An Overview of COVID-19 PAN India

COVID -19 is a highly contagious viral disease that affects human populations very differently ranging from mild-to-moderate flu-like symptoms to serious complications involving mainly the respiratory system. The causative pathogen is a new virus Severe Acute Respiratory Syndrome Coronavirus 2. The viral disease gripped millions of lives in a short span, due to which World Health Organization announced it as pandemic on March 11, 2020. Various measures were adopted at local and global levels to stop immediate escalation of the viral infection. A complete lockdown was imposed, movement was restricted, industries were shut down, vehicles were prohibited to ply; only the production and supply of essential services were permitted. On one hand, the fatal disease posed a serious threat to life and quarantine caused loneliness but on the other hand, such unprecedented crisis had a positive impact on overall healing of nature. The economy and health infrastructure of various countries collapsed in fighting the pandemic. To revive, switching over to green economy may be the most viable option and it will also be a climate-conscious approach. The current review article gives an insight about COVID-19 pandemic and fight against it from India’s perspective

Personalized Circulating Tumor DNA Biomarkers Dynamically Predict Treatment Response and Survival In Gynecologic Cancers.

BACKGROUND:High-grade serous ovarian and endometrial cancers are the most lethal female reproductive tract malignancies worldwide. In part, failure to treat these two aggressive cancers successfully centers on the fact that while the majority of patients are diagnosed based on current surveillance strategies as having a complete clinical response to their primary therapy, nearly half will develop disease recurrence within 18 months and the majority will die from disease recurrence within 5 years. Moreover, no currently used biomarkers or imaging studies can predict outcome following initial treatment. Circulating tumor DNA (ctDNA) represents a theoretically powerful biomarker for detecting otherwise occult disease. We therefore explored the use of personalized ctDNA markers as both a surveillance and prognostic biomarker in gynecologic cancers and compared this to current FDA-approved surveillance tools. METHODS AND FINDINGS:Tumor and serum samples were collected at time of surgery and then throughout treatment course for 44 patients with gynecologic cancers, representing 22 ovarian cancer cases, 17 uterine cancer cases, one peritoneal, three fallopian tube, and one patient with synchronous fallopian tube and uterine cancer. Patient/tumor-specific mutations were identified using whole-exome and targeted gene sequencing and ctDNA levels quantified using droplet digital PCR. CtDNA was detected in 93.8% of patients for whom probes were designed and levels were highly correlated with CA-125 serum and computed tomography (CT) scanning results. In six patients, ctDNA detected the presence of cancer even when CT scanning was negative and, on average, had a predictive lead time of seven months over CT imaging. Most notably, undetectable levels of ctDNA at six months following initial treatment was associated with markedly improved progression free and overall survival. CONCLUSIONS:Detection of residual disease in gynecologic, and indeed all cancers, represents a diagnostic dilemma and a potential critical inflection point in precision medicine. This study suggests that the use of personalized ctDNA biomarkers in gynecologic cancers can identify the presence of residual tumor while also more dynamically predicting response to treatment relative to currently used serum and imaging studies. Of particular interest, ctDNA was an independent predictor of survival in patients with ovarian and endometrial cancers. Earlier recognition of disease persistence and/or recurrence and the ability to stratify into better and worse outcome groups through ctDNA surveillance may open the window for improved survival and quality and life in these cancers

Undetectable levels of ctDNA following initial treatment are associated with improved survival.

<p>Kaplan–Meier analysis of progression-free (left panel) and overall survival (right panel) between individuals with undetectable (ctDNA = 0; blue lines) and detectable ctDNA (≥ 1; red lines). Significant differences in progression-free survival (p = 0.001) and overall survival (p = 0.0194) between undetectable and detectable groups.</p

Overview of patient enrollment, clinical follow-up and personalized ctDNA analysis.

<p>Overview of patient enrollment, clinical follow-up and personalized ctDNA analysis.</p