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Archive for the ‘Cancer Screening’ Category

Noninvasive blood test can detect cancer 4 years before conventional diagnosis

Reporter : Irina Robu, PhD

Several international researchers at  Fudan University and at Singlera Genomics have developed a noninvasive blood test, PanSeer that can detect whether a patient with five common type of cancers such as stomach, esophageal, colorectal, lung and liver cancer; four years before the condition can be diagnosed by the current methods. Early detection is significant for the reason that the survival of cancer patients increases when the disease is identified at early stages, as the tumor can be surgically removed or treated with suitable drugs. Yet, only a partial number of early screening tests exist for a few cancer types.

The blood test detected cancer in 91 percent of samples from individuals who have been asymptomatic when the samples were collected, but only diagnosed with cancer one to four years later. It was found that the test can accurately detect cancer in 88 percent from samples of 113 patience who were diagnosed. The blood test also detects cancer free samples 95 percent of the time.

What is clear is that the study is unique, in that the scientists had access to blood samples from patients who were asymptomatic but not diagnosed yet. This permitted the researchers to design a test that can find a cancer marker much earlier than conventional diagnosis. The sample were collected as part of 10-year longitudinal study started in 2007 by Fudan University in China.

The researchers highlight that the PanSeer assay is improbable to predict which patients will later go on to develop cancer. As a substitute, it is most possible identifying patients who already have cancerous growths, but continue  to be asymptomatic for current detection methods. The team decided that further large-scale longitudinal studies are needed to confirm the potential of the test for the early detection of cancer in pre-diagnosis individuals.

SOURCE

https://www.universityofcalifornia.edu/news/non-invasive-blood-test-can-detect-cancer-4-years-conventional-diagnosis-methods?utm_source=fiat-lux

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National Cancer Institute Director Neil Sharpless says mortality from delays in cancer screenings due to COVID19 pandemic could result in tens of thousands of extra deaths in next decade

Reporter: Stephen J Williams, PhD

UPDATED: 08/14/2023

A Cross Sectional Study Reveals What Oncologists Had Feared: Cancer Screenings During Pandemic Has Decreased, leading to Decreased Early Detection

As discussed in many articles here on COVID-19 and cancer, during the pandemic many oncologists were worried that people slowed getting their cancer screenings due to health risks due to the COVID-19 outbreak.  Governmental agencies went as far to project upticks in future cancer rates, as preventative screening rates were down due to closed hospitals, shuttered services, or patient trepidation during the height of the pandemic.  As many oncologists voiced, a decrease in cancer screenings might lead to missing out on the early stages of the disease, when most treatable. Now, reported in a Lancet cross-sectional analysis by investigators at ACS and University of Texas Southwest (1), we have the first indication of the effects of this decrease in preventative screening, namely decreased early detection and diagnosis.

The authors used data from the US National Cancer Database, a nationwide hospital-based cancer registry, to perform a cross sectional nationwide assessment of the prevalence of new cancer diagnosis before, during, and after the height of the pandemic (March 1 2020 to December 31, 2020).  Newly diagnosed cases of first primary malignant cancer between Jan1, 2018 to Dec 31, 2020 were identified and monthly and annual counts and stage distributions were caluculated andpresented as adjusted odds ratios (aORs).  They also used the period from 2018 to Jan 2020 as a baseline or prepandemic level of newly diagnosed cancer.

Results of this analysis identified 2,404,050 adults with newly diagnosed cancer during study period 2018 to 2020.  The monthly number of new cancer diagnoses (all stages) decreased significantly after the start of the COVID-19 pandemic in March 2020.  However new cancer diagnosis returned to pre-pandemic levels by end of 2020.  The decrease in diagnosis was largest for stage I diseases however the odds of being diagnosed with late stage IV disease were higher in 2020 than in 2019.  When the authors stratified the cohorts based on sociodemographic groups, interestingly those most affected (with lowest diagnosis rates during the pandemic) were those living in socioeconomic deprived areas, hispanics, asian americans, pacific Islanders, and uninsured individuals.

The authors’ interpretations are a warning: Substantial cancer underdiagnosis and decreases in the proportion of early stage diagnoses occurred during 2020 in the USA, particularly among medically underserved individuals. Monitoring the long-term effects of the pandemic on morbidity, survival, and mortality is warranted.

 

 

Evidence before this study

We searched PubMed using the terms “COVID”, “pandemic”, and “cancer” for studies published in English between

March 1, 2020, and Nov 30, 2022. Health care was disrupted during the emergence of the COVID-19 pandemic. In the USA, rapid decreases in screening were reported for nearly all types of cancer screening services after the declaration of the COVID-19 national emergency. Decreased screening, and delayed and forgone routine check-ups or health-care visits, can lead to underdiagnosis of cancer, especially for early stage disease for which treatment is most effective. Several studies have identified reduced use of diagnostic procedures and decreases in the number of newly diagnosed patients during 2020 in the USA. However, these studies were done in selected populations, in specific geographical areas, or for only a single cancer type, limiting understanding of the COVID-19 pandemic on cancer burden nationally.

Added value of this study

Using a recently released nationwide cancer registry dataset, we comprehensively evaluated changes in cancer diagnoses and stage distribution during the first year of the COVID-19 pandemic by cancer type and key sociodemographic factors in the USA.

Implications of all the available evidence

Along with existing evidence, our findings should help to inform future policy and cancer care delivery interventions to improve access to care for underserved populations. Research is warranted to monitor the long-term effects of the underdiagnosis of early stage cancer identified in this study on morbidity, mortality, and disparities in health outcomes.

Results

The main results from the paper are summarized below:

 

Between 2020 and 2019, annual stage I diagnoses decreased by 17·2% (95% CI 16·8–17·6), and annual stage IV diagnoses decreased 9·8% (9·2–10·5). Notably, by race and ethnicity, the largest percentage reduction in stage I diagnoses was among Hispanic individuals and Asian American and Pacific Islander individuals, and the largest percentage reduction in stage IV diagnoses was among non-Hispanic Black and non-Hispanic White individuals. Diagnoses of lung cancer, colorectal cancer, melanoma, and non-Hodgkin lymphoma had the largest percentage reduction among both stage I (>18%) and stage IV (>10%) diagnoses; cancers of the prostate, cervix, liver, oesophagus, stomach, and thyroid also had large percentage reductions in stage I diagnoses (>20).

After adjusting for sociodemographic and clinical factors, the stage distribution of new diagnoses changed in 2020 compared with 2019 (table 3). Specifically, the aOR for being diagnosed with stage I disease versus stage II–IV disease in 2020 compared with 2019 was 0·946 (95% CI 0·939–0·952), and the aOR for being diagnosed with stage IV disease versus stage I–III disease in 2020 compared with 2019 was 1·074 (1·066–1·083).

These results also confirmed results seen in other studies coming from Europe (2,3, 4).

References

  1. Han X, Yang NN, Nogueira L, Jiang C, Wagle NS, Zhao J, Shi KS, Fan Q, Schafer E, Yabroff KR, Jemal A. Changes in cancer diagnoses and stage distribution during the first year of the COVID-19 pandemic in the USA: a cross-sectional nationwide assessment. Lancet Oncol. 2023 Aug;24(8):855-867. doi: 10.1016/S1470-2045(23)00293-0. PMID: 37541271.
  2. Kuzuu K, Misawa N, Ashikari K, et al. Gastrointestinal cancer stage at diagnosis before and during the COVID-19 pandemic in Japan. JAMA Netw Open 2021; 4: e2126334. DOI: 10.1001/jamanetworkopen.2021.26334
  3. Linck PA, Garnier C, Depetiteville MP, et al. Impact of the COVID-19 lockdown in France on the diagnosis and staging of breast cancers in a tertiary cancer centre. Eur Radiol 2022; 32: 1644–51. DOI: 10.1007/s00330-021-08264-3
  4. Mynard N, Saxena A, Mavracick A, et al. Lung cancer stage shift as a result of COVID-19 lockdowns in New York City, a brief report. Clin Lung Cancer 2022; 23: e238–42.  DOI: 10.1016/j.cllc.2021.08.010

 

 

UPDATED: 10/11/2021

Source: https://cancerletter.com/articles/20200619_1/

NCI Director’s Report

Sharpless: COVID-19 expected to increase mortality by at least 10,000 deaths from breast and colorectal cancers over 10 years

By Matthew Bin Han Ong

This story is part of The Cancer Letter’s ongoing coverage of COVID-19’s impact on oncology. A full list of our coverage, as well as the latest meeting cancellations, is available here.

The COVID-19 pandemic will likely cause at least 10,000 excess deaths from breast cancer and colorectal cancer over the next 10 years in the United States.

Scenarios run by NCI and affiliated modeling groups predict that delays in screening for and diagnosis of breast and colorectal cancers will lead to a 1% increase in deaths through 2030. This translates into 10,000 additional deaths, on top of the expected one million deaths resulting from these two cancers.

“For both these cancer types, we believe the pandemic will influence cancer deaths for at least a decade,” NCI Director Ned Sharpless said in a virtual joint meeting of the Board of Scientific Advisors and the National Cancer Advisory Board June 15. “I find this worrisome as cancer mortality is common. Even a 1% increase every decade is a lot of cancer suffering.

“And this analysis, frankly, is pretty conservative. We do not consider cancers other than those of breast and colon, but there is every reason to believe the pandemic will affect other types of cancer, too. We did not account for the additional non-lethal morbidity from upstaging, but this could also be significant and burdensome.”

An editorial by Sharpless on this subject appears in the journal Science.

The early analyses, conducted by the institute’s Cancer Intervention and Surveillance Modeling Network, focused on breast and colorectal cancers, because these are common, with relatively high screening rates.

CISNET modelers created four scenarios to assess long-term increases in cancer mortality rates for these two diseases:

  1. The pandemic has no effect on cancer mortality
  1. Delayed screening—with 75% reduction in mammography and, colorectal screening and adenoma surveillance for six months
  1. Delayed diagnosis—with one-third of people delaying follow-up after a positive screening or diagnostic mammogram, positive FIT or clinical symptoms for six months during a six-month period
  1. Combination of scenarios two and three

Treatment scenarios after diagnosis were not included in the model. These would be: delays in treatment, cancellation of treatment, or modified treatment.

“What we did is show the impact of the number of excess deaths per year for 10 years for each year starting in 2020 for scenario four versus scenario one,” Eric “Rocky” Feuer, chief of the NCI’s Statistical Research and Applications Branch in the Surveillance Research Program, said to The Cancer Letter.

Feuer is the overall project scientist for CISNET, a collaborative group of investigators who use simulation modeling to guide public health research and priorities.

“The results for breast cancer were somewhat larger than for colorectal,” Feuer said. “And that’s because breast cancer has a longer preclinical natural history relative to colorectal cancer.”

Modelers in oncology are creating a global modeling consortium, COVID-19 and Cancer Taskforce, to “support decision-making in cancer control both during and after the crisis.” The consortium is supported by the Union for International Cancer Control, The International Agency for Research on Cancer, The International Cancer Screening Network, the Canadian Partnership Against Cancer, and Cancer Council NSW, Australia.

A spike in cancer mortality rates threatens to reverse or slow down—at least in the medium term—the steady trend of reduction of cancer deaths. On Jan. 8, the American Cancer Society published its annual estimates of new cancer cases and deaths, declaring that the latest data—from 2016 to 2017—show the “largest ever single-year drop in overall cancer mortality of 2.2%.” Experts say that innovation in lung cancer treatment and the success of smoking cessation programs are driving the sharp decrease (The Cancer LetterFeb. 7, 2020).

The pandemic is expected to have broader impact, including increases in mortality rates for other cancer types. Also, variations in severity of COVID-19 in different regions in the U.S. will influence mortality metrics.

“There’s some other cancers that might have delays in screening—for example cervical, prostate, and lung cancer, although lung cancer screening rates are still quite low and prostate cancer screening should only be conducted on those who determine that the benefits outweigh the harms,” Feuer said. “So, those are the major screening cancers, but impacts of delays in treatment, canceling treatment or alternative treatments—could impact a larger range of cancer sites.

“This model assumes a moderate disruption which resolves after six months, and doesn’t consider non-lethal morbidities associated with the delay. One thing I think probably is occurring is regional variation in these impacts,” Feuer said. “If you’re living in New York City where things were ground zero for some of the worst impact early on, probably delays were larger than other areas of the country. But now, as we’re seeing upticks in other areas of the country, there may be in impact in these areas as well”

How can health care providers mitigate some of these harms? For example, for people who delayed screening and diagnosis, are providers able to perform triage, so that those at highest risk are prioritized?

“From a strictly cancer control point of view, let’s get those people who delayed screening, or followup to a positive test, or treatment back on schedule as soon as possible,” Feuer said. “But it’s not a simple calculus, because in every situation, we have to weigh the harms and benefits. As we come out of the pandemic, it tips more and more to, ‘Let’s get back to business with respect to cancer control.’

“Telemedicine doesn’t completely substitute for seeing patients in person, but at least people could get the advice they need, and then are triaged through their health care providers to indicate if they really should prioritize coming in. That helps the individual and the health care provider  weigh the harms and benefits, and try to strategize about what’s best for any individual.”

If the pandemic continues to disrupt routine care, cancer-related mortality rates would rise beyond the predictions in this model.

“I think this analysis begins to help us understand the costs with regard to cancer outcomes of the pandemic,” Sharpless said. “Let’s all agree we will do everything in our power to minimize these adverse effects, to protect our patients from cancer suffering.”

UPDATED: 10/11/2021

Patients with Cancer Appear More Vulnerable to SARS-CoV-2: A Multicenter Study during the COVID-19 Outbreak

Source:

Mengyuan DaiDianbo LiuMiao LiuFuxiang ZhouGuiling LiZhen ChenZhian ZhangHua YouMeng WuQichao ZhengYong XiongHuihua XiongChun WangChangchun ChenFei XiongYan ZhangYaqin PengSiping GeBo ZhenTingting YuLing WangHua WangYu LiuYeshan ChenJunhua MeiXiaojia GaoZhuyan LiLijuan GanCan HeZhen LiYuying ShiYuwen QiJing YangDaniel G. TenenLi ChaiLorelei A. MucciMauricio Santillana and Hongbing Cai. Patients with Cancer Appear More Vulnerable to SARS-CoV-2: A Multicenter Study during the COVID-19 Outbreak

Abstract

The novel COVID-19 outbreak has affected more than 200 countries and territories as of March 2020. Given that patients with cancer are generally more vulnerable to infections, systematic analysis of diverse cohorts of patients with cancer affected by COVID-19 is needed. We performed a multicenter study including 105 patients with cancer and 536 age-matched noncancer patients confirmed with COVID-19. Our results showed COVID-19 patients with cancer had higher risks in all severe outcomes. Patients with hematologic cancer, lung cancer, or with metastatic cancer (stage IV) had the highest frequency of severe events. Patients with nonmetastatic cancer experienced similar frequencies of severe conditions to those observed in patients without cancer. Patients who received surgery had higher risks of having severe events, whereas patients who underwent only radiotherapy did not demonstrate significant differences in severe events when compared with patients without cancer. These findings indicate that patients with cancer appear more vulnerable to SARS-CoV-2 outbreak.

Significance: Because this is the first large cohort study on this topic, our report will provide much-needed information that will benefit patients with cancer globally. As such, we believe it is extremely important that our study be disseminated widely to alert clinicians and patients.

Introduction

A new acute respiratory syndrome coronavirus, named SARS-CoV-2 by the World Health Organization (WHO), has rapidly spread around the world since its first reported case in late December 2019 from Wuhan, China (1). As of March 2020, this virus has affected more than 200 countries and territories, infecting more than 800,000 individuals and causing more than 40,000 deaths (2).

With more than 18 million new cases per year globally, cancer affects a significant portion of the population. Individuals affected by cancer are more susceptible to infections due to coexisting chronic diseases, overall poor health status, and systemic immunosuppressive states caused by both cancer and anticancer treatments (3). As a consequence, patients with cancer who are infected by the SARS-CoV-2 coronavirus may experience more difficult outcomes than other populations. Until now, there is still no systematic evaluation of the effects that the SARS-CoV-2 coronavirus has of patients with cancer in a representative population. A recent study reported a higher risk of severe events in patients with cancer when compared with patients without cancer (4); however, the small sample size of SARS-CoV-2 patients with cancer used in the study limited how representative it was of the whole population and made it difficult to conduct more insightful analyses, such as comparing clinical characteristics of patients with different types of cancer, as well as anticancer treatments (5, 6).

Using patient information collected from 14 hospitals in Hubei Province, China, the epicenter of the 2019–2020 COVID-19 outbreak, we describe the clinical characteristics and outcomes [death, intensive care unit (ICU) admission, development of severe/critical symptoms, and utilization of invasive mechanical ventilation] of patients affected by the SARS-CoV-2 coronavirus for 105 hospitalized patients with cancer and 536 patients without cancer. We document our findings for different cancer types and stages, as well as different types of cancer treatments. We believe the information and insights provided in this study will help improve our understanding of the effects of SARS-CoV-2 in patients with cancer.

Results

Patients Characteristics

In total, 105 COVID-19 patients with cancer were enrolled in our study for the time period January 1, 2020, to February 24, 2020, from 14 hospitals in Wuhan, China. COVID-19 patients without cancer matched by the same hospital, hospitalization time, and age were randomly selected as our control group. Our patient population included 339 females and 302 males. Patients with cancer [median = 64.00, interquartile range (IQR) = 14.00], when compared with those without cancer (median = 63.50, IQR = 14.00) had similar age distributions (by design), experienced more in-hospital infections [20 (19.04%) of 105 patients vs. 8 (1.49%) of 536 patients;P < 0.01], and had more smoking history [36 (34.28%) of 105 patients vs. 46 (8.58%) of 536 patients; P < 0.01], but had no significant differences in sex, other baseline symptoms, and other comorbidities (Table 1). With respect to signs and symptoms upon admission, COVID-19 patients with cancer were similar to those without cancer except for a higher prevalence of chest distress [15 (14.29%) of 105 patients vs. 36 (6.16%) of 536 patients; P = 0.02].

Table 1.

Characteristics of COVID-19 patients with and without cancer

Clinical Outcomes

Compared with COVID-19 patients without cancer, patients with cancer had higher observed death rates [OR, 2.34; 95% confidence interval (CI), (1.15–4.77); P = 0.03], higher rates of ICU admission [OR, 2.84; 95% CI (1.59–5.08); P < 0.01], higher rates of having at least one severe or critical symptom [OR, 2.79; 95% CI, (1.74–4.41); P < 0.01], and higher chances of needing invasive mechanical ventilation (Fig. 1A). We also conducted survival analysis on occurrence of any severe condition which included death, ICU admission, having severe symptoms, and utilization of invasive mechanical ventilation (see cumulative incidence curves in Fig. 1B). In general, patients with cancer deteriorated more rapidly than those without cancer. These observations are consistent with logistic regression results (Supplementary Fig. S1), after adjusting for age, sex, smoking, and comorbidities including diabetes, hypertension, and chronic obstructive pulmonary disease (COPD). According to our multivariate logistic regression results, patients with cancer still had an excess OR of 2.17 (P = 0.06) for death (Supplementary Fig. S1A), 1.99 (P < 0.01) for experiencing any severe symptoms (Supplementary Fig. S1B), 3.13 (P < 0.01) for ICU admission (Supplementary Fig. S1C), and 2.71 (P = 0.04) for utilization of invasive mechanical ventilation (Supplementary Fig. S1D; Supplementary Table S1). The consistency of observed ORs between the multivariate regression model and unadjusted calculation reassures the association between cancer and severe events even in the presence of other factors such as age differences.

Figure 1.

Severe conditions in patients with and without cancer, and patients with different types, stages, and treatments of cancer. Severe conditions include death, ICU admission, having severe/critical symptoms, and usage of invasive mechanical ventilation. Incidence and survival analysis of severe conditions among COVID-19 patients with cancer and without cancer (A and B), among patients with different types of cancer (C and D), among patients with metastatic and nonmetastatic cancers (E and F), among patients with lung cancer, other cancers than lung with lung metastasis, and other cancers than lung without lung metastasis (G and H), and patients receiving different types of cancer treatments (I and J). P values indicate differences between cancer subgroups versus patients without cancer. For ACEGI, *, P < 0.05; **, P < 0.01. OR, 95% CI, and P values between different subgroups are listed in Supplementary Table S2. For BDFHJ, HR, 95% CI, and P values are listed in Supplementary Table S3.

Cancer Types

Information regarding potential risks of severe conditions in SARS-CoV-2 associated with each type of cancer was calculated. We compared different conditions among cancer types (Table 2). Lung cancer was the most frequent cancer type [22 (20.95%) of 105 patients], followed by gastrointestinal cancer [13 (12.38%) of 105 patients], breast cancer [11 (10.48%) of 105 patients], thyroid cancer [11 (10.48%) of 105 patients], and hematologic cancer [9 (8.57%) of 105 patients]. As shown in Fig. 1C and D and Supplementary Table S2, patients with hematologic cancer including leukemia, lymphoma, and myeloma have a relatively high death rate [3 (33.33%) of 9 patients], high ICU admission rate [4 (44.44%) of 9 patients], high risks of severe/critical symptoms [6 (66.67%) of 9 patients], and high chance of utilization of invasive mechanical ventilation [2 (22.22%) of 9 patients]. Patients with lung cancer had the second-highest risk levels, with death rate [4 (18.18%) of 22 patients], ICU admission rate [6 (27.27%) of 22 patients], risks of severe/critical symptoms [11 (50.00%) of 22 patients], and the chance of utilization of invasive mechanical ventilation [4 (18.18%) of 22 patients; Table 2].

Table 2.

Severe events in 105 patients with cancer for each type of cancer

Cancer Stage

We found that patients with metastatic cancer (stage IV) had even higher risks of death [OR, 5.58; 95% CI (1.71–18.23); P = 0.01], ICU admission [OR, 6.59; 95% CI (2.32–18.72); P < 0.01], having severe conditions [OR, 5.97; 95% CI (2.24–15.91); P < 0.01], and use of invasive mechanical ventilation [OR, 55.42; 95% CI (13.21–232.47); P < 0.01]. In contrast, patients with nonmetastatic cancer did not demonstrate statistically significant differences compared with patients without cancer, with all P > 0.05 (Fig. 1E and F; Supplementary Tables S2 and S3). In addition, when compared with patients without cancer, patients with lung cancer or other cancers with lung metastasis also showed higher risks of death, ICU admission rates, higher critical symptoms, and use of invasive mechanical ventilation, with all P values below 0.01, but other cancers without lung metastasis had no statistically significant differences (all P values > 0.05; Fig. 1G and H; Supplementary Table S3) when compared with patients without cancer.

Cancer Treatments

Among the 105 COVID-19 patients with cancer in our study, 13 (12.26%) had radiotherapy, 17 (14.15%) received chemotherapy, 8 (7.62%) received surgery, 4 (3.81%) had targeted therapy, and 6 (5.71%) had immunotherapy within 40 days before the onset of COVID-19 symptoms. All of the targeted therapeutic drugs were EGFR–tyrosine kinase inhibitors for treatment of lung cancer, and all of the immunotherapy drugs were PD-1 inhibitors for the treatment of lung cancer. A patient with cancer may have more than one type of therapy. Our observation suggested that patients who received immunotherapy tended to have high rates of death [2 (33.33%) of 6 patients] and high chances of developing critical symptoms [4 (66.67%) of 6 patients]. Patients who received surgery demonstrated higher rates of death [2 (25.00%) of 8 patients], higher chances of ICU admission [3 (37.50%) of 8 patients], higher chances of having severe or critical symptoms [5 (62.50%) of 8 patients], and higher use of invasive ventilation [2 (25.00%) of 8 patients] than other treatments excluding immunotherapy. However, patients with cancer who received radiotherapy did not show statistically significant differences in having any severe events when compared with patients without cancer, with all P values > 0.10 (Fig. 1I and J). Clinical details on the cancer diagnoses and cancer treatments are summarized in Supplementary Table S4.

Timeline of Severe Events

To evaluate the time-dependent evolution of the disease, we conducted the timeline of different events for COVID-19 patients with cancer (Fig. 2A) and COVID-19 patients without cancer (Fig. 2B) with death and other severe events marked in the figure. COVID-19 patients with cancer had a mean length of stay of 27.01 days (SD 9.52) and patients without cancer had a mean length of stay of 17.75 days (SD 8.64); the difference is significant (Wilcoxon test, P < 0.01). To better clarify the contributing factors that might influence outcomes, we also included logistic regression of COVID-19 patients with cancer adjusted by immunosuppression levels in Supplementary Table S5. However, no significant association between immunosuppression and severe outcomes was observed from the analysis (with all P > 0.05).

Figure 2.

Timeline of events for COVID-19 patients. A, Timeline of events in COVID-19 patients with cancer. B, Timeline of events in COVID-19 patients without cancer. For visualization purposes, patients without timeline information are excluded and only 105 COVID-19 patients without cancer are shown.

Discussion

The findings in this study suggest that patients with cancer infected with SARS-CoV-2 tend to have more severe outcomes when compared with patients without cancer. Patients with hematologic cancer, lung cancer, and cancers in metastatic stages demonstrated higher rates of severe events compared with patients without cancer. In addition, patients who underwent cancer surgery showed higher death rates and higher chances of having critical symptoms.

The SARS-CoV-2 virus has spread rapidly globally; thus, many countries have not been ready to handle the large volume of people affected by this outbreak due to a lack of knowledge about how this coronavirus affects the general population. To date, reports on the general population infected with SARS-CoV-2 suggest elderly males have a higher incidence and death rate (7, 8). Limited information is known about the outcome of patients with cancer who contract this highly communicable disease. Cancer is among the top causes of death. Asia, Europe, and North America have the highest incidence of cancer in the world (9), and at the moment of the writing of this study the SARS-CoV-2 virus is mainly spreading in these three areas (referred from https://www.cdc.gov/media/releases/2020/s0226-Covid-19-spread.htmlhttps://www.nytimes.com/2020/02/27/world/coronavirusnews.html). Although COVID-19 patients with cancer may share some epidemiologic features with the general population with this disease, they may also have additional clinical characteristics. Therefore, we conducted this study on patients with cancer with coexisting COVID-19 disease to evaluate the potential effect of COVID-19 on patients with cancer.

On the basis of our analysis, COVID-19 patients with cancer tend to have more severe outcomes when compared with the noncancer population. Although COVID-19 is reported to have a relatively low death rate of 2% to 3% in the general population (10), patients with cancer and COVID-19 not only have a nearly 3-fold increase in the death rate than that of COVID-19 patients without cancer, but also tend to have much higher severity of their illness. Altogether, these findings suggest that patients with cancer are a much more vulnerable population in the current COVID-19 outbreak. Our findings are consistent with those presented in a previous study based on 18 patients with cancer (4). Because of the limited number of patients with cancer in the previous study, the authors concluded that among patients with cancer, age is the only risk factor for the severity of the illness. On the basis of our data on 105 patients with cancer, we have discovered additional risk factors, including cancer types, cancer stage, and cancer treatments, which may contribute to the severity of the disease among patients with cancer.

Our data demonstrate that the severity of SARS-CoV-2 infection in patients is significantly affected by the types of tumors. From our analysis, patients with hematologic cancer have the highest severity and death rates among all patients with cancer, and lung cancer follows second. Patients with hematologic cancer in our study include patients with leukemia, myeloma, and lymphoma, who have a more compromised immune system than patients with solid tumors (11). These patients all had a rapidly deteriorating clinical course once infected with COVID-19. Because malignant or dysfunctional plasma cells, lymphocytes, or white blood cells in general in hematologic malignancies have decreased immunologic function (12–14), this could be the main reason why patients with hematologic cancer have very high severity and death rates. All patients with hematologic cancer are prone to the complications of serious infection (12–14), which can exacerbate the condition which could have worsened in patients with COVID-19. In our study, 55.56% of patients with hematologic cancer had severe immunosuppression, which may be the main reason for deteriorated outcomes. Although the small sample size limits representativity of the observation, we believe our finding can serve as an informative starting point for further investigation when a larger cohort from a wide range of healthcare providers becomes available. Among solid tumors, lung cancer is the highest risk category disease in patients with SARS-CoV-2 infection (Fig. 1C). Decreased lung function and severe infection in patients with lung cancer could contribute to the worse outcome in this subpopulation (15, 16).

In our analysis, we classified the SARS-CoV-2 infection–related high risk factors based on death, severe or critical illness, ICU admission, and the utilization of invasive mechanical ventilation. Using these parameters, we detected a multi-fold increase in risk in the cancer population, in contrast to the noncancer population. If there were primary or metastatic tumors in the lungs, patients were more prone to a deteriorated course in a short time. Intriguingly, when patients with cancer had only early-stage disease without metastasis, we did not observe any difference between the cancer and noncancer population in terms of COVID-19–related death rate or severity (Fig. 1E). The stage of cancer diagnosis seemed to play a significant role in the severity and death rate of COVID-19.

Patients with cancer received a wide range of treatments, and we also found that different types of treatments had different influences on severity and death when these patients contracted COVID-19. Recently, immunotherapy has assumed a very important role in treating tumors, which aids in treatment of cancer by blocking the immune escape of cancer cells. But in our study, in contrast to patients with cancer with other treatments, patients with immunotherapy had the highest death rate and the highest severity of illness, a very puzzling finding. According to pathologic studies on the patients with COVID-19, there were desquamation of pneumocytes and hyaline membrane formation, implying that these patients had acute respiratory distress syndrome (ARDS; ref. 17). ARDS induced by cytokine storm is reported to be the main reason for death of SARS-CoV-2–infected patients (18). It is possible that in this setting, immunotherapy induces the release of a large amount of cytokines, which can be toxic to normal cells, including lung epithelial cells (19–21), and therefore lead to a more severe illness. However, in this study the number of patients with immunotherapy was too small; further research with a large case population needs to be conducted in the future.

In addition, COVID-19 patients with cancer who are under active treatment or not under active treatment do not show differences in their outcomes, and there is a significant difference between COVID-19 patients with cancer but not with active treatment and patients without cancer (Supplementary Table S2). These results indicate that COVID-19 patients with both active treatment and just cancer history have a higher risk of developing severe events than noncancer COVID-19 patients. The possible reasons could be due to some known cancer-related complications, for example, anemia, hypoproteinaemia, or dyspnea in early phase of COVID-19 (22). We considered that cancer had a lifetime effect on patients and that cancer survivors always need routine follow-up after primary resection. Therefore, in clinical COVID-19 patient management, equivalent attention needs to be paid to those with cancer whether they are under active therapeutics or not during the outbreak of COVID-19.

This study has several limitations. Although the cohort of COVID-19 patients with cancer is one of the largest in Hubei province, China, the epicenter of the initial outbreak, a larger cohort from the whole country or even from multiple countries will be more representative. Large-scale national and international research collaboration will be necessary to achieve this. At the initial stage of the outbreak, data collection and research activities were not a priority of the hospitals. Therefore, it was not possible to record and collect some data that are potentially informative for our analysis in a timely manner. In addition, due to the urgency of clinical treatment, medical data used in this study were largely disconnected from the patients’ historical electronic medical records, which are mostly stored with a different healthcare provider than the medical center providing COVID-19 care. This left us with limited information about each patient.

Our study is the midsize cohort study on this topic and will provide much-needed information on risk factors of this population. We hope that our findings will help countries better protect patients with cancer affected by the ongoing COVID-19 pandemic.

Methods

Study Design and Patients

We conducted a multicenter study focusing on the clinical characteristics of confirmed cases of COVID-19 patients with cancer in 14 hospitals in Hubei province, China; all of the 14 hospitals served as government-designated hospitals for patients diagnosed with COVID-19. SARS-CoV-2–infected patients without cancer matched by the same hospital and hospitalization time were randomly selected as our control group. In addition, as age is one of the major predictors of severity of respiratory diseases like COVID-19 (4), we excluded from our analysis 117 younger COVID-19 patients without cancer so that median ages of patients with cancer (median = 64.0, IRQ = 14.00) and patients without cancers (median = 63.5, IQR = 14.00) would be comparable.

End Points and Assessments

There were four primary outcomes analyzed in this study: death, admission into the ICU, development of severe or critical symptoms, and utilization of invasive mechanical ventilation. The clinical definition of severe/critical symptoms follows the 5th edition of the 2019Novel Coronavirus Disease (COVID-19) Diagnostic Criteria published by the National Health Commission in China, including septic shock, ARDS, acute kidney injury, disseminated intravascular coagulation, and rhabdomyolysis.

Case Fatality Rate of Cancer Patients with COVID-19 in a New York Hospital System

Source:

Vikas MehtaSanjay GoelRafi KabarritiDaniel ColeMendel GoldfingerAna Acuna-VillaordunaKith PradhanRaja ThotaStan ReissmanJoseph A. SparanoBenjamin A. GartrellRichard V. SmithNitin OhriMadhur GargAndrew D. RacineShalom KalnickiRoman Perez-SolerBalazs Halmos and Amit Verma. Case Fatality Rate of Cancer Patients with COVID-19 in a New York Hospital System

Abstract

Patients with cancer are presumed to be at increased risk from COVID-19 infection–related fatality due to underlying malignancy, treatment-related immunosuppression, or increased comorbidities. A total of 218 COVID-19–positive patients from March 18, 2020, to April 8, 2020, with a malignant diagnosis were identified. A total of 61 (28%) patients with cancer died from COVID-19 with a case fatality rate (CFR) of 37% (20/54) for hematologic malignancies and 25% (41/164) for solid malignancies. Six of 11 (55%) patients with lung cancer died from COVID-19 disease. Increased mortality was significantly associated with older age, multiple comorbidities, need for ICU support, and elevated levels of D-dimer, lactate dehydrogenase, and lactate in multivariate analysis. Age-adjusted CFRs in patients with cancer compared with noncancer patients at our institution and New York City reported a significant increase in case fatality for patients with cancer. These data suggest the need for proactive strategies to reduce likelihood of infection and improve early identification in this vulnerable patient population.

Significance: COVID-19 in patients with cancer is associated with a significantly increased risk of case fatality, suggesting the need for proactive strategies to reduce likelihood of infection and improve early identification in this vulnerable patient population.

Introduction

The novel coronavirus COVID-19, or severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has spread rapidly throughout the world since its emergence in December 2019 (1). The virus has infected approximately 2.9 million people in more than 200 countries with more than 200,000 deaths at the time of writing (2). Most recently, the United States has become the epicenter of this pandemic, reporting an estimated 956,000 cases of COVID-19 infection, with the largest concentration in New York City (NYC) and its surrounding areas (approximately >203,000 cases or 35% of all U.S. infections; ref. 3).

Early data suggests that 14% to 19% of infected patients will develop significant sequelae with acute respiratory distress syndrome, septic shock, and/or multiorgan failure (1, 4, 5), and approximately 1% to 4% will die from the disease (2). Recent meta-analyses have demonstrated an almost 6-fold increase in the odds of mortality for patients with chronic obstructive pulmonary disease (COPD) and a 2.5-fold increase for those with diabetes, possibly due to the underlying pulmonary and immune dysfunction (6, 7). Given these findings, patients with cancer would ostensibly be at a higher risk of developing and succumbing to COVID-19 due to immunosuppression, increased coexisting medical conditions, and, in cases of lung malignancy, underlying pulmonary compromise. Patients with hematologic cancer, or those who are receiving active chemotherapy or immunotherapy, may be particularly susceptible because of increased immunosuppression and/or dysfunction.

According the NCI, there were approximately 15.5 million cancer survivors and an estimated 1,762,450 new cases of cancer diagnosed in the United States in 2019 (8). Early case series from China and Italy have suggested that patients with malignancy are more susceptible to severe infection and mortality from COVID-19 (9–12), a phenomenon that has been noted in other pandemics (13). Many of these descriptive studies have included small patient cohorts and have lacked cancer site–specific mortality data or information regarding active cancer treatment. As New York has emerged as the current epicenter of the pandemic, we sought to investigate the risk posed by COVID-19 to our cancer population with more granular data regarding cancer type and active treatment, and identify factors that placed patients with cancer at highest risk of fatality from COVID-19.

Results

Outcomes of 218 Cancer Patients with COVID-19 Show High Overall Mortality with Tumor-Specific Patterns

A total of 218 patients with cancer and COVID-19 were treated in Montefiore Health System (New York, NY) from March 18, 2020, to April 8, 2020. These included 164 (75%) patients with solid tumors and 54 (25%) with hematologic malignancies. This cohort included 127 (58%) males and 91 (42%) females. The cohort was predominantly composed of adult patients (215/218, 98.6%) with a median age of 69 years (range 10–92 years).

Sixty-one (28%) patients expired as a result of COVID-19disease at the time of analysis (Table 1). The mortality was 25% among all patients with solid tumors and was seen to occur at higher rates in patients with lung cancers (55%), gastrointestinal (GI) cancers [colorectal (38%), pancreatic (67%), upper GI (38%)], and gynecologic malignancies (38%). Genitourinary (15%) and breast (14%) cancers were associated with relatively lower mortality with COVID-19 infection.

Table 1.

Outcomes in patients with cancer and COVID-19

Hematologic malignancies were associated with higher rate of mortality with COVID-19 (37%). Myeloid malignancies [myelodysplastic syndromes (MDS)/acute myeloid leukemia (AML)/myeloproliferative neoplasm (MPN)] showed a trend for higher mortality compared with lymphoid neoplasms [non-Hodgkin lymphoma (NHL)/chronic lymphoid leukemia (CLL)/acute lymphoblastic leukemia (ALL)/multiple myeloma (MM)/Hodgkin lymphoma; Table 1]. Rates of ICU admission and ventilator use were slightly higher for hematologic malignancies than solid tumors (26% vs. 19% and 11% vs. 10%, respectively), but this did not achieve statistical significance.

Disease Characteristics of Cancer Patients with COVID-19 Demonstrate the Effect of Age, Comorbidities, and Laboratory Biomarkers on Mortality

Analysis of patient characteristics with mortality did not show any gender bias (Table 2). Older age was significantly associated with increased mortality, with median age of deceased cohort at 76 years when compared with 66 years for the nondeceased group (P = 0.0006; Cochran-Armitage test). No significant associations between race and mortality were seen.

Table 2.

Disease characteristics of patients with cancer with COVID-19 and association with mortality

COVID-19 disease severity, as evident from patients who needed ICU care and ventilator support, was significantly associated with increased mortality. Interestingly, active disease (<1 year) and advanced metastatic disease showed a trend for increased mortality, but the association did not achieve statistical significance (P = 0.09 and 0.06, respectively). Active chemotherapy and radiotherapy treatment were not associated with increased case fatality. Very few patients in this cohort were on immunotherapy, and this did not show any associations with mortality.

Analysis of comorbidities demonstrated increased risk of dying from COVID-19 in patients with cancer with concomitant heart disease [hypertension (HTN), coronary artery disease (CAD), and congestive heart failure (CHF)] and chronic lung disease (Table 2). Diabetes and chronic kidney disease were not associated with increased mortality in univariate analysis (Table 2).

We also analyzed laboratory values obtained prior to diagnosis of COVID-19 and during the time of nadir after COVID-19 positivity in our cancer cohort. Relative anemia pre–COVID-19 was associated with increased mortality, whereas pre-COVID platelet and lymphocyte counts were not (Table 3).Post–COVID-19 infection, lower hemoglobin levels, higher total white blood cell (WBC) counts, and higher absolute neutrophil counts were associated with increased mortality (Table 3). Analysis of other serologic biomarkers demonstrated that elevated D-dimer, lactate, and lactate dehydrogenase (LDH) in patients were significantly correlated with dying (Table 3).

Table 3.

Laboratory values of cancer patients with COVID-19 and association with mortality

Next, we conducted multivariate analyses and used variables that showed a significant association with mortality in univariate analysis (P < 0.05 in univariate was seen with age, ICU admission, hypertension, chronic lung disease, CAD, CHF, baseline hemoglobin, nadir hemoglobin, WBC counts, D-dimer, lactate, and LDH). Gender was forced in the model and we used a composite score of comorbidities from the sum of indicators for diabetes mellitus (DM), HTN, chronic lung disease, chronic kidney disease, CAD, and CHF capped at a maximum of 3. In the multivariate model (Supplementary Table S1), we observed that older age [age < 65; OR, 0.23; 95% confidence interval (CI), 0.07–0.6], higher composite comorbidity score (OR, 1.52; 95% CI, 1.02–2.33), ICU admission (OR, 4.83; 95% CI, 1.46–17.15), and elevated inflammatory markers (D-dimer, lactate, and LDH) were significantly associated with mortality after multivariate comparison in patients with cancer and COVID-19.

Interaction with the Healthcare Environment was a Prominent Source of Exposure for Patients with Cancer

A detailed analysis of deceased patients (N = 61; Supplementary Table S2) demonstrated that many were either nursing-home or shelter (n = 22) residents, and/or admitted as an inpatient or presented to the emergency room within the 30 days prior to their COVID-19 positive test (21/61). Altogether, 37/61 (61%) of the deceased cohort were exposed to the healthcare environment at the outset of the COVID-19 epidemic. Few of the patients in the cohort were on active oncologic therapy. The vast majority had a poor Eastern Cooperative Oncology Group performance status (ECOG PS; 51/61 with an ECOG PS of 2 or higher) and carried multiple comorbidities.

Patients with Cancer Demonstrate a Markedly Increased COVID-19 Mortality Rate Compared with Noncancer and All NYC COVID-19 Patients

An age- and sex-matched cohort of 1,090 patients at a 5:1 ratio of noncancer to cancer COVID-19 patients from the same time period and from the same hospital system was also obtained after propensity matching and used as control to estimate the increased risk posed to our cancer population (Table 4). We observed case fatality rates (CFR) were elevated in all age cohorts in patients with cancer and achieved statistical significance in the age groups 45–64 and in patients older than 75 years of age.

Table 4.

Comparison of cancer and COVID-19 mortality with all NYC cases (official NYC numbers up to 5 p.m., April 12, 2020) and a control group from the same healthcare facility

To also compare our CFRs with a larger dataset from the greater NYC region, we obtained official case numbers from New York State (current up to April 12, 2020; ref. 3). In all cohorts, the percentage of deceased patients was found to rise sharply with increasing age (Table 4). Strikingly, CFRs in cancer patients with COVID-19 were significantly, many-fold higher in all age groups when compared with all NYC cases (Table 4).

Discussion

To our knowledge, this is the first large report of COVID-19 CFRs among patients with cancer in the United States. The overall case fatality among COVID-19–infected patients with cancer in an academic center located within the current epicenter of the global pandemic exceeded 25%. In addition, striking tumor-specific discrepancies were seen, with marked increased susceptibility for those with hematologic malignancies and lung cancer. CFRs were 2 to 3 times the age-specific percentages seen in our noncancer population and the greater NYC area for all COVID-19 patients.

Our results seem to mirror the typical prognosis of the various cancer types. Among the most common malignancies within the U.S. population (lung, breast, prostate, and colorectal), there was 55% mortality among patients with lung cancer, 14% for breast cancer, 20% for prostate cancer, and 38% for colorectal cancer. This pattern reflects the overall known lethality of these cancers. The percent annual mortality (ratio of annual deaths/new diagnosis) is 59.3% for lung cancer, 15.2% for breast cancer, 17.4% for prostate cancer, and 36% for colorectal cancer (8). This suggests that COVID-19 infection amplifies the risk of death regardless of the cancer type.

Patients with hematologic malignancies demonstrate a higher mortality than those with solid tumors. These patients tend to be treated with more myelosuppressive therapy, and are often severely immunocompromised because of underlying disease. There is accumulating evidence that one major mechanism of injury may be a cytokine-storm syndrome secondary to hyperinflammation, which results in pulmonary damage. Patients with hematologic malignancy may potentially be more susceptible to cytokine-mediated inflammation due to perturbations in myeloid and lymphocyte cell compartments (14).

Many of the predictive risk factors for mortality in our cancer cohort were similar to published data among all COVID-19 patients. A recent meta-analysis highlighted the association of chronic diseases including hypertension (OR, 2.29), diabetes (OR, 2.47), COPD (OR, 5.97), cardiovascular disease (OR, 2.93), and cerebrovascular disease (OR, 3.89) with a risk for developing severe COVID-19 infection among all patients (15). In our cancer patient dataset, a large proportion of patients had at least one of these concurrent risk factors. In a univariate model, we observed significant associations of death from COVID-19 infection in patients with hypertension, chronic lung disease, coronary heart disease, and congestive heart failure. Serologic predictors in our dataset predictive for mortality included anemia at time of infection, and elevated LDH, D-dimer, and lactic acid, which correlate with available data from all COVID-19 patients.

Rapidly accumulating reports suggest that age and race may play a role in the severity of COVID-19 infection. In our cancer cohort, the median age of the patients succumbing to COVID-19 was 76 years, which was 10 years older than patients who have remained alive. The CDC has reported a disproportionate number of African Americans are affected by COVID-19 in the United States, accounting for 33% of all hospitalized patients while constituting only 13% of the U.S. population (15). However, the racial breakdown of our patients was proportional to the Bronx population as a whole, and race was not a significant predictor of mortality in our univariate or multivariate models. Our data might argue that the increased mortality noted in the larger NYC populations might also likely be driven by socioeconomic and health disparities in addition to underlying biological factors. Overall mortality with COVID-19 has been higher in the Bronx, which is a socioeconomically disadvantaged community with a mean per capita income of $19,721 (16, 17). Our patients with cancer were predominantly from the Bronx and potentially had increased mortality in part due to socioeconomic factors and comorbidities. Even after accounting for the increased mortality seen in COVID-19 in the Bronx, the many-fold magnitude increase in death rates within our cancer cohort can potentially be attributed to the vulnerability of oncology patients. This was evident in the comparison with a control group from the same hospital system that demonstrated a significant association of cancer with mortality in patients between 45 and 64 years of age and older than 75 years of age.

Interaction with the healthcare environment prior to widespread knowledge of the epidemic within NYC was a prominent source of exposure for our patients with cancer. Many of those who succumbed to COVID-19 infection were older and frail with significant impairment of pulmonary and/or immunologic function. These findings could be utilized to risk-stratify patients with cancer during this pandemic, or in future viral airborne outbreaks, and inform mitigation practices for high-risk individuals. These strategies could include early and aggressive social distancing, resource allocation toward more outpatient-based care and telemedicine, testing of asymptomatic high-risk patients, and institution of strict infection-control measures. Indeed, such strategies were implemented early in the pandemic at our center, possibly explaining the relatively low number of infected patients on active therapy.

There were several limitations to our study. Data regarding do not resuscitate or intubate orders were not included in the analysis and could have significantly affected the decision-making and mortality surrounding these patients. Although an attempt was made to control for those receiving active cancer treatment or with additional comorbidities, we could not fully account for the patients’ preexisting health conditions prior to COVID-19 infection. Differential treatment paradigms for COVID-19 infection and sequelae were not controlled for in our analysis. Because of the limited follow-up, the full clinical course of these patients may not be included. Future comparative studies to noncancer patients will be needed to fully ascertain the risk posed to oncology patients. Finally, though our data does include those who were tested and discharged within our health system, we cannot fully account for those who were tested in nonaffiliated outpatient settings, which may potentially bias our study to more severe cases. We also acknowledge that the mortality rate is highly dependent on the breadth of testing, and therefore understand that more widespread detection of viral infection would likely alter the results.

Our data suggest significant risk posed to patients with cancer infected with COVID-19, with an observed significant increase in mortality. The highest susceptibility appears to be in hematologic or lung malignancies, suggesting that proactive strategies to reduce likelihood of infection and improve early identification of COVID-19 positivity in the cancer patient population are clearly warranted. Overall, we hope and expect that our data from the current epicenter of the COVID-19 epidemic will help inform other healthcare systems, patients with cancer, and the public about the particular vulnerability of patients with cancer to this disease.

For more Articles on COVID-19 please see our Coronavirus Portal at

https://pharmaceuticalintelligence.com/coronavirus-portal/

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Live Conference Coverage AACR 2020 in Real Time: Monday June 22, 2020 8AM-Noon Sessions

Reporter: Stephen J. Williams, PhD

Follow Live in Real Time using

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Register for FREE at https://www.aacr.org/

AACR VIRTUAL ANNUAL MEETING II

 

June 22-24: Free Registration for AACR Members, the Cancer Community, and the Public
This virtual meeting will feature more than 120 sessions and 4,000 e-posters, including sessions on cancer health disparities and the impact of COVID-19 on clinical trials

 

This Virtual Meeting is Part II of the AACR Annual Meeting.  Part I was held online in April and was centered only on clinical findings.  This Part II of the virtual meeting will contain all the Sessions and Abstracts pertaining to basic and translational cancer research as well as clinical trial findings.

 

REGISTER NOW

 

Monday, June 22

8:30 AM – 10:10 AM EDT

Virtual Special Session

Opening Ceremony

The Opening Ceremony will include the following presentations:
Welcome from AACR CEO Margaret Foti, PhD, MD (hc)

CHIEF EXECUTIVE OFFICER

MARGARET FOTI, PHD, MD (HC)

​American Association for Cancer Research
Philadelphia, Pennsylvania

  • Dr. Foti mentions that AACR is making progress in including more ethnic and gender equality in cancer research and she feels that the disparities seen in health care, and in cancer care, is related to the disparities seen in the cancer research profession
  • AACR is very focused now on blood cancers and creating innovation summits on this matter
  • In 2019 awarded over 60 grants but feel they will be able to fund more research in 2020
  • Government funding is insufficient at current levels

Remarks from AACR Immediate Past President Elaine R. Mardis, PhD, FAACR

  • involved in planning and success of the first virtual meeting (it was really well done)
  • # of registrants was at unprecedented numbers
  • the scope for this meeting will be wider than the first meeting
  • they have included special sessions including COVID19 and health disparities
  • 70 educational and methodology workshops on over 70 channels

AACR Award for Lifetime Achievement in Cancer Research

  • Dr. Philip Sharp is awardee of Lifetime Achievement Award
  • Dr. Sharp is known for his work in RNA splicing and development of multiple cancer models including a mouse CRSPR model
  • worked under Jim Watson at Cold Spring Harbor
    Presentation of New Fellows of the AACR Academy
  • Dr. Radcliffe for hypoxic factors
  • CART therapies
  • Dr. Semenza for HIF1 discovery
  • Dr Swanton for stratification of patients and tumor heterogeneity
  • these are just some of the new fellows

AACR-Biedler Prizes for Cancer Journalism

  • Writer of Article War of Nerves awarded; reported on nerve intervation of tumors
  • writer Budman on reporting and curation of hedgehog inhibitors in cancers
  • patient advocacy book was awarded for journalism
  • cancer survivor Kasie Newsome produced multiple segments on personalized cancer therapy from a cancer survivor perspective

Remarks from Speaker of the United States House of Representatives Nancy Pelosi

  • helped secure a doubling of funding for NCI and NIH in the 90s
  • securing COVID funding to offset some of the productivity issues related to the shutdown due to COVID
  • advocating for more work to alleviate health disparities

 

Remarks from United States Senator Roy Blunt

  • tireless champion in the Senate for cancer research funding; he was a cancer survivor himself
  • we need to keep focus on advances in science

Margaret Foti

DETAILS

Monday, June 22

10:10 AM – 12:30 PM EDT

Virtual Plenary Session

Bioinformatics and Systems Biology, Epidemiology, Immunology, Molecular and Cellular Biology/Genetics

Opening Plenary Session: Turning Science into Lifesaving Care

Alexander Marson, Antoni Ribas, Ashani T Weeraratna, Olivier Elemento, Howard Y Chang, Daniel D. De Carvalho

DETAILS

Monday, June 22

12:45 PM – 1:30 PM EDT

Awards and Lectures

How should we think about exceptional and super responders to cancer therapy? What biologic insights might ensue from considering these cases? What are ways in which considering super responders may lead to misleading conclusions? What are the pros and cons of the quest to locate exceptional and super responders?

Alice P Chen, Vinay K Prasad, Celeste Leigh Pearce

DETAILS

Monday, June 22

1:30 PM – 3:30 PM EDT

Virtual Educational Session

Tumor Biology, Immunology

Experimental and Molecular Therapeutics, Immunology

Other Articles on this Open Access  Online Journal on Cancer Conferences and Conference Coverage in Real Time Include

Press Coverage

Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Symposium: New Drugs on the Horizon Part 3 12:30-1:25 PM

Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Session on NCI Activities: COVID-19 and Cancer Research 5:20 PM

Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Session on Evaluating Cancer Genomics from Normal Tissues Through Metastatic Disease 3:50 PM

Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Session on Novel Targets and Therapies 2:35 PM

 

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Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Session on Evaluating Cancer Genomics from Normal Tissues Through Metastatic Disease 3:50 PM

Reporter: Stephen J. Williams, PhD

 Minisymposium: Evaluating Cancer Genomics from Normal Tissues through Evolution to Metastatic Disease

Oncologic therapy shapes the fitness landscape of clonal hematopoiesis

April 28, 2020, 4:10 PM – 4:20 PM

Presenter/Authors
Kelly L. Bolton, Ryan N. Ptashkin, Teng Gao, Lior Braunstein, Sean M. Devlin, Minal Patel, Antonin Berthon, Aijazuddin Syed, Mariko Yabe, Catherine Coombs, Nicole M. Caltabellotta, Mike Walsh, Ken Offit, Zsofia Stadler, Choonsik Lee, Paul Pharoah, Konrad H. Stopsack, Barbara Spitzer, Simon Mantha, James Fagin, Laura Boucai, Christopher J. Gibson, Benjamin Ebert, Andrew L. Young, Todd Druley, Koichi Takahashi, Nancy Gillis, Markus Ball, Eric Padron, David Hyman, Jose Baselga, Larry Norton, Stuart Gardos, Virginia Klimek, Howard Scher, Dean Bajorin, Eder Paraiso, Ryma Benayed, Maria Arcilla, Marc Ladanyi, David Solit, Michael Berger, Martin Tallman, Montserrat Garcia-Closas, Nilanjan Chatterjee, Luis Diaz, Ross Levine, Lindsay Morton, Ahmet Zehir, Elli Papaemmanuil. Memorial Sloan Kettering Cancer Center, New York, NY, University of North Carolina at Chapel Hill, Chapel Hill, NC, University of Cambridge, Cambridge, United Kingdom, Dana-Farber Cancer Institute, Boston, MA, Washington University, St Louis, MO, The University of Texas MD Anderson Cancer Center, Houston, TX, Moffitt Cancer Center, Tampa, FL, National Cancer Institute, Bethesda, MD

Abstract
Recent studies among healthy individuals show evidence of somatic mutations in leukemia-associated genes, referred to as clonal hematopoiesis (CH). To determine the relationship between CH and oncologic therapy we collected sequential blood samples from 525 cancer patients (median sampling interval time = 23 months, range: 6-53 months) of whom 61% received cytotoxic therapy or external beam radiation therapy and 39% received either targeted/immunotherapy or were untreated. Samples were sequenced using deep targeted capture-based platforms. To determine whether CH mutational features were associated with tMN risk, we performed Cox proportional hazards regression on 9,549 cancer patients exposed to oncologic therapy of whom 75 cases developed tMN (median time to transformation=26 months). To further compare the genetic and clonal relationships between tMN and the proceeding CH, we analyzed 35 cases for which paired samples were available. We compared the growth rate of the variant allele fraction (VAF) of CH clones across treatment modalities and in untreated patients. A significant increase in the growth rate of CH mutations was seen in DDR genes among those receiving cytotoxic (p=0.03) or radiation therapy (p=0.02) during the follow-up period compared to patients who did not receive therapy. Similar growth rates among treated and untreated patients were seen for non-DDR CH genes such as DNMT3A. Increasing cumulative exposure to cytotoxic therapy (p=0.01) and external beam radiation therapy (2×10-8) resulted in higher growth rates for DDR CH mutations. Among 34 subjects with at least two CH mutations in which one mutation was in a DDR gene and one in a non-DDR gene, we studied competing clonal dynamics for multiple gene mutations within the same patient. The risk of tMN was positively associated with CH in a known myeloid neoplasm driver mutation (HR=6.9, p<10-6), and increased with the total number of mutations and clone size. The strongest associations were observed for mutations in TP53 and for CH with mutations in spliceosome genes (SRSF2, U2AF1 and SF3B1). Lower hemoglobin, lower platelet counts, lower neutrophil counts, higher red cell distribution width and higher mean corpuscular volume were all positively associated with increased tMN risk. Among 35 cases for which paired samples were available, in 19 patients (59%), we found evidence of at least one of these mutations at the time of pre-tMN sequencing and in 13 (41%), we identified two or more in the pre-tMN sample. In all cases the dominant clone at tMN transformation was defined by a mutation seen at CH Our serial sampling data provide clear evidence that oncologic therapy strongly selects for clones with mutations in the DDR genes and that these clones have limited competitive fitness, in the absence of cytotoxic or radiation therapy. We further validate the relevance of CH as a predictor and precursor of tMN in cancer patients. We show that CH mutations detected prior to tMN diagnosis were consistently part of the dominant clone at tMN diagnosis and demonstrate that oncologic therapy directly promotes clones with mutations in genes associated with chemo-resistant disease such as TP53.

  • therapy resulted also in clonal evolution and saw changes in splice variants and spliceosome
  • therapy promotes current DDR mutations
  • clonal hematopoeisis due to selective pressures
  • mutations, variants number all predictive of myeloid disease
  • deferring adjuvant therapy for breast cancer patients with patients in highest MDS risk group based on biomarkers, greatly reduced their risk for MDS

5704 – Pan-cancer genomic characterization of patient-matched primary, extracranial, and brain metastases

Presenter/AuthorsOlivia W. Lee, Akash Mitra, Won-Chul Lee, Kazutaka Fukumura, Hannah Beird, Miles Andrews, Grant Fischer, John N. Weinstein, Michael A. Davies, Jason Huse, P. Andrew Futreal. The University of Texas MD Anderson Cancer Center, TX, The University of Texas MD Anderson Cancer Center, TX, Olivia Newton-John Cancer Research Institute and School of Cancer Medicine, La Trobe University, AustraliaDisclosures O.W. Lee: None. A. Mitra: None. W. Lee: None. K. Fukumura: None. H. Beird: None. M. Andrews: ; Merck Sharp and Dohme. G. Fischer: None. J.N. Weinstein: None. M.A. Davies: ; Bristol-Myers Squibb. ; Novartis. ; Array BioPharma. ; Roche and Genentech. ; GlaxoSmithKline. ; Sanofi-Aventis. ; AstraZeneca. ; Myriad Genetics. ; Oncothyreon. J. Huse: None. P. Futreal: None.

Abstract: Brain metastases (BM) occur in 10-30% of patients with cancer. Approximately 200,000 new cases of brain metastases are diagnosed in the United States annually, with median survival after diagnosis ranging from 3 to 27 months. Recently, studies have identified significant genetic differences between BM and their corresponding primary tumors. It has been shown that BM harbor clinically actionable mutations that are distinct from those in the primary tumor samples. Additional genomic profiling of BM will provide deeper understanding of the pathogenesis of BM and suggest new therapeutic approaches.
We performed whole-exome sequencing of BM and matched tumors from 41 patients collected from renal cell carcinoma (RCC), breast cancer, lung cancer, and melanoma, which are known to be more likely to develop BM. We profiled total 126 fresh-frozen tumor samples and performed subsequent analyses of BM in comparison to paired primary tumor and extracranial metastases (ECM). We found that lung cancer shared the largest number of mutations between BM and matched tumors (83%), followed by melanoma (74%), RCC (51%), and Breast (26%), indicating that cancer type with high tumor mutational burden share more mutations with BM. Mutational signatures displayed limited differences, suggesting a lack of mutagenic processes specific to BM. However, point-mutation heterogeneity revealed that BM evolve separately into different subclones from their paired tumors regardless of cancer type, and some cancer driver genes were found in BM-specific subclones. These models and findings suggest that these driver genes may drive prometastatic subclones that lead to BM. 32 curated cancer gene mutations were detected and 71% of them were shared between BM and primary tumors or ECM. 29% of mutations were specific to BM, implying that BM often accumulate additional cancer gene mutations that are not present in primary tumors or ECM. Co-mutation analysis revealed a high frequency of TP53 nonsense mutation in BM, mostly in the DNA binding domain, suggesting TP53 nonsense mutation as a possible prerequisite for the development of BM. Copy number alteration analysis showed statistically significant differences between BM and their paired tumor samples in each cancer type (Wilcoxon test, p < 0.0385 for all). Both copy number gains and losses were consistently higher in BM for breast cancer (Wilcoxon test, p =1.307e-5) and lung cancer (Wilcoxon test, p =1.942e-5), implying greater genomic instability during the evolution of BM.
Our findings highlight that there are more unique mutations in BM, with significantly higher copy number alterations and tumor mutational burden. These genomic analyses could provide an opportunity for more reliable diagnostic decision-making, and these findings will be further tested with additional transcriptomic and epigenetic profiling for better characterization of BM-specific tumor microenvironments.

  • are there genomic signatures different in brain mets versus non metastatic or normal?
  • 32 genes from curated databases were different between brain mets and primary tumor
  • frequent nonsense mutations in TP53
  • divergent clonal evolution of drivers in BMets from primary
  • they were able to match BM with other mutational signatures like smokers and lung cancer signatures

5707 – A standard operating procedure for the interpretation of oncogenicity/pathogenicity of somatic mutations

Presenter/AuthorsPeter Horak, Malachi Griffith, Arpad Danos, Beth A. Pitel, Subha Madhavan, Xuelu Liu, Jennifer Lee, Gordana Raca, Shirley Li, Alex H. Wagner, Shashikant Kulkarni, Obi L. Griffith, Debyani Chakravarty, Dmitriy Sonkin. National Center for Tumor Diseases, Heidelberg, Germany, Washington University School of Medicine, St. Louis, MO, Mayo Clinic, Rochester, MN, Georgetown University Medical Center, Washington, DC, Dana-Farber Cancer Institute, Boston, MA, Frederick National Laboratory for Cancer Research, Rockville, MD, University of Southern California, Los Angeles, CA, Sunquest, Boston, MA, Baylor College of Medicine, Houston, TX, Memorial Sloan Kettering Cancer Center, New York, NY, National Cancer Institute, Rockville, MDDisclosures P. Horak: None. M. Griffith: None. A. Danos: None. B.A. Pitel: None. S. Madhavan: ; Perthera Inc. X. Liu: None. J. Lee: None. G. Raca: None. S. Li: ; Sunquest Information Systems, Inc. A.H. Wagner: None. S. Kulkarni: ; Baylor Genetics. O.L. Griffith: None. D. Chakravarty: None. D. Sonkin: None.AbstractSomatic variants in cancer-relevant genes are interpreted from multiple partially overlapping perspectives. When considered in discovery and translational research endeavors, it is important to determine if a particular variant observed in a gene of interest is oncogenic/pathogenic or not, as such knowledge provides the foundation on which targeted cancer treatment research is based. In contrast, clinical applications are dominated by diagnostic, prognostic, or therapeutic interpretations which in part also depends on underlying variant oncogenicity/pathogenicity. The Association for Molecular Pathology, the American Society of Clinical Oncology, and the College of American Pathologists (AMP/ASCO/CAP) have published structured somatic variant clinical interpretation guidelines which specifically address diagnostic, prognostic, and therapeutic implications. These guidelines have been well-received by the oncology community. Many variant knowledgebases, clinical laboratories/centers have adopted or are in the process of adopting these guidelines. The AMP/ASCO/CAP guidelines also describe different data types which are used to determine oncogenicity/pathogenicity of a variant, such as: population frequency, functional data, computational predictions, segregation, and somatic frequency. A second collaborative effort created the European Society for Medical Oncology (ESMO) Scale for Clinical Actionability of molecular Targets to provide a harmonized vocabulary that provides an evidence-based ranking system of molecular targets that supports their value as clinical targets. However, neither of these clinical guideline systems provide systematic and comprehensive procedures for aggregating population frequency, functional data, computational predictions, segregation, and somatic frequency to consistently interpret variant oncogenicity/pathogenicity, as has been published in the ACMG/AMP guidelines for interpretation of pathogenicity of germline variants. In order to address this unmet need for somatic variant oncogenicity/pathogenicity interpretation procedures, the Variant Interpretation for Cancer Consortium (VICC, a GA4GH driver project) Knowledge Curation and Interpretation Standards (KCIS) working group (WG) has developed a Standard Operating Procedure (SOP) with contributions from members of ClinGen Somatic Clinical Domain WG, and ClinGen Somatic/Germline variant curation WG using an approach similar to the ACMG/AMP germline pathogenicity guidelines to categorize evidence of oncogenicity/pathogenicity as very strong, strong, moderate or supporting. This SOP enables consistent and comprehensive assessment of oncogenicity/pathogenicity of somatic variants and latest version of an SOP can be found at https://cancervariants.org/wg/kcis/.

  • best to use this SOP for somatic mutations and not rearangements
  • variants based on oncogenicity as strong to weak
  • useful variant knowledge on pathogenicity curated from known databases
  • the recommendations would provide some guideline on curating unknown somatic variants versus known variants of hereditary diseases
  • they have not curated RB1 mutations or variants (or for other RBs like RB2? p130?)

 

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Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 27, 2020 Minisymposium on Signaling in Cancer 11:45am-1:30 pm

Reporter: Stephen J. Williams, PhD.

SESSION VMS.MCB01.01 – Emerging Signaling Vulnerabilities in Cancer
April 27, 2020, 11:45 AM – 1:30 PM
Virtual Meeting: All Session Times Are U.S. EDT
DESCRIPTION

All session times are U.S. Eastern Daylight Time (EDT). Access to AACR Virtual Annual Meeting I sessions are free with registration. Register now at http://www.aacr.org/virtualam2020

Session Type

Virtual Minisymposium

Track(s)

Molecular and Cellular Biology/Genetics

16 Presentations
11:45 AM – 1:30 PM
– Chairperson

J. Silvio Gutkind. UCSD Moores Cancer Center, La Jolla, CA

11:45 AM – 1:30 PM
– Chairperson

  • in 80’s and 90’s signaling focused on defects and also oncogene addiction.  Now the field is switching to finding vulnerabilities in signaling cascades in cancer

Adrienne D. Cox. University of North Carolina at Chapel Hill, Chapel Hill, NC

11:45 AM – 11:55 AM
– Introduction

J. Silvio Gutkind. UCSD Moores Cancer Center, La Jolla, CA

11:55 AM – 12:05 PM
1085 – Interrogating the RAS interactome identifies EFR3A as a novel enhancer of RAS oncogenesis

Hema Adhikari, Walaa Kattan, John F. Hancock, Christopher M. Counter. Duke University, Durham, NC, University of Texas MD Anderson Cancer Center, Houston, TX

Abstract: Activating mutations in one of the three RAS genes (HRAS, NRAS, and KRAS) are detected in as much as a third of all human cancers. As oncogenic RAS mediates it tumorigenic signaling through protein-protein interactions primarily at the plasma membrane, we sought to document the protein networks engaged by each RAS isoform to identify new vulnerabilities for future therapeutic development. To this end, we determined interactomes of oncogenic HRAS, NRAS, and KRAS by BirA-mediated proximity labeling. This analysis identified roughly ** proteins shared among multiple interactomes, as well as a smaller subset unique to a single RAS oncoprotein. To identify those interactome components promoting RAS oncogenesis, we created and screened sgRNA library targeting the interactomes for genes modifying oncogenic HRAS-, NRAS-, or KRAS-mediated transformation. This analysis identified the protein EFR3A as not only a common component of all three RAS interactomes, but when inactivated, uniformly reduced the growth of cells transformed by any of the three RAS isoforms. EFR3A recruits a complex containing the druggable phosphatidylinositol (Ptdlns) 4 kinase alpha (PI4KA) to the plasma membrane to generate the Ptdlns species PI4P. We show that EFR3A sgRNA reduced multiple RAS effector signaling pathways, suggesting that EFR3A acts at the level of the oncoprotein itself. As lipids play a critical role in the membrane localization of RAS, we tested and found that EFR3A sgRNA reduced not only the occupancy of RAS at the plasma membrane, but also the nanoclustering necessary for signaling. Furthermore, the loss of oncogenic RAS signaling induced by EFR3A sgRNA was rescued by targeting PI4K to the plasma membrane. Taken together, these data support a model whereby EFR3A recruits PI4K to oncogenic RAS to promote plasma membrane localization and nonclustering, and in turn, signaling and transformation. To investigate the therapeutic potential of this new RAS enhancer, we show that EFR3A sgRNA reduced oncogenic KRAS signaling and transformed growth in a panel of pancreatic ductal adenocarcinoma (PDAC) cell lines. Encouraged by these results we are exploring whether genetically inactivating the kinase activity of PI4KA inhibits oncogenic signaling and transformation in PDAC cell lines. If true, pharmacologically targeting PI4K may hold promise as a way to enhance the anti-neoplastic activity of drugs targeting oncogenic RAS or its effectors.

@DukeU

@DukeMedSchool

@MDAndersonNews

  • different isoforms of ras mutations exist differentially in various tumor types e.g. nras vs kras
  • the C terminal end serve as hotspots of mutations and probably isoform specific functions
  • they determined the interactomes of nras and kras and determined how many candidates are ras specific
  • they overlayed results from proteomic and CRSPR screen; EFR3a was a potential target that stuck out
  • using TCGA patients with higher EFR3a had poorer prognosis
  • EFR3a promotes Ras signaling; and required for RAS driven tumor growth (in RAS addicted tumors?)
  • EGFR3a promotes clustering of oncogenic RAS at plasma membrane

 

12:05 PM – 12:10 PM
– Discussion

12:10 PM – 12:20 PM
1086 – Downstream kinase signaling is dictated by specific KRAS mutations; Konstantin Budagyan, Jonathan Chernoff. Drexel University College of Medicine, Philadelphia, PA, Fox Chase Cancer Center, Philadelphia, PA @FoxChaseCancer

Abstract: Oncogenic KRAS mutations are common in colorectal cancer (CRC), found in ~50% of tumors, and are associated with poor prognosis and resistance to therapy. There is substantial diversity of KRAS alleles observed in CRC. Importantly, emerging clinical and experimental analysis of relatively common KRAS mutations at amino acids G12, G13, A146, and Q61 suggest that each mutation differently influences the clinical properties of a disease and response to therapy. For example, KRAS G12 mutations confer resistance to EGFR-targeted therapy, while G13D mutations do not. Although there is clinical evidence to suggest biological differences between mutant KRAS alleles, it is not yet known what drives these differences and whether they can be exploited for allele-specific therapy. We hypothesized that different KRAS mutants elicit variable alterations in downstream signaling pathways. To investigate this hypothesis, we created a novel system by which we can model KRAS mutants in isogenic mouse colon epithelial cell lines. To generate the cell lines, we developed an assay using fluorescent co-selection for CRISPR-driven genome editing. This assay involves simultaneous introduction of single-guide RNAs (sgRNAs) to two different endogenous loci resulting in double-editing events. We first introduced Cas9 and blue fluorescent protein (BFP) into mouse colon epithelial cell line containing heterozygous KRAS G12D mutation. We then used sgRNAs targeting BFP and the mutant G12D KRAS allele along with homology-directed repair (HDR) templates for a GFP gene and a KRAS mutant allele of our choice. Cells that successfully undergo HDR are GFP-positive and contain the desired KRAS mutation. Therefore, selection for GFP-positive cells allows us to identify those with phenotypically silent KRAS edits. Ultimately, this method allows us to toggle between different mutant alleles while preserving the wild-type allele, all in an isogenic background. Using this method, we have generated cell lines with endogenous heterozygous KRAS mutations commonly seen in CRC (G12D, G12V, G12C, G12R, G13D). In order to elucidate cellular signaling pathway differences between the KRAS mutants, we screened the mutated cell lines using a small-molecule library of ~160 protein kinase inhibitors. We found that there are mutation-specific differences in drug sensitivity profiles. These observations suggest that KRAS mutants drive specific cellular signaling pathways, and that further exploration of these pathways may prove to be valuable for identification of novel therapeutic opportunities in CRC.

  • Flourescent coselection of KRAS edits by CRSPR screen in a colorectal cancer line; a cell that is competent to undergo HR can undergo combination multiple KRAS
  • target only mutant allele while leaving wild type intact;
  • it was KRAS editing event in APC  +/- mouse cell line
  • this enabled a screen for kinase inhibitors that decreased tumor growth in isogenic cell lines; PKC alpha and beta 1 inhibitors, also CDK4 inhibitors inhibited cell growth
  • questions about heterogeneity in KRAS clones; they looked at off target guides and looked at effects in screens; then they used top two clones that did not have off target;  questions about 3D culture- they have not done that; Question ? dependency on AKT activity? perhaps the G12E has different downstream effectors

 

12:20 PM – 12:25 PM
– Discussion

12:25 PM – 12:35 PM
1087 – NF1 regulates the RAS-related GTPases, RRAS and RRAS2, independent of RAS activity; Jillian M. Silva, Lizzeth Canche, Frank McCormick. University of California, San Francisco, San Francisco, CA @UCSFMedicine

Abstract: Neurofibromin, which is encoded by the neurofibromatosis type 1 (NF1) gene, is a tumor suppressor that acts as a RAS-GTPase activating protein (RAS-GAP) to stimulate the intrinsic GTPase activity of RAS as well as the closely related RAS subfamily members, RRAS, RRAS2, and MRAS. This results in the conversion of the active GTP-bound form of RAS into the inactive GDP-bound state leading to the downregulation of several RAS downstream effector pathways, most notably MAPK signaling. While the region of NF1 that regulates RAS activity represents only a small fraction of the entire protein, a large extent of the NF1 structural domains and their corresponding mechanistic functions remain uncharacterized despite the fact there is a high frequency of NF1 mutations in several different types of cancer. Thus, we wanted to elucidate the underlying biochemical and signaling functions of NF1 that are unrelated to the regulation of RAS and how loss of these functions contributes to the pathogenesis of cancer. To accomplish this objective, we used CRISPR-Cas9 methods to knockout NF1 in an isogenic “RASless” MEF model system, which is devoid of the major oncogenic RAS isoforms (HRAS, KRAS, and NRAS) and reconstituted with the KRAS4b wild-type or mutant KRASG12C or KRASG12D isoform. Loss of NF1 led to elevated RAS-GTP levels, however, this increase was not as profound as the levels in KRAS-mutated cells or provided a proliferative advantage. Although ablation of NF1 resulted in sustained activation of MAPK signaling, it also unexpectedly, resulted in a robust increase in AKT phosphorylation compared to KRAS-mutated cells. Surprisingly, loss of NF1 in KRAS4b wild-type and KRAS-mutated cells potently suppressed the RAS-related GTPases, RRAS and RRAS2, with modest effects on MRAS, at both the transcript and protein levels. A Clariom™D transcriptome microarray analysis revealed a significant downregulation in the NF-κB target genes, insulin-like growth factor binding protein 2 (IGFBP2), argininosuccinate synthetase 1 (ASS1), and DUSP1, in both the NF1 knockout KRAS4b wild-type and KRAS-mutated cells. Moreover, NF1Null melanoma cells also displayed a potent suppression of RRAS and RRAS2 as well as these NF-κB transcription factors. Since RRAS and RRAS2 both contain the same NF-κB transcription factor binding sites, we hypothesize that IGFBP2, ASS1, and/or DUSP1 may contribute to the NF1-mediated regulation of these RAS-related GTPases. More importantly, this study provides the first evidence of at least one novel RAS-independent function of NF1 to regulate the RAS-related subfamily members, RRAS and RRAS2, in a manner exclusive of its RAS-GTPase activity and this may provide insight into new potential biomarkers and molecular targets for treating patients with mutations in NF1.
  • NF1 and SPRED work together to signal from RTK cKIT through RAS
  • NF1 knockout cells had higher KRAS and had increased cell proliferation
  • NF1 -/-  or SPRED loss had increased ERK phosphorylation and some increase in AKT activity compared to parental cells
  • they used isogenic cell lines devoid of all RAS isoforms and then reconstituted with specific RAS WT or mutants
  • NF1 and SPRED KO both reduce RRAS expression; in an AKT independent mannner
  • NF1 SPRED KO cells have almost no IGFBP2 protein expression and SNAIL so maybe affecting EMT?
  • this effect is independent of its RAS GTPAse activity (noncanonical)

12:35 PM – 12:40 PM
– Discussion

12:40 PM – 12:50 PM
1088 – Elucidating the regulation of delayed-early gene targets of sustained MAPK signaling; Kali J. Dale, Martin McMahon. University of Utah, Salt Lake City, UT, Huntsman Cancer Institute, Salt Lake City, UT

Abstract: RAS and its downstream effector, BRAF, are commonly mutated proto-oncogenes in many types of human cancer. Mutationally activated RAS or BRAF signal through the MEK→ERK MAP kinase (MAPK) pathway to regulate key cancer cell hallmarks such as cell division cycle progression, reduced programmed cell death, and enhanced cell motility. Amongst the list of RAS/RAF-regulated genes are those encoding integrins, alpha-beta heterodimeric transmembrane proteins that regulate cell adhesion to the extracellular matrix. Altered integrin expression has been linked to the acquisition of more aggressive behavior by melanoma, lung, and breast cancer cells leading to diminished survival of cancer patients. We have previously documented the ability of the RAS-activated MAPK pathway to induce the expression of ITGB3 encoding integrin β3 in several different cell types. RAS/RAF-mediated induction of ITGB3 mRNA requires sustained, high-level activation of RAF→MEK→ERK signaling mediated by oncogene activation and is classified as “delayed-early”, in that it is sensitive to the protein synthesis inhibitor cycloheximide. However, to date, the regulatory mechanisms that allow for induced ITGB3 downstream of sustained, high-level activation of MAPK signaling remains obscure. We have identified over 300 DEGs, including those expressing additional cell surface proteins, that display similar regulatory characteristics as ITGB3. We use integrin β3 as a model to test our hypothesis that there is a different mechanism of regulation for delayed-early genes (DEG) compared to the canonical regulation of Immediate-Early genes. There are three regions in the chromatin upstream of the ITGB3 that become more accessible during RAF activation. We are relating the chromatin changes seen during RAF activation to active enhancer histone marks. To elucidate the essential genes of this regulation process, we are employing the use of a genome-wide CRISPR knockout screen. The work presented from this abstract will help elucidate the regulatory properties of oncogenic progression in BRAF mutated cancers that could lead to the identification of biomarkers.

12:50 PM – 12:55 PM
– Discussion

12:55 PM – 1:05 PM
1090 – Regulation of PTEN translation by PI3K signaling maintains pathway homeostasis

Radha Mukherjee, Kiran Gireesan Vanaja, Jacob A. Boyer, Juan Qiu, Xiaoping Chen, Elisa De Stanchina, Sarat Chandarlapaty, Andre Levchenko, Neal Rosen. Memorial Sloan Kettering Cancer Center, New York, NY, Yale University, West Haven, CT, Memorial Sloan Kettering Cancer Center, New York, NY, Memorial Sloan Kettering Cancer Center, New York, NY @sloan_kettering

Abstract: The PI3K pathway is a key regulator of metabolism, cell proliferation and migration and some of its components (e.g. PIK3CA and PTEN) are frequently altered in cancer by genetic events that deregulate its output. However, PI3K signaling is not usually the primary driver of these tumors and inhibitors of components of the pathway have only modest antitumor effects. We now show that both physiologic and oncogenic activation of the PI3K signaling by growth factors and an activating hotspot PIK3CA mutation respectively, cause an increase in the expression of the lipid phosphatase PTEN, thus limiting the duration of the signal and the output of the pathway in tumors. Pharmacologic and physiologic inhibition of the pathway by HER2/PI3K/AKT/mTOR inhibitors and nutrient starvation respectively reduce PTEN, thus buffering the effects of inhibition and contributing to the rebound in pathway activity that occurs in tumors. This regulation is found to be a feature of multiple types of cancer, non-cancer cell line and PDX models thereby highlighting its role as a key conserved feedback loop within the PI3K signaling network, both in vitro and in vivo. Regulation of expression is due to mTOR/4EBP1 dependent control of PTEN translation and is lost when 4EBP1 is knocked out. Translational regulation of PTEN is therefore a major homeostatic regulator of physiologic PI3K signaling and plays a role in reducing the output of oncogenic mutants that deregulate the pathway and the antitumor activity of PI3K pathway inhibitors.

  • mTOR can be a potent regulator of PTEN and therefore a major issue when developing PI3K inhibitors

1:05 PM – 1:10 PM
– Discussion

1:10 PM – 1:20 PM
1091 – BI-3406 and BI 1701963: Potent and selective SOS1::KRAS inhibitors induce regressions in combination with MEK inhibitors or irinotecan

Daniel Gerlach, Michael Gmachl, Juergen Ramharter, Jessica Teh, Szu-Chin Fu, Francesca Trapani, Dirk Kessler, Klaus Rumpel, Dana-Adriana Botesteanu, Peter Ettmayer, Heribert Arnhof, Thomas Gerstberger, Christiane Kofink, Tobias Wunberg, Christopher P. Vellano, Timothy P. Heffernan, Joseph R. Marszalek, Mark Pearson, Darryl B. McConnell, Norbert Kraut, Marco H. Hofmann. Boehringer Ingelheim RCV GmbH & Co KG, Vienna, Austria, The University of Texas MD Anderson Cancer Center, Houston, TX, The University of Texas MD Anderson Cancer Center, Houston, TX, Boehringer Ingelheim RCV GmbH & Co KG, Vienna, Austria

  • there is rational for developing an SOS1 inhibitor (GEF); BI3406 shows better PK and PD as a candidate
  • most sensitive cell lines to inhibitor carry KRAS mutation; NRAS or BRAF mutations are not sensititve
  • KRAS mutation defines sensitivity so they created KRAS mut isogenic cell lines
  • found best to co inhibit SOS and MEK as observed plasticity with only SOS
  • dual combination in lung NSCLC pancreatic showed enhanced efficacy compared to monotherapy
  • SOS1 inhibition plus irinotecan enhances DNA double strand breaks; no increased DNA damage in normal stroma but preferentially in tumor cells
  • these SOS1 had broad activity against KRAS mutant models;
  • phase 1 started in 2019;

@Boehringer

1:20 PM – 1:25 PM
– Discussion

1:25 PM – 1:30 PM
– Closing Remarks

Adrienne D. Cox. University of North Carolina at Chapel Hill, Chapel Hill, NC

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Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 27, 2020 Opening Remarks and Clinical Session 9 am

Reporter: Stephen J. Williams, PhD.

9:00 AM Opening Session

9:00 AM – 9:05 AM
– Opening Video

9:05 AM – 9:15 AM
– AACR President: Opening Remarks Elaine R. Mardis. Nationwide Children’s Hospital, Columbus, OH

 

Dr. Mardis is the Robert E. and Louise F. Dunn Distinguished Professor of Medicine @GenomeInstitute at Washington University of St. Louis School of Medicine.

Opening remarks:  Dr. Mardis gave her welcome from her office.  She expressed many thanks to healthcare workers and the hard work of scientists and researchers.  She also expressed some regret for the many scientists who had wonderful research to present and how hard it was to make the decision to go virtual however she feels there now more than ever still needs a venue to discuss scientific and clinical findings.  Some of the initiatives that she has had the opportunity to engage in the areas of groundbreaking discoveries and clinical trials.  606,000 lives will be lost in US this year from cancer.  AACR is being vigilant as also an advocacy platform and public policy platform in Congress and Washington.  The AACR has been at the front of public policy on electronic cigarettes.  Blood Cancer Discovery is their newest journal.  They are going to host joint conferences with engineers, mathematicians and physicists to discuss how they can help to transform oncology.  Cancer Health Disparity Annual Conference is one of the fastest growing conferences.  They will release a report later this year about the scope of the problem and policy steps needed to alleviate these disparities.  Lack of racial and ethnic minorities in cancer research had been identified an issue and the AACR is actively working to reduce the disparities within the ranks of cancer researchers.   Special thanks to Dr. Margaret Foti for making the AACR the amazing organization it is.

 

9:15 AM – 9:30 AM- AACR Annual Meeting Program Chair: Review of Program for AACR Virtual Annual Meeting Antoni Ribas. UCLA Medical Center, Los Angeles, CA

Antoni Ribas, MD PhD is Professor, Medicine, Surgery, Molecular and Medical Pharmacology; Director, Parker Institute for Cancer Immunotherapy Center at UCLA; Director, UCLA Jonsson Comprehensive Cancer Center Tumor Immunology Program aribas@mednet.ucla.edu

The AACR felt it was important to keep the discourse in the cancer research field as the Annual AACR meeting is the major way scientists and clinicians discuss the latest and most pertinent results.  A three day virtual meeting June 22-24 will focus more on the translational and basic research while this meeting is more focused on clinical trials.  There will be educational programs during the June virtual meeting.  The COVID in Cancer part of this virtual meeting was put in specially for this meeting and there will be a special meeting on this in July.  They have created an AACR COVID task force.  The AACR has just asked Congress and NIH to extend the grants due to the COVID induced shutdown of many labs.

9:30  Open Clinical Plenary Session (there are 17 sessions today but will only cover a few of these)

9:30 AM – 9:31 AM
– Chairperson Nilofer S. Azad. Johns Hopkins Sidney Kimmel Comp. Cancer Center, Baltimore, MD @noza512

9:30 AM – 9:31 AM
– Chairperson Manuel Hidalgo. Weill Cornell Medicine, New York, NY

9:30 AM – 9:35 AM
– Introduction Nilofer S. Azad. Johns Hopkins Sidney Kimmel Comp. Cancer Center, Baltimore, MD

9:35 AM – 9:45 AM
CT011 – Evaluation of durvalumab in combination with olaparib and paclitaxel in high-risk HER2 negative stage II/III breast cancer: Results from the I-SPY 2 TRIAL Lajos Pusztai, et al

see https://www.abstractsonline.com/pp8/#!/9045/presentation/10593

AbstractBackground: I-SPY2 is a multicenter, phase 2 trial using response-adaptive randomization within molecular subtypes defined by receptor status and MammaPrint risk to evaluate novel agents as neoadjuvant therapy for breast cancer. The primary endpoint is pathologic complete response (pCR, ypT0/is ypN0)). DNA repair deficiency in cancer cells can lead to immunogenic neoantigens, activation of the STING pathway, and PARP inhibition can also upregulate PD-L1 expression. Based on these rationales we tested the combination of durvalumab (anti-PDL1), olaparib (PARP inhibitor) and paclitaxel in I-SPY2.
Methods: Women with tumors ≥ 2.5 cm were eligible for screening. Only HER2 negative (HER2-) patients were eligible for this treatment, hormone receptor positive (HR+) patients had to have MammaPrint high molecular profile. Treatment included durvalumab 1500 mg every 4 weeks x 3, olaparib 100 mg twice daily through weeks 1-11 concurrent with paclitaxel 80 mg/m2 weekly x 12 (DOP) followed by doxorubicin/cyclophosphamide (AC) x 4. The control arm was weekly paclitaxel x 12 followed by AC x 4. All patients undergo serial MRI imaging and imaging response at 3 & 12 weeks combined with accumulating pCR data are used to estimate, and continuously update, predicted pCR rate for the trial arm. Regimens “graduation with success” when the Bayesian predictive probability of success in a 300-patient phase 3 neoadjuvant trial in the appropriate biomarker groups reaches > 85%.
Results: A total of 73 patients received DOP treatment including 21 HR- tumors (i.e. triple-negative breast cancer, TNBC) and 52 HR+ tumors between May 2018 – June 2019. The control group included 299 patients with HER2- tumors. The DOP arm graduated in June 2019, 13 months after enrollment had started, for all HER2- negative and the HR+/HER2- cohorts with > 0.85% predictive probabilities of success. 72 patient completed surgery and evaluable for pCR, the final predicted probabilities of success in a future phase III trial to demonstrate higher pCR rate with DOP compared to control are 81% for all HER2- cancers (estimated pCR rate 37%), 80% for TNBC (estimated pCR rate 47%) and 74.5% for HR+/HER2- patients (estimated pCR rate 28%). Association between pCR and germline BRCA status and immune gene expression including PDL1 will be presented at the meeting. No unexpected toxicities were seen, but 10 patients (14%) had possibly immune or olaparib related grade 2/3 AEs (3 pneumonitis, 2 adrenal insufficiency, 1 colitis, 1 pancreatitis, 2 elevated LFT, 1 skin toxicity, 2 hypothyroidism, 1 hyperthyroidism, 1 esophagitis).
Conclusion: I-SPY2 demonstrated a significant improvement in pCR with durvalumab and olaparib included with paclitaxel compared to chemotherapy alone in women with stage II/III high-risk, HER2-negative breast cancer, improvement was seen in both the HR+ and TNBC subsets.

  • This combination of durvalumab and olaparib is safe in triple negative breast cancer
  • expected synergy between PARP inhibitors and PDL1 inhibitors as olaparib inhibits DNA repair and would increase the mutational burden, which is in lung cancer shown to be a biomarker for efficacy of immune checkpoint inhibitors such as Opdivio
  • three subsets of breast cancers were studied: her2 negative, triple negative and ER+ tumors
  • MRI imaging tumor size was used as response
  • olaparib arm had elevation of liver enzymes and there was a pancreatitis
  • however paclitaxel was used within the combination as well as a chemo arm but the immuno arm alone may not be better than chemo alone but experimental arm with all combo definitely better than chemo alone
  • they did not look at BRCA1/2 status, followup talk showed that this is a select group that may see enhanced benefit; PARP inhibitors were seen to be effective only in BRCA1/2 mutant ovarian cancer previously

 

10:10 AM – 10:20 AM
CT012 – Evaluation of atezolizumab (A), cobimetinib (C), and vemurafenib (V) in previously untreated patients with BRAFV600 mutation-positive advanced melanoma: Primary results from the phase 3 IMspire150 trial Grant A. McArthur,

for abstract please see https://www.abstractsonline.com/pp8/#!/9045/presentation/10594

AbstractBackground: Approved systemic treatments for advanced melanoma include immune checkpoint inhibitor therapy (CIT) and targeted therapy with BRAF plus MEK inhibitors for BRAFV600E/K mutant melanoma. Response rates with CITs are typically lower than those observed with targeted therapy, but CIT responses are more durable. Preclinical and clinical data suggest a potential for synergy between CIT and BRAF plus MEK inhibitors. We therefore evaluated whether combining CIT with targeted therapy could improve efficacy vs targeted therapy alone. Methods: Treatment-naive patients with unresectable stage IIIc/IV melanoma (AJCC 7th ed), measurable disease by RECIST 1.1, and BRAFV600 mutations in their tumors were randomized to the anti­-programmed death-ligand 1 antibody A + C + V or placebo (Pbo) + C + V. A or Pbo were given on days 1 and 15 of each 28-day cycle. Treatment was continued until disease progression or unacceptable toxicity. The primary outcome was investigator-assessed progression-free survival (PFS). Results: 514 patients were enrolled (A + C + V = 256; Pbo + C + V = 258) and followed for a median of 18.9 months. Investigator-assessed PFS was significantly prolonged with A + C + V vs Pbo + C + V (15.1 vs 10.6 months, respectively; hazard ratio: 0.78; 95% confidence interval: 0.63-0.97; P=0.025), an effect seen in all prognostic subgroups. While objective response rates were similar in the A + C + V and Pbo + C + V groups, median duration of response was prolonged with A + C + V (21.0 months) vs Pbo + C + V (12.6 months). Overall survival data were not mature at the time of analysis. Common treatment-related adverse events (AEs; >30%) in the A + C + V and Pbo + C + V groups were blood creatinine phosphokinase (CPK) increase (51.3% vs 44.8%), diarrhea (42.2% vs 46.6%), rash (40.9% in both arms), arthralgia (39.1% vs 28.1%), pyrexia (38.7% vs 26.0%), alanine aminotransferase (ALT) increase (33.9% vs 22.8%), and lipase increase (32.2% vs 27.4%). Common treatment-related grade 3/4 AEs (>10%) that occurred in the A + C + V and Pbo + C + V groups were lipase increase (20.4% vs 20.6%), blood CPK increase (20.0% vs 14.9%), ALT increase (13.0% vs 8.9%), and maculopapular rash (12.6% vs 9.6%). The incidence of treatment-related serious AEs was similar between the A + C + V (33.5%) and Pbo + C + V (28.8%) groups. 12.6% of patients in the A + C + V group and 15.7% in the Pbo + C + V group stopped all treatment because of AEs. The safety profile of the A + C + V regimen was generally consistent with the known profiles of the individual components. Conclusion: Combination therapy with A + C + V was tolerable and manageable, produced durable responses, and significantly increased PFS vs Pbo + C + V. Thus, A + C + V represents a viable treatment option for BRAFV600 mutation-positive advanced melanoma. ClinicalTrials.gov ID: NCT02908672

 

 

10:25 AM – 10:35 AM
CT013 – SWOG S1320: Improved progression-free survival with continuous compared to intermittent dosing with dabrafenib and trametinib in patients with BRAF mutated melanoma Alain Algazi,

for abstract and more author information please see https://www.abstractsonline.com/pp8/#!/9045/presentation/10595

AbstractBackground: BRAF and MEK inhibitors yield objective responses in the majority of BRAFV600E/K mutant melanoma patients, but acquired resistance limits response durations. Preclinical data suggests that intermittent dosing of these agents may delay acquired resistance by deselecting tumor cells that grow optimally in the presence of these agents. S1320 is a randomized phase 2 clinical trial designed to determine whether intermittent versus continuous dosing of dabrafenib and trametinib improves progression-free survival (PFS) in patients with advanced BRAFV600E/K melanoma.
Methods: All patients received continuous dabrafenib and trametinib for 8-weeks after which non-progressing patients were randomized to receive either continuous treatment or intermittent dosing of both drugs on a 3-week-off, 5-week-on schedule. Unscheduled treatment interruptions of both drugs for > 14 days were not permitted. Responses were assessed using RECIST v1.1 at 8-week intervals scheduled to coincide with on-treatment periods for patients on the intermittent dosing arm. Adverse events were assessed using CTCAE v4 monthly. The design assumed exponential PFS with a median of 9.4 months using continuous dosing, 206 eligible patients and 156 PFS events. It had 90% power with a two-sided α = 0.2 to detect a change to a median with an a priori hypothesis that intermittent dosing would improve the median PFS to 14.1 months using a Cox model stratified by the randomization stratification factors.
Results: 242 patients were treated and 206 patients without disease progression after 8 weeks were randomized, 105 to continuous and 101 to intermittent treatment. 70% of patients had not previously received immune checkpoint inhibitors. There were no significant differences between groups in terms of baseline patient characteristics. The median PFS was statistically significantly longer, 9.0 months from randomization, with continuous dosing vs. 5.5 months from randomization with intermittent dosing (p = 0.064). There was no difference in overall survival between groups (median OS = 29.2 months in both arms p = 0.93) at a median follow up of 2 years. 77% of patient treated continuously discontinued treatment due to disease progression vs. 84% treated intermittently (p = 0.34).
Conclusions: Continuous dosing with the BRAF and MEK inhibitors dabrafenib and trametinib yields superior PFS compared with intermittent dosing.

  • combo of MEK and BRAF inhibitors can attract immune cells like TREGs so PDL1 inhibitor might help improve outcome
  • PFS was outcome endpoint
  • LDH was elevated in three patients (why are they seeing liver tox?  curious like previous study); are seeing these tox with the PDL1 inhibitors
  • there was marked survival over placebo group and PFS was statistically  with continuous dosing however intermittent dosing shows no improvement

Dr. Wafik el Diery gave a nice insight as follows

Follow on Twitter at:

@pharma_BI

@AACR

@GenomeInstitute

@CureCancerNow

@UCLAJCCC

#AACR20

#AACR2020

#curecancernow

#pharmanews

 

 

 

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Opinion Articles from the Lancet: COVID-19 and Cancer Care in China and Africa

Reporter: Stephen J. Williams, PhD

Cancer Patients in SARS-CoV-2 infection: a nationwide analysis in China

Wenhua Liang, Weijie Guan, Ruchong Chen, Wei Wang, Jianfu Li, Ke Xu, Caichen Li, Qing Ai, Weixiang Lu, Hengrui Liang, Shiyue Li, Jianxing He

Lancet Oncol. 2020 Mar; 21(3): 335–337. Published online 2020 Feb 14. doi: 10.1016/S1470-2045(20)30096-6

PMCID: PMC7159000

 

The National Clinical Research Center for Respiratory Disease and the National Health Commission of the People’s Republic of China collaborated to establish a prospective cohort to monitor COVID-19 cases in China.  As on Jan31, 20202007 cases have been collected and analyzed with confirmed COVID-19 infection in these cohorts.

Results: 18 or 1% of COVID-19 cases had a history of cancer (the overall average cancer incidence in the overall China population is 0.29%) {2015 statistics}.  It appeared that cancer patients had an observable higher risk of COVID related complications upon hospitalization. However, this was a higher risk compared with the general population.  There was no comparison between cancer patients not diagnosed with COVID-19 and an assessment of their risk of infection.  Interestingly those who were also cancer survivors showed an increased incidence of COVID related severe complications compared to the no cancer group.

Although this study could have compared the risk within a cancer group, the authors still felt the results warranted precautions when dealing with cancer patients and issued recommendations including:

  1. Postponing of adjuvant chemotherapy or elective surgery for stable cancer should be considered
  2. Stronger personal protection for cancer patients
  3. More intensive surveillance or treatment should be considered when patients with cancer are infected, especially in older patients

Further studies will need to address the risk added by specific types of chemotherapy: cytolytic versus immunotherapy e.g.

 

Preparedness for COVID-19 in the oncology community in Africa

Lancet Oncology, Verna Vanderpuye, Moawia Mohammed,Ali Elhassan

Hannah Simonds: Published:April 03, 2020DOI:https://doi.org/10.1016/S1470-2045(20)30220-5

Africa has a heterogeneity of cultures, economies and disease patterns however fortunately it is one of the last countries to be hit by the COVID-19 pandemic, which allows some time for preparation by the African nations.  The authors note that with Africa’s previous experiences with epidemics, namely ebola and cholera, Africa should be prepared for this pandemic.

However, as a result of poor economic discipline, weak health systems, and poor health-seeking behaviors across the continent, outcomes could be dismal. Poverty, low health literacy rates, and cultural practices that negatively affect cancer outcomes will result in poor assimilation of COVID-19 containment strategies in Africa.”

In general African oncologists are following COVID-19 guidelines from other high-income countries, but as this writer acknowledges in previous posts, there was a significant lag from first cases in the United States to the concrete formulation of guidelines for both oncologists and patients with regard to this pandemic.  African oncologist are delaying the start of adjuvant therapies and switching more to oral therapies and rethink palliative care.

However the authors still have many more questions than answers, however even among countries that have dealt with this pandemic before Africa (like Italy and US), oncologists across the globe still have not been able to answer questions like: what if my patient develops a fever, what do I do during a period of neutropenia, to their satisfaction or the satisfaction of the patient.  These are questions even oncologists who are dealing in COVID hotspots are still trying to answer including what constitutes a necessary surgical procedure? As I have highlighted in recent posts, oncologists in New York have all but shut down all surgical procedures and relying on liquid biopsies taken in the at-home setting. But does Africa have this capability of access to at home liquid biopsy procedures?

In addition, as I had just highlighted in a recent posting, there exists extreme cancer health disparities across the African continent, as well as the COVID responses. In West Africa, COVID-19 protocols are defined at individual institutions.  This is more like the American system where even NCI designated centers were left to fashion some of their own guidelines initially, although individual oncologists had banded together to do impromptu meetings to discuss best practices. However this is fine for big institutions, but as in the US, there is a large rural population on the African continent with geographical barriers to these big centers. Elective procedures have been cancelled and small number of patients are seen by day.  This remote strategy actually may be well suited for African versus more developed nations, as highlighted in a post I did about mobile health app use in oncology, as this telemedicine strategy is rather new among US oncologists (reference my posts with the Town Hall meetings).

The situation is more complicated in South Africa where they are dealing with an HIV epidemic, where about 8 million are infected with HIV. Oncology services here are still expecting to run at full capacity as the local hospitals deal with the first signs of the COVID outbreak. In Sudan, despite low COVID numbers, cancer centers have developed contingency plans. and are deferring new referrals except for emergency cases.  Training sessions for staff have been developed.

For more articles in this online open access journal on Cancer and COVID-19 please see our

Coronovirus Portal
Responses to the #COVID-19 outbreak from Oncologists, Cancer Societies and the NCI: Important information for cancer patients

 

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Personalized Medicine, Omics, and Health Disparities in Cancer:  Can Personalized Medicine Help Reduce the Disparity Problem?

Curator: Stephen J. Williams, PhD

In a Science Perspectives article by Timothy Rebbeck, health disparities, specifically cancer disparities existing in the sub-Saharan African (SSA) nations, highlighting the cancer incidence disparities which exist compared with cancer incidence in high income areas of the world [1].  The sub-Saharan African nations display a much higher incidence of prostate, breast, and cervix cancer and these cancers are predicted to double within the next twenty years, according to IARC[2].  Most importantly,

 the histopathologic and demographic features of these tumors differ from those in high-income countries

meaning that the differences seen in incidence may reflect a true health disparity as increases rates in these cancers are not seen in high income countries (HIC).

Most frequent male cancers in SSA include prostate, lung, liver, leukemia, non-Hodgkin’s lymphoma, and Kaposi’s sarcoma (a cancer frequently seen in HIV infected patients [3]).  In SSA women, breast and cervical cancer are the most common and these display higher rates than seen in high income countries.  In fact, liver cancer is seen in SSA females at twice the rate, and in SSA males almost three times the rate as in high income countries.

 

 

 

 

 

 

Reasons for cancer disparity in SSA

Patients with cancer are often diagnosed at a late stage in SSA countries.  This contrasts with patients from high income countries, which have their cancers usually diagnosed at an earlier stage, and with many cancers, like breast[4], ovarian[5, 6], and colon, detecting the tumor in the early stages is critical for a favorable outcome and prognosis[7-10].  In addition, late diagnosis also limits many therapeutic options for the cancer patient and diseases at later stages are much harder to manage, especially with respect to unresponsiveness and/or resistance of many therapies.  In addition, treatments have to be performed in low-resource settings in SSA, and availability of clinical lab work and imaging technologies may be limited.

Molecular differences in SSA versus HIC cancers which may account for disparities

Emerging evidence suggests that there are distinct molecular signatures with SSA tumors with respect to histotype and pathology.  For example Dr. Rebbeck mentions that Nigerian breast cancers were defined by increased mutational signatures associated with deficiency of the homologous recombination DNA repair pathway, pervasive mutations in the tumor suppressor gene TP53, mutations in GATA binding protein 3 (GATA3), and greater mutational burden, compared with breast tumors from African Americans or Caucasians[11].  However more research will be required to understand the etiology and causal factors related to this molecular distinction in mutational spectra.

It is believed that there is a higher rate of hereditary cancers in SSA. And many SSA cancers exhibit the more aggressive phenotype than in other parts of the world.  For example breast tumors in SSA black cases are twice as likely than SSA Caucasian cases to be of the triple negative phenotype, which is generally more aggressive and tougher to detect and treat, as triple negative cancers are HER2 negative and therefore are not a candidate for Herceptin.  Also BRCA1/2 mutations are more frequent in black SSA cases than in Caucasian SSA cases [12, 13].

Initiatives to Combat Health Disparities in SSA

Multiple initiatives are being proposed or in action to bring personalized medicine to the sub-Saharan African nations.  These include:

H3Africa empowers African researchers to be competitive in genomic sciences, establishes and nurtures effective collaborations among African researchers on the African continent, and generates unique data that could be used to improve both African and global health.

There is currently a global effort to apply genomic science and associated technologies to further the understanding of health and disease in diverse populations. These efforts work to identify individuals and populations who are at risk for developing specific diseases, and to better understand underlying genetic and environmental contributions to that risk. Given the large amount of genetic diversity on the African continent, there exists an enormous opportunity to utilize such approaches to benefit African populations and to inform global health.

The Human Heredity and Health in Africa (H3Africa) consortium facilitates fundamental research into diseases on the African continent while also developing infrastructure, resources, training, and ethical guidelines to support a sustainable African research enterprise – led by African scientists, for the African people. The initiative consists of 51 African projects that include population-based genomic studies of common, non-communicable disorders such as heart and renal disease, as well as communicable diseases such as tuberculosis. These studies are led by African scientists and use genetic, clinical, and epidemiologic methods to identify hereditary and environmental contributions to health and disease. To establish a foundation for African scientists to continue this essential work into the future work, the consortium also supports many crucial capacity building elements, such as: ethical, legal, and social implications research; training and capacity building for bioinformatics; capacity for biobanking; and coordination and networking.

The World Economic Forum’s Leapfrogging with Precision Medicine project 

This project is part of the World Economic Forum’s Shaping the Future of Health and Healthcare Platform

The Challenge

Advancing precision medicine in a way that is equitable and beneficial to society means ensuring that healthcare systems can adopt the most scientifically and technologically appropriate approaches to a more targeted and personalized way of diagnosing and treating disease. In certain instances, countries or institutions may be able to bypass, or “leapfrog”, legacy systems or approaches that prevail in developed country contexts.

The World Economic Forum’s Leapfrogging with Precision Medicine project will develop a set of tools and case studies demonstrating how a precision medicine approach in countries with greenfield policy spaces can potentially transform their healthcare delivery and outcomes. Policies and governance mechanisms that enable leapfrogging will be iterated and scaled up to other projects.

Successes in personalized genomic research in SSA

As Dr. Rebbeck states:

 Because of the underlying genetic and genomic relationships between Africans and members of the African diaspora (primarily in North America and Europe), knowledge gained from research in SSA can be used to address health disparities that are prevalent in members of the African diaspora.

For example members of the West African heritage and genomic ancestry has been reported to confer the highest genomic risk for prostate cancer in any worldwide population [14].

 

PERSPECTIVEGLOBAL HEALTH

Cancer in sub-Saharan Africa

  1. Timothy R. Rebbeck

See all authors and affiliations

Science  03 Jan 2020:
Vol. 367, Issue 6473, pp. 27-28
DOI: 10.1126/science.aay474

Summary/Abstract

Cancer is an increasing global public health burden. This is especially the case in sub-Saharan Africa (SSA); high rates of cancer—particularly of the prostate, breast, and cervix—characterize cancer in most countries in SSA. The number of these cancers in SSA is predicted to more than double in the next 20 years (1). Both the explanations for these increasing rates and the solutions to address this cancer epidemic require SSA-specific data and approaches. The histopathologic and demographic features of these tumors differ from those in high-income countries (HICs). Basic knowledge of the epidemiology, clinical features, and molecular characteristics of cancers in SSA is needed to build prevention and treatment tools that will address the future cancer burden. The distinct distribution and determinants of cancer in SSA provide an opportunity to generate knowledge about cancer risk factors, genomics, and opportunities for prevention and treatment globally, not only in Africa.

 

References

  1. Rebbeck TR: Cancer in sub-Saharan Africa. Science 2020, 367(6473):27-28.
  2. Parkin DM, Ferlay J, Jemal A, Borok M, Manraj S, N’Da G, Ogunbiyi F, Liu B, Bray F: Cancer in Sub-Saharan Africa: International Agency for Research on Cancer; 2018.
  3. Chinula L, Moses A, Gopal S: HIV-associated malignancies in sub-Saharan Africa: progress, challenges, and opportunities. Current opinion in HIV and AIDS 2017, 12(1):89-95.
  4. Colditz GA: Epidemiology of breast cancer. Findings from the nurses’ health study. Cancer 1993, 71(4 Suppl):1480-1489.
  5. Hamilton TC, Penault-Llorca F, Dauplat J: [Natural history of ovarian adenocarcinomas: from epidemiology to experimentation]. Contracept Fertil Sex 1998, 26(11):800-804.
  6. Garner EI: Advances in the early detection of ovarian carcinoma. J Reprod Med 2005, 50(6):447-453.
  7. Brockbank EC, Harry V, Kolomainen D, Mukhopadhyay D, Sohaib A, Bridges JE, Nobbenhuis MA, Shepherd JH, Ind TE, Barton DP: Laparoscopic staging for apparent early stage ovarian or fallopian tube cancer. First case series from a UK cancer centre and systematic literature review. European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology 2013, 39(8):912-917.
  8. Kolligs FT: Diagnostics and Epidemiology of Colorectal Cancer. Visceral medicine 2016, 32(3):158-164.
  9. Rocken C, Neumann U, Ebert MP: [New approaches to early detection, estimation of prognosis and therapy for malignant tumours of the gastrointestinal tract]. Zeitschrift fur Gastroenterologie 2008, 46(2):216-222.
  10. Srivastava S, Verma M, Henson DE: Biomarkers for early detection of colon cancer. Clinical cancer research : an official journal of the American Association for Cancer Research 2001, 7(5):1118-1126.
  11. Pitt JJ, Riester M, Zheng Y, Yoshimatsu TF, Sanni A, Oluwasola O, Veloso A, Labrot E, Wang S, Odetunde A et al: Characterization of Nigerian breast cancer reveals prevalent homologous recombination deficiency and aggressive molecular features. Nature communications 2018, 9(1):4181.
  12. Zheng Y, Walsh T, Gulsuner S, Casadei S, Lee MK, Ogundiran TO, Ademola A, Falusi AG, Adebamowo CA, Oluwasola AO et al: Inherited Breast Cancer in Nigerian Women. Journal of clinical oncology : official journal of the American Society of Clinical Oncology 2018, 36(28):2820-2825.
  13. Rebbeck TR, Friebel TM, Friedman E, Hamann U, Huo D, Kwong A, Olah E, Olopade OI, Solano AR, Teo SH et al: Mutational spectrum in a worldwide study of 29,700 families with BRCA1 or BRCA2 mutations. Human mutation 2018, 39(5):593-620.
  14. Lachance J, Berens AJ, Hansen MEB, Teng AK, Tishkoff SA, Rebbeck TR: Genetic Hitchhiking and Population Bottlenecks Contribute to Prostate Cancer Disparities in Men of African Descent. Cancer research 2018, 78(9):2432-2443.

Other articles on Cancer Health Disparities and Genomics on this Online Open Access Journal Include:

Gender affects the prevalence of the cancer type
The Rutgers Global Health Institute, part of Rutgers Biomedical and Health Sciences, Rutgers University, New Brunswick, New Jersey – A New Venture Designed to Improve Health and Wellness Globally
Breast Cancer Disparities to be Sponsored by NIH: NIH Launches Largest-ever Study of Breast Cancer Genetics in Black Women
War on Cancer Needs to Refocus to Stay Ahead of Disease Says Cancer Expert
Ethical Concerns in Personalized Medicine: BRCA1/2 Testing in Minors and Communication of Breast Cancer Risk
Ethics Behind Genetic Testing in Breast Cancer: A Webinar by Laura Carfang of survivingbreastcancer.org
Live Notes from @HarvardMed Bioethics: Authors Jerome Groopman, MD & Pamela Hartzband, MD, discuss Your Medical Mind
Testing for Multiple Genetic Mutations via NGS for Patients: Very Strong Family History of Breast & Ovarian Cancer, Diagnosed at Young Ages, & Negative on BRCA Test
Study Finds that Both Women and their Primary Care Physicians Confusion over Ovarian Cancer Symptoms May Lead to Misdiagnosis

 

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Responses to the #COVID-19 outbreak from Oncologists, Cancer Societies and the NCI: Important information for cancer patients

Curator: Stephen J. Williams, Ph.D.

UPDATED 3/20/2020

Among the people who are identified at risk of coronovirus 2019 infection and complications of the virus include cancer patients undergoing chemotherapy, who in general, can be immunosuppressed, especially while patients are undergoing their treatment.  This has created anxiety among many cancer patients as well as their care givers and prompted many oncologist professional groups, cancer societies, and cancer centers to formulate some sort of guidelines for both the cancer patients and the oncology professional with respect to limiting the risk of infection to coronavirus (COVID19). 

 

This information will be periodically updated and we are working to get a Live Twitter Feed to bring oncologist and cancer patient advocacy groups together so up to date information can be communicated rapidly.  Please see this page regularly for updates as new information is curated.

IN ADDITION, I will curate a listing of drugs with adverse events of immunosuppression for people who might wonder if the medications they are taking are raising their risk of infections.

Please also see @pharma_BI for updates as well.

Please also see our Coronavirus Portal at https://pharmaceuticalintelligence.com/coronavirus-portal/

For ease of reading information for patients are BOLDED and in RED

ASCO’s Response to COVID-19

From the Cancer Letter: The following is a guest editorial by American Society of Clinical Oncology (ASCO) Executive Vice President and Chief Medical Officer Richard L. Schilsky MD, FACP, FSCT, FASCO. This story is part of The Cancer Letter’s ongoing coverage of COVID-19’s impact on oncology. A full list of our coverage, as well as the latest meeting cancellations, is available here.

 

The worldwide spread of the coronavirus (COVID-19) presents unprecedented challenges to the cancer care delivery system.

Our patients are already dealing with a life-threatening illness and are particularly vulnerable to this viral infection, which can be even more deadly for them. Further, as restrictions in daily movement and social distancing take hold, vulnerable patients may be disconnected from friends, family or other support they need as they manage their cancer.

As providers, we rely on evidence and experience when treating patients but now we face uncertainty. There are limited data to guide us in the specific management of cancer patients confronting COVID-19 and, at present, we have no population-level guidance regarding acceptable or appropriate adjustments of treatment and practice operations that both ensure the best outcome for our patients and protect the safety of our colleagues and staff.

As normal life is dramatically changed, we are all feeling anxious about the extreme economic challenges we face, but these issues are perhaps even more difficult for our patients, many of whom are now facing interruption

As we confront this extraordinary situation, the health and safety of members, staff, and individuals with cancer—in fact, the entire cancer community—is ASCO’s highest priority.

ASCO has been actively monitoring and responding to the pandemic to ensure that accurate information is readily available to clinicians and their patients. Recognizing that this is a rapidly evolving situation and that limited oncology-specific, evidence-based information is available, we are committed to sharing what is known and acknowledging what is unknown so that the most informed decisions can be made.

To help guide oncology professionals as they deal with the impact of coronavirus on both their patients and staff, ASCO has collated questions from its members, posted responses at asco.org and assembled a compendium of additional resources we hope will be helpful as the virus spreads and the disease unfolds. We continue to receive additional questions regarding clinical care and we are updating our FAQs on a regular basis.

We hope this information is helpful even when it merely confirms that there are no certain answers to many questions. Our answers are based on the best available information we identify in the literature, guidance from public health authorities, and input received from oncology and infectious disease experts.

For patients, we have posted a blog by Dr. Merry Jennifer Markham, chair of ASCO’s Cancer Communications Committee. This can be found on Cancer.Net, ASCO’s patient information website, and it provides practical guidance to help patients reduce their risk of exposure, better understand COVID-19 symptoms, and locate additional information.

This blog is available both in English and Spanish. Additional blog posts addressing patient questions will be posted as new questions are received and new information becomes available.

Find below a Tweet from Dr.Markham which includes links to her article on COVID-19 for cancer patients

https://twitter.com/DrMarkham/status/1237797251038220289?s=20

NCCN’s Response to COVID-19 and COVID-19 Resources

JNCCN: How to Manage Cancer Care during COVID-19 Pandemic

Experts from the Seattle Cancer Care Alliance (SCCA)—a Member Institution of the National Comprehensive Cancer Network® (NCCN®)—are sharing insights and advice on how to continue providing optimal cancer care during the novel coronavirus (COVID-19) pandemic. SCCA includes the Fred Hutchinson Cancer Research Center and the University of Washington, which are located in the epicenter of the COVID-19 outbreak in the United States. The peer-reviewed article sharing best practices is available for free online-ahead-of-print via open access at JNCCN.org.

Coronavirus disease 2019 (COVID-19) Resources for the Cancer Care Community

NCCN recognizes the rapidly changing medical information relating to COVID-19 in the oncology ecosystem, but understands that a forum for sharing best practices and specific institutional responses may be helpful to others.  Therefore, we are expeditiously providing documents and recommendations developed by NCCN Member Institutions or Guideline Panels as resources for oncology care providers. These resources have not been developed or reviewed by the standard NCCN processes, and are provided for information purposes only. We will post more resources as they become available so check back for additional updates.

Documents

Links

National Cancer Institute Response to COVID-19

More information at https://www.cancer.gov/contact/emergency-preparedness/coronavirus

What people with cancer should know: https://www.cancer.gov/coronavirus

Get the latest public health information from CDC: https://www.coronavirus.gov

Get the latest research information from NIH: https://www.nih.gov/coronavirus

 

Coronavirus: What People with Cancer Should Know

ON THIS PAGE

Both the resources at cancer.gov (NCI) as well as the resources from ASCO are updated as new information is evaluated and more guidelines are formulated by members of the oncologist and cancer care community and are excellent resources for those living with cancer, and also those who either care for cancer patients or their family and relatives.

Related Resources for Patients (please click on links)

 

 

 

Some resources and information for cancer patients from Twitter

Twitter feeds which may be useful sources of discussion and for cancer patients include:

 

@OncLive OncLive.com includes healthcare information for patients and includes videos and newsletters

 

 

@DrMarkham Dr. Markham is Chief of Heme-Onc & gyn med onc @UF | AD Med Affairs @UFHealthCancer and has collected very good information for patients concerning #Covid19 

 

 

@DrMaurieMarkman Dr. Maurie Markman is President of Medicine and Science (Cancer Centers of America, Philadelphia) @CancerCenter #TreatThePerson #Oncology #Genomics #PrecisionMedicine and hosts a great online live Tweet feed discussing current topics in cancer treatment and care for patients called #TreatThePerson Chat

UPDATED 3/20/2020 INFORMATION FROM NCI DESIGNATED CANCER CENTERS FOR PATIENTS/PROVIDERS

The following is a listing with links of NCI Designated Comprehensive Cancer Centers and some select designated Cancer Centers* which have information on infectious risk guidance for cancer patients as well as their physicians and caregivers.   There are 51 NCI Comprehensive Cancer Centers and as more cancer centers formulate guidance this list will be updated. 

 

Cancer Center State Link to COVID19 guidance
City of Hope CA Advice for cancer patients, survivors and caregivers
Jonsson Cancer Center at UCLA CA Cancer and COVID19
UCSF Hellen Diller Family Comprehensive Cancer CA COVID-19 Links for Patients and Providers
Lee Moffit FL Protecting against Coronavirus 19
University of Kansas Cancer Center* KS COVID19 Info for patients
Barbara & Karmanos Cancer Institute (Wayne State) MI COVID19 Resources
Rogel Cancer Center (Univ of Michigan) MI COVID19 Patient Specific Guidelines
Alvin J. Siteman Cancer Center (MO) Coronavirus
Fred & Pamela Buffet CC* NE Resources for Patients and Providers
Rutgers Cancer Institute of NJ NJ What patients should know about COVID19
Memorial Sloan Kettering NY What COVID19 means for cancer patients
Herbert Irving CC (Columbia University) NY Coronavirus Resource Center
MD Anderson Cancer  TX Planning for Patients, Providers
Hunstman Cancer Center UT COVID19 What you need to know
Fred Hutchinson WA COVID19 What patients need to know

 

 

Please also see related information on Coronavirus 2019 and Cancer and Immunotherapy at the following links on the Open Access Online Journal:

Volume Two: Cancer Therapies: Metabolic, Genomics, Interventional, Immunotherapy and Nanotechnology in Therapy Delivery 

at

https://pharmaceuticalintelligence.com/biomed-e-books/series-c-e-books-on-cancer-oncology/volume-two-immunotherapy-in-cancer-radiation-oncology/

AND

Coronavirus Portal

 

 

 

 

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Google AI improves accuracy of reading mammograms, study finds

Reporter: Stephen J. Williams, PhD

Updated on 12/7/2022

AI system beats doctors at scrutinizing breast cancer scans

AI learned to identify a protein targeted in immunotherapy in a process that could make doctors’ work faster, simpler and more precise.

SOURCE

https://www.israel21c.org/ai-system-beats-doctors-at-scrutinizing-breast-cancer-scans/

 

Google AI improves accuracy of reading mammograms, study finds

Google CFO Ruth Porat has blogged about twice battling breast cancer.

Artificial intelligence was often more accurate than radiologists in detecting breast cancer from mammograms in a study conducted by researchers using Google AI technology.

The study, published in the journal Nature, used mammograms from approximately 90,000 women in which the outcomes were known to train technology from Alphabet Inc’s DeepMind AI unit, now part of Google Health, Yahoo news reported.

The AI system was then used to analyze images from 28,000 other women and often diagnosed early cancers more accurately than the radiologists who originally interpreted the mammograms.

In another test, AI outperformed six radiologists in reading 500 mammograms. However, while the AI system found cancers the humans missed, it also failed to find cancers flagged by all six radiologists, reports The New York Times.

The researchers said the study “paves the way” for further clinical trials.

Writing in NatureEtta D. Pisano, chief research officer at the American College of Radiology and professor in residence at Harvard Medical School, noted, “The real world is more complicated and potentially more diverse than the type of controlled research environment reported in this study.”

Ruth Porat, senior vice president and chief financial officer Alphabet, Inc., wrote in a company blog titled “Breast cancer and tech…a reason for optimism” in October about twice battling the disease herself, and the importance of her company’s application of AI to healthcare innovations.

She said that focus had already led to the development of a deep learning algorithm to help pathologists assess tissue associated with metastatic breast cancer.

“By pinpointing the location of the cancer more accurately, quickly and at a lower cost, care providers might be able to deliver better treatment for more patients,” she wrote.

Google also has created algorithms that help medical professionals diagnose lung cancer, and eye disease in people with diabetes, per the Times.

Porat acknowledged that Google’s research showed the best results occur when medical professionals and technology work together.

Any insights provided by AI must be “paired with human intelligence and placed in the hands of skilled researchers, surgeons, oncologists, radiologists and others,” she said.

Anne Stych is a staff writer for Bizwomen.
Industries:

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