Mammalian cells are compartmentalised into membrane bound organelles, which serve distinct functions. Dysregulation of cellular lipid distribution leads to loss of organelle homeostasis and underlie numerous chronic diseases. While methods of spatial proteomics are relatively well established, such as Protein Correlation Profiling (PCP) and hyperLOPIT methods, high throughput organellar lipidomics and integration with organellar proteomics are yet to be established. This study aims to develop a high-throughput method for proteo-lipidomic profiling of organelles, termed integrative Protein and Lipid Organelle Profiling (iPLOP). iPLOP uses a continuous sucrose gradient to roughly separate various membrane bound organelles into different profiles. Lipids and proteins are extracted from the same sucrose gradient fractions and subjected to shotgun proteomics and targeted lipidomics using mass spectrometry. As most lipid species localize to several organelles at varying abundances, lipidomics will aim to quantify the lipid species at each organelle. Several computational analysis approaches will be explored to assign proteome and lipidome to appropriate organelles. Downstream pathway analyses and computational functional prediction will be integrated to determine functional effects of altering organelle composition. Here, we present the development of the iPLOP method and application in studying membrane remodelling abnormalities facilitated by cancer mediators, caveolin-1 and cavin-1, in advanced prostate cancer. We anticipate that applications of iPLOP method will contribute to an improved understanding of the spatial relationship between cellular lipids and proteins in health and disease.