COVID-19 and Cancer: Current Challenges and Perspectives.

Patients with cancer have been disproportionately affected by the COVID-19 pandemic. This effect has included the adverse outcomes in patients with cancer who develop COVID-19, the impact of the COVID-19 pandemic on the delivery of cancer care, and the severe disruption to cancer research. However, patients with cancer are a heterogeneous population, and recent studies have now documented factors that allow risk stratification of patients with cancer in order to optimize care. In this review, we highlight data at the intersection of COVID-19 and cancer, including the biological interplay between the two diseases and practical recommendations for the treatment of patients with cancer during the pandemic. We additionally discuss the potential long-lasting impact of the pandemic on cancer care due to its deleterious effect on cancer research, as well as biological insights from the cancer research community that could help develop novel therapies for all patients with COVID-19

Survey of the impact of COVID-19 on oncologists’ decision making in cancer

PURPOSE To understand readiness measures taken by oncologists to protect patients and health care workers from the novel coronavirus (COVID-19) and how their clinical decision making was influenced by the pandemic. METHODS An online survey was conducted between March 24 and April 29, 2020. RESULTS A total of 343 oncologists from 28 countries participated. The median age was 43 years (range, 29-68 years), and the majority were male (62%). At the time of the survey, nearly all participants self-reported an outbreak in their country (99.7%). Personal protective equipment was available to all participants, of which surgical mask was the most common (n = 308; 90%). Telemedicine, in the form of phone or video encounters, was common and implemented by 80% (n = 273). Testing patients with cancer for COVID-19 via reverse transcriptase polymerase chain reaction before systemic treatment was not routinely implemented: 58% reported no routine testing, 39% performed testing in selected patients, and 3% performed systematic testing in all patients. The most significant factors influencing an oncologist’s decision making regarding choice of systemic therapy included patient age and comorbidities (81% and 92%, respectively). Although hormonal treatments and tyrosine kinase inhibitors were considered to be relatively safe, cytotoxic chemotherapy and immune therapies were perceived as being less safe or unsafe by participants. The vast majority of participants stated that during the pandemic they would use less chemotherapy, immune checkpoint inhibitors, and steroids. Although treatment in neoadjuvant, adjuvant, and first-line metastatic disease was less affected, most of the participants stated that they would be more hesitant to recommend second- or third-line therapies in metastatic disease. CONCLUSION Decision making by oncologists has been significantly influenced by the ongoing COVID-19 pandemic

Strategies to design clinical studies to identify predictive biomarkers in cancer research

The discovery of reliable biomarkers to predict efficacy and toxicity of anticancer drugs remains one of the key challenges in cancer research. Despite its relevance, no efficient study designs to identify promising candidate biomarkers have been established. This has led to the proliferation of a myriad of exploratory studies using dissimilar strategies, most of which fail to identify any promising targets and are seldom validated. The lack of a proper methodology also determines that many anti-cancer drugs are developed below their potential, due to failure to identify predictive biomarkers. While some drugs will be systematically administered to many patients who will not benefit from them, leading to unnecessary toxicities and costs, others will never reach registration due to our inability to identify the specific patient population in which they are active. Despite these drawbacks, a limited number of outstanding predictive biomarkers have been successfully identified and validated, and have changed the standard practice of oncology. In this manuscript, a multidisciplinary panel reviews how those key biomarkers were identified and, based on those experiences, proposes a methodological framework—the DESIGN guidelines—to standardize the clinical design of biomarker identification studies and to develop future research in this pivotal field

Utilization of COVID-19 Treatments and Clinical Outcomes among Patients with Cancer: A COVID-19 and Cancer Consortium (CCC19) Cohort Study.

Among 2,186 U.S. adults with invasive cancer and laboratory-confirmed SARS-CoV-2 infection, we examined the association of COVID-19 treatments with 30-day all-cause mortality and factors associated with treatment. Logistic regression with multiple adjustments (e.g., comorbidities, cancer status, baseline COVID-19 severity) was performed. Hydroxychloroquine with any other drug was associated with increased mortality versus treatment with any COVID-19 treatment other than hydroxychloroquine or untreated controls; this association was not present with hydroxychloroquine alone. Remdesivir had numerically reduced mortality versus untreated controls that did not reach statistical significance. Baseline COVID-19 severity was strongly associated with receipt of any treatment. Black patients were approximately half as likely to receive remdesivir as white patients. Although observational studies can be limited by potential unmeasured confounding, our findings add to the emerging understanding of patterns of care for patients with cancer and COVID-19 and support evaluation of emerging treatments through inclusive prospective controlled trials. SIGNIFICANCE: Evaluating the potential role of COVID-19 treatments in patients with cancer in a large observational study, there was no statistically significant 30-day all-cause mortality benefit with hydroxychloroquine or high-dose corticosteroids alone or in combination; remdesivir showed potential benefit. Treatment receipt reflects clinical decision-making and suggests disparities in medication access.This article is highlighted in the In This Issue feature, p. 1426

The immune landscape of cancer

We performed an extensive immunogenomic analysis of more than 10,000 tumors comprising 33 diverse cancer types by utilizing data compiled by TCGA. Across cancer types, we identified six immune subtypes—wound healing, IFN-γ dominant, inflammatory, lymphocyte depleted, immunologically quiet, and TGF-β dominant—characterized by differences in macrophage or lymphocyte signatures, Th1:Th2 cell ratio, extent of intratumoral heterogeneity, aneuploidy, extent of neoantigen load, overall cell proliferation, expression of immunomodulatory genes, and prognosis. Specific driver mutations correlated with lower (CTNNB1, NRAS, or IDH1) or higher (BRAF, TP53, or CASP8) leukocyte levels across all cancers. Multiple control modalities of the intracellular and extracellular networks (transcription, microRNAs, copy number, and epigenetic processes) were involved in tumor-immune cell interactions, both across and within immune subtypes. Our immunogenomics pipeline to characterize these heterogeneous tumors and the resulting data are intended to serve as a resource for future targeted studies to further advance the field

The Cancer Genome Atlas Comprehensive Molecular Characterization of Renal Cell Carcinoma

Renal cell carcinoma(RCC) is not a single disease, but several histologically defined cancers with different genetic drivers, clinical courses, and therapeutic responses. The current study evaluated 843 RCC from the three major histologic subtypes, including 488 clear cell RCC, 274 papillary RCC, and 81 chromophobe RCC. Comprehensive genomic and phenotypic analysis of the RCC subtypes reveals distinctive features of each subtype that provide the foundation for the development of subtype-specific therapeutic and management strategies for patients affected with these cancers. Somatic alteration of BAP1, PBRM1, and PTEN and altered metabolic pathways correlated with subtype-specific decreased survival, while CDKN2A alteration, increased DNA hypermethylation, and increases in the immune-related Th2 gene expression signature correlated with decreased survival within all major histologic subtypes. CIMP-RCC demonstrated an increased immune signature, and a uniform and distinct metabolic expression pattern identified a subset of metabolically divergent (MD) ChRCC that associated with extremely poor survival

The Immune Landscape of Cancer

We performed an extensive immunogenomic anal-ysis of more than 10,000 tumors comprising 33diverse cancer types by utilizing data compiled byTCGA. Across cancer types, we identified six im-mune subtypes\u2014wound healing, IFN-gdominant,inflammatory, lymphocyte depleted, immunologi-cally quiet, and TGF-bdominant\u2014characterized bydifferences in macrophage or lymphocyte signa-tures, Th1:Th2 cell ratio, extent of intratumoral het-erogeneity, aneuploidy, extent of neoantigen load,overall cell proliferation, expression of immunomod-ulatory genes, and prognosis. Specific drivermutations correlated with lower (CTNNB1,NRAS,orIDH1) or higher (BRAF,TP53,orCASP8) leukocytelevels across all cancers. Multiple control modalitiesof the intracellular and extracellular networks (tran-scription, microRNAs, copy number, and epigeneticprocesses) were involved in tumor-immune cell inter-actions, both across and within immune subtypes.Our immunogenomics pipeline to characterize theseheterogeneous tumors and the resulting data areintended to serve as a resource for future targetedstudies to further advance the field

Treatment Decisions for Patients with Cancer during the COVID-19 Pandemic.

Patients with cancer have been disproportionally affected by the COVID-19 pandemic, with high rates of severe outcomes and death. Similarly, treatment decisions in this vulnerable population have been altered to a major degree during the past year, with significant disruption of care reported. Although complex, therapeutic choices in patients with cancer in times of COVID-19 are critical, as they may save thousands of lives. A mounting body of evidence, in addition to clear recommendations by multiple international societies, can help oncologists decide appropriately the necessity to administer antineoplastic regimens, helping to avoid a surge in cancer-related deaths in the upcoming months

The COVID-19 and Cancer Consortium: A Collaborative Effort to Understand the Effects of COVID-19 on Patients with Cancer.

National and international consortia will play a key role in understanding the effects of the coronavirus disease 2019 (COVID-19) pandemic on cancer patients. The COVID-19 and Cancer Consortium (CCC19) aims to collect and analyze observational data at scale to inform clinical practice in real-time