Background At the end of December 2019, a novel strain of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) disease (COVID-19) has been identified in Wuhan, a central city in China, and then spread to every corner of the globe. As of October 8, 2022, the total number of COVID-19 cases had reached over 621 million worldwide, with more than 6.56 million confirmed deaths. Since SARS-CoV-2 genome sequences change due to mutation and recombination, it is pivotal to surveil emerging variants and monitor changes for improving pandemic management. Methods 10,287,271 SARS-CoV-2 genome sequence samples were downloaded in FASTA format from the GISAID databases from February 24, 2020, to April 2022. Python programming language (version 3.8.0) software was utilized to process FASTA files to identify variants and sequence conservation. The NCBI RefSeq SARS-CoV-2 genome (accession no. NC_045512.2) was considered as the reference sequence. Results Six mutations had more than 50% frequency in global SARS-CoV-2. These mutations include the P323L (99.3%) in NSP12, D614G (97.6) in S, the T492I (70.4) in NSP4, R203M (62.8%) in N, T60A (61.4%) in Orf9b, and P1228L (50.0%) in NSP3. In the SARS-CoV-2 genome, no mutation was observed in more than 90% of nsp11, nsp7, nsp10, nsp9, nsp8, and nsp16 regions. On the other hand, N, nsp3, S, nsp4, nsp12, and M had the maximum rate of mutations. In the S protein, the highest mutation frequency was observed in aa 508–635(0.77%) and aa 381–508 (0.43%). The highest frequency of mutation was observed in aa 66–88 (2.19%), aa 7–14, and aa 164–246 (2.92%) in M, E, and N proteins, respectively. Conclusion Therefore, monitoring SARS-CoV-2 proteomic changes and detecting hot spots mutations and conserved regions could be applied to improve the SARS‐CoV‐2 diagnostic efficiency and design safe and effective vaccines against emerging variants.

Lung cancer is the leading cause of cancer-related death worldwide, with non-small-cell lung cancer (NSCLC) being the primary type. Unfortunately, it is often diagnosed at advanced stages, when therapy leaves patients with a dismal prognosis. Despite the advances in genomics and proteomics in the past decade, leading to progress in developing tools for early diagnosis, targeted therapies have shown promising results; however, the 5-year survival of NSCLC patients is only about 15%. Low-dose computed tomography or chest X-ray are the main types of screening tools. Lung cancer patients without specific, actionable mutations are currently treated with conventional therapies, such as platinum-based chemotherapy; however, resistances and relapses often occur in these patients. More noninvasive, inexpensive, and safer diagnostic methods based on novel biomarkers for NSCLC are of paramount importance. In the current review, we summarize genomic and proteomic biomarkers utilized for the early detection and treatment of NSCLC. We further discuss future opportunities to improve biomarkers for early detection and the effective treatment of NSCLC.

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BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a new emerging coronavirus that causes coronavirus disease 2019 (COVID-19). Whole-genome tracking of the SARS-CoV-2 enhanced our understanding of the mechanism of disease, control, and prevent COVID-19 infections.Materials and MethodsIn the current study, we investigated 1221 SARS-CoV-2 protein sequences of Iranian SARS-CoV-2 in the public database of the GISAID from January 2019 to April 2022. Prepare a list of suitable samples and preprocess performed by python programming language. To compare and identify mutation patterns SARS-CoV-2 genome was aligned to the Wuhan-Hu-1 as a reference sequence.ResultsOur investigation revealed that spike-P323L, ORF9c-G50N, NSP14-I42V, spike-D614G, NSP4-T492I, nucleocapsid-R203K, nucleocapsid-G204R, membrane-A63T, membrane-Q19E, NSP5-P132H, envelope-T9I, NSP3-G489S, ORF3a-T24I, membrane-D3G, spike-S477N, Spike-D478K, nucleocapsid-S235F, spike-N501Y, nucleocapsid-D3L, and spike-P861H as the most frequent mutations among the Iranian SARS-COV-2 sequences. Furthermore, it was observed that more than 95 % of the SARS-CoV-2 genome, including NSP7, NSP8, NSP9, NSP10, NSP11, and ORF8, had no mutation when compared to the Wuhan-Hu-1. Finally, our data indicated the ORF3a-T24I, NSP3-G489S, NSP5-P132H, NSP14-I42V, envelope-T9I, nucleocapsid-D3L, membrane-Q19E, and membrane-A63T mutations might be one of the responsible factors for the surge in the SARS-CoV-2 omicron variant wave in Iran.DiscussionOur results highlight the value of real-time genomic surveillance that help to identify novel SARS-CoV-2 variants and could be applied to update SARS-CoV-2 diagnostic tools, vaccine design, and understanding of the mechanisms of adaptation to a new host environment.