The Underappreciated Role of the Humoral Immune System and B Cells in Tumorigenesis and Cancer Therapeutics: A Review

CD19 (+) B Cell Combined with Prognostic Nutritional Index Predicts the Clinical Outcomes of Patients with Gastric Cancer Who Underwent Surgery

(1) Background: The aim of this study was to explore the predictive ability of lymphocyte subsets for the prognosis of gastric cancer patients who underwent surgery and the prognostic value of CD19 (+) B cell combined with the Prognostic Nutritional Index (PNI). (2) Methods: This study involved 291 patients with gastric cancer who underwent surgery at our institution between January 2016 and December 2017. All patients had complete clinical data and peripheral lymphocyte subsets. Differences in clinical and pathological characteristics were examined using the Chi-square test or independent sample t-tests. The difference in survival was evaluated using Kaplan-Meier survival curves and the Log-rank test. Cox's regression analysis was performed to identify independent prognostic indicators, and nomograms were used to predict survival probabilities. (3) Results: Patients were categorized into three groups based on their CD19 (+) B cell and PNI levels, with 56 cases in group one, 190 cases in group two, and 45 cases in group three. Patients in group one had a shorter progression-free survival (PFS) (HR = 0.444, p < 0.001) and overall survival (OS) (HR = 0.435, p < 0.001). CD19 (+) B cell-PNI had the highest area under the curve (AUC) compared with other indicators, and it was also identified as an independent prognostic factor. Moreover, CD3 (+) T cell, CD3 (+) CD8 (+) T cell, and CD3 (+) CD16 (+) CD56 (+) NK T cell were all negatively correlated with the prognosis, while CD19 (+) B cell was positively associated with the prognosis. The C-index and 95% confidence interval (CI) of nomograms for PFS and OS were 0.772 (0.752-0.833) and 0.773 (0.752-0.835), respectively. (4) Conclusions: Lymphocyte subsets including CD3 (+) T cell, CD3 (+) CD8 (+) T cell, CD3 (+) CD16 (+) CD56 (+) NK T cell, and CD19 (+) B cell were related to the clinical outcomes of patients with gastric cancer who underwent surgery. Additionally, PNI combined with CD19 (+) B cell had higher prognostic value and could be used to identify patients with a high risk of metastasis and recurrence after surgery.

The Tumor Microenvironment in Tumorigenesis and Therapy Resistance Revisited

Tumorigenesis is a complex and dynamic process involving cell-cell and cell-extracellular matrix (ECM) interactions that allow tumor cell growth, drug resistance and metastasis. This review provides an updated summary of the role played by the tumor microenvironment (TME) components and hypoxia in tumorigenesis, and highlight various ways through which tumor cells reprogram normal cells into phenotypes that are pro-tumorigenic, including cancer associated- fibroblasts, -macrophages and -endothelial cells. Tumor cells secrete numerous factors leading to the transformation of a previously anti-tumorigenic environment into a pro-tumorigenic environment. Once formed, solid tumors continue to interact with various stromal cells, including local and infiltrating fibroblasts, macrophages, mesenchymal stem cells, endothelial cells, pericytes, and secreted factors and the ECM within the tumor microenvironment (TME). The TME is key to tumorigenesis, drug response and treatment outcome. Importantly, stromal cells and secreted factors can initially be anti-tumorigenic, but over time promote tumorigenesis and induce therapy resistance. To counter hypoxia, increased angiogenesis leads to the formation of new vascular networks in order to actively promote and sustain tumor growth via the supply of oxygen and nutrients, whilst removing metabolic waste. Angiogenic vascular network formation aid in tumor cell metastatic dissemination. Successful tumor treatment and novel drug development require the identification and therapeutic targeting of pro-tumorigenic components of the TME including cancer-associated- fibroblasts (CAFs) and -macrophages (CAMs), hypoxia, blocking ECM-receptor interactions, in addition to the targeting of tumor cells. The reprogramming of stromal cells and the immune response to be anti-tumorigenic is key to therapeutic success. Lastly, this review highlights potential TME- and hypoxia-centered therapies under investigation.

Humoral Immune Response of SARS-CoV-2-Infected Patients with Cancer: Influencing Factors and Mechanisms

Background

Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2)–infected patients with cancer show worse outcomes compared with patients without cancer. The humoral immune response (HIR) of patients with cancer against SARS‐CoV‐2 is not well characterized. To better understand it, we conducted a serological study of hospitalized patients with cancer infected with SARS‐CoV‐2.

Materials and Methods

This was a unicentric, retrospective study enrolling adult patients with SARS‐CoV‐2 admitted to a central hospital from March 15 to June 17, 2020, whose serum samples were quantified for anti–SARS‐CoV‐2 receptor‐binding domain or spike protein IgM, IgG, and IgA antibodies. The aims of the study were to assess the HIR to SARS‐CoV‐2; correlate it with different cancer types, stages, and treatments; clarify the interplay between the HIR and clinical outcomes of patients with cancer; and compare the HIR of SARS‐CoV‐2–infected patients with and without cancer.

Results

We included 72 SARS‐CoV‐2–positive subjects (19 with cancer, 53 controls). About 90% of controls revealed a robust serological response. Among patients with cancer, a strong response was verified in 57.9%, with 42.1% showing a persistently weak response. Treatment with chemotherapy within 14 days before positivity was the only factor statistically shown to be associated with persistently weak serological responses among patients with cancer. No significant differences in outcomes were observed between patients with strong and weak responses. All IgG, IgM, IgA, and total Ig antibody titers were significantly lower in patients with cancer compared with those without.

Conclusion

A significant portion of patients with cancer develop a proper HIR. Recent chemotherapy treatment may be associated with weak serological responses among patients with cancer. Patients with cancer have a weaker SARS‐CoV‐2 antibody response compared with those without cancer.

Implications for Practice

These results place the spotlight on patients with cancer, particularly those actively treated with chemotherapy. These patients may potentially be more vulnerable to severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection, so it is important to provide oncologists further theoretical support (with concrete examples and respective mechanistic correlations) for the decision of starting, maintaining, or stopping antineoplastic treatments (particularly chemotherapy) not only on noninfected but also on infected patients with cancer in accordance with cancer type, stage and prognosis, treatment agents, treatment setting, and SARS‐CoV‐2 infection risks.

To better understand the anti‐viral immune response in the context of cancer, this serological study of hospitalized cancer patients infected with SARS‐CoV‐2 was conducted.

Nano-immunotherapy for each stage of cancer cellular immunity: which, why, and what?

Immunotherapy provides a new avenue for combating cancer. Current research in anticancer immunotherapy is primary based on T cell-mediated cellular immunity, which can be divided into seven steps and is named the cancer-immunity cycle. Unfortunately, clinical applications of cancer immunotherapies are restricted by inefficient drug delivery, low response rates, and unmanageable adverse reactions. In response to these challenges, the combination of nanotechnology and immunotherapy (nano-immunotherapy) has been extensively studied in recent years. Rational design of advanced nano-immunotherapies requires in-depth consideration of "which" immune step is targeted, "why" it needs to be further enhanced, and "what" nanotechnology can do for immunotherapy. However, the applications and effects of nanotechnology in the cancer-immunity cycle have not been well reviewed. Herein, we summarize the current developments in nano-immunotherapy for each stage of cancer cellular immunity, with special attention on the which, why and what. Furthermore, we summarize the advantages of nanotechnology for combination immunotherapy in two categories: enhanced efficacy and reduced toxicity. Finally, we discuss the challenges of nano-immunotherapy in detail and provide a perspective.