Deseq2 getting ANOVA-like result from 3 by 3 factor design

Question

[cwwong13]

I have an experiment that has 3 treatment groups (A, B and C) using 3 different cell types (WT, OE, KD).

I am interested to get the result of: within WT, whether the treatment effect is significant? I am not trying to know whether B vs A or C vs B etc are significant, but want to get the result similar to ANOVA.

How to get the result for OE cells and KD cells?

Similarly, I wonder within treatment A, B, and C: whether the 3 cell types are different?

I have been searching for so long but cannot find a good result for my question. I have tried (and probably made the question more complicated):

dds <- DESeqDataSetFromMatrix(countData = cts,
                              colData = coldata_filtered,
                              design = ~ Treatment + Cell + Treatment:Cell)
dds <- DESeq(dds)

I found that many forums said it can be tested by the LRT of the reduced model: ~ Treatment + Cell. But how to extract the overall Cell effect within treatment A, B, and C?