The Opportunity of Precision Medicine for Breast Cancer With Context-Sensitive Tumor Suppressor Maspin

Relative Quantification of Proteins in Formalin-Fixed Paraffin-Embedded Breast Cancer Tissue Using Multiplexed Mass Spectrometry Assays

The identification of clinically relevant biomarkers represents an important challenge in oncology. This problem can be addressed with biomarker discovery and verification studies performed directly in tumor samples using formalin-fixed paraffin-embedded (FFPE) tissues. However, reliably measuring proteins in FFPE samples remains challenging. Here, we demonstrate the use of liquid chromatography coupled to multiple reaction monitoring mass spectrometry (LC-MRM/MS) as an effective technique for such applications. An LC-MRM/MS method was developed to simultaneously quantify hundreds of peptides extracted from FFPE samples and was applied to the targeted measurement of 200 proteins in 48 triple-negative, 19 HER2-overexpressing, and 20 luminal A breast tumors. Quantitative information was obtained for 185 proteins, including known markers of breast cancer such as HER2, hormone receptors, Ki-67, or inflammation-related proteins. LC-MRM/MS results for these proteins matched immunohistochemistry or chromogenic in situ hybridization data. In addition, comparison of our results with data from the literature showed that several proteins representing potential biomarkers were identified as differentially expressed in triple-negative breast cancer samples. These results indicate that LC-MRM/MS assays can reliably measure large sets of proteins using the analysis of surrogate peptides extracted from FFPE samples. This approach allows to simultaneously quantify the expression of target proteins from various pathways in tumor samples. LC-MRM/MS is thus a powerful tool for the relative quantification of proteins in FFPE tissues and for biomarker discovery.

Transcriptome Profiling of A549 Xenografts of Nonsmall-cell Lung Cancer Treated with Qing-Re-Huo-Xue Formula

Lung cancer is one of the most common malignant tumors, and non-small cell lung cancer (NSCLC) accounts for 85% of all lung cancer cases. Chinese herbal formula Qing-Re-Huo-Xue (QRHXF) has shown antitumor effects in the NSCLC xenograft mouse model of Lewis cells. However, the molecular mechanisms underlying the antitumor effects of QRHXF remain unknown. In this study, an A549 xenograft mouse model was established, and the mice were then treated with QRHXF or vehicle through oral gavage. Tumor growth was monitored. Tumors were subsequently harvested, and RNA sequencing was performed. Compared with the control group, mice treated with QRHXF showed smaller tumor size and slower tumor growth. RNA sequencing results indicated 36 differentially expressed genes between QRHXF treated and control groups. 16 upregulated and 20 downregulated genes were identified. Enrichment analysis showed four differential expression genes (DEGs) related to tumor growth pathways RASAL2, SerpinB5, UTG1A4, and PDE3A. In conclusion, this study revealed that QRHXF could inhibit tumor growth in an A549 xenograft mouse model, and the target genes of QRHXF may include PDE3A, RASAL2, SERPIB5, and UTG1A4.

Blood biomarkers representing maternal-fetal interface tissues used to predict early-and late-onset preeclampsia but not COVID-19 infection

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Endothelial dysfunction misleads blood marker discovery by differential expression.

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Blood-derived surrogate transcriptome of target-tissue avoids the false discovery.

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ITGA5 implies polymicrobial infection of maternal-fetal interface in preeclampsia.

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ITGA5 and IRF6 implies viral co-infection in early-onset preeclampsia.

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ITGA5, IRF6, and P2RX7 differ imminent preeclampsia from COVID-19 infection.

Background

A well-known blood biomarker (soluble fms-like tyrosinase-1 [sFLT-1]) for preeclampsia, i.e., a pregnancy disorder, was found to predict severe COVID-19, including in males. True biomarker may be masked by more-abrupt changes related to endothelial instead of placental dysfunction. This study aimed to identify blood biomarkers that represent maternal-fetal interface tissues for predicting preeclampsia but not COVID-19 infection.

Methods

The surrogate transcriptome of tissues was determined by that in maternal blood, utilizing four datasets (n = 1354) which were collected before the COVID-19 pandemic. Applying machine learning, a preeclampsia prediction model was chosen between those using blood transcriptome (differentially expressed genes [DEGs]) and the blood-derived surrogate for tissues. We selected the best predictive model by the area under the receiver operating characteristic (AUROC) using a dataset for developing the model, and well-replicated in datasets both with and without an intervention. To identify eligible blood biomarkers that predicted any-onset preeclampsia from the datasets but that were not positive in the COVID-19 dataset (n = 47), we compared several methods of predictor discovery: (1) the best prediction model; (2) gene sets of standard pipelines; and (3) a validated gene set for predicting any-onset preeclampsia during the pandemic (n = 404). We chose the most predictive biomarkers from the best method with the significantly largest number of discoveries by a permutation test. The biological relevance was justified by exploring and reanalyzing low- and high-level, multiomics information.

Results

A prediction model using the surrogates developed for predicting any-onset preeclampsia (AUROC of 0.85, 95 % confidence interval [CI] 0.77 to 0.93) was the only that was well-replicated in an independent dataset with no intervention. No model was well-replicated in datasets with a vitamin D intervention. None of the blood biomarkers with high weights in the best model overlapped with blood DEGs. Blood biomarkers were transcripts of integrin-α5 (ITGA5), interferon regulatory factor-6 (IRF6), and P2X purinoreceptor-7 (P2RX7) from the prediction model, which was the only method that significantly discovered eligible blood biomarkers (n = 3/100 combinations, 3.0 %; P =.036). Most of the predicted events (73.70 %) among any-onset preeclampsia were cluster A as defined by ITGA5 (Z-score ≥ 1.1), but were only a minority (6.34 %) among positives in the COVID-19 dataset. The remaining were predicted events (26.30 %) among any-onset preeclampsia or those among COVID-19 infection (93.66 %) if IRF6 Z-score was ≥-0.73 (clusters B and C), in which none was the predicted events among either late-onset preeclampsia (LOPE) or COVID-19 infection if P2RX7 Z-score was <0.13 (cluster C). Greater proportions of predicted events among LOPE were cluster A (82.85 % vs 70.53 %) compared to early-onset preeclampsia (EOPE). The biological relevance by multiomics information explained the biomarker mechanism, polymicrobial infection in any-onset preeclampsia by ITGA5, viral co-infection in EOPE by ITGA5-IRF6, a shared prediction with COVID-19 infection by ITGA5-IRF6-P2RX7, and non-replicability in datasets with a vitamin D intervention by ITGA5.

Conclusions

In a model that predicts preeclampsia but not COVID-19 infection, the important predictors were genes in maternal blood that were not extremely expressed, including the proposed blood biomarkers. The predictive performance and biological relevance should be validated in future experiments.

refMiR 142 5p inhibits cell invasion and migration by targeting DNMT1 in breast cancer

Abnormal cell proliferation caused by abnormal transcription regulation mechanismseems to be one of the reasons for the progression of breast cancer and also thepathological basis. MicroRNA 142 5p (miR 142 5p) is a low expressed miRNA inbreast cancer. T he role of MKL1's regulation of DNMT1 in breast cancer cellproliferation and migration is still unclear. MKL 1 (myocardi n related transcriptionfactor A) can bind to the conserved cis regulatory element CC (A/T) 6GG (called CarGbox) in the promoter to re gulate the transcription of miR 142 5p. The expression ofmiR 142 5p and MKL 1 are positively correlated. In addition, it has been proved thatDNMT1 is the target of miR 142 5p, which inhibits the expression of DNMT1 bytargeting the 3'UTR of DNMT1, thereby forming a feedback loop and inhibiting themigration and proliferation of breast cancer. Our data provide important and novelinsights into the MKL 1/miR 142 5p/DNMT1/maspin signaling pathway, and maybecome a new idea for breast cancer diagnosis, treatment and prognosis.

Key drug-targeting genes in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal type of cancer. In this study, we undertook a pairwise comparison of gene expression pattern between tumor tissue and its matching adjacent normal tissue for 45 PDAC patients and identified 22 upregulated and 32 downregulated genes. PPI network revealed that fibronectin 1 and serpin peptidase inhibitor B5 were the most interconnected upregulated-nodes. Virtual screening identified bleomycin exhibited reasonably strong binding to both proteins. Effect of bleomycin on cell viability was examined against two PDAC cell lines, AsPC-1 and MIA PaCa-2. AsPC-1 did not respond to bleomycin, however, MIA PaCa-2 responded to bleomycin with an IC₅₀ of 2.6 μM. This implicates that bleomycin could be repurposed for the treatment of PDAC, especially in combination with other chemotherapy agents. In vivo mouse xenograft studies and patient clinical trials are warranted to understand the functional mechanism of bleomycin towards PDAC and optimize its therapeutic efficacy. Furthermore, we will evaluate the antitumor activity of the other identified drugs in our future studies.

Maspin is a PTEN-Upregulated and p53-Upregulated Tumor Suppressor Gene and Acts as an HDAC1 Inhibitor in Human Bladder Cancer

Maspin is a member of the clade B serine protease inhibitor superfamily and exhibits diverse regulatory effects in various types of solid tumors. We compared the expressions of maspin and determined its potential biological functions and regulatory mechanisms in bladder carcinoma cells in vitro and in vivo. The results of RT-qPCR indicated that maspin expressed significantly lower levels in the bladder cancer tissues than in the paired normal tissues. The immunohistochemical assays of human bladder tissue arrays revealed similar results. Maspin-knockdown enhanced cell invasion whereas the overexpression of maspin resulted in the opposite process taking place. Knockdown of maspin also enhanced tumorigenesis in vivo and downregulated protein levels of acetyl-histone H3. Moreover, in bladder carcinoma cells, maspin modulated HDAC1 target genes, including cyclin D1, p21, MMP9, and vimentin. Treatment with MK2206, which is an Akt inhibitor, upregulated maspin expression, whereas PTEN-knockdown or PTEN activity inhibitor (VO-OHpic) treatments demonstrated reverse results. The ectopic overexpression of p53 or camptothecin treatment induced maspin expression. Our study indicated that maspin is a PTEN-upregulated and p53-upregulated gene that blocks cell growth in vitro and in vivo, and may act as an HDAC1 inhibitor in bladder carcinoma cells. We consider that maspin is a potential tumor suppressor gene in bladder cancer.

Brown Spider (Loxosceles) Venom Toxins as Potential Biotools for the Development of Novel Therapeutics

Brown spider envenomation results in dermonecrosis with gravitational spreading characterized by a marked inflammatory reaction and with lower prevalence of systemic manifestations such as renal failure and hematological disturbances. Several toxins make up the venom of these species, and they are mainly peptides and proteins ranging from 5–40 kDa. The venoms have three major families of toxins: phospholipases-D, astacin-like metalloproteases, and the inhibitor cystine knot (ICK) peptides. Serine proteases, serpins, hyaluronidases, venom allergens, and a translationally controlled tumor protein (TCTP) are also present. Toxins hold essential biological properties that enable interactions with a range of distinct molecular targets. Therefore, the application of toxins as research tools and clinical products motivates repurposing their uses of interest. This review aims to discuss possibilities for brown spider venom toxins as putative models for designing molecules likely for therapeutics based on the status quo of brown spider venoms. Herein, we explore new possibilities for the venom components in the context of their biochemical and biological features, likewise their cellular targets, three-dimensional structures, and mechanisms of action.

Tackling tumor heterogeneity and phenotypic plasticity in cancer precision medicine: our experience and a literature review

The predominant cause of cancer mortality is metastasis. The major impediment to cancer cure is the intrinsic or acquired resistance to currently available therapies. Cancer is heterogeneous at the genetic, epigenetic, and metabolic levels. And, while a molecular-targeted drug may be pathway-precise, it can still fail to achieve wholesome cancer-precise toxicity. In the current review, we discuss the strategic differences between targeting the strengths of cancer cells in phenotypic plasticity and heterogeneity and targeting shared vulnerabilities of cancer cells such as the compromised integrity of membranous organelles. To better recapitulate subpopulations of cancer cells in different phenotypic and functional states, we developed a schematic combination of 2-dimensional culture (2D), 3-dimmensional culture in collagen I (3D), and mammosphere culture for stem cells (mammosphere), designated as Scheme 2D/3D/mammosphere. We investigated how the tumor suppressor maspin may limit carcinoma cell plasticity and affect their context-dependent response to drugs of different mechanisms including docetaxel, histone deacetylase (HDAC) inhibitor MS-275, and ionophore antibiotic salinomycin. We showed that tumor cell phenotypic plasticity is not an exclusive attribute to cancer stem cells. Nonetheless, three subpopulations of prostate cancer cells, enriched through Scheme 2D/3D/mammosphere, show qualitatively different drug responses. Interestingly, salinomycin was the only drug that effectively killed all three cancer cell subpopulations, irrespective of their capacity of stemness. Further, Scheme 2D/3D/mammosphere may be a useful model to accelerate the screening for curative cancer drugs while avoiding costly characterization of compounds that may have only selective toxicity to some, but not all, cancer cell subpopulations.

Nuclear expression of onco-suppressors nm23-H1 and maspin are associated with lower recurrence rate in laryngeal carcinoma

PURPOSE

The main aim of the study was to preliminarily investigate the possibly related role of nuclear onco-suppressors maspin and nm23-H1, a metastasis suppressor, in laryngeal squamous cell carcinoma (LSCC).

MATERIALS AND METHODS

Maspin expression pattern and nuclear nm23-H1 expression were ascertained in 62 consecutive LSCCs.

RESULTS

Recurrence rate was significantly lower in patients with a nuclear maspin pattern of expression; nuclear nm23-H1 expression was significantly lower in patients who experienced disease recurrence. Disease free survival (DFS) was significantly longer in patients with maspin nuclear pattern or with nuclear nm23-H1 expression ≥10%. A significant association was found between nuclear nm23-H1 expression and maspin pattern of expression in LSCC. KNN discriminant analysis considered N status, maspin sub-cellular localization and nuclear nm23-H1 expression. The selected variables' accuracy in terms of relapse was 82%. Positive predictive accuracy was 100%, and negative predictive accuracy 79%.

CONCLUSIONS

Nuclear nm23-H1 expression and maspin pattern, also in association, show promise as recurrence indicators in LSCC. Further studies are needed to shed more light on the nm23-H1 mechanism of action in LSCC and thus find ways to restore nm23-H1 loss. These preliminary findings suggest that re-activating maspin functions might represent an important goal in the treatment of advanced LSCC.

Microvesicle Proteomic Profiling of Uterine Liquid Biopsy for Ovarian Cancer Early Detection

High-grade ovarian cancer (HGOC) is the leading cause of mortality from gynecological malignancies, because of diagnosis at a metastatic stage. Current screening options fail to improve mortality because of the absence of early-stage-specific biomarkers. We postulated that a liquid biopsy, such as utero-tubal lavage (UtL), may identify localized lesions better than systemic approaches of serum/plasma analysis. Further, while mutation-based assays are challenged by the rarity of tumor DNA within nonmutated DNA, analyzing the proteomic profile, is expected to enable earlier detection, as it reveals perturbations in both the tumor as well as in its microenvironment. To attain deep proteomic coverage and overcome the high dynamic range of this body fluid, we applied our method for microvesicle proteomics to the UtL samples. Liquid biopsies from HGOC patients (n = 49) and controls (n = 127) were divided into a discovery and validation sets. Data-dependent analysis of the samples on the Q-Exactive mass spectrometer provided depth of 8578 UtL proteins in total, and on average ∼3000 proteins per sample. We used support vector machine algorithms for sample classification, and crossed three feature-selection algorithms, to construct and validate a 9-protein classifier with 70% sensitivity and 76.2% specificity. The signature correctly identified all Stage I lesions. These results demonstrate the potential power of microvesicle-based proteomic biomarkers for early cancer diagnosis.