This work was supported by the National Natural Science Foundation of China (82160550).

TMEM200A: A Novel Oncogene Regulating EMT and PI3K/AKT in Gastric Cancer

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The authors declare there are no conflicts of interest.

TMEM200A belongs to a family of TMEMs that is essential for cancer cells to proliferate38. The variable expression of TMEM200A in different malignancies has received less attention, and a thorough pan-cancer investigation is lacking. However, evidence continues to accumulate, showing that the TMEM transmembrane protein family may be important in keeping cancer cells malignant through interactions with several proteins, for example, activation of TMEM16A Ca2+-activated ...

Cancer has emerged as a persistent public health issue endangering human health globally1due to its high morbidity and mortality rates worldwide, posing a heavy financial and medical burden to society2. Significant advancements in cancer therapy have been achieved in recent years thanks to the discovery of cancer markers3, and researchers have developed novel diagnostic methods and new drugs to treat cancer. However, some patients with cancer still have poor prognoses because of factors such as medication resistance, side effects of drugs, and chemical sensitivity4. Therefore, there is an urgent need for identifying new biomarkers for screening and treating early-stage cancers5.
Membrane proteins are proteins that can bind and integrate into cells and organelle membranes6. These can be grouped into three categories depending on the strength of binding to the membrane and their location: lipid-anchored proteins, integral proteins, and peripheral membrane proteins7,8. A transmembrane (TMEM) protein is an integral membrane protein that consists of at least one transmembrane segment9, which passes either completely or partially through the biological membrane. 
Although the mechanisms of action of proteins belonging to the TMEM family are not well understood, these proteins are known to be involved in several types of cancers10. Several TMEM proteins are associated with migratory, proliferative, and invasive phenotypes, and their expression is often associated with a patient's prognosis11. Therefore, TMEM family members have become the target of research. A comprehensive review of existing reports on TMEM revealed that they are mostly associated with inter- and intracellular signaling12, immune-related diseases, and tumorigenesis10. Many TMEMs also possess important physiological functions, for example, ion channels in the plasma membrane, activation of signal transduction pathways, as well as the mediation of cell chemotaxis, adhesion, apoptosis, and autophagy10. Therefore, we hypothesized that TMEM proteins may be important prognostic markers in the detection and treatment of tumors.
TMEM200A expression is significantly elevated in gastric cancer (GC). Higher expression of TMEM200A13, which has eight exons and a full length of 77.536 kb on chromosome 6q23.1, has been linked to a poor prognosis for overall survival (OS) in cases of GC. Yet the changes in its expression have rarely been reported in oncology studies. This article compares and analyzes the usefulness of TMEM200A as a therapeutic target and tumor diagnostic marker in various cancer studies using different publicly available datasets. We assessed the effectiveness of TMEM200A as a pan-cancer diagnostic and prognostic biomarker as well as its expression levels in various human cancer types using RNA-seq data from the UCSC Xena and TCGA databases, as well as by real-time quantitative polymerase chain reaction (qRT-PCR) and western blotting. 
The effect of TMEM200A expression levels on mutation rates, regulatory processes, tumor diagnosis and prognosis, immune infiltration, and immunotherapy was further investigated using a mix of computational tools and dataset websites. CBioPortal and the Catalog of Somatic Mutations in Cancer Cells (COSMIC) databases were used to examine mutations in TMEM200A. Sangerbox and TISIDB websites were utilized to understand how TMEM200A influences immune infiltration. The Tumor Immune Single Cell Center (TISCH) online tool and CancerSEA database were used to investigate the function of TMEM200A. Finally, to assess the impact of TMEM200A on the malignant behavior and tumor development function of GC cells, a loss-of-function experiment was conducted in an in vitro assay. Additionally, western blotting was performed to assess how TMEM200A knockdown affected the PI3K/AKT signaling pathway and the epithelial-mesenchymal transition (EMT) in GC.

<table><tbody><tr><td>Anti-AKT antibody</td><td>Proteintech Group, Inc</td><td>60203-2-Ig</td><td></td></tr><tr><td>Anti-E-cadherin antibody</td><td>Proteintech Group, Inc</td><td>20874-1-AP</td><td></td></tr><tr><td>anti-glyceraldehyde 3-phosphate dehydrogenase (GAPDH) antibody</td><td>Proteintech Group, Inc</td><td>10494-1-AP</td><td></td></tr><tr><td>Anti-N-cadherin antibody</td><td>Proteintech Group, Inc</td><td>22018-1-AP</td><td></td></tr><tr><td>Anti-P-AKT antibody</td><td>Proteintech Group, Inc</td><td>66444-1-Ig</td><td></td></tr><tr><td>Anti-snail antibody</td><td>Proteintech Group, Inc</td><td>13099-1-AP</td><td></td></tr><tr><td>Anti-Vimentin antibody</td><td>Proteintech Group, Inc</td><td>10366-1-AP</td><td></td></tr><tr><td>AxyPrepMultisourceTotalRNAMini-&lt;br/&gt; prep Kit</td><td>Suzhou Youyi Landi Biotechnology Co., Ltd</td><td>UEL-UE-MN-MS-RNA-50G</td><td></td></tr><tr><td>BCA Protein Assay Kit</td><td>Epizyme Biotech</td><td>ZJ101L</td><td></td></tr><tr><td>CCK-8 reagent</td><td>MedChemExpress</td><td>HY-K0301-500T</td><td></td></tr><tr><td>Fetal bovine serum (FBS)</td><td>CYAGEN BIOSCIENCES (GUANGZHOU) INC</td><td>FBSSR-01021</td><td></td></tr><tr><td>&lt;em&gt;GAPDH &lt;/em&gt;primer</td><td>Sangon Biotech (Shanghai) Co., Ltd.</td><td></td><td>Forward primer (5&amp;rsquo;-3&amp;rsquo;): TGACATCAAGAAGGTG&lt;br/&gt; GTGAAGCAG; Reverse primer (5&amp;rsquo;-3&amp;rsquo;): GTGTCGCTGTTGAAG&lt;br/&gt; TCAGAGGAG</td></tr><tr><td>HighGene plus Transfection reagent</td><td>ABclonal</td><td>RM09014P</td><td></td></tr><tr><td>HRP-conjugated Affinipure Goat Anti-Mouse lgG (H+L)</td><td>Proteintech Group, Inc</td><td>SA00001-1</td><td></td></tr><tr><td>HRP-conjugated Affinipure Goat Anti-Rabbit lgG (H+L)</td><td>Proteintech Group, Inc</td><td>SA00001-2</td><td></td></tr><tr><td>Human gastric mucosal epithelial &lt;strong&gt;GES-1 cells&lt;/strong&gt;</td><td>Guangzhou Cellcook Biotech Co.,Ltd.</td><td></td><td></td></tr><tr><td>Human STAD HGC-27 cells</td><td>Procell Life Science&amp;amp;Technology Co.,Ltd</td><td></td><td></td></tr><tr><td>Human STAD SGC-7901 cells</td><td>Procell Life Science&amp;amp;Technology Co.,Ltd</td><td></td><td></td></tr><tr><td>MonAmp SYBR Green qPCR Mix (None ROX)</td><td>Mona (Suzhou) Biotechnology Co., Ltd</td><td>MQ10101S</td><td></td></tr><tr><td>MonScript RTIII All-in-One Mix with dsDNase&amp;nbsp;&amp;nbsp;</td><td>Mona (Suzhou) Biotechnology Co., Ltd</td><td>MR05101M</td><td></td></tr><tr><td>Omni-ECL Femto Light Chemiluminescence Kit</td><td>Epizyme Biotech</td><td>SQ201</td><td></td></tr><tr><td>PAGE Gel Fast Preparationb Kit&amp;nbsp;</td><td>Epizyme Biotech</td><td>PG111</td><td></td></tr><tr><td>Penicillin-streptomycin (Pen-Strep)</td><td>Beijing Solarbio Science &amp;amp; Technology Co.,Ltd</td><td>P1400-100</td><td></td></tr><tr><td>Polyvinylidene difluoride (PVDF) membrane</td><td>Merck KGaA</td><td>IPVH00010-1</td><td></td></tr><tr><td>Protein Free Rapid Blocking Buffer</td><td>Epizyme Biotech</td><td>PS108P</td><td></td></tr><tr><td>RIPA lysis solution</td><td>Beijing Solarbio Science &amp;amp; Technology Co., Ltd</td><td>R0010</td><td></td></tr><tr><td>RPMI 1640 complete medium</td><td>Thermo Fisher Scientific</td><td>C11875500BT</td><td></td></tr><tr><td>Skimmed milk</td><td>Campina: Elk</td><td></td><td></td></tr><tr><td>TBST buffer solution</td><td>Beijing Solarbio Science &amp;amp; Technology Co., Ltd</td><td>T1082</td><td></td></tr><tr><td>The protein loading buffer</td><td>Epizyme Biotech</td><td>LT101S</td><td></td></tr><tr><td>TMEM200A knockdown plasmid</td><td>MiaoLing Plasmid</td><td></td><td></td></tr><tr><td>&lt;em&gt;TMEM200A &lt;/em&gt;primer</td><td>Sangon Biotech (Shanghai) Co., Ltd.</td><td></td><td>Forward primer (5&amp;rsquo;-3&amp;rsquo;): AAGGCGGTGTGGTGGTTCG; Reverse primer (5&amp;rsquo;-3&amp;rsquo;): GATTTTGGTCTCTTTGTCACGGTT</td></tr><tr><td>&lt;em&gt;TMEM200A &lt;/em&gt;SiRNA1</td><td>MiaoLing Plasmid</td><td></td><td>Forward primer (5&amp;rsquo;-3&amp;rsquo;): ACAACTGATGATAAGACCAG; Reverse primer (5&amp;rsquo;-3&amp;rsquo;): TGTTGACTACTATTCTGGTC</td></tr><tr><td>&lt;em&gt;TMEM200A &lt;/em&gt;SiRNA2</td><td>MiaoLing Plasmid</td><td></td><td>Forward primer (5&amp;rsquo;-3&amp;rsquo;): CGTGTGAATGTCAATGACTG; Reverse primer (5&amp;rsquo;-3&amp;rsquo;): GCACACTTACAGTTACTGAC</td></tr><tr><td>&lt;em&gt;TMEM200A &lt;/em&gt;SiRNA3</td><td>MiaoLing Plasmid</td><td></td><td>Forward primer (5&amp;rsquo;-3&amp;rsquo;): ACAACCACAACATCTGCCCG; Reverse primer (5&amp;rsquo;-3&amp;rsquo;): TGTTGGTGTTGTAGACGGGC</td></tr><tr><td>Transmembrane protein 200A Antibody</td><td>Proteintech Group, Inc</td><td>48081-1</td><td></td></tr><tr><td>&lt;strong&gt;Equipment&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>CO&lt;sub&gt;2&lt;/sub&gt; cell culture incubator</td><td>Haier Group</td><td>PYXE-80IR</td><td></td></tr><tr><td>Electrophoresis instrument</td><td>Bio-RAD</td><td></td><td></td></tr><tr><td>Fluorescence quantitative PCR instrument</td><td>Bio-RAD</td><td></td><td></td></tr><tr><td>Multifunctional Enzyme Labeler</td><td>Berthold</td><td></td><td></td></tr></tbody></table>

multiomics analysis of tmem200a as a pan-cancer biomarker

The transmembrane protein, TMEM200A, is known to be associated with human cancers and immune infiltration. Here, we assessed the function of TMEM200A in common cancers by multiomics analysis and used in vitro cell cultures of gastric cells to verify the results. The expression of TMEM200A in several human cancer types was assessed using the RNA-seq data from the UCSC Xena database. Bioinformatic analysis revealed a potential role of TMEM200A as a diagnostic and prognostic biomarker. 
Cultures of normal gastric and cancer cell lines were grown and TMEM200A was knocked down. The expression levels of TMEM200A were measured by using quantitative real-time polymerase chain reaction and western blotting. In vitro loss-of-function studies were then used to determine the roles of TMEM200A in the malignant behavior and tumor formation of gastric cancer (GC) cells. Western blots were used to assess the effect of the knockdown on epithelial-mesenchymal transition (EMT) and PI3K/AKT signaling pathway in GC. Bioinformatic analysis showed that TMEM200A was expressed at high levels in GC. 
The proliferation of GC cells was inhibited by TMEM200A knockdown, which also decreased vimentin, N-cadherin, and Snai proteins, and inhibited AKT phosphorylation. The PI3K/AKT signaling pathway also appeared to be involved in TMEM200A-mediated regulation of GC development. The results presented here suggest that TMEM200A regulates the tumor microenvironment by affecting the EMT. TMEM200A may also affect EMT through PI3K/AKT signaling, thus influencing the tumor microenvironment. Therefore, in pan-cancers, especially GC, TMEM200A may be a potential biomarker and oncogene.

Expression of TMEM200A in various cancers 
As illustrated in Figure 1, we first analyzed the differential expression levels of TMEM200A in various cancers through different databases. TMEM200A expression was elevated in cholangiocarcinoma (CHOL), head and neck squamous cell carcinoma (HNSC), renal clear cell carcinoma (KIRC), renal papillary cell carcinoma (KIRP), hepatocellular carcinoma (LIHC), STAD, and thyroid carcinoma (T...

Watch this Scientific Journal Video about Unveiling Transmembrane Protein Family-Related Markers in Gastric Cancer and Implications for Targeted Therapies at JoVE.com

Author Spotlight: Unveiling Transmembrane Protein Family-Related Markers in Gastric Cancer and Implications for Targeted Therapies 

Here, a protocol is presented in which multiple bioinformatic tools are combined to study the biological functions of TMEM200A in cancer. In addition, we also experimentally validate the bioinformatics predictions.

Multiomics Analysis of TMEM200A as a Pan-Cancer Biomarker

The transmembrane protein, TMEM200A, is known to be associated with human cancers and immune infiltration. Here, we assessed the function of TMEM200A in ...

multiomics-analysis-of-tmem200a-as-a-pan-cancer-biomarker

Research

JoVE Journal

Cancer Research

1.4K Views.  Youjiang Medical University for Nationalities. Er is aanzienlijke vooruitgang geboekt in het onderzoek naar biomarkers voor kanker. Desalniettemin blijft de extractfunctie van tumorgerelateerde zaken die verband houden met de transmembraaneiwitfamilie ongeïdentificeerd. Als gevolg hiervan heeft ons onderzoek naar de TMEM200A bij maagkanker nieuwe onderzoeksrichtingen voor verwante cellen gegenereerd.In deze studie gebruikten we de combinatie van online databasevoorspelling en validatie van experimentele technieken, wat de onderzoe...

Video: Auteur in de schijnwerpers: onthulling van transmembraan-eiwitfamiliegerelateerde markers bij maagkanker en implicaties voor gerichte therapieën 

The Colon-26 Carcinoma Tumor-bearing Mouse as a Model for the Study of Cancer Cachexia

Cancer cachexia is the progressive loss of skeletal muscle mass and adipose tissue, negative nitrogen balance, anorexia, fatigue, inflammation, and activation of lipolysis and proteolysis systems. Cancer patients with cachexia benefit less from anti-neoplastic therapies and show increased mortality1. Several animal models have been established in order to investigate the molecular causes responsible for body and muscle wasting as a result of tumor growth. Here, we describe methodologies pertaining to a well-characterized model of cancer cachexia: mice bearing the C26 carcinoma2-4. Although this model is heavily used in cachexia research, different approaches make reproducibility a potential issue. The growth of the C26 tumor causes a marked and progressive loss of body and skeletal muscle mass, accompanied by reduced muscle cross-sectional area and muscle strength3-5. Adipose tissue is also lost. Wasting is coincident with elevated circulating levels of pro-inflammatory cytokines, particularly Interleukin-6 (IL-6)3, which is directly, although not entirely, responsible for C26 cachexia. It is well-accepted that a primary mechanism by which the C26 tumor induces muscle tissue depletion is the activation of skeletal muscle proteolytic systems. Thus, expression of muscle-specific ubiquitin ligases, such as atrogin-1/MAFbx and MuRF-1, represent an accepted method for the evaluation of the ongoing muscle catabolism2. Here, we present how to execute this model in a reproducible manner and how to excise several tissues and organs (the liver, spleen, and heart), as well as fat and skeletal muscles (the gastrocnemius, tibialis anterior, and quadriceps). We also provide useful protocols that describe how to perform muscle freezing, sectioning, and fiber size quantification.

Mice bearing the Colon-26 (C26) carcinoma represent a classical model of cancer cachexia. Progressive muscle wasting occurs in association with tumor growth, over-expression of muscle-specific ubiquitin ligases, and reductions in muscle cross-sectional area. Fat loss is also observed. Cachexia is studied in a time-dependent manner with increasing severity of wasting.

Cancer cachexia is the progressive loss of skeletal muscle mass and adipose tissue, negative nitrogen balance, anorexia, fatigue, inflammation, and ...

Simple and Rapid Method to Obtain High-quality Tumor DNA from Clinical-pathological Specimens Using Touch Imprint Cytology

It is critical to determine the mutational status in cancer before administration and treatment of specific molecular targeted drugs for cancer patients. In the clinical setting, formalin-fixed paraffin-embedded (FFPE) tissues are widely used for genetic testing. However, FFPE DNA is generally damaged and fragmented during the fixation process with formalin. Therefore, FFPE DNA is sometimes not adequate for genetic testing because of low quality and quantity of DNA. Here we present a method of touch imprint cytology (TIC) to obtain genomic DNA from cancer cells, which can be observed under a microscope. Cell morphology and cancer cell numbers can be evaluated using TIC specimens. Furthermore, the extraction of genomic DNA from TIC samples can be completed within two days. The total amount and quality of TIC DNA obtained using this method was higher than that of FFPE DNA. This rapid and simple method allows researchers to obtain high-quality DNA for genetic testing (e.g., next generation sequencing analysis, digital PCR, and quantitative real time PCR) and to shorten the turnaround time for reporting results.

Obtaining high-quality genomic DNA from tumor tissues is an essential first step for analyzing genetic alterations using next generation sequencing. In this article, we present a simple and rapid method to enrich tumor cells and obtain intact DNA from touch imprint cytology specimens.

It is critical to determine the mutational status in cancer before administration and treatment of specific molecular targeted drugs for cancer patients. ...

The Application of 1% Methylene Blue Dye As a Single Technique in Breast Cancer Sentinel Node Biopsy

In this study, we injected 1% methylene blue dye (MBD) into the subareolar or peritumoral space of the breast. In the case of breast conserving surgery (BCS), a separate incision in the lower axilla hairline was made to find the sentinel nodes (SNs). In mastectomy, the SNs were identified through the same mastectomy incision. The SNs were described as blue nodes or nodes with lymphatic blue channels. An anatomical landmark in the axilla was used to facilitate SNs identification. The SNs metastases were evaluated by intraoperative frozen section analysis and histopathology examination as it is a gold standard. Here, we described the MBD as the lone technique in breast cancer sentinel node biopsy (SNB) which could be useful when radioisotope tracer or patent or isosulfan blue dye (PBD) cannot be provided.

In Indonesia, sentinel node biopsy (SNB) is not routinely performed for breast cancer surgery because of the limitation to provide radioisotope tracer and isosulfan or patent blue dye (PBD). To overcome this obstacle, we applied 1% methylene blue dye (MBD) as a single agent to map the sentinel nodes (SNs).

In this study, we injected 1% methylene blue dye (MBD) into the subareolar or peritumoral space of the breast. In the case of breast conserving surgery ...

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Biomarker detection is one of the more important biomedical questions for high-throughput &#39;omics&#39; researchers, and almost all existing biomarker detection algorithms generate one biomarker subset with the optimized performance measurement for a given dataset. However, a recent study demonstrated the existence of multiple biomarker subsets with similarly effective or even identical classification performances. This protocol presents a simple and straightforward methodology for detecting biomarker subsets with binary classification performances, better than a user-defined cutoff. The protocol consists of data preparation and loading, baseline information summarization, parameter tuning, biomarker screening, result visualization and interpretation, biomarker gene annotations, and result and visualization exportation at publication quality. The proposed biomarker screening strategy is intuitive and demonstrates a general rule for developing biomarker detection algorithms. A user-friendly graphical user interface (GUI) was developed using the programming language Python, allowing biomedical researchers to have direct access to their results. The source code and manual of kSolutionVis can be downloaded from http://www.healthinformaticslab.org/supp/resources.php.

Existing algorithms generate one solution for a biomarker detection dataset. This protocol demonstrates the existence of multiple similarly effective solutions and presents a user-friendly software to help biomedical researchers investigate their datasets for the proposed challenge. Computer scientists may also provide this feature in their biomarker detection algorithms.

Biomarker detection is one of the more important biomedical questions for high-throughput &#39;omics&#39; researchers, and almost all existing biomarker ...

Phospho Flow Cytometry with Fluorescent Cell Barcoding for Single Cell Signaling Analysis and Biomarker Discovery

Aberrant cell signaling plays a central role in cancer development and progression. Most novel targeted therapies are indeed directed at proteins and protein functions, and cell signaling aberrations may therefore serve as biomarkers to indicate personalized treatment options. As opposed to DNA and RNA analyses, changes in protein activity can more efficiently evaluate the mechanisms underlying drug sensitivity and resistance. Phospho flow cytometry is a powerful technique that measures protein phosphorylation events at the cellular level, an important feature that distinguishes this method from other antibody-based approaches. The method allows for simultaneous analysis of multiple signaling proteins. In combination with fluorescent cell barcoding, larger medium- to high-throughput data-sets can be acquired by standard cytometer hardware in short time. Phospho flow cytometry has applications both in studies of basic biology and in clinical research, including signaling analysis, biomarker discovery and assessment of pharmacodynamics. Here, a detailed experimental protocol is provided for phospho flow analysis of purified peripheral blood mononuclear cells, using chronic lymphocytic leukemia cells as an example.

Here, a protocol for medium- to high-throughput analysis of protein phosphorylation events at the cellular level is presented. Phospho flow cytometry is a powerful approach to characterize signaling aberrations, identify and validate biomarkers, and assess pharmacodynamics.

Aberrant cell signaling plays a central role in cancer development and progression. Most novel targeted therapies are indeed directed at proteins and ...

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

In recent years, emerging databases were designed to lower the barriers for approaching the intricate cancer genomic datasets, thereby, facilitating investigators to analyze and interpret genes, samples and clinical data across different types of cancer. Herein, we describe a practical operation procedure, taking ID1 (Inhibitor of DNA binding proteins 1) as an example, to characterize the expression patterns of biomarker and survival predictors of breast cancer based on pooled clinical datasets derived from online accessible databases, including ONCOMINE, bcGenExMiner v4.0 (Breast cancer gene-expression miner v4.0), GOBO (Gene expression-based Outcome for Breast cancer Online), HPA (The human protein atlas), and Kaplan-Meier plotter. The analysis began with querying the expression pattern of the gene of interest (e.g., ID1) in cancerous samples vs. normal samples. Then, the correlation analysis between ID1 and clinicopathological characteristics in breast cancer was performed. Next, the expression profiles of ID1 was stratified according to different subgroups. Finally, the association between ID1 expression and survival outcome was analyzed. The operation procedure simplifies the concept to integrate multidimensional data types at the gene level from different databases and test hypotheses regarding recurrence and genomic context of gene alteration events in breast cancer. This method can improve the credibility and representativeness of the conclusions, thereby, present informative perspective on a gene of interest.

Here, we present a protocol to explore the biomarker and survival predictor of breast cancer based on the comprehensive analysis of pooled clinical datasets derived from a variety of publicly accessible databases, using the strategy of expression, correlation and survival analysis step by step.

In recent years, emerging databases were designed to lower the barriers for approaching the intricate cancer genomic datasets, thereby, facilitating ...

Multiplex Immunofluorescence and Spatial Image Analysis of the Tumor Microenvironment

Multiplex Immunofluorescence Combined with Spatial Image Analysis for the Clinical and Biological Assessment of the Tumor Microenvironment

The tumor microenvironment (TME) is composed of a plethora of different cell types, such as cytotoxic immune cells and immunomodulatory cells. Depending on its composition and the interactions between cancer cells and peri-tumoral cells, the TME may affect cancer progression. The characterization of tumors and their complex microenvironment could improve the understanding of cancer diseases and may help scientists and clinicians to discover new biomarkers.
We recently developed several multiplex immunofluorescence (mIF) panels based on tyramide signal amplification (TSA) for the characterization of the TME in colorectal cancer, head and neck squamous cell carcinoma, melanoma, and lung cancer. Once the staining and scanning of the corresponding panels are completed, the samples are analyzed on an image analysis software. The spatial position and the staining of each cell are then exported from this quantification software into R. We developed R scripts that allow us not only to analyze the density of each cell type in several tumor compartments (e.g. the center of the tumor, the margin of the tumor, and the stroma) but also to perform distance-based analyses between different cell types.
This particular workflow adds a spatial dimension to the classical density analysis already routinely performed for several markers. mIF analysis could allow scientists to have a better understanding of the complex interaction between cancer cells and the TME and to discover new predictive biomarkers of response to treatments, such as immune checkpoint inhibitors, and targeted therapies.

Author Spotlight: Multiplex Immunofluorescence Combined with Spatial Image Analysis for the Clinical and Biological Assessment of the Tumor Microenvironment  

In this article, a protocol for manual tyramide signal amplification (TSA) multiplex immunofluorescence (mIF) combined with image analysis and spatial analysis is described. This protocol can be used with formalin-fixed paraffin-embedded (FFPE) sections for the staining of two to six antigens per slide depending on the slide scanner available in the laboratory.

The tumor microenvironment (TME) is composed of a plethora of different cell types, such as cytotoxic immune cells and immunomodulatory cells. Depending ...

Mapping the Tumor Immune Landscape: An In-Depth Multiplex IHC Analysis Protocol

Multiplex Immunohistochemical Analysis of the Spatial Immune Cell Landscape of the Tumor Microenvironment

The immune cell landscape of the tumor microenvironment potentially contains information for the discovery of prognostic and predictive biomarkers. Multiplex immunohistochemistry is a valuable tool to visualize and identify different types of immune cells in tumor tissues while retaining its spatial information. Here we provide detailed protocols to analyze lymphocyte, myeloid, and dendritic cell populations in tissue sections. Starting from cutting formalin-fixed paraffin-embedded sections, automatic multiplex staining procedures on an automated platform, scanning of the slides on a multispectral imaging microscope, to the analysis of images using an in-house-developed machine learning algorithm ImmuNet. These protocols can be applied to a variety of tumor specimens by simply switching tumor markers to analyze immune cells in different compartments of the sample (tumor versus invasive margin) and apply nearest-neighbor analysis. This analysis is not limited to tumor samples but can also be applied to other (non-)pathogenic tissues. Improvements to the equipment and workflow over the past few years have significantly shortened throughput times, which facilitates the future application of this procedure in the diagnostic setting.

Author Spotlight: Unlocking Insights into the Immune Cell Landscape of Tumors

This protocol describes in detail how immune cell characterization of the tumor microenvironment using multiplex immunohistochemistry is carried out.

The immune cell landscape of the tumor microenvironment potentially contains information for the discovery of prognostic and predictive biomarkers. ...

A Next-generation Tissue Microarray (ngTMA) Protocol for Biomarker Studies

Biomarker research relies on tissue microarrays (TMA). TMAs are produced by repeated transfer of small tissue cores from a &#8216;donor&#8217; block into a &#8216;recipient&#8217; block and then used for a variety of biomarker applications. The construction of conventional TMAs is labor intensive, imprecise, and time-consuming. Here, a protocol using next-generation Tissue Microarrays (ngTMA) is outlined. ngTMA is based on TMA planning and design, digital pathology, and automated tissue microarraying. The protocol is illustrated using an example of 134 metastatic colorectal cancer patients. Histological, statistical and logistical aspects are considered, such as the tissue type, specific histological regions, and cell types for inclusion in the TMA, the number of tissue spots, sample size, statistical analysis, and number of TMA copies. Histological slides for each patient are scanned and uploaded onto a web-based digital platform. There, they are viewed and annotated (marked) using a 0.6-2.0 mm diameter tool, multiple times using various colors to distinguish tissue areas. Donor blocks and 12 &#8216;recipient&#8217; blocks are loaded into the instrument. Digital slides are retrieved and matched to donor block images. Repeated arraying of annotated regions is automatically performed resulting in an ngTMA. In this example, six ngTMAs are planned containing six different tissue types/histological zones. Two copies of the ngTMAs are desired. Three to four slides for each patient are scanned; 3 scan runs are necessary and performed overnight. All slides are annotated; different colors are used to represent the different tissues/zones, namely tumor center, invasion front, tumor/stroma, lymph node metastases, liver metastases, and normal tissue. 17 annotations/case are made; time for annotation is 2-3 min/case. 12 ngTMAs are produced containing 4,556 spots. Arraying time is 15-20 hr. Due to its precision, flexibility and speed, ngTMA is a powerful tool to further improve the quality of TMAs used in clinical and translational research.

A Next-generation Tissue Microarray ngTMA Protocol for Biomarker Studies

The protocol aims at optimizing the construction and quality of tissue microarrays for biomarker research. It includes aspects of planning and design, digital pathology, virtual slide annotation, and automated tissue arraying.

Biomarker research relies on tissue microarrays (TMA). TMAs are produced by repeated transfer of small tissue cores from a &#8216;donor&#8217; block into ...

Medicine

TMOD3 Expression and Its Role in Ovarian Cancer Progression

Tropomodulin 3 Overexpression as a Marker for Platinum Resistance and Immune Infiltration in Ovarian Cancer

The cytoskeleton plays an important role in platinum resistance in ovarian cancer. Tropomodulin 3 (TMOD3) is critical in the development of many tumors, but its role in the drug resistance of ovarian cancer remains unexplored. By analyzing data from the Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), and Clinical Proteomic Tumor Analysis Consortium (CPTAC) databases, this study compared TMOD3 expression in ovarian cancer and normal tissues, and examined the expression of TMOD3 after platinum treatment in platinum-sensitive and platinum-resistant ovarian cancers. The Kaplan-Meier method was used to assess the effect of TMOD3 on overall survival (OS) and progression-free survival (PFS) in ovarian cancer patients. microRNAs (miRNAs) targeting TMOD3 were predicted using TargetScan and analyzed using the TCGA database. Tumor Immune Estimation Resource (TIMER) and an integrated repository portal for tumor-immune system interactions (TISIDB) were used to determine the relationship between TMOD3 expression and immune infiltration. TMOD3 coexpression networks in ovarian cancer were explored using LinkedOmics, the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), and The Database for Annotation, Visualization, and Integrated Discovery (DAVID) Bioinformatics. The results showed that TMOD3 was highly expressed in ovarian cancer and was associated with the grading, staging, and metastasis of ovarian cancer. TMOD3 expression was significantly reduced in platinum-treated ovarian cancer cells and patients. However, TMOD3 expression was higher in platinum-resistant ovarian cancer cells and tissues compared to platinum-sensitive ones. Higher TMOD3 expression was significantly associated with lower OS and PFS in ovarian cancer patients treated with platinum-based chemotherapy. miRNA-mediated post-transcriptional regulation is likely responsible for high TMOD3 expression in ovarian cancer and platinum-resistant ovarian tissues. The expression of TMOD3 mRNA was associated with immune infiltration in ovarian cancer. These findings indicate that TMOD3 is highly expressed in ovarian cancer and is closely associated with platinum resistance and immune infiltration.

Author Spotlight: Unveiling the Role of TMOD3 in Platinum Resistance and Immune Infiltration in Ovarian Cancer

Tropomodulin 3 (TMOD3) has been increasingly studied in tumors in recent years. This study is the first to report that TMOD3 is highly expressed in ovarian cancer and is closely associated with platinum resistance and immune infiltration. These results could help improve the therapeutic outcomes for ovarian cancer.

The cytoskeleton plays an important role in platinum resistance in ovarian cancer. Tropomodulin 3 (TMOD3) is critical in the development of many tumors, ...

Multiomics Analysis of TMEM200A as a Pan-Cancer Biomarker

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