Giα proteins exhibit functional differences in the activation of ERK1/2, Akt and mTORC1 by growth factors in normal and breast cancer cells

Background In a classic model, Giα proteins including Gi1α, Gi2α and Gi3α are important for transducing signals from Giα protein-coupled receptors (GiαPCRs) to their downstream cascades in response to hormones and neurotransmitters. Our previous study has suggested that Gi1α, Gi2α and Gi3α are also important for the activation of the PI3K/Akt/mTORC1 pathway by epidermal growth factor (EGF) and its family members. However, a genetic role of these Giα proteins in the activation of extracellular signal-regulated protein kinase 1 and 2 (ERK1/2) by EGF is largely unknown. Further, it is not clear whether these Giα proteins are also engaged in the activation of both the Akt/mTORC1 and ERK1/2 pathways by other growth factor family members. Additionally, a role of these Giα proteins in breast cancer remains to be elucidated. Results We found that Gi1/3 deficient MEFs with the low expression level of Gi2α showed defective ERK1/2 activation by EGFs, IGF-1 and insulin, and Akt and mTORC1 activation by EGFs and FGFs. Gi1/2/3 knockdown breast cancer cells exhibited a similar defect in the activations and a defect in in vitro growth and invasion. The Giα proteins associated with RTKs, Gab1, FRS2 and Shp2 in breast cancer cells and their ablation impaired Gab1’s interactions with Shp2 in response to EGF and IGF-1, or with FRS2 and Grb2 in response to bFGF. Conclusions Giα proteins differentially regulate the activation of Akt, mTORC1 and ERK1/2 by different families of growth factors. Giα proteins are important for breast cancer cell growth and invasion.Fil: Wang, Zhanwei. University of Hawaii Cancer Center. Honolulu; Estados UnidosFil: Dela Cruz, Rica. University of Hawaii Cancer Center. Honolulu; Estados UnidosFil: Ji, Fang. Shanghai Jiao Tong University . Sahnghai; ChinaFil: Guo, Sheng. University of Hawaii Cancer Center. Honolulu; Estados Unidos. Shanghai Jiaotong University. Shangha; Estados UnidosFil: Zhang, Jianhua. Shanghai Jiaotong University. Shangha; Estados Unidos. University of Hawaii Cancer Center. Honolulu; Estados UnidosFil: Wang, Ying. David Geffen School of Medicine at UCLA. Los Angeles; Estados UnidosFil: Feng, Gen-Sheng. University of California at San Diego; Estados UnidosFil: Birnbaumer, Lutz. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. National Institutes of Health; Estados UnidosFil: Jiang, Meisheng. David Geffen School of Medicine at UCLA. Los Angeles; Estados UnidosFil: Chu, Wen Ming. University of Hawaii Cancer Center. Honolulu; Estados Unido

COVID-19 in Austin, Texas: Relaxing Social Distancing Measures

To support planning by the city of Austin and Travis County, we analyzed the Austin-Round Rock module of our US COVID-19 Pandemic Model to project the number of hospitalizations under different scenarios for relaxing social distancing measures following the March 24th Stay Home-Work Safe order. Note that the results presented herein are based on multiple assumptions about the transmission rate and age-specific severity of COVID-19. There is still much we do not understand about the transmission dynamics of this virus, including the extent of asymptomatic infection and transmission. These results do not represent the full range of uncertainty. Rather, they are meant to serve as plausible scenarios for gauging the likely impacts of social distancing measures in the Austin-Round Rock Metropolitan Area. We have updated our model inputs based on the daily number of COVID-19 hospitalizations in the Austin-Round Rock MSA between March 13 and April 19, 2020. The data suggest that social distancing following the March 24th Stay Home-Work Safe order has resulted in a 94% reduction in COVID-19 transmission, with our uncertainty in this estimate ranging from 70% and 100%. The data also suggest that approximately 13.6% of symptomatic cases are detected (i.e., reported as confirmed cases). We are posting these results prior to peer review to provide intuition for both policy makers and the public regarding both the threat of COVID-19 and the extent to which social distancing measures can mitigate that threat. Our projections indicate that the Stay Home-Work Safe has likely prevented a COVID-19 healthcare crisis in the region during the first wave of the pandemic. When current measures are relaxed, we may see more COVID-19 transmission in the area leading to a second pandemic wave. Whether or not and how quickly COVID-19 cases and hospitalizations rise in the second wave will critically depend on the extent to which individuals and communities continue to take steps to reduce the risks of transmission.Integrative Biolog

COVID-19 in Austin, Texas: Epidemiological Assessment of Grocery Shopping

There are an estimated 24,000 grocery store workers in the Austin-Round Rock metropolitan area (MSA) representing 2% of the labor force [1]. The Austin Stay Home - Work Safe order that was issued on March 24, 2020 and extended on April 13, 2020 restricts non-essential work, but permits work in grocery stores and public grocery shopping [2,3]. Daily interactions between grocery workers and the general population may undermine efforts to reduce person-to-person contact, and exacerbate the individual and city-wide risks associated with COVID-19 transmission. In response to a request from the city of Austin, we projected the epidemiological impacts of grocery work under different assumptions regarding the effectiveness of precautionary measures taken by workers and shoppers in grocery stores. To do so, we modified the Austin-Round Rock module of our US COVID-19 Pandemic Model to explicitly include a population subgroup representing grocery workers and contacts that occur between members of the general public and grocery workers in stores. As a base case scenario, we assumed that grocery workers would maintain typical workforce contact rates, estimated as twice the average workplace contacts for 18-49 year olds in the general population. Our analysis suggests that grocery shopping can considerably increase the community-wide risk of COVID-19 and that both shoppers and workers can and should do their part to protect themselves and others from transmission in stores. Furthermore, the risk of COVID-19 hospitalizations within the population of grocery workers is expected to be much higher than that in the non-working 18-49 year old population.Integrative Biolog

Risk for Transportation of Coronavirus Disease from Wuhan to Other Cities in China.

On January 23, 2020, China quarantined Wuhan to contain coronavirus disease (COVID-19). We estimated the probability of transportation of COVID-19 from Wuhan to 369 other cities in China before the quarantine. Expected COVID-19 risk is >50% in 130 (95% CI 89-190) cities and >99% in the 4 largest metropolitan areas

Serial Interval of COVID-19 among Publicly Reported Confirmed Cases.

We estimate the distribution of serial intervals for 468 confirmed cases of coronavirus disease reported in China as of February 8, 2020. The mean interval was 3.96 days (95% CI 3.53-4.39 days), SD 4.75 days (95% CI 4.46-5.07 days); 12.6% of case reports indicated presymptomatic transmission

COVID-19 serial interval estimates based on confirmed cases in public reports from 86 Chinese cities

As a novel coronavirus (COVID-19) continues to spread widely and claim lives worldwide, its transmission characteristics remain uncertain. Here, we present and analyze the serial intervals-the time period between the onset of symptoms in an index (infector) case and the onset of symptoms in a secondary (infectee) case-of 339 confirmed cases of COVID-19 identified from 264 cities in mainland China prior to February 19, 2020. Here, we provide the complete dataset in both English and Chinese to support further COVID-19 research and modeling efforts.Integrative Biolog

COVID-19 Healthcare Demand Projections: 22 Texas Cities

To support planning by cities across Texas, we analyzed all 22 Texas city modules of our US COVID-19 Pandemic Model​ to project the number of hospitalizations under four different social distancing scenarios. Note that the results presented herein are based on multiple assumptions about the transmission rate and age-specific severity of COVID-19. There is still much we do not understand about the transmission dynamics of this virus, including the extent of asymptomatic infection and transmission. We update our model inputs on a daily basis, as our understanding of the virus improves. Appendix 1 below provides our current estimates. These results are not forecasts and do not represent the full range of uncertainty. Rather, they are meant to serve as plausible scenarios for gauging the likely impacts of social distancing measures in Texas cities. We are sharing these results prior to peer review to provide intuition for policy makers regarding the immediate threat of COVID-19, the risks of medical surges, and the extent to which early social distancing measures can mitigate the threat. Our projections indicate that COVID-19 may quickly exceed healthcare capacity across Texas cities and that extensive social distancing measures can both delay and diminish pandemic surges.Integrative Biolog

COVID-19 Healthcare Demand Projections: Austin, Texas

To support planning by the city of Austin and Travis County, we analyzed the Austin-Round Rock module of our US COVID-19 Pandemic Model to project the number of hospitalizations under different social distancing scenarios. Note that the results presented herein are based on multiple assumptions about the transmission rate and age-specific severity of COVID-19. There is still much we do not understand about the transmission dynamics of this virus, including the extent of asymptomatic infection and transmission. These results do not represent the full range of uncertainty. Rather, they are meant to serve as plausible scenarios for gauging the likely impacts of social distancing measures in the Austin-Round Rock Metropolitan Area. We have updated our model inputs based on the daily number of COVID-19 hospitalizations in the Austin-Round Rock MSA between March 13 and April 19, 2020. The data suggest that social distancing following the March 24th Stay Home-Work Safe order has resulted in a 94% reduction in COVID-19 transmission, with our uncertainty in this estimate ranging from 55% and 100%. The data also suggest that approximately 13.6% of symptomatic cases are detected (i.e., reported as confirmed cases). We are posting these results prior to peer review to provide intuition for both policy makers and the public regarding both the immediate threat of COVID-19 and the extent to which early social distancing measures are mitigating that threat. Our projections indicate that the Stay Home-Work Safe has delayed and possibly even prevented a COVID-19 healthcare crisis in the region.Integrative Biolog

The effectiveness of COVID-19 testing and contact tracing in a US city

Although testing, contact tracing, and case isolation programs can mitigate COVID-19 transmission and allow the relaxation of social distancing measures, few countries world-wide have succeeded in scaling such efforts to levels that suppress spread. The efficacy of test-trace-isolate likely depends on the speed and extent of follow-up and the prevalence of SARS-CoV-2 in the community. Here, we use a granular model of COVID-19 transmission to estimate the public health impacts of test-trace-isolate programs across a range of programmatic and epidemiological scenarios, based on testing and contact tracing data collected on a university campus and surrounding community in Austin, TX, between October 1, 2020, and January 1, 2021. The median time between specimen collection from a symptomatic case and quarantine of a traced contact was 2 days (interquartile range [IQR]: 2 to 3) on campus and 5 days (IQR: 3 to 8) in the community. Assuming a reproduction number of 1.2, we found that detection of 40% of all symptomatic cases followed by isolation is expected to avert 39% (IQR: 30% to 45%) of COVID-19 cases. Contact tracing is expected to increase the cases averted to 53% (IQR: 42% to 58%) or 40% (32% to 47%), assuming the 2- and 5-day delays estimated on campus and in the community, respectively. In a tracing-accelerated scenario, in which 75% of contacts are notified the day after specimen collection, cases averted increase to 68% (IQR: 55% to 72%). An accelerated contact tracing program leveraging rapid testing and electronic reporting of test results can significantly curtail local COVID-19 transmission.This research was supported by NIH grant R01 AI151176 (to X.W., Z.D., S.J.F., and L.A.M.), CDC grant U01 IP001136 (to X.W.,Z.D., S.J.F., and L.A.M.), and a donation from Love, Tito’s (the philanthropic arm of Tito’s Homemade Vodka, Austin, TX) to the University of Texas to support the modeling of COVID-19 mitigation strategies (to X.W., Z.D., M.L., L.A.M., and D.B.). D.B.’s effort on this project was also supported by core funds of the Dell Medical School at UT.Dell Medical SchoolIntegrative Biolog

COVID-19 Healthcare Demand Projections: Austin, Texas

To support planning by the city of Austin, we analyzed the Austin-Round Rock module of our US COVID-19 Pandemic Model​ to project the number of hospitalizations under four different social distancing scenarios. Note that the results presented herein are based on multiple assumptions about the transmission rate and age-specific severity of COVID-19. There is still much we do not understand about the transmission dynamics of this virus, including the extent of asymptomatic infection and transmission. We update our model inputs on a daily basis, as our understanding of the virus improves. These results do not represent the full range of uncertainty. Rather, they are meant to serve as plausible scenarios for gauging the likely impacts of social distancing measures in the Austin-Round Rock Metropolitan Area. We are posting these results prior to peer review to provide intuition for both policy makers and the public regarding both the immediate threat of COVID-19 and the extent to which early social distancing measures can mitigate that threat. Our projections indicate that without extensive social distancing measures, the emerging outbreak will quickly surpass healthcare capacity in the region. Although these analyses are specific to the Austin-Round Rock metropolitan area, we expect that the impacts of the mitigation strategies will be qualitatively similar for cities throughout the US.Integrative Biolog