Cancer is globally the second leading cause of death. Early diagnosis of cancer is crucial for reducing the associated morbidity and mortality along with the growing cancer burden. In resource-poor settings, cancer is often diagnosed at a late-stage of the disease resulting in lower survival and potentially greater morbidity and higher costs of treatment. Even in countries with a strong health care system and services, many cancer cases are diagnosed at a late stage due to the lack of proper early detection tools. The delay in cancer diagnosis and inaccessible treatment are therefore the critical bottle necks for cancer control. Currently, tissue biopsy is considered as the gold standard technique for the accurate diagnosis of solid tumours. Furthermore, multiple protein biomarkers are used in either diagnosis or therapy monitoring of cancer. However, these techniques are limited either by detection at the later stage or being tedious, costly and time consuming. Moreover, the lack of sophisticated scientific equipment in resource-poor settings leads to an urgent need for developing methods that rely on minimally equipped facilities and deliver sensitive and specific results in a rapid and inexpensive manner. The overall objective of my PhD is to develop simple, inexpensive and accurate platforms for early detection of cancer. To achieve the above-mentioned objective, my first research endeavour was to develop a cancer diagnostic technique by detection of autoantibodies against tumour associated autoantigens (TAAs). Autoantibodies are produced against TAAs long before the appearance of any symptoms and thus can serve as promising biomarker of cancer. In this study, we used gold embedded magnetic nanoparticles functionalized with the tumour antigen p53. The p53 conjugated nanoparticles were dispersed into the serum of colon cancer sample, where they bound to p53 specific autoantibodies. Electrochemical detection demonstrated the limit of detection as low as 0.02 U ml-1. In addition, spectrophotometric and visual (naked eye) measurements for rapid detection of autoantibodies was performed. Overall, the platform reported had shown excellent analytical performance with high specificity and sensitivity. In the second part of the thesis, I explored a diagnostic approach for cancer based on biophysical properties of the cells. Cell stiffness is an important marker that changes in metastatic cells. Measurement of cell stiffness may predict the possible metastasis of cells. Here, we used an electromagnetic cell stretching device to apply cyclic strain onto the cells. The effects of stretching forces on cancer cells was first evaluated by morphological examination. I observed that mechanical force applied to cancer cells increased the rearrangement of actin microfilament and enhanced their expression. Cancer cells were also observed to reduce their roundness (as determined by perimeter: area), increasing their length and forming filopodia in the initial stretching cycle. As biophysical clues are present long before the onset of cancer, this work suggested that the rigidity measured with the cell stretching platform can serve as an indicator of the cancer status of cells. I further investigated the effect of stretching on the expression of RhoA and Rac1 by using ELISA (Enzyme Linked Immunosorbent assay) in breast and liver cancer cells. RhoA and Rac1 are member of RhoGTPases and are involved in maintaining homeostasis in cells during mechanical stresses. We noticed that stretching cancer cells induces significantly higher expression of RhoA and Rac1 markers as compared to non-stretched cells and stretched control cells in vitro. This stretching strategy indicate the ability to detect and quantify signals, which are normally too weak to be detected. The major advantage of this platform was the enhancement of the sensitivity of assay by overexpression of the markers. This simple and effective approach ensured a sensitive and inexpensive method to detect cancer protein biomarkers. Collectively, this thesis reports simple platforms for cancer diagnostics either by estimating the autoantibodies or by exploiting the biophysical cues. Estimating difference in biophysical properties have opened a new avenue on cancer diagnostics research. Extending some fundamental research and further evaluation on a larger cancer type and sample cohort would increase the translational readiness of the platforms reported in this thesis.