Results and Discussion

In a typical heat map, each row represents a gene, and each column represents a sample. The color intensity of each square in the grid corresponds to the expression level of the gene in the corresponding sample according to the color gradient given, with brighter colors indicating higher expression and darker colors indicating lower expression. They are useful in identifying patterns and trends in gene expression data, such as clusters of genes with similar expression patterns or samples with similar gene expression profiles.

The bar plots below represent the expression levels of each particular gene across the normal and tumor conditions, with the height of the bar indicating the magnitude of expression.

Gene ontology (GO) enrichment analysis is a powerful tool for interpreting the biological significance of sets of genes derived from high-throughput experiments like RNA sequencing (RNA-seq). By identifying overrepresented GO terms within gene sets, it provides insights into gene function and biological processes.

PCA plots provide a powerful way to explore and visualize complex gene expression data, aiding in the identification of patterns and differences between biological samples that can guide subsequent analyses, such as differential gene expression analysis. PCA does not discard any samples or characteristics (variables). Instead, it reduces the overwhelming number of dimensions by constructing principal components (PCs). PCs describe variation and account for the varied influences of the original characteristics. Such influences, or loadings, can be traced back from the PCA plot to find out what produces the differences among clusters. Samples that cluster together are more similar in terms of gene expression profiles while those that cluster apart are differentially expressed.

Specific genes that we found significantly upregulated in our studies include KRT79, KRT1, and KRT2, along with PM20D1 and DES. Keratins (KRTs) are the intermediate filament-forming proteins of epithelial cells and are known to play a critical role in several aspects of cancer pathophysiology. Studies from Takan et al., Han et al., and Kim et al. have highlighted that alterations in keratin expression correlate with cancer invasion, metastasis, and epithelial-mesenchymal transition, or EMT. All of these factors are known to be primarily responsible for the aggression and metastasis of breast cancer. DES, a gene that encodes for desmin, is involved in maintaining the structural integrity and function of muscle fibers which are often differentially expressed in smooth muscle tumors or mesenchymal-origin tumors. PM20D1 (Peptidase M20 Domain-Containing 1) has only been highlighted in the last few years and changes in its methylation and expression levels have been reported to be associated with several disease phenotypes. A direct link TNBC is yet to be established. 

Some genes that we highlighted as downregulated in tumor cells, substantially as compared to healthy cells include MYBL2 , EN1, FDCSP and CXCL10. FDCSP supports immune cell interactions, particularly with T follicular helper cells (TFHs) and chemokine pathways critical for immune cell recruitment. In cancer, FDCSP downregulation can disrupt these interactions, leading to impaired immune surveillance and reduced infiltration of cytotoxic T cells into the tumor microenvironment; however, a direct link to its upregulation in TNBC has not been reported elsewhere. MYBL2 and EN1 are known to be a central regulator in progression of cancers such as bladder cancer, prostate cancer etc. the downregulation of such a downregulator is striking and can indicate towards a more complicated gene regulation in case of TNBC cells .We also found a bunch of HIST1 family genes downregulation, which can be correlated with the role of genomic stability and histone post-translational modifications involved in tumor suppression. CXCL10, also known as interferon-inducible protein 10 (IP-10), plays several important roles in immune regulation. CXCL10 is a chemokine that attracts various immune cells, particularly T cells, natural killer (NK) cells, and monocytes/macrophages, to sites of inflammation or tissue injury. It has been well studied previously that production of CXCL10 is inversely correlated with tumor progression which results in a marked reduction in tumor-associated angiogenesis. Other studies highlight the role of CXCL10 in inhibiting the growth of cervical carcinoma through an increase in the apoptotic rate which reasonably explains its downregulation in tumor cells as observed in our work. 

Apart from directly looking at the identity of the DEGs, we also found a significant enrichment of GO terms related to cell motility, cell migration, and its regulation among the upregulated genes in tumor samples compared to the normal samples. This enrichment suggests an active involvement of these genes in promoting tumor progression and metastasis. By elucidating the specific biological processes affected by dysregulated gene expression, these findings can contribute to a better understanding of the molecular mechanisms driving TNBC development and open up new potential drug targets.