The issues and challenges with cancer biomarkers.

A biomarker is a measurable indicator used to distinguish precisely/objectively either normal biological state/pathological condition/response to a specific therapeutic intervention. The use of novel molecular biomarkers within evidence-based medicine may improve the diagnosis/treatment of disease, improve health outcomes, and reduce the disease's socio-economic impact. Presently cancer biomarkers are the backbone of therapy, with greater efficacy and better survival rates. Cancer biomarkers are extensively used to treat cancer and monitor the disease's progress, drug response, relapses, and drug resistance. The highest percent of all biomarkers explored are in the domain of cancer. Extensive research using various methods/tissues is carried out for identifying biomarkers for early detection, which has been mostly unsuccessful. The quantitative/qualitative detection of various biomarkers in different tissues should ideally be done in accordance with qualification rules laid down by the Early Detection Research Network (EDRN), Program for the Assessment of Clinical Cancer Tests (PACCT), and National Academy of Clinical Biochemistry. Many biomarkers are presently under investigation, but lacunae lie in the biomarker's sensitivity and specificity. An ideal biomarker should be quantifiable, reliable, of considerable high/low expression, correlate with the outcome progression, cost-effective, and consistent across gender and ethnic groups. Further, we also highlight that these biomarkers' application remains questionable in childhood malignancies due to the lack of reference values in the pediatric population. The development of a cancer biomarker stands very challenging due to its complexity and sensitivity/resistance to the therapy. In past decades, the cross-talks between molecular pathways have been targeted to study the nature of cancer. To generate sensitive and specific biomarkers representing the pathogenesis of specific cancer, predicting the treatment responses and outcomes would necessitate inclusion of multiple biomarkers.

EMTiness in pseudo-malignant behavior of trophoblasts during embryo implantation.

Implantation in humans is a multistep process that involves apposition, adhesion, and invasion of the developing blastocyst into the receptive maternal endometrium. Though significant volume of research in this direction has identified important players orchestrating this delicate process, there are still gaps in our understanding of all the sequence of events during embryo implantation. Also, the early pregnancy-related complications that lead to fetal loss and miscarriage often occur in this critical window of implantation, which is primarily defined as the time when the maternal endometrium is supposed to be most receptive to the free blastocyst that emerges out from the zona pellucida. Studies in humans and rodents have identified several mediators like folliculin, LIF, IL11Ra, splicing factor SC35, etc. to be essential for early implantation. Trophoblasts, that form the outer epithelial layer of the blastocyst, participate in the formation of the placenta. During placentation, invasive extravillous trophoblasts (EVTs), migrate into the endometrium, and a transient epithelial to mesenchymal transition (EMT) and remodel the uterine arteries for blood and nutrient exchange.

Potential SARS-CoV-2 interactions with proteins involved in trophoblast functions - An in-silico study.

BACKGROUND: Though a large number of pregnant females have been affected by COVID-19, there is a dearth of information on the effects of SARS-CoV-2 infection on trophoblast function. We explored in silico, the potential interactions between SARS-CoV-2 proteins and proteins involved in the key functions of placenta. METHODS: Human proteins interacting with SARS-CoV-2 proteins were identified by Gordon et al. (2020). Genes that are upregulated in trophoblast sub-types and stages were obtained by gene-expression data from NCBI-GEO and by text-mining. Genes altered in pathological states like pre-eclampsia and gestational diabetes mellitus were also identified. Genes crucial in placental functions thus identified were compared to the SARS-CoV-2 interactome for overlaps. Proteins recurring across multiple study scenarios were analyzed using text mining and network analysis for their biological functions. RESULTS: The entry receptors for SARS-CoV-2 - ACE2 and TMPRSS2 are expressed in placenta. Other proteins that interact with SARS-CoV-2 like LOX, Fibulins-2 and 5, NUP98, GDF15, RBX1, CUL3, HMOX1, PLAT, MFGE8, and MRPs are vital in placental functions like trophoblast invasion and migration, syncytium formation, differentiation, and implantation. TLE3, expressed across first trimester placental tissues and cell lines, is involved in formation of placental vasculature, and is important in SARS-CoV (2003) budding and exit from the cells by COPI vesicles. CONCLUSION: SARS-CoV-2 can potentially interact with proteins having crucial roles in the placental function. Whether these potential interactions identified in silico have effects on trophoblast functions in biological settings needs to be addressed by further in vitro and clinical studies.

De novo assembly of the Indian blue peacock (Pavo cristatus) genome using Oxford Nanopore technology and Illumina sequencing.

BACKGROUND: The Indian peafowl (Pavo cristanus) is native to South Asia and is the national bird of India. Here we present a draft genome sequence of the male blue peacock using Illumina and Oxford Nanopore technology (ONT). RESULTS: ONT sequencing gave ∼2.3-fold sequencing coverage, whereas Illumina generated 150-base pair paired-end sequence data at 284.6-fold coverage from 5 libraries. Subsequently, we generated a 0.915-gigabase pair de novo assembly of the peacock genome with a scaffold N50 of 0.23 megabase pairs (Mb). We predict that the peacock genome contains 23,153 protein-coding genes and 75.3 Mb (7.33%) of repetitive sequences. CONCLUSIONS: We report a high-quality assembly of the peacock genome using a hybrid approach of sequences generated by both Illumina and ONT. The long-read chemistry generated by ONT was useful for addressing challenges related to de novo assembly, particularly at regions containing repetitive sequences spanning longer than the read length, and which could not be resolved with only short-read-based assembly. Contig assembly of Illumina short reads gave an N50 of 1,639 bases, whereas with ONT, the N50 increased by >9-fold to 14,749 bases. The initial contig assembly based on Illumina sequencing reads alone gave 685,241 contigs. Further scaffolding on assembled contigs using both Illumina and ONT sequencing reads resulted in a final assembly of 15,025 super-scaffolds, with an N50 of ∼0.23 Mb. Ninety-five percent of proteins predicted by homology matched with those in a public repository, verifying the completeness of our assembly. Like other phylogenetic studies of avian conserved genes, we found P. cristatus to be most closely related to Gallus gallus, followed by Meleagris gallopavo and Anas platyrhynchos. Compared with the recently published peacock genome assembly, the current, superior, hybrid assembly has greater sequencing depth, fewer non-ATGC sequences, and fewer scaffolds.