No, you cannot. Please use the search function for previous threads on that matter. The crux here is that the condition (tumor/normal) are confounded by study so you cannot distinguish biological from technical/batch effects, and there will be plenty. For illustration, you can go through Basic normalization, batch correction and visualization of RNA-seq data which contains data from the exact same specimen but prepared with different library prep kits. That somewhat mimics different studies. You will see that if you perform DEG analysis between the sample sample, just comparing kits there will be hundreds of DEGs. That means your analysis would be spawned with false calls that do not reflect any biological but pure technical differences. For tumor-only data it will probably come down to either defining sub-groups in your data, either basic on clinical metadata or clustering-based approaches, and then compare these groups with each other.