Cervical cancer exerts a significant public health burden globally and in India. While HPV-16 and HPV-18 are well-known etiological agents, emerging evidence highlights the regional significance of other high-risk genotypes like HPV-58 and HPV-59. This study aimed to evaluate the prevalence and cytological associations of HPV genotypes, particularly 58 and 59, in Northeast Indian women. A total of 429 cervical swab specimens were collected from women attending the routine outpatient department at NEIGRIHMS, Shillong, between 2021 and 2025, following informed consent and institutional ethical approval. Cytological analysis and demographic data collection were performed. HPV genotyping was carried out at the reference lab at Pune using the Xpert HPV assay and qPCR Panel. Among 429 participants, 74 (17.25%) tested positive for HPV. Among the HPV positive cases, the genotype distribution was: HPV-16 (52.70%), HPV-18 (8.10%), and HPV-58(5.40%) and HPV-59 (13.51%). Notably, HPV-58 positive women exhibited abnormal cytology, while HPV-59 positive patients (n = 10), Pap smears showed NILM (6), ASC-US (1), Bacterial vaginosis (2), and One case of Poorly Differentiated Malignancy. This study underscores the emerging clinical relevance of HPV-58 and 59 in Northeast India. The higher cytological abnormality in HPV-58 cases highlights the need for expanded HPV genotyping in screening programs.

Accurate detection of low-frequency DNA mutations in body fluids is essential for cancer monitoring and treatment evaluation. However, the high abundance of wild-type DNA often masks rare mutant signals, making sensitive detection particularly challenging.

We developed a screening strategy termed the CbAgo-enriched Cas12a mutation screening system (CECMS). By integrating the single-nucleotide resolution of CbAgo with the trans-cleavage activity of CRISPR-Cas12a, this system selectively eliminates wild-type DNA while enriching targeted mutant alleles. CECMS achieves up to 100-fold higher sensitivity at 37 °C compared with conventional Cas12a biosensors, enabling reliable detection of variant allele frequencies (VAFs) as low as 0.01%. In undiluted serum spiked samples for circulating tumor DNA (ctDNA) detection, the method successfully detected pancreatic cancer-associated KRAS G12D mutations at a VAF of 0.1%.

By leveraging CbAgo-mediated enrichment, the capability of exposing rare SNV for downstream detection is markedly improved. With its high efficiency and ease of use, CECMS holds strong potential as a convenient tool for clinical cancer diagnostics and monitoring.

Acute Myeloid Leukemia (AML) is a hematopoietic malignancy characterized by the uncontrolled proliferation of aberrant myeloid blasts within the bone marrow, resulting in disrupted hematopoiesis and severe clinical consequences. Drug resistance represents a major barrier in AML treatment, frequently manifesting as relapse following initial remission with conventional chemotherapeutic agents such as cytarabine and venetoclax. The underlying mechanisms of drug resistance include enhanced drug efflux, altered drug metabolism, and activation of pro-survival signaling pathways, necessitating the elucidation of specific genetic determinants to enable the development of effective therapeutic strategies. The advent of CRISPR/Cas9 system has facilitated precise genomic modifications, permitting the generation of cell libraries with targeted gene knockouts in AML cells. This approach can identify genes whose disruption alters drug sensitivity, implicating their involvement in survival and resistance to cell death. This protocol outlines a systematic strategy to uncover genes associated with drug resistance in AML cells by leveraging CRISPR/Cas9-mediated functional genomic screening. By employing this methodology, genes conferring drug susceptibility upon knockout are noted as potential drivers of drug resistance, offering valuable insights for the rational design of targeted therapies.

While only 5-10% of postmenopausal bleeding (PMB) and perimenopausal abnormal uterine bleeding (AUB) represents an underlying endometrial cancer (EC) or precancerous lesion, the current standard of care recommends endometrial sampling to evaluate all presenting with this clinical concern. We aimed to develop a highly sensitive panel of methylated DNA markers (MDMs) to identify patients with underlying EC through less invasive testing of self-collected vaginal fluid.

Patients with AUB/PMB ≥45 years or EC or atypical endometrial hyperplasia (AEH) ≥18 years were prospectively enrolled to self-collect vaginal fluid using a tampon. Bisulfite-converted DNA from vaginal fluid was assayed with long-probe quantitative amplified signal (LQAS) for the quantification of MDM signal. Samples were tested with the goal of building a parsimonious model to discriminate EC from benign endometrium (BE). This marker reduction study started with 19 previously identified MDMs. Down-selection was then performed on a panel of 12 MDMs in an independent marker selection study. A random forest model was developed and validated in an independent test set.

In marker reduction, a 19-MDM model achieved a sensitivity of 91% (83-96%) in EC with a specificity of 87% (80-92%) observed in BE in an independent set. In marker selection, a 2-MDM model generated a sensitivity for EC of 96% (84-99%), specificity of 82% (67-91%), and an AUC of 0.97 (0.94-1) in an independent test set.

Rigorous marker reduction from 19 MDMs to 12 allowed for marker selection of a 2-MDM panel with high sensitivity and specificity to detect EC in vaginal fluid.

Habitat imaging has been widely used to assess tumor treatment response; however, the role of MRI-based habitat analysis in identifying pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer remains an unresolved issue.

To evaluate the utility of dynamic contrast-enhanced MRI (DCE-MRI)-based habitat imaging in identifying pCR after NAC in breast cancer patients.

Retrospective.

1.5 T or 3.0 T, DCE-MRI (Gradient echo).

Three hundred and sixty-three women with biopsy-confirmed breast cancer from Center A (n = 249, training set) and Center B and Center C (n = 114, external validation set).

DCE-MRI peak-enhancement images were used to generate habitat maps via supervoxel segmentation and K-means clustering. Two intratumoral heterogeneity (ITH) metrics (Volume Entropy and Intensity Entropy) were extracted to quantify the structural and signal complexity of tumors. Three discriminative models were developed: a clinical model based on clinicopathologic variables, an ITH model incorporating Volume Entropy and Intensity Entropy, and an integrated nomogram combining both feature sets.

Student's t test, Wilcoxon U test, χ², Fisher exact test, and receiver operating characteristic curve analysis. Significance was set at p < 0.05.

Volume Entropy and Intensity Entropy were significantly lower in pCR versus non-pCR groups. HR status, HER2 status, and both ITH features were independent indicators of pCR. The nomogram showed superior performance (AUC = 0.849 in the training set and 0.825 in the validation set), outperforming the clinical model (DeLong test). Subgroup analysis across four molecular subtypes showed AUCs ranging from 0.762 to 0.890. An interactive online tool was developed for clinical application.

MRI-based habitat analysis offers a simple, interpretable, and clinically applicable approach for noninvasive identification of pCR to NAC in breast cancer.

Stage 3.

Accurate brain tumour segmentation is crucial for clinical diagnosis and treatment planning, yet remains challenging due to the scale diversity of tumour regions, ambiguous boundary structures, and highly irregular shapes.

We propose a novel Edge Attention Network that integrates two key components: a Multi-Scale Context Fusion Module to dynamically adjust receptive fields and capture multi-scale contextual information, and an Edge Segmentation Module that explicitly extracts tumour boundaries and injects them into the backbone as spatial attention to refine segmentation details, particularly at edges.

Experiments show that our model achieves Dice coefficients of 90.37% for Tumour Core (TC) and 88.91% for Whole Tumour (WT) on the BraTS2021 dataset. In cross-dataset generalisation tests on BTM-PVS, it maintains strong performance with 75.20% TC and 74.20% WT.

The proposed method demonstrates superior segmentation accuracy and robust generalisation capability, highlighting its clinical potential and offering new insights for medical image segmentation.

HER2 plays a crucial role in breast cancer (BC) progression, with the D769H and D769Y mutations significantly influencing its structural integrity, drug-binding dynamics, and therapeutic response. This study employs molecular docking and molecular dynamics simulations (MDS), with trajectories propagated for 1000 ns, to examine their distinct effects. Root mean square deviation (RMSD) analysis indicates increased conformational deviations in mutant structures, signifying heightened instability, while root mean square fluctuation (RMSF) reveals enhanced flexibility near the mutation site. Solvent accessible surface area (SASA) calculations highlight changes in solvent exposure, directly affecting ligand accessibility, while radius of gyration (Rg) assessments suggest structural loosening or tightening in response to mutation-induced alterations. Binding free energy calculations using MM-PBSA indicate variability in drug affinity, with mutations disrupting hydrogen-bonding networks and altering ligand stability. Principal Component Analysis (PCA) delineates distinct motion trajectories in mutant proteins, revealing shifts in conformational behavior. Umbrella sampling simulations indicate that while the wild-type HER2-drug complex requires 150 ps to reach equilibrium, the D769H mutant stabilizes within 100 ps, suggesting diminished drug retention. Conversely, the D769Y mutation enhances ligand binding, surpassing wild-type interaction strength. These findings elucidate mutation-specific effects on HER2 structural dynamics and drug interactions, underscoring the need for mutation-tailored therapeutic strategies to mitigate the impact of these variants.

Pituitary Neuroendocrine Tumors (PitNETs) are the most frequently diagnosed intracranial neoplasms in adults. The World Health Organization's 2022 fifth edition classification of pituitary neuroendocrine tumours (PitNETs) maintains an immunohistochemistry based taxonomy that places molecular biology at the centre of diagnosis. This framework provides a solid basis for subtype classification and therapy development. Methylation, defined as the transfer of a methyl group (CH₃) to DNA bases, histone side chains, or RNA nucleotides, is an epigenetic modification that has emerged as a key mechanism in neoplastic transformation. In this review, we synthesise current knowledge on histone, DNA, and RNA methylation in pituitary tumourigenesis, describing their distinct roles and mutual molecular crosstalk. By examining how these epigenetic modifications promote tumour initiation and progression, we assess their potential as drug targets and their translational applicability. Our objective is to propose new research directions and precision treatment strategies that exploit methylation related vulnerabilities, with the goal of improving clinical outcomes for patients with PitNETs.

Malignant tumors currently pose a significant threat to global health. Tumor progression is jointly regulated by genetic mutations and the mechanical properties of the tumor microenvironment (TME), including increased tissue stiffness, elevated fluid pressure, and mechanical compression experienced by circulating tumor cells (CTCs) within microvessels. These mechanical signals are transmitted through mechanosensitive pathways, with the Piezo channel family (Piezo1/Piezo2) serving as a core mediator.With their propeller-like trimeric structure, Piezo channels sense membrane tension, mediate calcium influx, and activate downstream signaling pathways (e.g., MAPK, PI3K/AKT/mTOR, YAP/TAZ), thereby regulating tumor cell proliferation, migration, immune microenvironment remodeling, and cancer stem cell-like transformation. Its expression exhibits tissue specificity and correlates with tumor staging, invasiveness, and pro gnosis.

Piezo1 is upregulated in breast, esophageal, colorectal, glioma, and prostate cancers to promote tumor progression, while its downregulation in lung cancer enhances malignancy.Notably, the Piezo1 channel can be activated by mechanical compression in microcapillaries, subsequently promoting circulating tumor cells to acquire stem cell-like properties through calcium signaling pathways, thereby enhancing their metastatic potential. This discovery not only reveals the pivotal role of mechanical forces in tumor metastasis but also positions the Piezo channel as a promising biomarker for tumor diagnosis and prognostic assessment. Currently, targeted strategies for the Piezo channel-including small-molecule modulators and treatments based on piezoelectric materials-are gradually opening new avenues for precision cancer therapy, although issues such as tissue specificity of function and drug selectivity require further exploration.

Overall, as a vital bridge linking mechanical signals in the tumor microenvironment to cellular biological behavior, Piezo channels hold significant importance for deepening our understanding of tumor mechanisms, developing novel biomarkers, and optimizing therapeutic strategies.

Chemotherapy affects over 300,000 U.S. breast cancer patients, which disrupts the gut microbiome and induces gut inflammation-an effect hypothesized to drive gastrointestinal side effects (e.g., diarrhea, vomiting) experienced by 50%-80% of patients. Preclinical studies have found causal links amongst chemotherapy-induced gut microbiome disruption, systemic inflammation, and brain-mediated side effects. Therefore, the gut microbiome represents a therapeutic target to attenuate chemotherapy side effects. Because clinical populations are administered multiple chemotherapeutics in combination, a comprehensive understanding of which treatments disrupt the gut microbiome‒blood‒brain axis is lacking. Here, translationally-relevant regimens of four commonly used breast cancer chemotherapies (paclitaxel, cyclophosphamide, cisplatin, and doxorubicin) were given to adult female C57BL/6 mice, and inflammatory, metabolomics and/or bacteriome outcomes were measured in the gut, gut contents, blood, and brain tissues, along with a fatigue and anxiety-like behavioral assessment. Many inter-chemotherapy differences were observed but notable findings include prolonged circulation and central proinflammatory signals by paclitaxel and sustained disruption of the gut microbiome by cisplatin. In contrast, cyclophosphamide and doxorubicin modestly disrupted the gut microbiome‒blood‒brain axis. Taken together, this study systematically identified that paclitaxel and cisplatin most robustly disrupted the gut microbiome‒blood‒brain axis, suggesting that those treated with these drugs may benefit the most from gut-targeted interventions for associated side effects.