PD-L1 testing in advanced gastric cancer-what physicians who treat this disease must know-a literature review

Background and Objective

Immune checkpoint inhibition has shed light on a new era in cancer therapy, and randomized clinical trials have demonstrated that a meaningful portion of the overall population of metastatic gastric cancer (GC) patients may derive clinical benefit from immunotherapy, which raises the relevance in identifying predictive biomarkers. Programmed cell death-ligand 1 (PD-L1) expression has demonstrated a significant association between level of expression and the magnitude of benefit derived from immune checkpoint inhibition in GC. Nevertheless, this biomarker shows several pitfalls that must be considered in the therapeutic decision to incorporate immune checkpoint inhibition as the standard of care of GC, such as spatial and temporal heterogeneity, interobserver variability, immunohistochemistry (IHC) assay, and influence by chemotherapy or radiation therapy.

Methods

In the present comprehensive review, we revised the main studies regarding PD-L1 evaluation in GC.

Key Content and Findings

Here we describe the molecular characteristics of the tumor microenvironment in GC, the obstacles in the interpretation of PD-L1 expression and present the data of the clinical trials that have evaluated the efficacy and safety of immune checkpoint inhibition and the association with the biomarker expression, both in first-line and later lines of therapy.

Conclusions

From the emerging predictive biomarkers for immune checkpoint inhibition, PD-L1 has demonstrated a meaningful association between level of expression in tumor microenvironment and the magnitude of benefit derived from immune checkpoint inhibition in GC.

Determinants of COVID-19 Mortality in Patients With Cancer From a Community Oncology Practice in Brazil

PURPOSE

The COVID-19 pandemic remains a public health emergency of global concern. Determinants of mortality in the general population are now clear, but specific data on patients with cancer remain limited, particularly in Latin America.

MATERIALS AND METHODS

A longitudinal multicenter cohort study of patients with cancer and confirmed COVID-19 from Oncoclínicas community oncology practice in Brazil was conducted. The primary end point was all-cause mortality after isolation of the SARS-CoV-2 by Real-Time Polymerase Chain Reaction (RT-PCR) in patients initially diagnosed in an outpatient environment. We performed univariate and multivariable logistic regression analysis and recursive partitioning modeling to define the baseline clinical determinants of death in the overall population.

RESULTS

From March 29 to July 4, 2020, 198 patients with COVID-19 were prospectively registered in the database, of which 167 (84%) had solid tumors and 31 (16%) had hematologic malignancies. Most patients were on active systemic therapy or radiotherapy (77%), largely for advanced or metastatic disease (64%). The overall mortality rate was 16.7% (95% CI, 11.9 to 22.7). In univariate models, factors associated with death after COVID-19 diagnosis were age ≥ 60 years, current or former smoking, coexisting comorbidities, respiratory tract cancer, and management in a noncurative setting (P < .05). In multivariable logistic regression and recursive partitioning modeling, only age, smoking history, and noncurative disease setting remained significant determinants of mortality, ranging from 1% in cancer survivors under surveillance or (neo)adjuvant therapy to 60% in elderly smokers with advanced or metastatic disease.

CONCLUSION

Mortality after COVID-19 in patients with cancer is influenced by prognostic factors that also affect outcomes of the general population. Fragile patients and smokers are entitled to active preventive measures to reduce the risk of SARS-CoV-2 infection and close monitoring in the case of exposure or COVID-19-related symptoms.