Taking a Full Snapshot of Cancer Biology: Deciphering the Tumor Microenvironment for Effective Cancer Therapy in the Oncology Clinic

Development and Validation of a Machine Learning Model for Bone Metastasis in Prostate Cancer: Based on Inflammatory and Nutritional Indicators

OBJECTIVE

To establish a predictive model for prostate cancer bone metastasis utilizing multiple machine learning algorithms.

METHODS

Retrospective analysis of the clinical data of prostate cancer initially diagnosed in the Department of Urology of Gansu Provincial People's Hospital from June 2017 to June 2022. Logistic regression (LR) and least absolute shrinkage and selection operator (LASSO) are used to jointly screen the model features. The filtered features are incorporated into algorithms including LR, random forest (RF), extreme gradient boosting (XGBoost), naive Bayes (NB), k-nearest neighbor (KNN), and decision tree (DT), to develop prostate cancer bone metastasis models.

RESULTS

A total of 404 patients were finally screened. Gleason score, T stage, N stage, PSA, and ALP were used as features for modeling. The average AUC of the 5-fold cross-validation for each machine learning model in the training set is as follows: LR (AUC=0.9054), RF (AUC=0.9032), NB (AUC=0.8961), KNN (AUC=0.8704), DT (AUC=0.8526), XGBoost (AUC=0.8066). The AUC of each machine learning model in the test set is KNN (AUC=0.9390, 95%CI: 0.8760-1), RF (AUC=0.9290, 95%CI: 0.8718-0.9861), NB (AUC=0.9268, 95%CI: 0.8615-0.9920), LR (AUC=0.9212, 95%CI: 0.8506-0.9917), XGBoost (AUC=0.8292, 95%CI: 0.7442-0.9141), DT (AUC=0.8057, 95%CI: 0.7100-0.9014). A comprehensive evaluation showed that LR performed well in interpretability and clinical applications.

CONCLUSION

A bone metastasis model of prostate cancer was established, and it was observed that indicators such as inflammation and nutrition had a weak correlation with bone metastasis.

Ex vivo drug testing of patient-derived lung organoids to predict treatment responses for personalized medicine

Lung cancer is the leading cause of global cancer-related mortality resulting in ∼ 1.8 million deaths annually. Systemic, molecular targeted, and immune therapies have provided significant improvements of survival outcomes for patients. However, drug resistance usually arises and there is an urgent need for novel therapy screening and personalized medicine. 3D patient-derived organoid (PDO) models have emerged as a more effective and efficient alternative for ex vivo drug screening than 2D cell culture and patient-derived xenograft (PDX) models. In this review, we performed an extensive search of lung cancer PDO-based ex vivo drug screening studies. Lung cancer PDOs were successfully established from fresh or bio-banked sections and/or biopsies, pleural effusions and PDX mouse models. PDOs were subject to ex vivo drug screening with chemotherapy, targeted therapy and/or immunotherapy. PDOs consistently recapitulated the genomic alterations and drug sensitivity of primary tumors. Although sample sizes of the previous studies were limited and some technical challenges remain, PDOs showed great promise in the screening of novel therapy drugs. With the technical advances of high throughput, tumor-on-chip, and combined microenvironment, the drug screening process using PDOs will enhance precision care of lung cancer patients.

Nanomedicine as a multimodal therapeutic paradigm against cancer: on the way forward in advancing precision therapy

Recent years have witnessed dramatic improvements in nanotechnology-based cancer therapeutics, and it continues to evolve from the use of conventional therapies (chemotherapy, surgery, and radiotherapy) to increasingly multi-complex approaches incorporating thermal energy-based tumor ablation (e.g. magnetic hyperthermia and photothermal therapy), dynamic therapy (e.g. photodynamic therapy), gene therapy, sonodynamic therapy (e.g. ultrasound), immunotherapy, and more recently real-time treatment efficacy monitoring (e.g. theranostic MRI-sensitive nanoparticles). Unlike monotherapy, these multimodal therapies (bimodal, i.e., a combination of two therapies, and trimodal, i.e., a combination of more than two therapies) incorporating nanoplatforms have tremendous potential to improve the tumor tissue penetration and retention of therapeutic agents through selective active/passive targeting effects. These combinatorial therapies can correspondingly alleviate drug response against hypoxic/acidic and immunosuppressive tumor microenvironments and promote/induce tumor cell death through various multi-mechanisms such as apoptosis, autophagy, and reactive oxygen-based cytotoxicity, e.g., ferroptosis, etc. These multi-faced approaches such as targeting the tumor vasculature, neoangiogenic vessels, drug-resistant cancer stem cells (CSCs), preventing intra/extravasation to reduce metastatic growth, and modulation of antitumor immune responses work complementary to each other, enhancing treatment efficacy. In this review, we discuss recent advances in different nanotechnology-mediated synergistic/additive combination therapies, emphasizing their underlying mechanisms for improving cancer prognosis and survival outcomes. Additionally, significant challenges such as CSCs, hypoxia, immunosuppression, and distant/local metastasis associated with therapy resistance and tumor recurrences are reviewed. Furthermore, to improve the clinical precision of these multimodal nanoplatforms in cancer treatment, their successful bench-to-clinic translation with controlled and localized drug-release kinetics, maximizing the therapeutic window while addressing safety and regulatory concerns are discussed. As we advance further, exploiting these strategies in clinically more relevant models such as patient-derived xenografts and 3D organoids will pave the way for the application of precision therapy.

High expression of ARPC1B correlates with immune infiltration and poor outcomes in glioblastoma

Objective

To investigate the role of ARPC1B in GBM and its prognostic value.

Methods

mRNA and protein expression of ARPC1B in GBM was analyzed using the TCGA; TIMER2 and the HPA databases, and protein expression differences were detected using immunohistochemistry. K-M analysis and Cox regression analysis were performed on high and low ARPC1B expression groups in the TCGA database. The relationship between immune cells and ARPC1B expression was explored using the TIMER2 database. GO and KEGG analyses were conducted to investigate the functions of ARPC1B-related genes in GBM.

Results

ARPC1B was highly expressed in both GBM tissues and cell lines, and it was demonstrated as a prognostic biomarker for GBM. ARPC1B expression levels showed associations with immune cell populations within the GBM microenvironment.

Conclusion

ARPC1B can regulating immune infiltration in the GBM microenvironment, indicating its potential as a novel therapeutic target for GBM.

Cellular signaling in the hypoxic cancer microenvironment: Implications for drug resistance and therapeutic targeting

The rewiring of cellular metabolism is a defining characteristic of cancer, as tumor cells adapt to acquire essential nutrients from a nutrient-poor environment to sustain their viability and biomass. While hypoxia has been identified as a major factor depriving cancer cells of nutrients, recent studies have revealed that cancer cells distant from supporting blood vessels also face nutrient limitations. To overcome this challenge, hypoxic cancer cells, which heavily rely on glucose as an energy source, employ alternative pathways such as glycogen metabolism and reductive carboxylation of glutamine to meet their energy requirements for survival. Our preliminary studies, alongside others in the field, have shown that under glucose-deficient conditions, hypoxic cells can utilize mannose and maltose as alternative energy sources. This review aims to comprehensively examine the hypoxic cancer microenvironment, its association with drug resistance, and potential therapeutic strategies for targeting this unique niche. Furthermore, we will critically evaluate the current literature on hypoxic cancer microenvironments and explore state-of-the-art techniques used to analyze alternate carbohydrates, specifically mannose and maltose, in complex biological fluids. We will also propose the most effective analytical methods for quantifying mannose and maltose in such biological samples. By gaining a deeper understanding of the hypoxic cancer cell microenvironment and its role in drug resistance, novel therapeutic approaches can be developed to exploit this knowledge.

Targeting cancer stem cells as a strategy for reducing chemotherapy resistance in head and neck cancers

PURPOSE

Resistance to chemotherapy and radiotherapy is the primary cause of a poor prognosis in oncological patients. Researchers identified many possible mechanisms involved in gaining a therapy-resistant phenotype by cancer cells, including alterations in intracellular drug accumulation, detoxification, and enhanced DNA damage repair. All these features are characteristic of stem cells, making them the major culprit of chemoresistance. This paper reviews the most recent evidence regarding the association between the stemness phenotype and chemoresistance in head and neck cancers. It also investigates the impact of pharmacologically targeting cancer stem cell populations in this subset of malignancies.

METHODS

This narrative review was prepared based on the search of the PubMed database for relevant papers.

RESULTS

Head and neck cancer cells belonging to the stem cell population are distinguished by the high expression of certain surface proteins (e.g., CD10, CD44, CD133), pluripotency-related transcription factors (SOX2, OCT4, NANOG), and increased activity of aldehyde dehydrogenase (ALDH). Chemotherapy itself increases the percentage of stem-like cells. Importantly, the intratumor heterogeneity of stem cell subpopulations reflects cell plasticity which has great importance for chemoresistance induction.

CONCLUSIONS

Evidence points to the advantage of combining classical chemotherapeutics with stemness modulators thanks to the joint targeting of the bulk of proliferating tumor cells and chemoresistant cancer stem cells, which could cause recurrence.

Cancer-associated fibroblasts in hematologic malignancies: elucidating roles and spotlighting therapeutic targets

Hematologic malignancies comprise a diverse range of blood, bone marrow, and organ-related disorders that present significant challenges due to drug resistance, relapse, and treatment failure. Cancer-associated fibroblasts (CAFs) represent a critical component of the tumor microenvironment (TME) and have recently emerged as potential therapeutic targets. In this comprehensive review, we summarize the latest findings on the roles of CAFs in various hematologic malignancies, including acute leukemia, multiple myeloma, chronic lymphocytic leukemia, myeloproliferative neoplasms, and lymphoma. We also explore their involvement in tumor progression, drug resistance, and the various signaling pathways implicated in their activation and function. While the underlying mechanisms and the existence of multiple CAF subtypes pose challenges, targeting CAFs and their associated pathways offers a promising avenue for the development of innovative treatments to improve patient outcomes in hematologic malignancies.

Environmental insults and compensative responses: when microbiome meets cancer

Tumor microenvironment has recently been ascribed a new hallmark-the polymorphic microbiome. Accumulating evidence regarding the tissue specific territories of tumor-microbiome have opened new and interesting avenues. A pertinent question is regarding the functional consequence of the interface between host-microbiome and cancer. Given microbial communities have predominantly been explored through an ecological perspective, it is important that the foundational aspects of ecological stress and the fight to 'survive and thrive' are accounted for tumor-micro(b)environment as well. Building on existing evidence and classical microbial ecology, here we attempt to characterize the ecological stresses and the compensative responses of the microorganisms inside the tumor microenvironment. What insults would microbes experience inside the cancer jungle? How would they respond to these insults? How the interplay of stress and microbial quest for survival would influence the fate of tumor? This work asks these questions and tries to describe this underdiscussed ecological interface of the tumor and its microbiota. It is hoped that a larger scientific thought on the importance of microbial competition sensing vis-à-vis tumor-microenvironment would be stimulated.

Bacterial Outer Membrane Vesicles Loaded with Perhexiline Suppress Tumor Development by Regulating Tumor-Associated Macrophages Repolarization in a Synergistic Way

Tumor-associated macrophages (TAMs) promote tumor development and metastasis and are categorized into M1-like macrophages, suppressing tumor cells, and M2-like macrophages. M2-like macrophages, occupying a major role in TAMs, can be repolarized into anti-tumoral phenotypes. In this study, outer membrane vesicles (OMVs) secreted by Escherichia coli Nissle 1917 carry perhexiline (OMV@Perhx) to explore the influence of OMVs and perhexiline on TAM repolarization. OMV@Perhx was internalized by macrophages and regulated the phenotype of TAMs from M2-like to M1-like efficiently to increase the level of tumor suppressor accordingly. Re-polarized macrophages promoted apoptosis and inhibited the mobility of tumor, cells including invasion and migration. The results indicate that OMVs improve the efficacy of perhexiline and also represent a promising natural immunomodulator. Combining OMVs with perhexiline treatments shows powerfully synergistic anti-tumor effects through co-culturing with re-polarized macrophages. This work is promising to exploit the extensive applications of OMVs and chemical drugs, therefore developing a meaningful drug carrier and immunomodulator as well as expanding the purposes of traditional chemical drugs.

The Extracellular Matrix: Its Composition, Function, Remodeling, and Role in Tumorigenesis

The extracellular matrix (ECM) is a ubiquitous member of the body and is key to the maintenance of tissue and organ integrity. Initially thought to be a bystander in many cellular processes, the extracellular matrix has been shown to have diverse components that regulate and activate many cellular processes and ultimately influence cell phenotype. Importantly, the ECM's composition, architecture, and stiffness/elasticity influence cellular phenotypes. Under normal conditions and during development, the synthesized ECM constantly undergoes degradation and remodeling processes via the action of matrix proteases that maintain tissue homeostasis. In many pathological conditions including fibrosis and cancer, ECM synthesis, remodeling, and degradation is dysregulated, causing its integrity to be altered. Both physical and chemical cues from the ECM are sensed via receptors including integrins and play key roles in driving cellular proliferation and differentiation and in the progression of various diseases such as cancers. Advances in 'omics' technologies have seen an increase in studies focusing on bidirectional cell-matrix interactions, and here, we highlight the emerging knowledge on the role played by the ECM during normal development and in pathological conditions. This review summarizes current ECM-targeted therapies that can modify ECM tumors to overcome drug resistance and better cancer treatment.

Multimodal data fusion for cancer biomarker discovery with deep learning

Technological advances now make it possible to study a patient from multiple angles with high-dimensional, high-throughput multi-scale biomedical data. In oncology, massive amounts of data are being generated ranging from molecular, histopathology, radiology to clinical records. The introduction of deep learning has significantly advanced the analysis of biomedical data. However, most approaches focus on single data modalities leading to slow progress in methods to integrate complementary data types. Development of effective multimodal fusion approaches is becoming increasingly important as a single modality might not be consistent and sufficient to capture the heterogeneity of complex diseases to tailor medical care and improve personalised medicine. Many initiatives now focus on integrating these disparate modalities to unravel the biological processes involved in multifactorial diseases such as cancer. However, many obstacles remain, including lack of usable data as well as methods for clinical validation and interpretation. Here, we cover these current challenges and reflect on opportunities through deep learning to tackle data sparsity and scarcity, multimodal interpretability, and standardisation of datasets.

Mass Spectrometry Contribution to Pediatric Cancers Research

For over four decades, mass spectrometry-based methods have provided a wealth of information relevant to various challenges in the field of cancers research. These challenges included identification and validation of novel biomarkers for various diseases, in particular for various forms of cancer. These biomarkers serve various objectives including monitoring patient response to the various forms of therapy, differentiating subgroups of the same type of cancer, and providing proteomic data to complement datasets generated by genomic, epigenetic, and transcriptomic methods. The same proteomic data can be used to provide prognostic information and could guide scientists and medics to new and innovative targeted therapies The past decade has seen a rapid emergence of epigenetics as a major contributor to carcinogenesis. This development has given a fresh momentum to MS-based proteomics, which demonstrated to be an unrivalled tool for the analyses of protein post-translational modifications associated with chromatin modifications. In particular, high-resolution mass spectrometry has been recently used for systematic quantification of chromatin modifications. Data generated by this approach are central in the search for new therapies for various forms of cancer and will help in attempts to decipher antitumor drug resistance. To appreciate the contribution of mass spectrometry-based proteomics to biomarkers discovery and to our understanding of mechanisms behind the initiation and progression of various forms of cancer, a number of recent investigations are discussed. These investigations also include results provided by two-dimensional gel electrophoresis combined with mass spectrometry.

Targeting cancer drug resistance utilizing organoid technology

Cancer organoids generated from 3D in vitro cell cultures have contributed to the study of drug resistance. Maintenance of genomic and transcriptomic similarity between organoids and parental cancer allows organoids to have the ability of accurate prediction in drug resistance testing. Protocols of establishing therapy-sensitive and therapy-resistant organoids are concluded in two aspects, which are generated directly from respective patients' cancer and by induction of anti-cancer drug. Genomic and transcriptomic analyses and gene editing have been applied to organoid studies to identify key targets in drug resistance and FGFR3, KHDRBS3, lnc-RP11-536 K7.3 and FBN1 were found to be key targets. Furthermore, mechanisms contributing to resistance have been identified, including metabolic adaptation, activation of DNA damage response, defects in apoptosis, reduced cellular senescence, cellular plasticity, subpopulation interactions and gene fusions. Additionally, cancer stem cells (CSCs) have been verified to be involved in drug resistance utilizing organoid technology. Reversal of drug resistance can be achieved by targeting key genes and CSCs in cancer organoids. In this review, we summarize applications of organoids to cancer drug resistance research, indicating prospects and limitations.

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.

Liquid biopsy approaches and immunotherapy in colorectal cancer for precision medicine: Are we there yet?

Colorectal cancer (CRC) is the second leading cause of cancer-related deaths globally, with nearly half of patients detected in the advanced stages. This is due to the fact that symptoms associated with CRC often do not appear until the cancer has reached an advanced stage. This suggests that CRC is a cancer with a slow progression, making it curable and preventive if detected in its early stage. Therefore, there is an urgent clinical need to improve CRC early detection and personalize therapy for patients with this cancer. Recently, liquid biopsy as a non-invasive or nominally invasive approach has attracted considerable interest for its real-time disease monitoring capability through repeated sample analysis. Several studies in CRC have revealed the potential for liquid biopsy application in a real clinical setting using circulating RNA/miRNA, circulating tumor cells (CTCs), exosomes, etc. However, Liquid biopsy still remains a challenge since there are currently no promising results with high specificity and specificity that might be employed as optimal circulatory biomarkers. Therefore, in this review, we conferred the plausible role of less explored liquid biopsy components like mitochondrial DNA (mtDNA), organoid model of CTCs, and circulating cancer-associated fibroblasts (cCAFs); which may allow researchers to develop improved strategies to unravel unfulfilled clinical requirements in CRC patients. Moreover, we have also discussed immunotherapy approaches to improve the prognosis of MSI (Microsatellite Instability) CRC patients using neoantigens and immune cells in the tumor microenvironment (TME) as a liquid biopsy approach in detail.

Patient-Derived Primary Cancer-Associated Fibroblasts Mediate Resistance to Anti-Angiogenic Drug in Ovarian Cancers

Ovarian cancers rank first in both aggressiveness and dismal prognosis among gynecological neoplasms. The poor outcome is explained by the fact that most patients present with late-stage disease and progress through the first line of treatment. Ovarian neoplasms, especially epithelial ovarian cancers, are diagnosed at advanced/metastatic stages, often with a high angiogenesis index, one of the hallmarks of ovarian cancers with rapid progression and poor outcome as resistance to anti-angiogenic therapy develops. Despite therapy, the metastatic progression of aggressive ovarian cancer is a spectacularly selective function of tumor cells aided and abetted by the immune, mesenchymal and angiogenic components of the tumor microenvironment (TME) that enforces several pro-metastatic event(s) via direct and indirect interactions with stromal immune cells, cancer-associated fibroblasts (CAFs), and vascular endothelial cells. Since transdifferentiation of tumor endothelium is one of the major sources of CAFs, we hypothesized that ovarian CAF plays a critical role in resisting anti-angiogenic effects via direct crosstalk with endothelium and hence plays a direct role in the development of resistance to anti-angiogenic drugs. To test the hypothesis, we set up a hybrid ex vivo model for co-culture comprising Patient-Derived ex vivo primary CAFs from ovarian tumor samples and human umbilical vein endothelial cells (HUVEC). Patient-Derived CAFs were characterized by the mRNA and protein expression of positive (SMA, S100A4, TE-7, FAP-A, CD90/THY1), negative (EpCAM, CK 8,18, CD31, CD44, CD45), functional (PDGFRA, TGFB1, TGFB2, TGFRA) and immunological markers (PD-L1, PD-L2, PD-1) associated with CAFs by qRT-PCR, flow cytometry, Western blot, and ICC. Data from our HUVEC-on-CAF ex vivo Hybrid Co-Culture (HyCC) study demonstrate the pro-angiogenic effect of Patient-Derived ovarian CAFs by virtue of their ability to resist the effect of anti-angiogenic drugs, thereby aiding the development of resistance to anti-angiogenic drugs. Ascertaining direct experimental proof of the role of CAFs in developing resistance to specific anti-angiogenic drugs will provide an opportunity to investigate new drugs for counteracting CAF resistance and "normalizing/re-educating" TME in aggressive ovarian cancers. Our data provide a unique experimental tool for the personalized testing of anti-angiogenic drugs, positively predicting the development of future resistance to anti-angiogenic drugs well before it is clinically encountered in patients.

Molecular subtypes of osteosarcoma classified by cancer stem cell related genes define immunological cell infiltration and patient survival

Recent studies have shown that tumor stemness has biological significance in tumorigenicity and tumor progression. However, the characteristics of TME immune infiltration in osteosarcoma mediated by the combined effects of multiple cancer stem cell-related genes remain unknown.

Methods

In this study, we identified different cancer stem cell-associated subtypes in osteosarcoma based on 25 cancer stem cell-associated genes by consensus clustering analysis, and we comprehensively evaluated the association between these subtypes and immunocytes infiltration in the TME. The cancer stem cell (CSC) score was constructed to quantify the stemness of individual tumors.

Results

We performed a comprehensive evaluation of 218 osteosarcoma patients based on 25 cancer stem cell-related genes. Three different cancer stem cells related subtypes were identified, which were related to different biological processes and clinical outcomes. The three subtypes have different TME cells infiltrating characteristics, and CSC Cluster A had a higher level of immunocyte infiltration compared to CSC Cluster B and C. We constructed a scoring system, called the CSC score, to assess the stemness of individual patients. Then we found that the prognosis of patients was predicted by CSC score, and patients with low CSC score had prolonged survival. Further analyses showed that low CSC score was correlated with enhanced immune infiltration. CSC score may predict the effect of immunotherapy, and patients with low CSC score may have better immune response and clinical prognosis.

Conclusions

This study demonstrates that there could be three cancer stem cell-associated subtypes in osteosarcoma and that they were associated with different patient prognosis and TME immune infiltration characteristics. CSC score could be used to assess the stemness of individual patients, improve our comprehension of TME characteristics, and direct more effective immune therapy.

Immunomodulatory Properties of Immune Checkpoint Inhibitors-More than Boosting T-Cell Responses?

The approval of immune checkpoint inhibitors (ICI) that serve to enhance effector T-cell anti-tumor responses has strongly improved success rates in the treatment of metastatic melanoma and other tumor types. The currently approved ICI constitute monoclonal antibodies blocking cytotoxic T-lymphocyte-associated protein (CTLA)-4 and anti-programmed cell death (PD)-1. By this, the T-cell-inhibitory CTLA-4/CD80/86 and PD-1/PD-1L/2L signaling axes are inhibited. This leads to sustained effector T-cell activity and circumvents the immune evasion of tumor cells, which frequently upregulate PD-L1 expression and modulate immune checkpoint molecule expression on leukocytes. As a result, profound clinical responses are observed in 40-60% of metastatic melanoma patients. Despite the pivotal role of T effector cells for triggering anti-tumor immunity, mounting evidence indicates that ICI efficacy may also be attributable to other cell types than T effector cells. In particular, emerging research has shown that ICI also impacts innate immune cells, such as myeloid cells, natural killer cells and innate lymphoid cells, which may amplify tumoricidal functions beyond triggering T effector cells, and thus improves clinical efficacy. Effects of ICI on non-T cells may additionally explain, in part, the character and extent of adverse effects associated with treatment. Deeper knowledge of these effects is required to further develop ICI treatment in terms of responsiveness of patients to treatment, to overcome resistance to ICI and to alleviate adverse effects. In this review we give an overview into the currently known immunomodulatory effects of ICI treatment in immune cell types other than the T cell compartment.

Application of tumoroids derived from advanced colorectal cancer patients to predict individual response to chemotherapy

Therapeutic approaches of advanced colorectal cancer are more complex, here we present a living biobank of patient-derived tumoroids from advanced colorectal cancer patients and show examples of how these tumoroids can be used to to simulate cancer behavior ex vivo and provide more evidence for tumoroids could be utilized as a predictive platform during chemotherapy treatment to identify the chemotherapy response. Morphological, histological and genomic characterization analysis of colorectal cancer tumoroids was conducted. Further, we treated colorectal cancer tumoroids with different drugs to detect cellular activities to evaluate drug sensitivity using CellTiter-Glo 3 D cell viability assay. Then the drug sensitivity of tumoroids was compared with clinical outcomes. Our results implied that tumoroids recapitulated the histological features of the original tumours and genotypic profiling of tumoroids showed a high-level of similarity to the matched primary tumours. Dose-response curves, area under the curve and tumour inhibitory rate of each therapeutic profiling calculations in tumoroids demonstrated a great diversity and we gained 88.24% match ratio between the sensitivity data of tumoroids with their paired patients' clinical outcomes. tumour inhibitory rate of each treatment parameters in tumoroids performed positive correlation with progression-free survival while area under the curve of each treatment parameters performed negative correlation with progression-free survival of the corresponding patients. In summary, We presented a living biobank of tumoroids from advanced colorectal cancer patients and show tumoroids got great potential for predicting clinical responses to chemotherapy treatment of advanced colorectal cancer.

Spheroid Culture Differentially Affects Cancer Cell Sensitivity to Drugs in Melanoma and RCC Models

2D culture as a model for drug testing often turns to be clinically futile. Therefore, 3D cultures (3Ds) show potential to better model responses to drugs observed in vivo. In preliminary studies, using melanoma (B16F10) and renal (RenCa) cancer, we confirmed that 3Ds better mimics the tumor microenvironment. Here, we evaluated how the proposed 3D mode of culture affects tumor cell susceptibility to anti-cancer drugs, which have distinct mechanisms of action (everolimus, doxorubicin, cisplatin). Melanoma spheroids showed higher resistance to all used drugs, as compared to 2D. In an RCC model, such modulation was only observed for doxorubicin treatment. As drug distribution was not affected by the 3D shape, we assessed the expression of MDR1 and mTor. Upregulation of MDR1 in RCC spheroids was observed, in contrast to melanoma. In both models, mTor expression was not affected by the 3D cultures. By NGS, 10 genes related with metabolism of xenobiotics by cytochrome p450 were deregulated in renal cancer spheroids; 9 of them were later confirmed in the melanoma model. The differences between 3D models and classical 2D cultures point to the potential to uncover new non-canonical mechanisms to explain drug resistance set by the tumor in its microenvironment.

3D bioprinted drug-resistant breast cancer spheroids for quantitative in situ evaluation of drug resistance

Drug-resistant cancer spheroids were fabricated by three-dimensional (3D) bioprinting for the quantitative evaluation of drug resistance of cancer cells, which is a very important issue in cancer treatment. Cancer spheroids have received great attention as a powerful in vitro model to replace animal experiments because of their ability to mimic the tumor microenvironment. In this work, the extrusion printing of gelatin-alginate hydrogel containing MCF-7 breast cancer stem cells successfully provided 3D growth of many single drug-resistant breast cancer spheroids in a cost-effective 3D-printed mini-well dish. The drug-resistant MCF-7 breast cancer spheroids were able to maintain their drug-resistant phenotype of CD44^high/CD24^low/ALDH1^high in the gelatin-alginate media during 3D culture and exhibited higher expression levels of drug resistance markers, such as GRP78 chaperon and ABCG2 transporter, than bulk MCF-7 breast cancer spheroids. Furthermore, the effective concentration 50 (EC₅₀) values for apoptotic and necrotic spheroid death could be directly determined from the 3D printed-gelatin-alginate gel matrix based on in situ 3D fluorescence imaging of cancer spheroids located out of the focal point and on the focal point. The EC₅₀ values of anti-tumor agents (camptothecin and paclitaxel) for apoptotic and necrotic drug-resistant cancer spheroid death were higher than those for bulk cancer spheroid death, indicating a greater drug resistance. STATEMENT OF SIGNIFICANCE: This study proposed a novel 3D bioprinting-based drug screening model, to quantitatively evaluate the efficacy of anticancer drugs using drug-resistant MCF-7 breast cancer spheroids formed within a 3D-printed hydrogel. Quantitative determination of anticancer drug efficacy using EC₅₀, which is extremely important in drug discovery, was achieved by 3D printing that enables concurrent growth of many single spheroids efficiently. This study verified whether drug-resistant cancer spheroids grown within 3D-printed gelatin-alginate hydrogel could maintain and present drug resistance. Also, the EC₅₀ values of the apoptotic and necrotic cell deaths were directly acquired in 3D-embedded spheroids based on in situ fluorescence imaging. This platform provides a single-step straightforward strategy to cultivate and characterize drug-resistant spheroids to facilitate anticancer drug screening.

The Role of Natural Products as Sources of Therapeutic Agents for Innovative Drug Discovery

Emerging threats to human health require a concerted effort in search of both preventive and treatment strategies, placing natural products at the center of efforts to obtain new therapies and reduce disease spread and associated mortality. The therapeutic value of compounds found in plants has been known for ages, resulting in their utilization in homes and in clinics for the treatment of many ailments ranging from common headache to serious conditions such as wounds. Despite the advancement observed in the world, plant based medicines are still being used to treat many pathological conditions or are used as alternatives to modern medicines. In most cases, these natural products or plant-based medicines are used in an un-purified state as extracts. A lot of research is underway to identify and purify the active compounds responsible for the healing process. Some of the current drugs used in clinics have their origins as natural products or came from plant extracts. In addition, several synthetic analogues are natural product-based or plant-based. With the emergence of novel infectious agents such as the SARS-CoV-2 in addition to already burdensome diseases such as diabetes, cancer, tuberculosis and HIV/AIDS, there is need to come up with new drugs that can cure these conditions. Natural products offer an opportunity to discover new compounds that can be converted into drugs given their chemical structure diversity. Advances in analytical processes make drug discovery a multi-dimensional process involving computational designing and testing and eventual laboratory screening of potential drug candidates. Lead compounds will then be evaluated for safety, pharmacokinetics and efficacy. New technologies including Artificial Intelligence, better organ and tissue models such as organoids allow virtual screening, automation and high-throughput screening to be part of drug discovery. The use of bioinformatics and computation means that drug discovery can be a fast and efficient process and enable the use of natural products structures to obtain novel drugs. The removal of potential bottlenecks resulting in minimal false positive leads in drug development has enabled an efficient system of drug discovery. This review describes the biosynthesis and screening of natural products during drug discovery as well as methods used in studying natural products.

Galectin-9/TIM-3 as a Key Regulator of Immune Response in Gliomas With Chromosome 1p/19q Codeletion

Gliomas with chromosome 1p/19q codeletion were considered a specific tumor entity. This study was designed to reveal the biological function alterations tightly associated with 1p/19q codeletion in gliomas. Clinicopathological and RNA sequencing data from glioma patients were obtained from The Cancer Genome Atlas and Chinese Glioma Genome Atlas databases. Gene set variation analysis was performed to explore the differences in biological functions between glioma subgroups stratified by 1p/19q codeletion status. The abundance of immune cells in each sample was detected using the CIBERSORT analytical tool. Single-cell sequencing data from public databases were analyzed using the t-distributed stochastic neighbor embedding (t-SNE) algorithm, and the findings were verified by in vitro and in vivo experiments and patient samples.We found that the activation of immune and inflammatory responses was tightly associated with 1p/19q codeletion in gliomas. As the most important transcriptional regulator of Galectin-9 in gliomas, the expression level of CCAAT enhancer-binding protein alpha in samples with 1p/19q codeletion was significantly decreased, which led to the downregulation of the immune checkpoints Galectin-9 and TIM-3. These results were validated in three independent datasets. The t-SNE analysis showed that the loss of chromosome 19q was the main reason for the promotion of the antitumor immune response. IHC protein staining, in vitro and in vivo experiments verified the results of bioinformatics analysis. In gliomas, 1p/19q codeletion can promote the antitumor immune response by downregulating the expression levels of the immune checkpoint TIM-3 and its ligand Galectin-9.

Identification of Immune-Related Genes Associated With Bladder Cancer Based on Immunological Characteristics and Their Correlation With the Prognosis

Background:To identify the immune-related genes of bladder cancer (BLCA) based on immunological characteristics and explore their correlation with the prognosis. Methods:We downloaded the gene and clinical data of BLCA from the Cancer Genome Atlas (TCGA) as the training group, and obtained immune-related genes from the Immport database. We downloaded GSE31684 and GSE39281 from the Gene Expression Omnibus (GEO) as the external validation group. R (version 4.0.5) and Perl were used to analyze all data. Result:Univariate Cox regression analysis and Lasso regression analysis revealed that 9 prognosis-related immunity genes (PIMGs) of differentially expressed immune genes (DEIGs) were significantly associated with the survival of BLCA patients (p < 0.01), of which 5 genes, including NPR2, PDGFRA, VIM, RBP1, RBP1 and TNC, increased the risk of the prognosis, while the rest, including CD3D, GNLY, LCK, and ZAP70, decreased the risk of the prognosis. Then, we used these genes to establish a prognostic model. We drew receiver operator characteristic (ROC) curves in the training group, and estimated the area under the curve (AUC) of 1-, 3- and 5-year survival for this model, which were 0.688, 0.719, and 0.706, respectively. The accuracy of the prognostic model was verified by the calibration chart. Combining clinical factors, we established a nomogram. The ROC curve in the external validation group showed that the nomogram had a good predictive ability for the survival rate, with a high accuracy, and the AUC values of 1-, 3-, and 5-year survival were 0.744, 0.770, and 0.782, respectively. The calibration chart indicated that the nomogram performed similarly with the ideal model. Conclusion:We had identified nine genes, including PDGFRA, VIM, RBP1, RBP1, TNC, CD3D, GNLY, LCK, and ZAP70, which played important roles in the occurrence and development of BLCA. The prognostic model based on these genes had good accuracy in predicting the OS of patients and might be promising candidates of therapeutic targets. This study may provide a new insight for the diagnosis, treatment and prognosis of BLCA from the perspective of immunology. However, further experimental studies are necessary to reveal the underlying mechanisms by which these genes mediate the progression of BLCA.

Personalized models of heterogeneous 3D epithelial tumor microenvironments: Ovarian cancer as a model

Intractable human diseases such as cancers, are context dependent, unique to both the individual patient and to the specific tumor microenvironment. However, conventional cancer treatments are often nonspecific, targeting global similarities rather than unique drivers. This limits treatment efficacy across heterogeneous patient populations and even at different tumor locations within the same patient. Ultimately, this poor efficacy can lead to adverse clinical outcomes and the development of treatment-resistant relapse. To prevent this and improve outcomes, it is necessary to be selective when choosing a patient's optimal adjuvant treatment. In this review, we posit the use of personalized, tumor-specific models (TSM) as tools to achieve this remarkable feat. First, using ovarian cancer as a model disease, we outline the heterogeneity and complexity of both the cellular and extracellular components in the tumor microenvironment. Then we examine the advantages and disadvantages of contemporary cancer models and the rationale for personalized TSM. We discuss how to generate precision 3D models through careful and detailed analysis of patient biopsies. Finally, we provide clinically relevant applications of these versatile personalized cancer models to highlight their potential impact. These models are ideal for a myriad of fundamental cancer biology and translational studies. Importantly, these approaches can be extended to other carcinomas, facilitating the discovery of new therapeutics that more effectively target the unique aspects of each individual patient's TME. STATEMENT OF SIGNIFICANCE: In this article, we have presented the case for the application of biomaterials in developing personalized models of complex diseases such as cancers. TSM could bring about breakthroughs in the promise of precision medicine. The critical components of the diverse tumor microenvironments, that lead to treatment failures, include cellular- and extracellular matrix- heterogeneity, and biophysical signals to the cells. Therefore, we have described these dynamic components of the tumor microenvironments, and have highlighted how contemporary biomaterials can be utilized to create personalized in vitro models of cancers. We have also described the application of the TSM to predict the dynamic patterns of disease progression, and predict effective therapies that can produce durable responses, limit relapses, and treat any minimal residual disease.

What to Do for Increasing Cancer Burden on the African Continent? Accelerating Public Health Diagnostics Innovation for Prevention and Early Intervention on Cancers

No other place illustrates the increasing burden of cancer than in Africa and in particular, sub-Saharan Africa. Many of the individuals to be diagnosed with cancer will be in low-resource settings in the future due to, for example, an increase in populations and aging, and high co-morbidity with infections with viruses such as human immunodeficiency virus (HIV) and human papillomavirus (HPV), as well as the presence of infectious agents linked to cancer development. Due to lack of prevention and diagnostic innovation, patients present with advanced cancers, leading to poor survival and increased mortality. HIV infection-associated cancers such as B cell lymphomas, Kaposi's sarcoma, and HPV-associated cancers such as cervical cancer are particularly noteworthy in this context. Recent reports show that a host of other cancers are also associated with viral infection and these include lung, oral cavity, esophageal, and pharyngeal, hepatocellular carcinoma, and anal and vulvar cancers. This article examines the ways in which diagnostic innovation empowered by integrative biology and informed by public health priorities can improve cancer prevention or early intervention in Africa and beyond. In addition, I argue that because diagnostic biomarkers can often overlap with novel therapeutic targets, diagnostics research and development can have broader value for and impact on medical innovation.

Modulation of the tumor microenvironment (TME) by melatonin

The tumor microenvironment (TME) includes a number of non-cancerous cells that affect cancer cell survival. Although CD8⁺ T lymphocytes and natural killer (NK) cells suppress tumor growth through induction of cell death in cancer cells, there are various immunosuppressive cells such as regulatory T cells (Tregs), tumor-associated macrophages (TAMs), cancer-associated fibroblasts (CAFs), myeloid-derived suppressor cells (MDSCs), etc., which drive cancer cell proliferation. These cells may also support tumor growth and metastasis by stimulating angiogenesis, epithelial-mesenchymal transition (EMT), and resistance to apoptosis. Interactions between cancer cells and other cells, as well as molecules released into EMT, play a key role in tumor growth and suppression of antitumoral immunity. Melatonin is a natural hormone that may be found in certain foods and is also available as a drug. Melatonin has been demonstrated to modulate cell activity and the release of cytokines and growth factors in TME. The purpose of this review is to explain the cellular and molecular mechanisms of cancer cell resistance as a result of interactions with TME. Next, we explain how melatonin affects cells and interactions within the TME.

Integrins Within the Tumor Microenvironment: Biological Functions, Importance for Molecular Targeting, and Cancer Therapeutics Innovation

Many cellular functions important for solid tumor initiation and progression are mediated by members of the integrin family, a diverse family of cell attachment receptors. With recent studies emphasizing the role of the tumor microenvironment (TME) in tumor initiation and progression, it is not surprising that considerable attention is being paid to integrins. Several integrin antagonists are under clinical trials, with many demonstrating promising activity in patients with different cancers. A deeper knowledge of the functions of integrins within the TME is still required and might lead to better inhibitors being discovered. Integrin expression is commonly dysregulated in many tumors with integrins playing key roles in signaling as well as promotion of tumor cell invasion and migration. Integrins also play a major role in adhesion of circulating tumor cells to new sites and the resulting formation of secondary tumors. Furthermore, integrins have demonstrated the ability to promoting stem cell-like properties in tumor cells as well as drug resistance. Anti-integrin therapies rely heavily on the doses or concentrations used as these determine whether the drugs act as antagonists or as integrin agonists. This expert review offers the latest synthesis in terms of the current knowledge of integrins functions within the TME and as potential molecular targets for cancer therapeutics innovation.

Broadening Drug Design and Targets to Tumor Microenvironment? Cancer-Associated Fibroblast Marker Expression in Cancers and Relevance for Survival Outcomes

Solid tumors have complex biology and structure comprising cancer cells, stromal cells, and the extracellular matrix. While most therapeutics target the cancer cells, recent data suggest that cancer cell behavior and response to treatment are markedly influenced by the tumor microenvironment (TME). In particular, the cancer-associated fibroblasts (CAFs) are the most abundant stromal cells, and play a significant contextual role in shaping tumor initiation, progression, and metastasis. CAFs have therefore emerged as part of the next-generation cancer drug design and discovery innovation strategy. We report here new findings on differential expression and prognostic significance of CAF markers in several cancers. We utilized two publicly available resources: The Cancer Genomic Atlas and Gene Expression Profiling Interactive Analysis. We examined the expression of CAF markers, ACTA2, S100A4, platelet-derived growth factor receptor-beta [PDGFR-β], CD10, and fibroblast activation protein-alpha (FAP-α), in tumor tissues versus the adjacent normal tissues. We found that CAF markers were differentially expressed in various different tumors such as colon, breast, and esophageal cancers and melanoma. No CAF marker is expressed in the same pattern in all cancers, however. Importantly, we report that patients with colon adenocarcinoma and esophageal carcinoma expressing high FAP-α and CD10, respectively, had significantly shorter overall survival, compared with those with low levels of these CAF markers (p < 0.05). We call for continued research on TME biology and clinical evaluation of the CAF markers ACTA2, S100A4, PDGFR-β, CD10, and FAP-α in relation to prognosis of solid cancers in large population samples. An effective cancer drug design and discovery roadmap in the 21st century ought to be broadly framed, and include molecular targets informed by both cancer cell and TME variations.

Recent Trends in Multipotent Human Mesenchymal Stem/Stromal Cells: Learning from History and Advancing Clinical Applications

Early cell biology reports demonstrated the presence of cells with stem-like properties in bone marrow, with both hematopoietic and mesenchymal lineages. Over the years, various investigations have purified and characterized mesenchymal stromal/stem cells (MSCs) from different human tissues as cells with multilineage differentiation potential under the appropriate conditions. Due to their appealing characteristics and versatile potentials, MSCs are leveraged in many applications in medicine such as oncology, bioprinting, and as recent as therapeutics discovery and innovation for COVID-19. To date, studies indicate that MSCs have varied differentiation capabilities into different cell types, and demonstrate immunomodulating and anti-inflammatory properties. Different microenvironments or niche for MSCs and their resulting heterogeneity may influence attendant cellular behavior and differentiation capacity. The potential clinical applications of MSCs and exosomes derived from these cells have led to an avalanche of research reports on their properties and hundreds of clinical trials being undertaken. There is ample reason to think, as discussed in this expert review that the future looks bright and promising for MSC research, with many clinical trials under way to ascertain their clinical utility. This review provides a synthesis of the latest advances and trends in MSC research to allow for broad and critically informed use of MSCs. Early observations of the presence of these cells in the bone marrow and their remarkable differentiation capabilities and immunomodulation are also presented.

Cancer Stem Cell Marker CD44 Plays Multiple Key Roles in Human Cancers: Immune Suppression/Evasion, Drug Resistance, Epithelial-Mesenchymal Transition, and Metastasis

One of the most frequently utilized cancer stem cell markers in human cancers, including colorectal cancer and breast cancer, is CD44. A glycoprotein, CD44, traverses the cell membrane and binds to many ligands, including hyaluronan, resulting in activation of signaling cascades. There are conflicting data, however, on expression of CD44 in relationship to subtypes of cancers. Moreover, the associations of CD44 expression with drug resistance, immune infiltration, epithelial-mesenchymal transition (EMT), metastasis, and clinical prognosis in several cancer types are not clear and call for further studies. We report here an original study on CD44 expression in several human cancers and its relationship with tumorigenesis. We harnessed data from the publicly available databases, including The Cancer Genome Atlas, Gene Expression Profiling Interactive Analysis, Oncomine, Genomics of Drug Sensitivity in Cancer, and the Tumor Immune Estimation Resource. Our analysis reveals that CD44 expression varies across cancer types and is significantly associated with cancer patients' survival, in gastric and pancreatic cancers (p < 0.05). In addition, CD44 expression is closely linked with immune infiltration and immune suppressive features in pancreatic, colon adenocarcinoma, and stomach cancer. High CD44 expression was significantly correlated with the expression of drug resistance, EMT, and metastasis associated genes. Tumors expressing high CD44 have higher mutation burden and afflict older patients compared to tumors expressing low CD44. Cell lines expressing high CD44 are more resistant to anticancer drugs compared to those expressing low CD44. Protein-protein interaction investigations and functional enrichment analysis showed that CD44 interacts with gene products related to cell-substrate adhesion, migration, platelet activation, and cellular response to stress. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that these genes play key roles in biological adhesion, cell component organization, locomotion, G-α-signaling, and the response to stimulus. In summary, these findings lend evidence for the multiple key roles played by CD44 in tumorigenesis and suggest that CD44 is considered further in future studies of cancer pathogenesis and the search for novel molecular targets and personalized medicine biomarkers in clinical oncology.

Hydrogels to engineer tumor microenvironments in vitro

Illustration of engineered hydrogel to recapitulate aspects of the tumor microenvironment.

Cancer Stem Cell Markers in Relation to Patient Survival Outcomes: Lessons for Integrative Diagnostics and Next-Generation Anticancer Drug Development

Solid tumors display a complex biology that requires a multipronged treatment strategy. Most anticancer interventions, including chemotherapy, are currently unable to prevent treatment resistance and relapse. In general, therapeutics target cancer cells and overlook the tumor microenvironment (TME) and the presence of cancer stem cells (CSCs) with self-renewal and tumorigenic abilities. CSCs have been postulated to play key roles in tumor initiation, progression, therapy resistance, and metastasis. Hence, CSC markers have been suggested as diagnostics to forecast cancer prognosis as well as molecular targets for new-generation cancer treatments, especially in resistant disease. We report here original findings on expression and prognostic significance of CSC markers in several cancers. We examined and compared the transcriptional expression of CSC markers (ABCB1, ABCG2, ALDH1A1, CD24, CD44, CD90, CD133, CXCR4, EPCAM, ICAM1, and NES) in tumor tissues versus the adjacent normal tissues using publicly available databases, The Cancer Genome Atlas and Gene Expression Profiling Interactive Analysis. We found that CSC transcriptional markers were, to a large extent, expressed in higher abundance in solid tumors such as colon, lung, pancreatic, and esophageal cancers. On the other hand, no CSC marker in our analysis was expressed in the same pattern in all cancers, while individual CSC marker expression, alone, was not significantly associated with overall patient survival. Innovation in next-generation cancer therapeutics and diagnostics ought to combine CSC markers as well as integrative diagnostics that pool knowledge from CSCs and other TME components and cancer cells.

Nanomedicine and chemotherapeutics drug delivery: challenges and opportunities

Cancer is considered as one of the biggest threats to humans worldwide. Researchers suggest that tumour is not just a single mass, it comprises cancerous cells surrounded by noncancerous cells such as immune cells, adipocytes and cancer stem cells (CSCs) in the extracellular matrix (ECM) containing distinct components such as proteins, glycoproteins and enzymes; thus tumour microenvironment (TME) is partially complex. Multiple interactions happen in the dynamic microenvironment (ME) lead to an acidic, hypoxic and stiff ME that is considered as one of the major contributors to cancer progression and metastasis. Furthermore, TME involves in drug resistance mechanisms and affects enhanced permeability and retention (EPR) in tumours. In such a scenario, the first step to accomplish satisfying results is the identification and recognition of this ME. Then designing proper drug delivery systems can perform selectively towards cancerous cells. In this way, several targeting and stimuli/enzyme responsive drug delivery systems have been designed. More importantly, it is necessary to design a drug delivery system that can penetrate deeper into the tumours, efficiently and selectively. Various drug delivery systems such as exosomes and size-switchable nanocarriers (NCs) could decrease side effects and increase tumour treatment results by selective accumulation in tumours. In this review, TME features, current drug delivery approaches, challenges and promising strategies towards cancer treatment are discussed.

Coronavirus Disease-2019 Treatment Strategies Targeting Interleukin-6 Signaling and Herbal Medicine

Coronavirus disease-2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is evolving across the world and new treatments are urgently needed as with vaccines to prevent the illness and stem the contagion. The virus affects not only the lungs but also other tissues, thus lending support to the idea that COVID-19 is a systemic disease. The current vaccine and treatment development strategies ought to consider such systems medicine perspectives rather than a narrower focus on the lung infection only. COVID-19 is associated with elevated levels of the inflammatory cytokines such as interleukin-6 (IL-6), IL-10, and interferon-gamma (IFN-γ). Elevated levels of cytokines and the cytokine storm have been linked to fatal disease. This suggests new therapeutic strategies through blocking the cytokine storm. IL-6 is one of the major cytokines associated with the cytokine storm. IL-6 is also known to display pleiotropic/diverse pathophysiological effects. We suggest the blockage of IL-6 signaling and its downstream mediators such as Janus kinases (JAKs), and signal transducer and activators of transcription (STATs) offer potential hope for the treatment of severe cases of COVID-19. Thus, repurposing of already approved IL-6-JAK-STAT signaling inhibitors as well as other anti-inflammatory drugs, including dexamethasone, is under development for severe COVID-19 cases. We conclude this expert review by highlighting the potential role of precision herbal medicines, for example, the Cannabis sativa, provided that omics technologies can be utilized to build a robust scientific evidence base on their clinical safety and efficacy. Precision herbal medicine buttressed by omics systems science would also help identify new molecular targets for drug discovery against COVID-19.