST) model. The aim is to develop precise and effective techniques for cancer genomics analysis using advanced computational and analytical techniques. The preprocessing stage comprises min-max normalization, handling missing values, encoding target labels, and splitting the dataset into training and testing sets. Furthermore, the AIMACGD-SFST model employs the coati optimization algorithm (COA) method for feature selection process to choose the related features from the dataset. Finally, the ensemble models, namely deep belief network (DBN), temporal convolutional network (TCN), and variational stacked autoencoder (VSAE) are employed for the classification process. The experimental validation of the AIMACGD-SFST approach is performed under three diverse datasets. The comparison study of the AIMACGD-SFST approach illustrated superior accuracy value of 97.06%, 99.07%, and 98.55% over existing models under diverse datasets.

Refractory cancers may arise either through the acquisition of resistance mechanisms or represent distinct disease states. The origin of childhood T-cell acute lymphoblastic leukaemia (T-ALL) that does not respond to initial treatment, i.e. refractory disease, is unknown. Refractory T-ALL carries a poor prognosis and cannot be predicted at diagnosis. Here, we perform single cell mRNA sequencing of T-ALL from 58 children (84 samples) who did, or did not respond to initial treatment. We identify a transcriptionally distinctive blast population, exhibiting features of innate-like lymphocytes, as the major source of refractory disease. Evidence of such blasts at diagnosis heralds refractory disease across independent datasets and is associated with survival in a large, contemporary trial cohort. Our findings portray refractory T-ALL as a distinct disease with the potential for immediate clinical utility.

The role of m6A RNA methylation of self non-coding RNA remains poorly understood. Here we show that m6A-methylated self U6 snRNA is recognized by YTHDF2 to reduce its stability and prevent its binding to Toll-like receptor 3 (TLR3), leading to decreased inflammatory responses in human and mouse cells and mouse models. At the molecular level, endosomal U6 snRNA binds to the LRR21 domain in TLR3, independent of m6A methylation, to activate inflammatory gene expression, a mechanism that is distinct from that of the best known synthetic TLR3 agonist poly I:C. Both U6 snRNA and YTHDF2 are localized to endosomes via the transmembrane protein SIDT2, where YTHDF2 functions to prevent the U6-TLR3 interaction. We further show that UVB exposure inhibits YTHDF2 by inducing its dephosphorylation and autophagic protein degradation in human keratinocytes and mouse skin. Skin-specific deletion of Ythdf2 in mice enhanced the UVB-induced skin inflammatory response and promoted tumor initiation. Taken together, our findings demonstrate that YTHDF2 plays a crucial role in controlling inflammation by inhibiting m6A U6-mediated TLR3 activation, suggesting that YTHDF2 and m6A U6 are potential therapeutic targets for preventing and treating inflammation and tumorigenesis.

Incisional recurrence, also known as metastasis to the surgical scar, is a relatively rare but serious complication following the surgical resection of lung cancer. Herein, we report a case of postoperative incision metastasis of lung cancer. A 75-year-old Han Chinese male patient was admitted upon discovery of a chest wall mass during a routine physical examination 3 months ago. The patient underwent a radical resection of left lower lobe lung cancer 12 years ago. Notably, he experienced left chest pain and discomfort during a routine examination 12 years postoperatively, leading to the discovery of a chest wall mass measuring 3.5 cm × 2.1 cm × 4.2 cm at the original incision site. Ultrasound-guided core biopsy confirmed the pathological diagnosis of lung adenocarcinoma derived from the chest wall incision, and subsequent gene testing identified a SLC34A2-ROS1 (S4;R31) fusion gene mutation. After the patient underwent two cycles of chemotherapy, a re-examination of the chest computed tomography scan revealed that the mass on the chest wall had significantly shrunk. Subsequently, the patient underwent surgical resection of the chest wall mass. Postoperative pathology confirmed metastatic lung adenocarcinoma from the postoperative incision of lung cancer. The patient was discharged uneventfully and has not shown any obvious recurrence or metastasis during the 2-month follow-up. Improved prognosis of postoperative incisional metastasis of lung cancer is observed after timely comprehensive treatment.

This manuscript highlights the importance of incorporating Lynch syndrome-related genes into prenatal genetic testing to facilitate early detection of constitutional mismatch repair deficiency syndrome (CMMRD). CMMRD, linked to biallelic pathogenic variants in mismatch repair genes, is an aggressive hereditary cancer syndrome. A couple conceived through in vitro fertilisation (IVF), unaware they were carriers of Lynch syndrome. Their child, initially healthy, was diagnosed with acute bilineal leukaemia and later found to have CMMRD. His diagnosis highlighted gaps in prenatal testing. Advances in next-generation sequencing enable broader genetic screening, offering parents crucial risk assessment tools, especially those undergoing IVF, to make informed reproductive choices.

Biomarker testing, multigene expression assays, and mutation profiling can be employed to direct treatment following the pathologic diagnosis of an invasive breast carcinoma. This article provides a summary for the surgical pathologist, underscoring clinically significant genomic alterations in breast cancer, and an overview of the testing process. Preanalytical obstacles, such as tissue selection and preparation, will also be highlighted to ensure successful transition of tissue to the molecular laboratory and the reporting of high-fidelity results.

This review examines prognostic and predictive molecular assays in invasive breast carcinoma beyond estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2. It highlights the clinical utility of multigene assays for risk stratification and treatment planning, alongside emerging biomarkers and technologies, such as liquid biopsy. These advances enable a more precise, personalized approach to breast cancer care and represent a shift toward dynamic, data-driven breast oncology.

The first part of the review of the fibroepithelial lesions of the breast discussed both fibroadenoma and phyllodes tumors (PTs), including their differential diagnoses. In this part of the review, the management, prognosis, and molecular updates of phyllodes tumor (PT) are discussed.

Fibroepithelial lesions of the breast are neoplasms composed of epithelial and stromal elements. The ubiquitous fibroadenoma shows intracanalicular and pericanalicular growth patterns, along with other histologic changes. The subtypes of fibroadenoma include cellular, complex, juvenile, myxoid. The rare phyllodes tumour shows an exaggerated intracanalicular growth pattern and comprises benign, borderline and malignant forms, based on histologic parameters of stromal hypercellularity, atypia, mitoses, overgrowth and tumor borders. Differential diagnostic dilemmas occur for the various grades of phyllodes tumors. This 2 part review discusses both fibroadenoma and phyllodes tumor, their differential diagnoses, with an update on molecular information.

Thyroid disorders encompass a variety of autoimmune conditions such as Graves' disease, Hashimoto's thyroiditis, as well as several types of thyroid cancer. Recent advancements in next-generation sequencing methodologies have elucidated significant genetic mutations, which include RET, BRAF, TPO, and more, which are associated with thyroid cancers and autoimmune disorders. BRAF V600E mutation as an indicator of prognosis in papillary thyroid carcinoma or the identification of genetic markers clarifies treatment strategies. Similarly, polymorphisms in immune regulatory genes such as CTLA-4, particularly when combined with HLA-DR, are linked to higher risk to autoimmune thyroid diseases. Molecular analysis plays a central role in achieving high diagnostic precision. Emerging molecular profiles offer further insight into the complex nature of these multifactorial conditions. This review highlights the impact of genetic and molecular research on diagnosis and management, highlighting the importance of these approaches for precision medicine in thyroid disorders.

FOXA1 is a key transcription factor that mediates the effects of estrogen receptor (ER) and HER2 signaling in breast cancer. However, the mechanisms underlying FOXA1 regulation by HER2 and ER remain poorly understood. Here, we investigated FOXA1 regulation in cells with varying HER2 levels and its impact on endocrine therapy response. Chromatin interaction analyses revealed that high HER2 levels enhance FOXA1 binding to chromatin regions while reducing ER occupancy. Mechanistically, FOXA1 is acetylated by the histone acetyltransferase EP300 at the WD1 domain in ER-positive cells, attenuating its DNA binding at HER2-induced chromatin regions. Conversely, FOXA1 deacetylation-triggered by HER2/HER3 activation-increases its binding to ER-independent regions and promotes insensitivity to hormone therapy. In a luminal breast cancer patient-derived xenograft model, HER2/HER3 signaling increased FOXA1 chromatin binding and reduced sensitivity to ER-targeted treatment. We identify HDAC2 as a key deacetylase modulating FOXA1 acetylation and partially mediating the effects of HER2/HER3 signaling. Altogether, our findings highlight the significance of FOXA1 acetylation, regulated by the HER2/HER3-HDAC2-FOXA1 axis, in controlling FOXA1 chromatin binding and shaping breast cancer progression and therapy response. These insights may inform future therapeutic strategies.

This study aimed to assess the real-world treatment outcomes in South Korean patients with epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer (NSCLC) receiving first-line (1L) EGFR tyrosine kinase inhibitors (TKIs).

Circulating exosomal microRNAs (miRNAs) can serve as diagnostic and prognostic biomarkers for cancer. This study aimed to identify specific miRNAs in serum exosomes of patients with hepatocellular carcinoma (HCC) and validate their biological functions as novel diagnostic and predictive biomarkers.

Huntingtin-interacting protein 1 (HIP1)-anaplastic lymphoma kinase (ALK) is a relatively rare fusion in ALK-positive lung cancers. HIP1-ALK (H19:A20) is a rare variant among HIP1-ALK-positive lung cancers, and data on the efficacy of ALK tyrosine kinase inhibitors are limited. We report a 37-year-old man with HIP1-ALK (H19:A20) lung adenocarcinoma treated with silicone stent placement and alectinib. Stent placement was effective in improving symptoms, and the best treatment response with alectinib was a partial response. Routine ALK screening using IHC or comprehensive genomic profiling should be considered for patients with lung cancer with suspected ALK gene.

There is currently no effective treatment for malignant peripheral nerve sheath tumors (MPNSTs), half of which result from malignant progression of neurofibromas (NFs) in patients with neurofibromatosis type 1 (NF1). NFs are due to biallelic loss-of-function of NF1, which negatively regulates the RAS pathway, in the Schwann cell lineage. We generated a conditional Nf1-mutant mouse model where NFs spontaneously transform into MPNSTs, faithfully recapitulating the human situation. Single-cell transcriptomic profiling demonstrated progression of NFs into MPNSTs, with a glial-to-mesenchymal transition. Sox9 was identified as a marker of this transition and key player in tumor growth. The transition is followed by a loss of the tumor suppressor gene (TSG) Cdkn2a and acquisition of pathogenic variants of other TSGs. Finally, a proof-of-concept drug screen aimed at reducing Sox9 expression in tumor cells identified 12 FDA-approved drugs. Notably, several of these agents target the RAS signaling cascade, suggesting that multi-targeted inhibition of this pathway may represent a promising therapeutic strategy against MPNSTs.

Characterizing cell-type-specific spatially variable genes (SVGs) within tissue context is essential for exploring the landscape of complex biological systems in spatial transcriptomic (ST) studies. In this paper, we present a unified framework, the Mixture of Mixed Models (MMM), designed to directly model RNA count data and identify cell-type-specific SVGs while accounting for cell type composition and correcting for platform effects. Through a comprehensive simulation study and the analyses of eight publicly available ST datasets from various tissues and technologies with different resolutions, we demonstrate the effectiveness and robustness of MMM in identifying cell-type-specific SVGs. Notably, our integrative analysis with genome-wide association studies reveals that the cell-type-specific SVGs identified by MMM in a mouse brain study exhibit significant heritability enrichment in brain-related phenotypes. This finding suggests that cell-type-specific SVGs play a vital role in elucidating the mechanisms underlying complex traits and diseases. When applying MMM to analyze a high-resolution Xenium human breast cancer dataset by accounting for the uncertainties in cell segmentation, we find that certain cell-type-specific SVGs may contribute to cell-cell communications, thereby regulating the tissue microenvironment. Furthermore, we show the versatility of MMM by applying it to the 3D tissue models constructed from multiple ST slices, highlighting its utility in analyzing the 3D ST data.

Treatment benefits of paclitaxel (Px)-based chemotherapy are often offset by dose-limiting side effects. The sigma-1 receptor (Sig1R) is implicated in chemotherapy (ChT)-induced neuropathy but its role in the metastatic potential of breast cancer (BCa) has not been properly explored.

Human breast cancer cells exhibit organotropism during metastasis, showing preferential homing to certain organs such as bone, lung, liver, and brain. Spatial genome organization plays a crucial role in oncogenic transformation and progression, but the extent to which chromosome architecture contributes to organ-specific metastatic traits is unclear. This work characterizes chromosome architecture changes associated with organotropic metastatic traits. By comparing a collection of human genomic data from different subtypes of localized and lung metastatic breast cancer cells with both normal and cancerous lung cells, we find important trends of genomic reorganization. The most striking differences in 3D genome compartments segregate cell types according to their epithelial vs. mesenchymal status. This epithelial-mesenchymal transition (EMT) compartment signature occurs at genomic regions distinct from transcription-defined EMT signatures, suggesting a separate layer of regulation. Specifically querying organotropism, we find 3D genome changes consistent with adaptations needed to survive in a new microenvironment, with lung metastatic breast cancer cells exhibiting compartment switch signatures that shift the genome architecture to a lung cell-like conformation and brain metastatic prostate cancer cells showing compartment shifts toward a brain-like state. TCGA patient data reveals gene expression changes concordant with these organ-permissive compartment changes. These results suggest that genome architecture provides an additional level of cell fate specification informing organotropism and enabling survival at the metastatic site.