Cancer is one of the leading causes of mortality around the world accounting for about 10 million deaths in 2020 according to the World Health Organization. The cancer types that claim the most lives around the world include breast cancer, lung cancer, stomach cancer, colon, and rectum cancer. There are a variety of risk factors that can lead to cancers ranging from the type of diet to the type of virus infection. The number of lives claimed by cancer every year can however be reduced through early detection of cancer during which there is a very high chance that the cancer can be cured if appropriate treatment is provided. Today, due to the development of microarray technology, large amounts of data on differentially expressed genes can be obtained from cancerous cells. This vast amount of data, therefore, requires the use of computational tools and databases to store, process, and extract valuable information from the collected data for example discovering new biomarkers for cancer diagnosis. This, therefore, calls for the application of bioinformatics resources to perform this task. The research article, therefore, focuses on how the different bioinformatics tools and databases have been used to improve cancer diagnosis through a systematic literature search on PubMed. From the literature search, it was seen that bioinformatics tools and databases have been used to detect different diagnostic biomarkers that were associated with the different cancer types such as cervical cancer, ovarian cancer, pancreatic cancer, and lung cancer. The biomarkers detected thus help to improve early cancer detection and hence reduce cancer-related mortality. From the literature studied, it was also seen that some of the biomarkers detected for one type of cancer were also common to other cancer types. Bioinformatics, therefore, plays a vital role in the improvement of cancer diagnosis by detecting biomarkers that can be used to diagnose cancer. Bioinformatics also helps in identifying common biomarkers and differentially expressed genes in different cancer types which further improves the process of cancer diagnosis.