A Flavonoid-Rich Extract of Mandarin Juice Counteracts 6-OHDA-Induced Oxidative Stress in SH-SY5Y Cells and Modulates Parkinson-Related Genes

Parkinson’s disease (PD) is a degenerative disorder of the nervous system due to unceasing impairment of dopaminergic neurons situated in the substantia nigra. At present, anti-PD drugs acting on dopamine receptors are mainly symptomatic and have only very limited neuroprotective effects, whereas drugs slowing down neurodegeneration of dopaminergic neurons and deterioration of clinical symptoms are not yet available. Given that, the development of more valuable pharmacological strategies is highly demanded. Comprehensive research on innovative neuroprotective drugs has proven that anti-inflammatory and antioxidant molecules from food sources may prevent and/or counteract neurodegenerative diseases, such as PD. The present study was aimed at the evaluation the protective effect of mandarin juice extract (MJe) against 6-hydroxydopamine (6-OHDA)-induced SH-SY5Y human neuroblastoma cell death. Treatment of differentiated SH-SY5Y cells with 6-OHDA brought cell death, and specifically, apoptosis, which was significantly inhibited by the preincubation with MJe through caspase 3 blockage and the modulation of p53, Bax, and Bcl-2 genes. In addition, it showed antioxidant properties in abiotic models as well as in vitro, where it reduced both reactive oxygen and nitrogen species induced by 6-OHDA, along with restored mitochondrial membrane potential, and prevented the oxidative DNA damage evoked by 6-OHDA. Furthermore, MJe restored the impaired balance of SNCA, LRRK2, PINK1, parkin, and DJ-1 gene levels, PD-related factors, caused by 6-OHDA oxidative stress. Overall, these results indicate that MJe exerts neuroprotective effects against 6-OHDA-induced cell death in SH-SY5Y cells by mechanisms involving both the specific interaction with intracellular pathways and its antioxidant capability. Our study suggests a novel possible strategy to prevent and/or ameliorate neurodegenerative diseases, such as PD.

Partitioning Pattern of Natural Products Based on Molecular Properties Descriptors Representing Drug-Likeness

A cheminformatics procedure for a partitioning model based on 135 natural compounds including Flavonoids, Saponins, Alkaloids, Terpenes and Triterpenes with drug-like features based on a descriptors pool was developed. The knowledge about the applicability of natural products as a unique source for the development of new candidates towards deadly infectious disease is a contemporary challenge for drug discovery. We propose a partitioning scheme for unveiling drug-likeness candidates with properties that are important for a prompt and efficient drug discovery process. In the present study, the vantage point is about the matching of descriptors to build the partitioning model applied to natural compounds with diversity in structures and complexity of action towards the severe diseases, as the actual SARS-CoV-2 virus. In the times of the de novo design techniques, such tools based on a chemometric and symmetrical effect by the implied descriptors represent another noticeable sign for the power and level of the descriptors applicability in drug discovery in establishing activity and target prediction pipeline for unknown drugs properties.

Mortality and morbidity of curative and palliative anticancer treatments during the COVID-19 pandemic: A multicenter population-based retrospective study

Administration of effective anticancer treatments should continue during pandemics. However, the outcomes of curative and palliative anticancer treatments during the coronavirus disease (COVID-19) pandemic remain unclear. The present retrospective observational study aimed to determine the 30-day mortality and morbidity of curative and palliative anticancer treatments during the COVID-19 pandemic. Between March 1 and June 30, 2020, all adults (n=2,504) with solid and hematological malignancies irrespective of cancer stage and type of anticancer treatments at five large comprehensive cancer centers in Saudi Arabia were included. The 30-day mortality was 5.1% (n=127) for all patients receiving anticancer treatment, 1.8% (n=24) for curative intent, 8.6% (n=103) for palliative intent and 13.4% (n=12) for COVID-19 cases. The 30-day morbidity was 28.2% (n=705) for all patients, 17.9% (n=234) for curative intent, 39.3% (n=470) for palliative intent and 75% (n=77) for COVID-19 cases. The 30-day mortality was significantly increased with male sex [odds ratio (OR), 2.011; 95% confidence interval (CI), 1.141-3.546; P=0.016], body mass index (BMI) <25 (OR, 1.997; 95% CI, 1.292-3.087; P=0.002), hormone therapy (OR, 6.315; 95% CI, 0.074-2.068; P=0.001) and number of cycles (OR, 2.110; 95% CI, 0.830-0.948; P=0.001), but decreased with Eastern Cooperative Oncology Group performance status (ECOG-PS) of 0-1 (OR, 0.157; 95% CI, 0.098-0.256; P=0.001), stage I-II cancer (OR, 0.254; 95% CI, 0.069-0.934; P=0.039) and curative intent (OR, 0.217; 95% CI, 0.106-0.443; P=0.001). Furthermore, the 30-day morbidity significantly increased with age >65 years (OR, 1.420; 95% CI, 1.075-1.877; P=0.014), BMI <25 (OR, 1.484; 95% CI, 1.194-1.845; P=0.001), chemotherapy (OR, 1.397; 95% CI, 1.089-5.438; P=0.032), hormone therapy (OR, 1.527; 95% CI, 0.211-1.322; P=0.038) and immunotherapy (OR, 1.859; 95% CI, 0.648-4.287; P=0.038), but decreased with ECOG-PS of 0-1 (OR, 0.502; 95% CI, 0.399-0.632; P=0.001), breast cancer (OR, 0.569; 95% CI, 0.387-0.836; P=0.004) and curative intent (OR, 0.410; 95% CI, 0.296-0.586; P=0.001). The mortality risk was lowest with curative treatments. Therefore, such treatments should not be delayed. The morbidity risk doubled with palliative treatments and was highest among COVID-19 cases. Mortality appeared to be driven by male sex, BMI <25, hormonal therapy and number of cycles, while morbidity increased with age >65 years, BMI <25, chemotherapy, hormonal therapy and immunotherapy. Therefore, oncologists should select the most effective anticancer treatments based on the aforementioned factors.

Engineered Antibody Fragment against the Urokinase Plasminogen Activator for Fast Delineation of Triple-Negative Breast Cancer by Positron Emission Tomography

The urokinase plasminogen activator (uPA) and its cofactors are important regulators of tumor initiation and progression (including metastasis), and its overexpression is associated with unfavorable situations in cancer patients. We have previously used positron emission tomography (PET) imaging with a radiolabeled monoclonal antibody against the uPA (named ATN-291) to detect the uPA signaling activity in various cancer types; however, good tumor contrast can only be observed 24 h postinjection. To shorten the antibody circulation time and decrease interactions of ATN-291 with the mononuclear phagocyte system (MPS), our goal in this study is to develop an engineered antibody fragment (F(ab')₂) from the parent antibody. By pepsin digestion and chromatography purification, ATN-291 F(ab')₂ was obtained and characterized. Subsequently, it was conjugated with NOTA-Bn-NCS or fluorescein isothiocyanate (FITC) for PET imaging and fluorescence-mediated cellular analysis (i.e., flow cytometry or fluorescence microscopy). We confirmed that ATN-291 F(ab')₂ still maintained a good targeting efficacy for the uPA in MDA-MB-231 cells (uPA⁺) and it had a faster blood clearance speed compared with ATN-291, while its interaction with MPS has been significantly decreased. In rodent tumor xenografts, radiolabeled ATN-291 F(ab')₂ had a selective and persistent uptake in MDA-MB-231 tumors, with an early tumor-to-blood ratio of 1.3 ± 0.8 (n = 4) at 2 h postinjection from PET imaging. During our observation, radiolabeled ATN-291 F(ab')₂ was excreted from both renal and hepatobiliary pathways. Radiolabeled ATN-291 F(ab')₂ was also used for detecting uPA fluctuation during the tumor treatment in test animals. We concluded that radiolabeled ATN-291 F(ab')₂ could be used as fast as PET cancer diagnostics with versatile applicability.

EIF5A2 enhances stemness of epithelial ovarian cancer cells via a E2F1/KLF4 axis

Background

Ovarian cancer stem cells (OCSC), endowed with tumor-initiating and self-renewal capacity, would account not only for the tumor growth, the peritoneal metastasis, and the relapse, but also for the acquisition of chemotherapy resistance. Nevertheless, figuring out their phenotypical and functional traits has proven quite challenging, mainly because of the heterogeneity of ovarian cancer. A deeper understanding of OCSC mechanisms will shed light on the development of the disease. Therefore, we aim to explore it for the design of innovative treatment regimens which aim at the eradication of ovarian cancer through the elimination of the CSC component.

Methods

In this study, immunohistochemistry assay and western blot assay were used to detect protein expression in the primary tumor and peritoneal multi-cellular aggregates/spheroids (MCAs/MCSs). OCSCs induced from cell line SKOV3 and HO-8910 were enriched in a serum-free medium (SFM). The effect of EIF5A2 on CSC-like properties was detected by sphere-forming assays, re-differentiation assays, quantitative real-time polymerase chain reaction, western blotting, flow cytometry, cell viability assays, immunofluorescence staining, and in vivo xenograft experiments. RNA-sequencing (RNA-seq) was used to reveal the mechanism by which EIF5A2 positively modulates the stem-like properties of ovarian cancer cells.

Results

Expression of EIF5A2 was significantly higher in peritoneal MCAs/MCSs compared to matched primary tumors, and EIF5A2 was also unregulated in ovarian cancer cell line-derived spheroids. Knockdown of EIF5A2 reduced the expression of the stem-related markers (ALDH1A1 and OCT-4), inhibited self-renewal ability, improved the sensitivity to chemotherapeutic drugs, and inhibited tumorigenesis in vivo. Mechanistic studies revealed that EIF5A2 knockdown reduced the expression of KLF4, which could partially rescue stem-like properties abolished by EIF5A2 knockdown or strengthened by EIF5A2 overexpression, through the transcription factor E2F1, which directly bind to KLF4 promoter.

Conclusion

Our results imply that EIF5A2 positively regulates stemness in ovarian cancer cells via E2F1/KLF4 pathway and may serve as a potential target in CSCs-targeted therapy for ovarian cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13287-021-02256-2.

Integrating immunotherapy in the (neo)adjuvant setting of early breast cancer

PURPOSE OF REVIEW

Breast cancer is a relative latecomer in the success story of immuno-oncology. In this review, we focus on the preclinical and clinical lines of evidence to justify the evaluation of immune checkpoint inhibition (ICI) for the curative-intent treatment of breast cancer, the latest and ongoing trials of (neo)adjuvant immunotherapy, and practical considerations in clinical practice associated with this new treatment paradigm.

RECENT FINDINGS

Insights from the immunobiology of breast cancer have paved the way for the new frontier of immunotherapy in this malignancy, starting from advanced stages and moving onto curable cases. Tumor-infiltrating lymphocyte quantification and PD-L1 immunohistochemistry are forerunners of predictive biomarkers for sensitivity to ICI in breast cancers. Preliminary results from phase III trials of combinatorial immunochemotherapy to treat early high-risk or locally advanced triple-negative breast cancer are encouraging for pathological complete response. Additional efficacy and patient-reported outcomes of (neo)adjuvant immunochemotherapy trials are awaited.

SUMMARY

The prospect of integrating ICI in the treatment of early-stage breast cancer is promising. Questions regarding patient selection, the choice of ICI agent and combination partner in escalation strategies, sequencing and duration of treatments, cost-effectiveness and mechanisms of resistance remain to be answered by future research.

2D LC as a tool for standardization of Foenugraeci semen extracts containing compounds with anti-Helicobacter pylori activity

The on-line heart-cutting two-dimensional liquid chromatography method with the use of a diode array detector and a mass spectrometer (LC-LC-DAD-ESI-MS) was established and validated for quantitation of C-glycosylflavones in fenugreek seeds (Foenugraeci semen, Trigonella foenum-graecum L.). The first- (¹D) and second- (²D) dimensional separations were performed on Kinetex C-18 columns with different diameters, respectively, and gradient (¹D) and isocratic elution (²D). Finally, 17 compounds were separated, 13 of which were quantified by ¹D separation and 4 compounds by ²D separation. As a result, it was pointed out that fenugreek seeds of Polish origin can be considered as a rich source of C-glycosylflavones. Antibacterial activity against Helicobacter pylori of standardized 70% methanol extract from fenugreek seeds has been demonstrated, in contrast to the inactive aqueous extract. Anti-H. pylori activity of the 70% methanol extract can be related to a higher concentration of C-glycosylflavones. This is the first report on the bactericidal activity of vitexin, diosgenin, tigogenin and sarsasapogenin against H. pylori and the bacteriostatic activity of orientin against this bacterium.

Immune Checkpoint Inhibitors in Triple Negative Breast Cancer Treatment: Promising Future Prospects

Immunotherapy has emerged as the fifth pillar of cancer treatment alongside surgery, radiotherapy, chemotherapy, and targeted therapy. Immune checkpoint inhibitors are the current superheroes of immunotherapy, unleashing a patient’s own immune cells to kill tumors and revolutionizing cancer treatment in a variety of cancers. Although breast cancer was historically believed to be immunologically silent, treatment with immune checkpoint inhibitors has been shown to induce modest responses in metastatic breast cancer. Given the inherent heterogeneity of breast tumors, this raised the question whether certain breast tumors might benefit more from immune-based interventions and which cancer cell-intrinsic and/or microenvironmental factors define the likelihood of inducing a potent and durable anti-tumor immune response. In this review, we will focus on triple negative breast cancer as immunogenic breast cancer subtype, and specifically discuss the relevance of tumor mutational burden, the plethora and diversity of tumor infiltrating immune cells in addition to the immunoscore, the presence of immune checkpoint expression, and the microbiome in defining immune checkpoint blockade response. We will highlight the current immune checkpoint inhibitor treatment options, either as monotherapy or in combination with standard-of-care treatment modalities such as chemotherapy and targeted therapy. In addition, we will look into the potential of immunotherapy-based combination strategies using immune checkpoint inhibitors to enhance both innate and adaptive immune responses, or to establish a more immune favorable environment for cancer vaccines. Finally, the review will address the need for unambiguous predictive biomarkers as one of the main challenges of immune checkpoint blockade. To conclude, the potential of immune checkpoint blockade for triple negative breast cancer treatment could be enhanced by exploration of aforementioned factors and treatment strategies thereby providing promising future prospects.

Association of Fusobacterium nucleatum with Specific T-cell Subsets in the Colorectal Carcinoma Microenvironment

PURPOSE

While evidence indicates that Fusobacterium nucleatum (F. nucleatum) may promote colorectal carcinogenesis through its suppressive effect on T-cell-mediated antitumor immunity, the specific T-cell subsets involved remain uncertain.

EXPERIMENTAL DESIGN

We measured F. nucleatum DNA within tumor tissue by quantitative PCR on 933 cases (including 128 F. nucleatum-positive cases) among 4,465 incident colorectal carcinoma cases in two prospective cohorts. Multiplex immunofluorescence combined with digital image analysis and machine learning algorithms for CD3, CD4, CD8, CD45RO (PTPRC isoform), and FOXP3 measured various T-cell subsets. We leveraged data on Bifidobacterium, microsatellite instability (MSI), tumor whole-exome sequencing, and M1/M2-type tumor-associated macrophages [TAM; by CD68, CD86, IRF5, MAF, and MRC1 (CD206) multimarker assay]. Using the 4,465 cancer cases and inverse probability weighting method to control for selection bias due to tissue availability, multivariable-adjusted logistic regression analysis assessed the association between F. nucleatum and T-cell subsets.

RESULTS

The amount of F. nucleatum was inversely associated with tumor stromal CD3⁺ lymphocytes [multivariable OR, 0.47; 95% confidence interval (CI), 0.28-0.79, for F. nucleatum-high vs. -negative category; P _trend = 0.0004] and specifically stromal CD3⁺CD4⁺CD45RO⁺ cells (corresponding multivariable OR, 0.52; 95% CI, 0.32-0.85; P _trend = 0.003). These relationships did not substantially differ by MSI status, neoantigen load, or exome-wide tumor mutational burden. F. nucleatum was not significantly associated with tumor intraepithelial T cells or with M1 or M2 TAMs.

CONCLUSIONS

The amount of tissue F. nucleatum is associated with lower density of stromal memory helper T cells. Our findings provide evidence for the interactive pathogenic roles of microbiota and specific immune cells.

A White Grape Juice Extract Reduces Fat Accumulation through the Modulation of Ghrelin and Leptin Expression in an In Vivo Model of Overfed Zebrafish

A caloric surplus and a sedentary lifestyle are undoubtedly known to be the leading causes of obesity. Natural products represent valuable allies to face this problematic issue. This study was planned to assess the effect of a white grape (Vitis vinifera) juice extract (WGJe) in diet-induced obese zebrafish (Danio rerio). Fish were divided into four different diet groups: (i) normally fed (NF); (ii) overfed (OF); (iii) WGJe-supplemented NF (5 mL/L in fish water); (iv) WGJe-supplemented OF. Body mass index (BMI) was extrapolated each week. After the fourth week, euthanized zebrafish were processed for both microscopic evaluations and gene expression analyses. OF zebrafish showed higher BMI values with respect to NF counterparts, an effect that was hindered by WGJe treatment. Moreover, histological analyses showed that the area of the adipose tissue, as well as the number, size, and density of adipocytes was significantly higher in OF fish. On the other hand, WGJe was able to avoid these outcomes both at the subcutaneous and visceral levels, albeit to different extents. At the gene level, WGJe restored the altered levels of ghrelin and leptin of OF fish both in gut and brain. Overall, our results support the anti-obesity property of WGJe, suggesting its potential role in weight management.

PD-L1 Expression after Neoadjuvant Chemotherapy in Triple-Negative Breast Cancers Is Associated with Aggressive Residual Disease, Suggesting a Potential for Immunotherapy

The consequences of neoadjuvant chemotherapy (NAC) for PD-L1 activity in triple-negative breast cancers (TNBC) are not well-understood. This is an important issue as PD-LI might act as a biomarker for immune checkpoint inhibitors' (ICI) efficacy, at a time where ICI are undergoing rapid development and could be beneficial in patients who do not achieve a pathological complete response. We used immunohistochemistry to assess PD-L1 expression in surgical specimens (E1L3N clone, cutoff for positivity: ≥1%) on both tumor (PD-L1-TC) and immune cells (PD-L1-IC) from a cohort of T1-T3NxM0 TNBCs treated with NAC. PD-L1-TC was detected in 17 cases (19.1%) and PD-L1-IC in 14 cases (15.7%). None of the baseline characteristics of the tumor or the patient were associated with PD-L1 positivity, except for pre-NAC stromal TIL levels, which were higher in post-NAC PD-L1-TC-positive than in negative tumors. PD-L1-TC were significantly associated with a higher residual cancer burden (p = 0.035) and aggressive post-NAC tumor characteristics, whereas PD-L1-IC were not. PD-L1 expression was not associated with relapse-free survival (RFS) (PD-L1-TC, p = 0.25, and PD-L1-IC, p = 0.95) or overall survival (OS) (PD-L1-TC, p = 0.48, and PD-L1-IC, p = 0.58), but high Ki67 levels after NAC were strongly associated with a poor prognosis (RFS, p = 0.0014, and OS, p = 0.001). A small subset of TNBC patients displaying PD-L1 expression in the context of an extensive post-NAC tumor burden could benefit from ICI treatment after standard NAC.

2020 FDA TIDES (Peptides and Oligonucleotides) Harvest

2020 has been an extremely difficult and challenging year as a result of the coronavirus disease 2019 (COVID-19) pandemic and one in which most efforts have been channeled into tackling the global health crisis. The US Food and Drug Administration (FDA) has approved 53 new drug entities, six of which fall in the peptides and oligonucleotides (TIDES) category. The number of authorizations for these kinds of drugs has been similar to that of previous years, thereby reflecting the consolidation of the TIDES market. Here, the TIDES approved in 2020 are analyzed in terms of chemical structure, medical target, mode of action, and adverse effects.

Long non-coding RNAs in colorectal cancer: Novel oncogenic mechanisms and promising clinical applications

Colorectal cancer (CRC) is the third most common malignancy and ranks as the second leading cause of cancer-related deaths worldwide. Despite the improvements in CRC diagnosis and treatment approaches, a considerable proportion of CRC patients still suffers from poor prognosis due to late disease detections and lack of personalized disease managements. Recent evidences have not only provided important molecular insights into their mechanistic behaviors but also indicated that identification of cancer-specific long non-coding RNAs (LncRNAs) could benefit earlier disease detections and improve treatment outcomes in patients suffering from CRC. LncRNAs have raised extensive attentions as they participate in various hallmarks of CRC. The mechanistic evidence gleaned in the recent decade clearly reveals that lncRNAs exert their oncogenic roles by regulating autophagy, epigenetic modifications, enhancing stem phenotype and modifying tumor microenvironment. In view of their pleiotropic functional roles in malignant progression, and their frequently dysregulated expression in CRC patients, they have great potential to be reliable diagnostic and prognostic biomarkers, as well as therapeutic targets for CRC. In the present review, we will focus on the oncogenic roles of lncRNAs and related mechanisms in CRC as well as discuss their clinical potential in the early diagnosis, prognostic prediction and therapeutic translation in patients with this malignancy.

Infiltrating immune cells in benign breast disease and risk of subsequent invasive breast cancer

Background

It is well established that tumors are antigenic and can induce an immune response by the host, entailing lymphocytic infiltration of the tumor and surrounding stroma. The extent and composition of the immune response to the tumor, assessed through evaluation of tumor-infiltrating lymphocyte counts, has been shown in many studies to have prognostic and predictive value for invasive breast cancer, but currently, there is little evidence regarding the association between infiltrating immune cell counts (IICCs) in women with benign breast disease (BBD) and risk of subsequent invasive breast cancer.

Methods

Using a cohort of 15,395 women biopsied for BBD at Kaiser Permanente Northwest, we conducted a nested case-control study in which cases were women who developed a subsequent invasive breast cancer during follow-up and controls were individually matched to cases on age at BBD diagnosis. We assessed IICCs in normal tissue and in the BBD lesions, and we used unconditional logistic regression to estimate the multivariable odds ratios (OR) and 95% confidence intervals (CI) for the associations between IICCs and breast cancer risk.

Results

There was no association between the IICC in normal tissue (multivariable OR per 5% increase in IICC = 1.05, 95% CI = 0.96–1.16) or in the BBD lesion (OR per 5% increase in IICC = 1.06, 95% CI = 0.96–1.18) and risk of subsequent invasive breast cancer. Also, there were no associations within subgroups defined by menopausal status, BBD histology, BMI, and history of smoking.

Conclusion

The results of this study suggest that IICCs in BBD tissue are not associated with altered risk of subsequent invasive breast cancer.

MUC1-C integrates activation of the IFN-γ pathway with suppression of the tumor immune microenvironment in triple-negative breast cancer

Background

Immune checkpoint inhibitors (ICIs) have had a profound impact on the treatment of many tumors; however, their effectiveness against triple-negative breast cancers (TNBCs) has been limited. One factor limiting responsiveness of TNBCs to ICIs is a lack of functional tumor-infiltrating lymphocytes (TILs) in ‘non-inflamed’ or ‘cold’ tumor immune microenvironments (TIMEs), although by unknown mechanisms. Targeting MUC1-C in a mouse transgenic TNBC tumor model increases cytotoxic tumor-infiltrating CD8+ T cells (CTLs), supporting a role for MUC1-C in immune evasion. The basis for these findings and whether they extend to human TNBCs are not known.

Methods

Human TNBC cells silenced for MUC1-C using short hairpin RNAs (shRNAs) were analyzed for the effects of MUC1-C on global transcriptional profiles. Differential expression and rank order analysis was used for gene set enrichment analysis (GSEA). Gene expression was confirmed by quantitative reverse-transcription PCR and immunoblotting. The The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) datasets were analyzed for effects of MUC1 on GSEA, cell-type enrichment, and tumor immune dysfunction and exclusion. Single-cell scRNA-seq datasets of TNBC samples were analyzed for normalized expression associations between MUC1 and selected genes within tumor cells.

Results

Our results demonstrate that MUC1-C is a master regulator of the TNBC transcriptome and that MUC1-C-induced gene expression is driven by STAT1 and IRF1. We found that MUC1-C activates the inflammatory interferon (IFN)-γ-driven JAK1→STAT1→IRF1 pathway and induces the IDO1 and COX2/PTGS2 effectors, which play key roles in immunosuppression. Involvement of MUC1-C in activating the immunosuppressive IFN-γ pathway was extended by analysis of human bulk and scRNA-seq datasets. We further demonstrate that MUC1 associates with the depletion and dysfunction of CD8+ T cells in the TNBC TIME.

Conclusions

These findings demonstrate that MUC1-C integrates activation of the immunosuppressive IFN-γ pathway with depletion of TILs in the TNBC TIME and provide support for MUC1-C as a potential target for improving TNBC treatment alone and in combination with ICIs. Of translational significance, MUC1-C is a druggable target with chimeric antigen receptor (CAR) T cells, antibody-drug conjugates (ADCs) and a functional inhibitor that are under clinical development.

Targeting Non-Oncogene Addiction for Cancer Therapy

While Next-Generation Sequencing (NGS) and technological advances have been useful in identifying genetic profiles of tumorigenesis, novel target proteins and various clinical biomarkers, cancer continues to be a major global health threat. DNA replication, DNA damage response (DDR) and repair, and cell cycle regulation continue to be essential systems in targeted cancer therapies. Although many genes involved in DDR are known to be tumor suppressor genes, cancer cells are often dependent and addicted to these genes, making them excellent therapeutic targets. In this review, genes implicated in DNA replication, DDR, DNA repair, cell cycle regulation are discussed with reference to peptide or small molecule inhibitors which may prove therapeutic in cancer patients. Additionally, the potential of utilizing novel synthetic lethal genes in these pathways is examined, providing possible new targets for future therapeutics. Specifically, we evaluate the potential of TONSL as a novel gene for targeted therapy. Although it is a scaffold protein with no known enzymatic activity, the strategy used for developing PCNA inhibitors can also be utilized to target TONSL. This review summarizes current knowledge on non-oncogene addiction, and the utilization of synthetic lethality for developing novel inhibitors targeting non-oncogenic addiction for cancer therapy.

Biomarkers in ovarian cancer and saliva: An update

Asymptomatic nature at the initial stage and heterogeneity makes ovarian cancer a “silent killer” which is being considered as most lethal gynecological cancer by acquiring the fifth leading cause of cancer-related deaths in women. Detection of ovarian cancer frequently requires painful invasive procedures such as multiple biopsies and blood tests which results in an undue stress and discomforts in patient. Recently, saliva is being opted as an alternative source for biomarker discovery due to procedure being non-invasive collection method cost-effectiveness, ease of sample collection, and handling. Saliva, a multiconstituent oral fluid secretion from the major and minor salivary glands enriched with proteins, DNAs, RNAs, and metabolites, behaves as a “mirror of the body.” Salivary diagnostics has become booming field with the development of new and advanced technologies accompanying with proteomics, RNA sequencing, liquid biopsy, and point-of-care (POC) diagnostics. Reliable and reproducible biomarkers identified through advanced salivaomics techniques such as proteomics, transcriptomics, genomics, and metabolomics for oral and systemic diseases including cancers can serve as a diagnostic and monitoring tool. Scientific communities are engaged in developing new technologies for the identification and validation of an extensive range of salivary biomarkers that will provide clinical and scientific credibility for saliva. This review provides a comprehensive update about the significant salivary biomarkers identified by the omics method that can be used for the early detection of ovarian cancer. In coming years, salivaomics may become a very important tool for early detection of ovarian cancer and salivary biomarkers may translate into improvement of treatment outcome and increased survival rate.

Standardized pathology report for breast cancer

Given the recent advances in management and understanding of breast cancer, a standardized pathology report reflecting these changes is critical. To meet this need, the Breast Pathology Study Group of the Korean Society of Pathologists has developed a standardized pathology reporting format for breast cancer, consisting of 'standard data elements,' 'conditional data elements,' and a biomarker report form. The 'standard data elements' consist of the basic pathologic features used for prognostication, while other factors related to prognosis or diagnosis are described in the 'conditional data elements.' In addition to standard data elements, all recommended issues are also presented. We expect that this standardized pathology report for breast cancer will improve diagnostic concordance and communication between pathologists and clinicians, as well as between pathologists inter-institutionally.

Whole-Lesion Histogram Analysis of the Apparent Diffusion Coefficient as a Quantitative Imaging Biomarker for Assessing the Level of Tumor-Infiltrating Lymphocytes: Value in Molecular Subtypes of Breast Cancer

Purpose

To assess whether apparent diffusion coefficient (ADC) metrics can be used to assess tumor-infiltrating lymphocyte (TIL) levels in breast cancer, particularly in the molecular subtypes of breast cancer.

Methods

In total, 114 patients with breast cancer met the inclusion criteria (mean age: 52 years; range: 29–85 years) and underwent multi-parametric breast magnetic resonance imaging (MRI). The patients were imaged by diffusion-weighted (DW)-MRI (1.5 T) using a single-shot spin-echo echo-planar imaging sequence. Two readers independently drew a region of interest (ROI) on the ADC maps of the whole tumor. The mean ADC and histogram parameters (10^th, 25^th, 50^th, 75^th, and 90^th percentiles of ADC, skewness, entropy, and kurtosis) were used as features to analyze associations with the TIL levels in breast cancer. Additionally, the correlation between the ADC values and Ki-67 expression were analyzed. Continuous variables were compared with Student’s t-test or Mann-Whitney U test if the variables were not normally distributed. Categorical variables were compared using Pearson’s chi-square test or Fisher’s exact test. Associations between TIL levels and imaging features were evaluated by the Mann-Whitney U and Kruskal-Wallis tests.

Results

A statistically significant difference existed in the 10^th and 25^th percentile ADC values between the low and high TIL groups in breast cancer (P=0.012 and 0.027). For the luminal subtype of breast cancer, the 10^th percentile ADC value was significantly lower in the low TIL group (P=0.041); for the non-luminal subtype of breast cancer, the kurtosis was significantly lower in the low TIL group (P=0.023). The Ki-67 index showed statistical significance for evaluating the TIL levels in breast cancer (P=0.007). Additionally, the skewness was significantly higher for samples with high Ki-67 levels in breast cancer (P=0.029).

Conclusions

Our findings suggest that whole-lesion ADC histogram parameters can be used as surrogate biomarkers to evaluate TIL levels in molecular subtypes of breast cancer.

Multiplex immunofluorescence to measure dynamic changes in tumor-infiltrating lymphocytes and PD-L1 in early-stage breast cancer

Background

The H&E stromal tumor-infiltrating lymphocyte (sTIL) score and programmed death ligand 1 (PD-L1) SP142 immunohistochemistry assay are prognostic and predictive in early-stage breast cancer, but are operator-dependent and may have insufficient precision to characterize dynamic changes in sTILs/PD-L1 in the context of clinical research. We illustrate how multiplex immunofluorescence (mIF) combined with statistical modeling can be used to precisely estimate dynamic changes in sTIL score, PD-L1 expression, and other immune variables from a single paraffin-embedded slide, thus enabling comprehensive characterization of activity of novel immunotherapy agents.

Methods

Serial tissue was obtained from a recent clinical trial evaluating loco-regional cytokine delivery as a strategy to promote immune cell infiltration and activation in breast tumors. Pre-treatment biopsies and post-treatment tumor resections were analyzed by mIF (PerkinElmer Vectra) using an antibody panel that characterized tumor cells (cytokeratin-positive), immune cells (CD3, CD8, CD163, FoxP3), and PD-L1 expression. mIF estimates of sTIL score and PD-L1 expression were compared to the H&E/SP142 clinical assays. Hierarchical linear modeling was utilized to compare pre- and post-treatment immune cell expression, account for correlation of time-dependent measurement, variation across high-powered magnification views within each subject, and variation between subjects. Simulation methods (Monte Carlo, bootstrapping) were used to evaluate the impact of model and tissue sample size on statistical power.

Results

mIF estimates of sTIL and PD-L1 expression were strongly correlated with their respective clinical assays (p < .001). Hierarchical linear modeling resulted in more precise estimates of treatment-related increases in sTIL, PD-L1, and other metrics such as CD8+ tumor nest infiltration. Statistical precision was dependent on adequate tissue sampling, with at least 15 high-powered fields recommended per specimen. Compared to conventional t-testing of means, hierarchical linear modeling was associated with substantial reductions in enrollment size required (n = 25➔n = 13) to detect the observed increases in sTIL/PD-L1.

Conclusion

mIF is useful for quantifying treatment-related dynamic changes in sTILs/PD-L1 and is concordant with clinical assays, but with greater precision. Hierarchical linear modeling can mitigate the effects of intratumoral heterogeneity on immune cell count estimations, allowing for more efficient detection of treatment-related pharmocodynamic effects in the context of clinical trials.

Trial registration

NCT02950259.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13058-020-01378-4.

Differential PD-1/LAG-3 expression and immune phenotypes in metastatic sites of breast cancer

Background

A dual blockade against the novel immune checkpoint inhibitor lymphocyte activation gene-3 (LAG-3) and programmed cell death protein-1 (PD-1) is currently considered in advanced breast cancer. Nevertheless, PD-1 or LAG-3 expression within distant metastatic breast cancer tissue remains understudied.

Methods

To address this knowledge gap, we investigated the PD-1 and LAG-3 expression in combination with the CD8-based immune phenotype in intrapatient matched primary tumor distant metastases, representing 95 breast cancer patients with metastases occurring at four different anatomical locations. The immune phenotype was categorized into 2 categories: inflamed corresponding to the clinical category “hot” and exhausted or desert consistent with clinically “cold” tumors.

Results

Metastases of “cold” primary tumors always remained “cold” at their matched metastatic site. Expression of PD-1/LAG-3 was associated with a “hot” immune phenotype in both the primary tumors and metastases. We could not observe any association between the immune phenotype and the breast cancer molecular subtype. Brain and soft tissue metastases were more commonly inflamed with signs of exhaustion than other anatomical sites of metastases. Taken together, (i) the immune phenotype varied between sites of distant metastases, and (ii) PD-1⁺/LAG-3⁺ was strongly associated with a “hot” immune phenotype and (iii) was most prevalent in brain and soft tissue metastases among distant metastases.

Conclusions

Our data strongly support an integrated analysis of the immune phenotype together with the PD-1/LAG-3 expression in distant metastases to identify patients with inflamed but exhausted tumors. This may eventually improve the stratification and likelihood for advanced breast cancer patients to profit from immunotherapy.

Potential roles and prognostic significance of exosomes in cancer drug resistance

Drug resistance is a major impediment in cancer therapy which strongly reduces the efficiency of anti-cancer drugs. Exosomes are extracellular vesicles with cup or spherical shape with a size range of 40–150 nm released by eukaryotic cells that contain genetic materials, proteins, and lipids which mediate a specific cell-to-cell communication. The potential roles of exosomes in intrinsic and acquired drug resistance have been reported in several studies. Furthermore, a line of evidence suggested that the content of exosomes released from tumor cells in biological samples may be associated with the clinical outcomes of cancer patients. In this review, we highlighted the recent studies regarding the potential roles of exosomes in tumor initiation, progression, and chemoresistance. This study suggests the possible role of exosomes for drug delivery and their contents in prognosis and resistance to chemotherapy in cancer patients.

An efficient chemical screening method for structure-based inhibitors to nucleic acid enzymes targeting the DNA repair-replication interface and SARS CoV-2

We present a Chemistry and Structure Screen Integrated Efficiently (CASSIE) approach (named for Greek prophet Cassandra) to design inhibitors for cancer biology and pathogenesis. CASSIE provides an effective path to target master keys to control the repair-replication interface for cancer cells and SARS CoV-2 pathogenesis as exemplified here by specific targeting of Poly(ADP-ribose) glycohydrolase (PARG) and ADP-ribose glycohydrolase ARH3 macrodomains plus SARS CoV-2 nonstructural protein 3 (Nsp3) Macrodomain 1 (Mac1) and Nsp15 nuclease. As opposed to the classical massive effort employing libraries with large numbers of compounds against single proteins, we make inhibitor design for multiple targets efficient. Our compact, chemically diverse, 5000 compound Goldilocks (GL) library has an intermediate number of compounds sized between fragments and drugs with predicted favorable ADME (absorption, distribution, metabolism, and excretion) and toxicological profiles. Amalgamating our core GL library with an approved drug (AD) library, we employ a combined GLAD library virtual screen, enabling an effective and efficient design cycle of ranked computer docking, top hit biophysical and cell validations, and defined bound structures using human proteins or their avatars. As new drug design is increasingly pathway directed as well as molecular and mechanism based, our CASSIE approach facilitates testing multiple related targets by efficiently turning a set of interacting drug discovery problems into a tractable medicinal chemistry engineering problem of optimizing affinity and ADME properties based upon early co-crystal structures. Optimization efforts are made efficient by a computationally-focused iterative chemistry and structure screen. Thus, we herein describe and apply CASSIE to define prototypic, specific inhibitors for PARG vs distinct inhibitors for the related macrodomains of ARH3 and SARS CoV-2 Nsp3 plus the SARS CoV-2 Nsp15 RNA nuclease.

Standardized Pathology Report for Breast Cancer

Given the recent advances in management and understanding of breast cancer, a standardized pathology report reflecting these changes is critical. To meet this need, the Breast Pathology Study Group of the Korean Society of Pathologists has developed a standardized pathology reporting format for breast cancer, consisting of ‘standard data elements,’ ‘conditional data elements,’ and a biomarker report form. The ‘standard data elements’ consist of the basic pathologic features used for prognostication, while other factors related to prognosis or diagnosis are described in the ‘conditional data elements.’ In addition to standard data elements, all recommended issues are also presented. We expect that this standardized pathology report for breast cancer will improve diagnostic concordance and communication between pathologists and clinicians, as well as between pathologists inter-institutionally.

Representation and participation across 20 years of plant genome sequencing

The field of plant genome sequencing has grown rapidly in the past 20 years, leading to increases in the quantity and quality of publicly available genomic resources. The growing wealth of genomic data from an increasingly diverse set of taxa provides unprecedented potential to better understand the genome biology and evolution of land plants. Here we provide a contemporary view of land plant genomics, including analyses on assembly quality, taxonomic distribution of sequenced species and national participation. We show that assembly quality has increased dramatically in recent years, that substantial taxonomic gaps exist and that the field has been dominated by affluent nations in the Global North and China, despite a wide geographic distribution of study species. We identify numerous disconnects between the native range of focal species and the national affiliation of the researchers studying them, which we argue are rooted in colonialism-both past and present. Luckily, falling sequencing costs, widening availability of analytical tools and an increasingly connected scientific community provide key opportunities to improve existing assemblies, fill sampling gaps and empower a more global plant genomics community.

Computational estimation of potential inhibitors from known drugs against the main protease of SARS-CoV-2

The coronavirus disease (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has rapidly spread worldwide recently, leading to global social and economic disruption. Although the emergently approved vaccine programs against SARS-CoV-2 have been rolled out globally, the number of COVID-19 daily cases and deaths has remained significantly high. Here, we attempt to computationally screen for possible medications for COVID-19 via rapidly estimating the highly potential inhibitors from an FDA-approved drug database against the main protease (Mpro) of SARS-CoV-2. The approach combined molecular docking and fast pulling of ligand (FPL) simulations that were demonstrated to be accurate and suitable for quick prediction of SARS-CoV-2 Mpro inhibitors. The results suggested that twenty-seven compounds were capable of strongly associating with SARS-CoV-2 Mpro. Among them, the seven top leads are daclatasvir, teniposide, etoposide, levoleucovorin, naldemedine, cabozantinib, and irinotecan. The potential application of these drugs in COVID-19 therapy has thus been discussed.

Approved drugs predicted to interact with critical residues in the substrate-binding site of SARS-CoV-2 Mpro can be promising inhibitors.

Recent Therapeutic Interventions of Fenugreek Seed: A Mechanistic Approach

Fenugreek seeds have widespread relations with Ayurveda, Unani, and Arabic medicine. The seeds were useful for the treatment and prevention of different ailments. Fenugreek (Trigonella foenum-graecum) or methi is from the Leguminosae family and are primarily known for its anti-diabetic and hypocholesterolemic activities. The germinated fenugreek seeds were used in the treatment of E.coli infection in Germany and France. The important phytoconstituents responsible for such medicinal applications are saponins, polyunsaturated fatty acids, galactomannans, trigonelline, and 4-hydroxy isoleucine. Flavonoids, apigenin 6,8-di-C-glucoside, apigenin-6-C-glucosyl-8-C-galactoside, 6-Cgalactosyl- 8-C-arabinoside are the chief ingredients of fenugreek seeds; responsible for reducing blood glucose while given to diabetic rats, whereas important flavones are epigenin, luteolin and vitexin. The other major bioactive components in fenugreek seeds are polyphenols like rhaponticin and isovitexin. Fenugreek seeds contain phosphorus and are categorized into different classes such as inorganic phosphorus, phospholipids, phytates, phosphor-proteins, and nucleic acid. Germinated seeds profusely filled with amino acids with amino acids, proteins, ascorbic acid, sugars. Further, this review shares information about the recent therapeutic intervention not covered earlier; on in vivo and in vitro and some clinical applications against certain interesting ailments other than older applications. This review includes certain nano delivery systems of Fenugreek seeds and their medicinal application.

Characterizing Immune Responses in Whole Slide Images of Cancer With Digital Pathology and Pathomics

Purpose of Review

Our goal is to show how readily available Pathomics tissue analytics can be used to study tumor immune interactions in cancer. We provide a brief overview of how Pathomics complements traditional histopathologic examination of cancer tissue samples. We highlight a novel Pathomics application, Tumor-TILs, that quantitatively measures and generates maps of tumor infiltrating lymphocytes in breast, pancreatic, and lung cancer by leveraging deep learning computer vision applications to perform automated analyses of whole slide images.

Recent Findings

Tumor-TIL maps have been generated to analyze WSIs from thousands of cases of breast, pancreatic, and lung cancer. We report the availability of these tools in an effort to promote collaborative research and motivate future development of ensemble Pathomics applications to discover novel biomarkers and perform a wide range of correlative clinicopathologic research in cancer immunopathology and beyond.

Summary

Tumor immune interactions in cancer are a fascinating aspect of cancer pathobiology with particular significance due to the emergence of immunotherapy. We present simple yet powerful specialized Pathomics methods that serve as powerful clinical research tools and potential standalone clinical screening tests to predict clinical outcomes and treatment responses for precision medicine applications in immunotherapy.

Interactive Classification of Whole-Slide Imaging Data for Cancer Researchers

Whole-slide histology images contain information that is valuable for clinical and basic science investigations of cancer but extracting quantitative measurements from these images is challenging for researchers who are not image analysis specialists. In this article, we describe HistomicsML2, a software tool for learn-by-example training of machine learning classifiers for histologic patterns in whole-slide images. This tool improves training efficiency and classifier performance by guiding users to the most informative training examples for labeling and can be used to develop classifiers for prospective application or as a rapid annotation tool that is adaptable to different cancer types. HistomicsML2 runs as a containerized server application that provides web-based user interfaces for classifier training, validation, exporting inference results, and collaborative review, and that can be deployed on GPU servers or cloud platforms. We demonstrate the utility of this tool by using it to classify tumor-infiltrating lymphocytes in breast carcinoma and cutaneous melanoma. SIGNIFICANCE: An interactive machine learning tool for analyzing digital pathology images enables cancer researchers to apply this tool to measure histologic patterns for clinical and basic science studies.

The Molecular Mechanisms of Regulating Oxidative Stress-Induced Ferroptosis and Therapeutic Strategy in Tumors

Ferroptosis is an atypical form of regulated cell death, which is different from apoptosis, necrosis, pyroptosis, and autophagy. Ferroptosis is characterized by iron-dependent oxidative destruction of cellular membranes following the antioxidant system's failure. The sensitivity of ferroptosis is tightly regulated by a series of biological processes, the metabolism of iron, amino acids, and polyunsaturated fatty acids, and the interaction of glutathione (GSH), NADPH, coenzyme Q10 (CoQ10), and phospholipids. Elevated oxidative stress (ROS) level is a hallmark of cancer, and ferroptosis serves as a link between nutrition metabolism and redox biology. Targeting ferroptosis may be an effective and selective way for cancer therapy. The underlying molecular mechanism of ferroptosis occurrence is still not enough. This review will briefly summarize the process of ferroptosis and introduce critical molecules in the ferroptotic cascade. Furthermore, we reviewed the occurrence and regulation of reduction-oxidation (redox) for ferroptosis in cancer metabolism. The role of the tumor suppressor and the epigenetic regulator in tumor cell ferroptosis will also be described. Finally, old drugs that can be repurposed to induce ferroptosis will be characterized, aiming for drug repurposing and novel drug combinations for cancer therapy more efficiently and economically.

Increased Stromal Infiltrating Lymphocytes Are Associated with the Risk of Disease Progression in Mesenchymal Circulating Tumor Cell-Positive Primary Breast Cancer Patients

Circulating tumor cells (CTCs) and the immune infiltration of tumors are closely related to clinical outcomes. This study aimed to verify the influence of stromal lymphocyte infiltration and the immune context of tumor microenvironment on the hematogenous spread and prognosis of 282 chemotherapy naïve primary BC patients. To detect the presence of mesenchymal CTCs, RNA extracted from CD45-depleted peripheral blood was interrogated for the expression of mesenchymal gene transcripts. Tumor-infiltrating lymphocytes (TILs) were detected in the stromal areas by immunohistochemistry, using CD3, CD8, and CD45RO antibodies. The concentrations of 51 plasma cytokines were measured by multiplex bead arrays. TILs infiltration in mesenchymal CTC-positive patients significantly decreased their progression-free survival (HR = 4.88, 95% CI 2.30–10.37, p < 0.001 for CD3^high; HR = 6.17, 95% CI 2.75–13.80, p < 0.001 for CD8^high; HR = 6.93, 95% CI 2.86–16.81, p < 0.001 for CD45RO^high). Moreover, the combination of elevated plasma concentrations of transforming growth factor beta-3 (cut-off 662 pg/mL), decreased monocyte chemotactic protein-3 (cut-off 52.5 pg/mL) and interleukin-15 (cut-off 17.1 pg/mL) significantly increased the risk of disease recurrence (HR = 4.838, 95% CI 2.048–11.427, p < 0.001). Our results suggest a strong impact of the immune tumor microenvironment on BC progression, especially through influencing the dissemination and survival of more aggressive, mesenchymal CTC subtypes.

Triple negative breast cancer in the era of miRNA

The objective of this review is to elucidate the role of miRNAs in triple negative breast cancer (TNBC). To achieve our goal, we searched databases such as PubMed, ScienceDirect, Springer, Web of Science and Scopus. We retrieved up to 1233 articles, based a rigorous selection criterion, only 197 articles were extensively reviewed. We selected articles only addressing TNBC, but not other types of breast cancer, with the employed approach being miRNA analysis and/or profiling. Our extensive review resulted in grouping of miRNAs into categories in which specific members of miRNAs have roles in specific mechanism in TNBC i.e., carcinogenesis, invasion, metastasis, apoptosis, diagnosis, prognosis, and treatment. TNBC is an aggressive subtype of breast cancer; therefore, different approaches for accurate diagnosis, prognosis and treatment are needed. In this review we summarize the up-to-date miRNA profiling, prognostic, and therapeutic findings that add to the route of controlling TNBC.

PD-L1 expression is associated with higher residual cancer burden in triple-negative breast cancers with residual disease after neoadjuvant chemotherapy.. [DOI: 10.1101/2020.12.04.20244277] [Cited by in Crossref: 0] [Impact Index Per Article: 0] The consequences of neoadjuvant chemotherapy (NAC) for PD-L1 activity in triple-negative breast cancers (TNBC) are not well understood. This is an important issue as immune checkpoint inhibitors (ICI) are undergoing rapid development and could be beneficial in patients who do not achieve a pathological complete response. We used immunohistochemistry to assess PD-L1 expression (E1L3N clone, cutoff for positivity: ≥ 1%) on both tumor (PD-L1-TC) and immune cells (PD-L1-IC) from a cohort of surgical specimens of T1-T3NxM0 TNBCs treated with NAC. PD-L1-TC was detected in 17 cases (19.1%) and PD-L1-IC in 14 cases (15.7%). None of the baseline characteristics of the tumor or the patient were associated with PD-L1 positivity, except for pre-NAC stromal TIL levels, which were higher in post-NAC PD-L1-TC-positive than in negative tumors. PD-L1-TC were significantly associated with a higher residual cancer burden (p=0.035) and aggressive post-NAC tumor characteristics, whereas PD-L1-IC were not. PD-L1 expression was not associated with DFS (p=0.38) or OS (p=0.48), but high Ki67 levels after NAC were strongly associated with a poor prognosis (DFS p=0.0014 and OS p=0.001). A small subset of TNBC patients displaying PD-L1 expression in the context of an extensive post-NAC tumor burden could benefit from ICI treatment after standard NAC

The consequences of neoadjuvant chemotherapy (NAC) for PD-L1 activity in triple-negative breast cancers (TNBC) are not well understood. This is an important issue as immune checkpoint inhibitors (ICI) are undergoing rapid development and could be beneficial in patients who do not achieve a pathological complete response. We used immunohistochemistry to assess PD-L1 expression (E1L3N clone, cutoff for positivity: ≥ 1%) on both tumor (PD-L1-TC) and immune cells (PD-L1-IC) from a cohort of surgical specimens of T1-T3NxM0 TNBCs treated with NAC. PD-L1-TC was detected in 17 cases (19.1%) and PD-L1-IC in 14 cases (15.7%). None of the baseline characteristics of the tumor or the patient were associated with PD-L1 positivity, except for pre-NAC stromal TIL levels, which were higher in post-NAC PD-L1-TC-positive than in negative tumors. PD-L1-TC were significantly associated with a higher residual cancer burden (p=0.035) and aggressive post-NAC tumor characteristics, whereas PD-L1-IC were not. PD-L1 expression was not associated with DFS (p=0.38) or OS (p=0.48), but high Ki67 levels after NAC were strongly associated with a poor prognosis (DFS p=0.0014 and OS p=0.001). A small subset of TNBC patients displaying PD-L1 expression in the context of an extensive post-NAC tumor burden could benefit from ICI treatment after standard NAC.

HPTLC fingerprinting analysis and in vitro pharmacological activities of Hermannia geniculata roots phenols

Hermannia geniculata is a herb that plays an important role in the treatment of an array of diseases including diabetes, ulcer, and colitis in the South African traditional medicine. The bioactive constituent and medicinal properties in phenols of Hermannia geniculata (PoHG) roots were investigated using high pressure thin layer chromatography (HPTLC). The α-amylase inhibitory potentials of PoHG was determined by reacting different concentration of the plant extract with 1% starch solution containing α-amylase. The inhibitory effect of the extract on α-glucosidase was evaluated by pre-incubating α-glucosidase with varying extract concentrations followed by the addition of ρ -nitrophenylglucopyranoside.. The reactive oxygen and free radical scavenging potentials of the extract were also analyzed. The result showed the presence of phenolic compounds in the extract with retention factor (Rf) values ranging from 0.14 to 095. The extract scavenged DPPH, ABTS+, hydroxyl, and superoxide anion radicals. The extract was able to chelate metallic ions with a lower IC50 value which differs significantly (p≤0.05) from silymarin. Moreover, PoHG extract inhibited the key enzymes (α-glucosidase and α-amylase) involved in carbohydrate catabolism with IC50 values of 1.76 ±0.14 and 7.52 ±0.23 mg/mL respectively while IC50 value reported for acarbose were 7.62 ±0.12 and 4.38 ±0.25 mg/mL for glucosidase and α-amylase, respectively. The α-glucosidase exhibited non-competitive inhibition by PoHG extract while α-amylase showed uncompetitive inhibition. This study confirmed the presence of phenol in PoHG extract and also showed an appreciable antioxidant and antidiabetic activities in vitro. Therefore, PoHG extract may be of nutraceutical importance.

Flavonoid-rich extracts from okra flowers exert antitumor activity in colorectal cancer through induction of mitochondrial dysfunction-associated apoptosis, senescence and autophagy

Okra flowers contain a higher content of total flavonoids than most other flowers; however little research has been conducted on their potential benefits, including antitumor activity. In this study, we extracted and purified flavonoids from okra flower (AFE), and aimed to evaluate the effect of AFE and its underlying mechanism on colorectal cancer (CRC) cell growth in vitro and in vivo. Here, we identify that AFE is a safe, natural antioxidant and exerts significant antitumor efficacy on the inhibition of CRC cell proliferation and metastasis as well as tumour growth in vivo. We further reveal that AFE inhibits CRC cell proliferation by inducing mitochondrial dysfunction, which results from the activation of p53 and induction of apoptosis and senescence, and inhibits autophagic degradation. Furthermore, AFE inhibited migration and invasion of CRC cells by regulating the balance of MMP2/TIMP2 and MMP9 expression levels. Of note, administration of AFE as a preventive agent achieves a more effective antitumor effect than the therapeutic agent in a xenograft mouse model. Our results reveal, for the first time, that AFE is a safe, natural antioxidant with significant antitumor efficacy, which has great potential in the application for CRC prevention and treatment.

Immunogenetic Association Underlying Severe COVID-19

SARS-CoV2 has caused the current pandemic of new coronavirus disease 2019 (COVID-19) worldwide. Clinical outcomes of COVID-19 illness range broadly from asymptotic and mild to a life-threatening situation. This casts uncertainties for defining host determinants underlying the disease severity. Recent genetic analyses based on extensive clinical sample cohorts using genome-wide association studies (GWAS) and high throughput sequencing curation revealed genetic errors and gene loci associated with about 20% of life-threatening COVID-19 cases. Significantly, most of these critical genetic loci are enriched in two immune signaling pathways, i.e., interferon-mediated antiviral signaling and chemokine-mediated/inflammatory signaling. In line with these genetic profiling studies, the broad spectrum of COVID-19 illness could be explained by immuno-pathological regulation of these critical immunogenetic pathways through various epigenetic mechanisms, which further interconnect to other vital components such as those in the renin-angiotensin-aldosterone system (RAAS) because of its direct interaction with the virus causing COVID-19. Together, key genes unraveled by genetic profiling may provide targets for precisely early risk diagnosis and prophylactic design to relieve severe COVID-19. The confounding epigenetic mechanisms may be key to understanding the clinical broadness of COVID-19 illness.

Role of GLUT-1 in the Upregulation of PD-L1 Expression After Radiotherapy and Association of PD-L1 with Favourable Overall Survival in Hypopharyngeal Cancer

Purpose

The alteration of tumor immunity after radiotherapy (RT) has been widely studied in recent years. However, the mechanism through which RT mediates tumor immunity and the involvement of glycolysis in this mediation in hypopharyngeal cancer remain unclear. This study investigated whether RT regulates programmed cell death ligand 1(PD-L1) partly via glucose transporter 1(GLUT-1) expression and whether PD-L1 expression predicts overall survival (OS) in patients with hypopharyngeal cancer.

Methods

The expression of PD-L1 and Glut-1, and the numbers of CD4+, CD8+ T cells were detected by immunohistochemical analysis on 47 pre-RT and 25 post-RT specimens of hypopharyngeal cancer. Changes in these indicators before and after RT were compared, and their association with the OS of patients was analyzed. Moreover, we used siRNA-GLUT-1 to inhibit GLUT-1 expression and examined whether GLUT-1 was a key factor involved in the mediation of PD-L1 expression by RT in vitro.

Results

In the multivariate analysis, patients with higher PD-L1 expression (p=0.037), higher CD4+ T cell infiltration (p=0.016) and earlier clinical stage (p=0.019) had favourable OS. The expression of PD-L1, and the CD4+ and CD8+ T cells was markedly increased following RT. PD-L1 expression was correlated with Glut-1 pre-RT (p=0.002), but not after RT (p=0.051). The expression of PD-L1 in FaDu cells was upregulated after RT, especially at 96h after RT in vitro. However, the expression of PD-L1 in siRNA-GLUT-1 FaDu cells was markedly decreased at 96h after RT compared with that measured in FaDu cells.

Conclusion

Patients with high PD-L1 expression and CD4+ T cell infiltration may have favourable OS in hypopharyngeal cancer. RT may increase PD-L1 expression and alter tumor immunity. The expression of PD-L1 was correlated with Glut-1, and inhibition of GLUT-1 expression may decrease the expression of PD-L1. GLUT-1 may participate in the alteration of tumor immunity after RT.

Bioactivity assessment of natural compounds using machine learning models based on drug target similarity.. [DOI: 10.1101/2020.11.06.371112] [Cited by in Crossref: 0] [Impact Index Per Article: 0] Natural compounds constitute a rich resource of potential small-molecule therapeutics. While experimental access to this resource is limited due to its vast diversity and difficulties in systematic purification, computational assessment of structural similarity with known therapeutic molecules offers a scalable approach. Here, we assessed functional similarity between natural compounds and approved drugs by combining multiple chemical similarity metrics and physicochemical properties through a random forest model. As a training set, we used pair-wise similarity between 1410 drugs in terms of their shared protein targets. The resulting model featured high performance metrics (matthews correlation coefficient of 0.81, and balanced accuracy of 0.91) suggesting that it well-captured the structure-activity relation. The model was then used to predict protein targets of circa 11k natural compounds by comparing them with the drugs. This revealed therapeutic potential of several natural compounds, including those with support from previously published sources as well as those hitherto unexplored. We experimentally validated one of the predicted link’s activities, viz., Cox-1 inhibition by 5-methoxysalicylic acid, a molecule commonly found in tea, herbs and spices. In contrast, another natural compound, 4-isopropylbenzoic acid, which showed a higher similarity when considering the most weighted similarity metric but was not picked by the random forest model, did not inhibit Cox-1. Our results demonstrate the utility of a machine-learning approach combining multiple chemical features for uncovering protein binding potential of natural compounds

Natural compounds constitute a rich resource of potential small-molecule therapeutics. While experimental access to this resource is limited due to its vast diversity and difficulties in systematic purification, computational assessment of structural similarity with known therapeutic molecules offers a scalable approach. Here, we assessed functional similarity between natural compounds and approved drugs by combining multiple chemical similarity metrics and physicochemical properties through a random forest model. As a training set, we used pair-wise similarity between 1410 drugs in terms of their shared protein targets. The resulting model featured high performance metrics (matthews correlation coefficient of 0.81, and balanced accuracy of 0.91) suggesting that it well-captured the structure-activity relation. The model was then used to predict protein targets of circa 11k natural compounds by comparing them with the drugs. This revealed therapeutic potential of several natural compounds, including those with support from previously published sources as well as those hitherto unexplored. We experimentally validated one of the predicted link’s activities, viz., Cox-1 inhibition by 5-methoxysalicylic acid, a molecule commonly found in tea, herbs and spices. In contrast, another natural compound, 4-isopropylbenzoic acid, which showed a higher similarity when considering the most weighted similarity metric but was not picked by the random forest model, did not inhibit Cox-1. Our results demonstrate the utility of a machine-learning approach combining multiple chemical features for uncovering protein binding potential of natural compounds.