MD Shakhaowat Hossain

Independent Project

Mapping the Immune Landscape of Lung Cancer with Xenium Spatial Transcriptomics

Self-directed analysis of a public 10x Genomics dataset, conducted independently of my dissertation research.

I analysed a public 10x Genomics Xenium lung cancer dataset end to end at single-cell resolution. Starting from the raw instrument output, the workflow covers transcript- and cell-level quality control, re-segmentation, cell-type annotation validated against a reference atlas, H&E image alignment, spatial graph construction, neighbourhood and niche analysis, tissue-domain mapping, ligand-receptor cell-cell communication and spatial differential expression, with the key results re-tested for segmentation artefacts.

Key findings

• Predominantly CD8-excluded tumour regions: Only 12% of GZMK+ CD8 T cells were within 15 µm of a tumour cell, compared with 34% of non-tumour cells overall; 65% of 119 scored tumour tiles were classified as immune-excluded under default thresholds.
• Six TLS-like aggregates: Six tertiary lymphoid structure-like aggregates contained 71% of B cells. CCR7 was detected in 36% of GZMK+ CD8 T cells within the aggregates versus 11% within 15 µm of tumour cells, with the difference retained after re-segmentation.
• Myeloid-associated PD-L1 expression: PD-L1 transcripts were detected in 12–13% of CXCL9+ macrophages and LAMP3+ dendritic cells, compared with less than 1% of tumour cells.

Working with single-cell or spatial transcriptomics data? I collaborate on analyses from quality control through statistics, visualization and biological interpretation, with an emphasis on rigour and reproducible code. I am especially interested in immunology and translational questions. Contact me at [email protected].