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Cervical cancer remains a leading cause of cancer-related deaths in women worldwide, with limited treatment options for advanced stages and therapy-resistant cases. Despite advances in treatment, the variability in the patient response to standard therapies underscores the need for molecular biomarkers to guide personalized treatment strategies. This study aimed to explore the transcriptomic changes associated with the therapeutic response in locally advanced cervical cancer, focusing on 770 immune-related genes. We employed a digital multiplexed gene expression analysis, comparing gene expression profiles between matching pre- and post-treatment samples. The results revealed the significant upregulation of C7 and EGR2 in the post-treatment samples, suggesting that enhanced immune activity is a key factor in therapeutic success. Conversely, IL17RB, S100A7, and SAA1 were upregulated in the pre-treatment samples, potentially indicating resistance mechanisms. Pathway enrichment analysis highlighted that the immune response and apoptosis pathways are crucial to post-treatment changes. These findings suggest that C7, EGR2, and IL17RB may serve as biomarkers for predicting therapeutic outcomes and could inform the development of more effective, individualized treatment strategies for cervical cancer. This study provides new insights into the molecular mechanisms underlying treatment response and resistance.

Tag-Seq is a high-throughput approach used for discovering SNPs and characterizing gene expression. In comparison to RNA-Seq, Tag-Seq eases data processing and allows detection of rare mRNA species using only one tag per transcript molecule. However, reduced library complexity raises the issue of PCR duplicates, which distort gene expression levels. Here we present a novel Tag-Seq protocol that uses the least biased methods for RNA library preparation combined with a novel approach for joint PCR template and sample labeling. In our protocol, input RNA is fragmented by hydrolysis, and poly(A)-bearing RNAs are selected and directly ligated to mixed DNA—RNA P5 adapters. The P5 adapters contain i5 barcodes composed of sample-specific (moderately) degenerate base regions (mDBRs), which later allow detection of PCR duplicates. The P7 adapter is attached via reverse transcription with individual i7 barcodes added during the amplification step. The resulting libraries can be sequenced on an Illumina sequencer. After sample demultiplexing and PCR duplicate removal with a free software tool we designed, the data are ready for downstream analysis. Our protocol was tested on RNA samples from predator-induced and control Daphnia microcrustaceans.