Biology subjects

Banda, K.

Publications and source records attributed to Banda, K..

4 recordsLinked to original sources

bioRxiv2025

ADAPTIVE MULTI-SCALE GRAPH TRANSFORMER FRAMEWORK FORHISTOPATHOLOGICAL IMAGES

Whole slide images (WSIs) contain hierarchical information from cellular to tissue architecture but their gigapixel scale poses major memory and computational challenges. Existing multi-scale graph and transformer models capture complex WSI features effectively but struggle with efficiency. We propose an Adaptive Multi-Scale Graph Transformer (AMGT) for WSI classification that addresses this limitation through two key modules: a Self-Guided Token Aggregation (SGTA) mechanism that fuses multi-resolution features to reduce redundancy, and a Prototypical Transformer (PT) that groups similar tokens into phenotype-representative prototypes with linear complexity. This design preserves essential spatial and semantic information, substantially lowering memory cost and improving interpretability by prototypical learning. AMGT achieves superior performance and efficiency, outperforming state-of-the-art models by 1.8% and 5.3% AUC on high-grade ovarian cancer and Camelyon16 datasets, respectively. These results demonstrate AMGTs capacity for scalable, interpretable multi-scale representation learning.

bioinformatics↗

bioRxiv2025

HRDPath: An Explainable Multi-Model Deep Learning Architecture for Predicting Homologous Recombination Deficiency from Histopathology Images

Homologous recombination deficiency (HRD) is a critical biomarker for guiding treatment decisions in high-grade serous tubo-ovarian carcinoma (HGSOC), a cancer with few reliable biomarkers. However, existing genomic-based tests for HRD are variable, expensive, and time-consuming. To this end, we developed HRDPath, a novel patient-level deep learning architecture that combines the strengths of two complementary models with a multi-task design, to predict genomically derived HRD status from whole slide images in HGSOC. HRDPath was comprehensively validated across three datasets and benchmarked against leading deep learning models. It achieved an AUC of 0.846, surpassing previously reported H&E-based HRD prediction results for HGSOC images by 0.09, and for the first time, reporting a specificity of 0.938, where accuracy significantly increased when multiple slides per patient were used. Our proposed patient-level approach and interpretability pipeline enhance model trustworthiness and reveal important clinical and biological insights into HRD-positive cancers, highlighting the associated morphological and pathological changes at the cellular and tissue levels. HRDPath is a potentially accessible and scalable digital biomarker that could improve ovarian cancer diagnosis and therapy selection.

bioinformatics↗

bioRxiv2021

Specific BRCA and immune configurations determine optimal response to platinum-based chemotherapy in triple negative breast and ovarian carcinomas

Loss of homologous recombination repair (HRR) via germline and somatic BRCA1 or BRCA2 gene mutations and via BRCA1 promoter methylation has been associated with better response to platinum agents and PARP inhibitors, in both triple negative breast cancer (TNBC) and ovarian carcinoma (OvCa). A major conundrum arising from recent clinical studies is why cancers with BRCA1 promoter methylation (BRCA1meth) respond more poorly as compared to those bearing mutations in BRCA1 and BRCA2 (BRCAmut), given the biologically equivalent HRR deficiency in both states. We dissected this problem through detailed genomic analyses of primary TNBC and OvCa cohorts, as well as experimentation with patient-derived xenograft (PDX) models and genetically engineered cell lines. Using the precise genomic scar of the tandem duplicator phenotype as a precise genomic indicator of BRCA1 deficiency, we found that, in all cohorts, BRCA1mut and BRCA1meth cancers share an equivalent degree of BRCA1-linked genomic rearrangements. Nonetheless, we consistently found that patients with BRCAmut cancers, but not those with BRCA1meth cancers, had significantly better response outcomes when compared to those with BRCA proficient cancers. When fully promoter methylated BRCA1 PDX TNBCs were exposed to a single short course of platinum chemotherapy an unmethylated BRCA1 promoter allele emerged in resultant tumors associated with an increase in BRCA1 expression. A separate analysis of PDXs derived from treatment naive TNBCs featured complete methylation of the BRCA1 promoter, whereas those derived from post-chemotherapy TNBCs invariably had only partial methylation. PDXs with partial methylation were significantly associated with lower response rates to in vivo platinum-based therapy compared to those with complete promoter methylation. Using single cell clonal expansions from a partially BRCA1meth PDX, we confirmed that the reduced level of methylation was due to the demethylation of one of the BRCA1 promoter alleles and not to the outgrowth of a non-methylated clone. Clinically, analysis of primary OvCas confirmed that high levels of BRCA1 methylation were significantly associated with reduced BRCA1 gene expression whereas cancers with lower levels of BRCA1 methylation had expression levels approaching those found in BRCA1 proficient cancers. These data suggest that unlike BRCAmut cancers, where HRR deficiency is achieved via mutations that are genetically fixed, BRCA1meth cancers are highly adaptive to genotoxin exposure and more likely to recover BRCA1 expression, which may explain their poorer therapeutic response. We further found that an increased immune transcriptional signal, especially an elevated M1 macrophage signature, is associated with enhanced response to platinum-based chemotherapy only in patients with BRCA proficient cancers, in both TNBC and OvCa cohorts underscoring the importance of characterizing molecular heterogeneity to enhance predictive precision in assigning response probabilities in TNBC and OvCa.

cancer biology↗

bioRxiv2017

Multidisciplinary field research in Kabwe, Zambia, towards better understanding of lead contamination of the city - A short report from a field survey

Heavy metal contamination is a serious issue in many post-mining regions around the world. Kabwe town, Zambia, is known as one of the most polluted cities in the world, where high lead (Pb) levels have been reported in soils, plants, animals and human blood. Multidisciplinary approaches are critically needed to understand the current situation and to remediate the polluted area. In the current research, a large-scale preliminary field survey was performed to understand the current situation in Kabwe and to plan future mitigation approaches. Three aspects were mainly observed; 1) plant communities during the dry season in Kabwe city, 2) spectral images of the land surfaces in various locations in Kabwe and 3) Pb concentrations in soils and water. Overall, >15 different plant species were observed and many of them maintained their green colour even during the dry season. Some tree species, for example, Caesalpiniaceae and Fabaceae families may be utilised as phytostabilization approaches although their impacts on the soil Pb mobility should be further studied. For the spectral images, we used a handmade portable spectrometer, and our obtained spectral images showed typical curves observed from soils. These data may be used to understand the distribution of different soil types in this area, using aboveground images such as satellite images. For Pb concentrations in soils, extremely high total Pb levels (>1,000 ppm) was observed only within 2 km from the mining site. There was a weak but a positive correlation between the total and soluble Pb thus further study should also focus on the mobility of Pb from soils to plant ecosystems.

ecology↗